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22 pages, 29370 KiB  
Article
Investigating the Structure of Detachment Faulting and Its Role in Ore Formation: The Kallintiri Detachment System and the Associated Polymetallic Ore Deposit (Rhodope, NE Greece)
by Konstantinos Soukis, Christos Kanellopoulos, Panagiotis Voudouris, Constantinos Mavrogonatos, Ilias Lazos, Sotiris Sboras, Alexandre Tarantola, Daniel Koehn and Robert Moritz
Geosciences 2025, 15(2), 46; https://doi.org/10.3390/geosciences15020046 (registering DOI) - 1 Feb 2025
Viewed by 33
Abstract
The Kallintiri area (SW Byala Reka–Kechros Dome, Rhodope) hosts a polymetallic (critical, base, and precious metals) ore deposit, tectonically controlled by the late Eocene–Oligocene, top-to-SW Kallintiri Detachment System. The earliest structure associated with the Kallintiri Detachment is a ductile shear zone at the [...] Read more.
The Kallintiri area (SW Byala Reka–Kechros Dome, Rhodope) hosts a polymetallic (critical, base, and precious metals) ore deposit, tectonically controlled by the late Eocene–Oligocene, top-to-SW Kallintiri Detachment System. The earliest structure associated with the Kallintiri Detachment is a ductile shear zone at the interface between the high-grade footwall gneisses of the Lower and Intermediate Rhodope Terranes. The detachment zone encompasses the uppermost part of the gneisses and the ultramylonitic Makri Unit marble. The marble is bound by a brittle–ductile shear zone at the base and a knife-sharp, low-angle normal fault at the roof, exhibiting considerable brecciation and ultracataclasite development. The hanging wall includes the Makri Unit phyllites and the overlying mid–late-Eocene–Oligocene supra-detachment sediments, which show syn-depositional slump structures and brittle deformation with low- and high-angle faulting and non-cohesive cataclasites. Extensive hydrothermal fluid circulation along the detachment zone and through NW tension gashes and high-angle faults led to pronounced silicification and ore deposition. Field observations and mineralogical and geochemical analyses revealed two primary types of ore mineralization spatially and temporally associated with different structures. Base and precious metals-rich ores are associated with the detachment, while Sb ore deposition is localized mostly within the NW-trending tension gashes and high-angle faults. Full article
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Figure 1

Figure 1
<p>Simplified geological map of the Rhodope Massif (modified after [<a href="#B30-geosciences-15-00046" class="html-bibr">30</a>,<a href="#B32-geosciences-15-00046" class="html-bibr">32</a>,<a href="#B36-geosciences-15-00046" class="html-bibr">36</a>]). Inlet: the major geotectonic domains of Greece and the location of the Rhodope Massif.</p>
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<p>(<b>a</b>) Geological map of the Kallintiri area. (<b>b</b>) Tectonostratigraphic column. (<b>c</b>) Cross-section: A-A′-A″ (exaggerated ×1.5).</p>
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<p>(<b>a</b>) Two-mica paragneisses of the Lower Terrane showing brittle–ductile to brittle structures (top-SW S-C’ fabric and an array of kinematically similar high-angle faults). (<b>b</b>) Amphibolitic (Hornblende) gneisses with light-colored felsic layers alternating with dark-green amphibolitic layers. A protomylonitic S-C’ fabric can be observed, indicating top-to-SW sense of shear. Late-stage small-scale folds accommodate brittle deformation with similar overall kinematics. (<b>c</b>) Photomicrograph of the meta-ophiolitic rocks (XZ plane section, //polars) showing a top-SW proto- to mesomylonitic fabric (Cal: calcite, Chl: chlorite, Qz: quartz, Ser: sericite). (<b>d</b>) Strongly foliated light-colored gneiss with NE-SW stretching lineation towards the upper structural levels of the footwall. The foliation dips SE due to large-scale extensional folding of footwall rocks.</p>
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<p>(<b>a</b>) View of the Kallintiri Detachment with the footwall Lower Terrane gneiss (Gn) below the undulated SW-dipping detachment surface and the Makri Unit rocks (MU) and the Eocene–Oligocene supra-detachment sediments in the hanging wall (E-Ol). (<b>b</b>) Strongly foliated (Sm mylonitic foliation) and altered gneiss infiltrated by fluids. (<b>c</b>) Photomicrograph of the gneiss (XZ plane section, //polars) showing a top-SW brittle–ductile (meso)mylonitic fabric. Feldspar and plagioclase are fractured, whereas shear-band boudinage, ribbon quartz, and mica fish reveal ductile deformation. A dense network of fractures and low-angle micro-faults crosscut the mylonitic fabric and create proto- to ultracataclasites. All structures indicate a top-SW sense of shear (Fsp: feldspar, Chl: chlorite, Qz: quartz, Bt: biotite). (<b>d</b>,<b>e</b>) Stereoplot of great circles and poles to foliation in the footwall and detachment zone units and rose diagram of the strike of foliation, showing a NE-SW domal geometry. (<b>f</b>) Stereoplot of C’ shear bands (great circles and poles, pink color) and stretching lineation (Lm) (blue circles). (<b>g</b>) Stereoplot of the detachment surface and high-angle faults (thick red and black great circles, respectively) and associated striations (red and black dots, respectively).</p>
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<p>(<b>a</b>) Ultramylontic marble from the Detachment Zone with an SCC’ fabric indicating a top-to-SW sense of shear. (<b>b</b>) Shear-band boudinage in the lowermost layers of the ultramylonitic marble (top-to-SW). Notice the cataclastic fault zone (top-right). (<b>c</b>) Photomicrograph of the ultramylonitic marble (XZ plane section, //polars) showing the fine-grained top-SW mylonitic foliation cut by numerous veins and micro-faults and infiltrated by fluids. (<b>d</b>) Spectacular knife-sharp, low-angle fault surface of the Kallintiri Detachment, dipping SW, accompanied by massive fluid infiltration, as indicated by the light-brown color, replacing the original color of the marble. (<b>e</b>) Polished surface from the top layer of the detachment zone, showing extreme cataclastic deformation, which created an ultracataclasite with obliquely aligned clasts in a dark matrix. (<b>f</b>) Detail from the striated and corrugated detachment fault surface. (<b>g</b>) Photomicrograph of the cataclasite from the topmost Detachment Zone (XZ plane section, +polars) showing oblique-aligned marble clasts in a dark cryptocrystalline ultrafine-grained matrix and a composite SCC’ fabric, revealing top-SW sense of shear.</p>
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<p>(<b>a</b>) Strongly brecciated calc–phyllites from the hanging wall directly above the detachment zone. Low- and high-angle shear zones and scaly fabrics indicate top-to-SW sense. (<b>b</b>,<b>c</b>) Eocene–Oligocene supra-detachment sediments dipping moderately to SW and detail of the volcaniclastic tuffite layers. (<b>d</b>) High-angle fault zone in the supra-detachment sediments. (<b>e</b>) A late-stage, low-angle brittle fault zone accompanied by a white foliated ultracataclasite juxtaposes the uppermost supra-detachment sediments and the lowermost footwall gneiss, omitting the Makri Unit lithologies.</p>
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<p>(<b>a</b>) A high-angle NW-SE fault, where former mining activities occurred, that contains antimony mineralization. (<b>b</b>) Antimony mineralization within the mining gallery shown in the preceding image. Antimony ore remnants are present in the gallery’s ceiling as massive, large ore bodies filling tension gashes, signifying brittle deformation. (<b>c</b>) Characteristic massive antimony ore from the Kallintiri region. (<b>d</b>) Antimony ore comprising of stibnite, barite, red realgar, and quartz. (<b>e</b>,<b>f</b>) Mineralized specimen from the Kallintiri Detachment, more specifically from the black silica formation (BS), featuring a high-grade ore zone of hydrothermal breccia predominantly containing sulfide minerals of base metals. (<b>g</b>) Mineralized marble through carbonate replacement, incorporating silicified veinlets. (<b>h</b>) Oxidized mineralized marble.</p>
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<p>Schematic model of the successive large-scale tectonic structures (<b>a</b>–<b>d</b>) identified in the Kallintiri area. (<b>a</b>) Early ductile shear zone juxtaposing the metaophiolites (above) against the Lower Terrane gneisses, back-tilted due to subsequent faulting. (<b>b</b>) Low-angle brittle–ductile faults of the Kallintiri Detachment Zone and associated high-angle faults. (<b>c</b>) Low- to medium-angle brittle normal fault juxtaposing the supra-detachment sediments against the Makri Unit and/or the gneisses. (<b>d</b>) Post-kinematic high-angle brittle normal fault cutting all previous structures (for colors and structures, see the legend of <a href="#geosciences-15-00046-f002" class="html-fig">Figure 2</a>).</p>
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<p>3-D schematic model showing the major low- and high-angle shear zones and faults and the main pathways of fluid circulation and two-stage mineralization (brown and fuchsia shading). (For colors and structures, see the legend of <a href="#geosciences-15-00046-f002" class="html-fig">Figure 2</a>).</p>
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17 pages, 8911 KiB  
Article
The Central Mindoro Fault: An Active Sinistral Fault Within the Translational Boundary Between the Palawan Microcontinental Block and the Philippine Mobile Belt
by Rolly Rimando and Jeremy Rimando
GeoHazards 2025, 6(1), 6; https://doi.org/10.3390/geohazards6010006 (registering DOI) - 1 Feb 2025
Viewed by 74
Abstract
The NNW-trending Central Mindoro Fault (CMF) is an active oblique left-lateral strike-slip fault as determined from offset morphotectonic features such as spurs and streams. Mapping of the trace and determination of the sinistral strike-slip sense of motion of the CMF is essential not [...] Read more.
The NNW-trending Central Mindoro Fault (CMF) is an active oblique left-lateral strike-slip fault as determined from offset morphotectonic features such as spurs and streams. Mapping of the trace and determination of the sinistral strike-slip sense of motion of the CMF is essential not only to the assessment of hazards but also to providing a clearer perspective of its role in accommodating deformation resulting from the NW relative motion between the Philippine Sea Plate and the Sunda Plate. Its sense of motion is also kinematically congruent with the NW-SE translation along a transcurrent zone between the Philippine Mobile Belt and the Palawan Microcontinental Block on the western part of the Philippine archipelago. It is also consistent with the left-lateral motion of other structures within the zone, such as the Verde Passage Fault—another structure believed to be accommodating the NW-SE translation. Mapping of the CMF provides a key constraint in identifying the possible mechanism(s) involved in the dextral strike-slip motion of the 1994 Mindoro Earthquake ground rupture, which is subparallel to the CMF. Full article
31 pages, 11061 KiB  
Article
Root Cause Analysis of a Collapse in a Hydropower Tunnel
by Paul Schlotfeldt, Joe Carvalho and Brad Panton
Appl. Sci. 2025, 15(3), 1437; https://doi.org/10.3390/app15031437 - 30 Jan 2025
Viewed by 186
Abstract
This paper describes the investigation and findings from the root cause analysis (RCA) of a significant collapse that occurred in a hydropower tunnel at a confidential location. This collapse involved about 12,000 m3 of material being deposited in the tunnel from a [...] Read more.
This paper describes the investigation and findings from the root cause analysis (RCA) of a significant collapse that occurred in a hydropower tunnel at a confidential location. This collapse involved about 12,000 m3 of material being deposited in the tunnel from a narrow 20 m width failure zone encountered in the haunch and crown area of the main power tunnel. This paper describes contributing factors which include the following: (1) degradation of a highly zeolitized (laumontite-rich) zone of rock within a bedding concordant fault zone, termed the fault-damaged zone or FDZ; (2) relatively high in situ rock stresses concentrated in the haunch and crown area of the collapse zone in the tunnel; (3) large transient water pressure differences in the rock above the collapse zone and upstream and downstream of the collapse zone; (4) cyclical repetition of the above-described factors resulted in the propagation of crown and sidewall collapse in and around the FDZ. Lessons learnt on this project and other projects with similar durability problems in volcanic rock are distilled in this paper. It is hoped that advances made in the understanding of the failure mechanism at the unnamed tunnel can be included in future tunnel investigations and design in volcanic rocks. Full article
(This article belongs to the Special Issue Recent Research on Tunneling and Underground Engineering)
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Figure 1
<p>Tunnel profile with main collapse, collapse debris, and estimated collapse zone void shown. “?” indicates inferred top of main collapse debris.</p>
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<p>By-pass tunnel, collapse zone, and main power tunnel layout with geotechnical test holes and geological units encountered in test holes also shown in (<b>A</b>) plan view. (<b>B</b>) Photo showing white veins infilled with laumontite taken in the FDZ during construction of the by-pass tunnel.</p>
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<p>Tunnel profile showing the fault-damaged zone (FDZ) and close-up of rock types in the collapse zone.</p>
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<p>Total area of shotcrete detachment vs. tunnel mapping “Clock Time” facing downstream. (<b>A</b>) Chart and (<b>B</b>) mapping clock time legend, inset B.</p>
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<p>Tunnel section downstream of the collapse in AA rocks showing stress-induced failure initiation of zeolite-filled veins. (<b>A</b>) Section showing interpreted stress orientations; (<b>B</b>) close up showing dilation in rapid dewatering condition.</p>
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<p>Oblique view showing the interpreted FDZ including FDZ-HART (green) and FDZ-CLT (blue) geological units.</p>
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<p>Failure mechanism and failure progression for (<b>A</b>) pre-collapse, (<b>B</b>) initial liner failure and Rockfall, (<b>C</b>) additional collapse, rockfall progressing into the FDZ, (<b>D</b>) temporary tunnel blockage, and (<b>E</b>) final collapse.</p>
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<p>Interpreted bedding parallel fault movement (slippage) forming the fault-damaged zone (FDZ)—not to scale (adapted from [<a href="#B23-applsci-15-01437" class="html-bibr">23</a>]).</p>
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<p>XRD weight percent (%) vs. distance from the FDZ from geotechnical test hole samples. Red numbers on x-axis indicate upstream distance from FDZ midpoint.</p>
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<p>XRD weight percent (%) vs. by-pass tunnel station samples.</p>
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<p>Swell pressure data vs. distance from the FDZ from the geotechnical test hole sample. Red numbers on x-axis indicate upstream distance from FDZ midpoint.</p>
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<p>Swell pressure data vs. by-pass tunnel station samples.</p>
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<p>In situ stress measurement results. (<b>A</b>) Orientation and magnitude of the in situ stress tensor from various tests and models, and (<b>B</b>) tunnel plan view showing general orientation of major principal stress from in situ Test 1 and Test 3 and the topographic model. Test 2 shows the rotated position of the principal stress measured well upstream of the collapse, and (<b>C</b>) schematic tunnel section showing the orientation of the major principal stress from in situ tests in the AA rocks downstream of the collapse (see <a href="#applsci-15-01437-f005" class="html-fig">Figure 5</a>) Test 1 was conducted approximately 500 m upstream of the collapse. Test 2 was conducted around 90 m upstream of the collapse, and Test 3 was executed around 140 m downstream of the collapse. A topographic model was also generated, and numerical modelling was undertaken to develop an understanding of the likely stress field as a result of the overburden and valley side effects. The orientation and magnitude of the in situ stresses from the numerical modelling based on the topography and from the three in situ stress measurements are shown in <a href="#applsci-15-01437-f013" class="html-fig">Figure 13</a>.</p>
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<p>Comparison of rock mass damage between the elastic and plastic liners in the collapse zone for (<b>A</b>) condition after excavation, (<b>B</b>) condition after deterioration, and (<b>C</b>) condition after swelling (using Phase2 Version 7.0 by Rocscience and [<a href="#B50-applsci-15-01437" class="html-bibr">50</a>]).</p>
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<p>Loads on the elastic and plastic liners compared to the strength envelop with shotcrete and bolts in the collapse zone for (<b>A</b>) elastic and (<b>B</b>) plastic (using approach presented in [<a href="#B48-applsci-15-01437" class="html-bibr">48</a>,<a href="#B49-applsci-15-01437" class="html-bibr">49</a>]).</p>
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17 pages, 6561 KiB  
Article
A Study on the Controlling Effect of Geological Structures on Coalbed Methane Occurrence in the Northeast Margin of Qinshui Basin, North China
by Rui Li, Le Zhang, Jun Xie, Zhaoying Chen, Baoke Yang, Wenting Xiang and Xikun Zhai
Energies 2025, 18(3), 647; https://doi.org/10.3390/en18030647 - 30 Jan 2025
Viewed by 321
Abstract
This study investigated the patterns of gas occurrence in the coal seam structural zones of the northeastern margin of the Qinshui Basin, with a focus on the Sijiazhuang Coal Mine. Using laboratory experiments, theoretical analysis, and field exploration, we examined how geological structures [...] Read more.
This study investigated the patterns of gas occurrence in the coal seam structural zones of the northeastern margin of the Qinshui Basin, with a focus on the Sijiazhuang Coal Mine. Using laboratory experiments, theoretical analysis, and field exploration, we examined how geological structures influence gas distribution. The results show that gas content and pressure near normal faults are generally higher than those in reverse fault areas. However, fault-induced gas occurrence is complex, with stress superposition potentially reversing this trend. When a normal fault intersects modern tectonic stress at a perpendicular or large angle, the fault zone may transition to a compressional state, enhancing gas preservation. Fold structures were found to play a significant role in gas distribution, with anticline zones exhibiting the highest gas content, followed by syncline and normal zones. Collapse columns were shown to affect gas occurrence within a range of 15 to 180 m, with the impact depending on factors such as surrounding rock properties, hydrogeological conditions, and fault activity during collapse formation. Additionally, mirror-like sliding surfaces, formed by multiple factors, are prevalent in the coal seam structures of this region. These sliding surfaces are closely linked to structural zones and serve as valuable indicators for geological predictions in coal seam development. Full article
20 pages, 16230 KiB  
Article
Regional Geological Data on the Volturno Basin Filling and Its Relationship to the Massico Structure (Southern Tyrrhenian Sea, Italy)
by Gemma Aiello
J. Mar. Sci. Eng. 2025, 13(2), 241; https://doi.org/10.3390/jmse13020241 - 26 Jan 2025
Viewed by 314
Abstract
We built a regional geological section founded upon the assessment of a seismic line in the Volturno Basin, which is situated on the northern Campania continental shelf of the Tyrrhenian margin of Southern Italy. This section has been integrated with multichannel seismic data [...] Read more.
We built a regional geological section founded upon the assessment of a seismic line in the Volturno Basin, which is situated on the northern Campania continental shelf of the Tyrrhenian margin of Southern Italy. This section has been integrated with multichannel seismic data of Zone E (ViDEPI project) to highlight its relationships with the Massico structure. In the Volturno basin, there are four Pleistocene to Holocene units, recognized based on seismic analysis lie above deep seismo-stratigraphic units, related to Campania Latium carbonate platform and The Frosinone Flysch. Onshore and offshore seismic data, calibrated with lithostratigraphic correlation, have displayed the seismo-stratigraphic framework, including both sedimentary and volcanic seismo-stratigraphic units. Of these, the lavas associated with the Northern Campania Volcanic Zone’s Villa Literno volcano are associated with seismic unit 2a. Seismo-stratigraphic data has shown the offshore prolongation of the Massico structure, as involved by normal faults and flower structures. The whole-data interpretation suggests that the tectonic activity acted in correspondence to normal faults, which have controlled half-graben and interposed structural highs, fitting to the regional geological setting of the continental margin. Full article
18 pages, 1597 KiB  
Article
Analysis of Tunnel Lining Damage Characteristics Under the Combined Actions of Fault Dislocation and Seismic Action
by Jiaxuan Du, Songhong Yan, Weiyu Sun, Yuxiang Li and Mingxing Cao
Appl. Sci. 2025, 15(3), 1150; https://doi.org/10.3390/app15031150 - 23 Jan 2025
Viewed by 411
Abstract
Tunnels crossing active faults frequently experience simultaneous exposure to fault dislocation and seismic action during operation. To study the damage behavior of tunnels under the combined effects of fault dislocation and seismic action, a three-dimensional nonlinear finite element model was established. This model [...] Read more.
Tunnels crossing active faults frequently experience simultaneous exposure to fault dislocation and seismic action during operation. To study the damage behavior of tunnels under the combined effects of fault dislocation and seismic action, a three-dimensional nonlinear finite element model was established. This model simulates fault dislocation superimposed on seismic action in the context of tunnel engineering through active faults. The main conclusions are as follows: (1) The acceleration amplification phenomenon occurs in the tunnels after the superposition of seismic action; at the same time, the degree and scope of tunnel damage increase significantly, in which the increase in tensile damage is more significant. (2) The initial damage from fault dislocation worsens tunnel damage under seismic action, as evidenced by the energy dissipation characteristics. (3) As the initial fault displacement and peak seismic acceleration increase, the extent of lining damage also increases. Notably, compressive damage to the lining is symmetrically distributed along the fault plane, whereas tensile damage is significantly more severe within the fault rupture zone. (4) Even moderate earthquakes can cause severe damage to tunnels crossing active faults. Therefore, tunnel construction in these areas must include disaster prevention and mitigation strategies. Full article
(This article belongs to the Special Issue Advances in Tunnelling and Underground Space Technology)
64 pages, 13137 KiB  
Article
Compositional and Numerical Geomorphology Along a Basement–Foreland Transition, SE Germany, with Special Reference to Landscape-Forming Indices and Parameters in Genetic and Applied Terrain Analyses
by Harald G. Dill, Andrei Buzatu, Sorin-Ionut Balaban and Christopher Kleyer
Geosciences 2025, 15(2), 37; https://doi.org/10.3390/geosciences15020037 - 23 Jan 2025
Viewed by 380
Abstract
The Münchberg Gneiss Complex (Central European Variscides, Germany) is separated by a deep-seated lineamentary fault zone, the Franconian Lineamentary Fault Zone, from its Mesozoic foreland. The study area offers insight into a great variety of landforms created by fluvial and mass wasting processes [...] Read more.
The Münchberg Gneiss Complex (Central European Variscides, Germany) is separated by a deep-seated lineamentary fault zone, the Franconian Lineamentary Fault Zone, from its Mesozoic foreland. The study area offers insight into a great variety of landforms created by fluvial and mass wasting processes together with their bedrocks, covering the full range from unmetamorphosed sediments to high-grade regionally metamorphic rocks. It renders the region an ideal place to conduct a study of compositional and numerical geomorphology and their landscape-forming indices and parameters. The landforms under consideration are sculpted out of the bedrocks (erosional landforms) and overlain by depositional landforms which are discussed by means of numerical landform indices (LFIs), all of which are coined for the first time in the current paper. They are designed to be suitable for applied geosciences such as extractive/economic geology as well as environmental geology. The erosional landform series are subdivided into three categories: (1) The landscape roughness indices, e.g., VeSival (vertical sinuosity—valley of landform series) and the VaSlAnalti (variation in slope angle altitude), which are used for a first order classification of landscapes into relief generations. The second order classification LFIs are devoted to the material properties of the landforms’ bedrocks, such as the rock strength (VeSilith) and the bedrock anisotropy (VaSlAnnorm). The third order scheme describes the hydrography as to its vertical changes by the inclination of the talweg and the different types of knickpoints (IncTallith/grad) and horizontal sinuosity (HoSilith/grad). The study area is subjected to a tripartite zonation into the headwater zone, synonymous with the paleoplain which undergoes some dissection at its edge, the step-fault plain representative of the track zone which undergoes widespread fluvial piracy, and the foreland plains which act as an intermediate sedimentary trap named the deposition zone. The area can be described in space and time with these landform indices reflecting fluvial and mass wasting processes operative in four different stages (around 17 Ma, 6 to 4 Ma, <1.7 Ma, and <0.4 Ma). The various groups of LFIs are a function of landscape maturity (pre-mature, mature, and super-mature). The depositional landforms are numerically defined in the same way and only differ from each other by their subscripts. Their set of LFIs is a mirror image of the composition of depositional landforms in relation to their grain size. The leading part of the acronym, such as QuantSanheav and QuantGravlith, refers to the process of quantification, the second part to the grain size, such as sand and gravel, and the subscript to the material, such as heavy minerals or lithological fragments. The three numerical indices applicable to depositional landforms are a direct measurement of the hydrodynamic and gravity-driven conditions of the fluvial and mass wasting processes using granulometry, grain morphology, and situmetry (clast orientation). Together with the previous compositional indices, the latter directly translate into the provenance analysis which can be used for environmental analyses and as a tool for mineral exploration. It creates a network between numerical geomorphology, geomorphometry, and the E&E issue disciplines (economic/extractive geology vs. environmental geology). The linguistics of the LFIs adopted in this publication are designed so as to be open for individual amendments by the reader. An easy adaptation to different landform suites worldwide, irrespective of their climatic conditions, geodynamic setting, and age of formation, is feasible due to the use of a software and a database available on a global basis. Full article
(This article belongs to the Section Sedimentology, Stratigraphy and Palaeontology)
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Figure 1

Figure 1
<p>Geodynamic overview of the NE Bavarian basement and the study area at the western edge of the Münchberg Gneiss Complex, SE Germany. (<b>a</b>) The position of the study area in Germany. (<b>b</b>) The geological setting of the study area in SE Germany and its neighboring geodynamic units of the Frankenwald and Fichtelgebirge Mts. (modified from Emmert et al. [<a href="#B26-geosciences-15-00037" class="html-bibr">26</a>]. (<b>c</b>) Legend for the map in <a href="#geosciences-15-00037-f001" class="html-fig">Figure 1</a>b. The area with the dashed line denotes the close-up view of the geological setting in <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>.</p>
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<p>Geological overview and the bedrock lithologies of the landform series under consideration. (<b>a</b>) The geological map of the study area with the Cenozoic overburden and the fluvial drainage network and sampling sites. The geological basis is the geological maps published by Emmert and Weinelt [<a href="#B36-geosciences-15-00037" class="html-bibr">36</a>], Emmert et al. [<a href="#B35-geosciences-15-00037" class="html-bibr">35</a>], Stettner [<a href="#B39-geosciences-15-00037" class="html-bibr">39</a>] and Stettner [<a href="#B40-geosciences-15-00037" class="html-bibr">40</a>] which, in places, have been updated during the current investigation. (<b>b</b>) Lithological units shown in <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a and symbols used in the cross-sections through the landforms (see <a href="#geosciences-15-00037-f004" class="html-fig">Figure 4</a>).</p>
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<p>Geological overview and the bedrock lithologies of the landform series under consideration. (<b>a</b>) The geological map of the study area with the Cenozoic overburden and the fluvial drainage network and sampling sites. The geological basis is the geological maps published by Emmert and Weinelt [<a href="#B36-geosciences-15-00037" class="html-bibr">36</a>], Emmert et al. [<a href="#B35-geosciences-15-00037" class="html-bibr">35</a>], Stettner [<a href="#B39-geosciences-15-00037" class="html-bibr">39</a>] and Stettner [<a href="#B40-geosciences-15-00037" class="html-bibr">40</a>] which, in places, have been updated during the current investigation. (<b>b</b>) Lithological units shown in <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a and symbols used in the cross-sections through the landforms (see <a href="#geosciences-15-00037-f004" class="html-fig">Figure 4</a>).</p>
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<p>Geomorphological overview of the washboard landscape and the study areas defined by the two paleosurfaces, I and II. (<b>a</b>) Cartoon showing two paleosurfaces. Paleosurface I is gently dipping off the FLFZ (Franconian Line Fault Zone) as a presumed architectural planar element covering the Franconian Scarpland. Paleosurface II is a presumed surface covering the basement and the immediate foreland affected by the FLFZ. It is a tripartite curved surface covering three plains [<a href="#B29-geosciences-15-00037" class="html-bibr">29</a>] (<b>b</b>) Cartoon providing an idealized cross-section of the tripartite paleosurface II. For geology, see key of <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a. Dotted line marks the modern-day surface and longitudinal profile of the talweg with its knickpoints. (<b>c</b>) Digital terrain model of the study area showing the controlling linear tectonic elements of the main anticline of the MGC. (<b>d</b>) Topographic map showing the altitude of the study area in meters a.m.s.l. (<b>e</b>) Thematic map showing the slope angle values of the various land forms under consideration in degrees. (<b>f</b>) Geomorphological index map showing the morphotectonic units currently on display: 1 = paleoplain undissected, 2 = paleoplain dissected, 3 = step-fault plain inclined, 4 = foreland plain inclined off the basement, and 5 = foreland plain towards the basement (<a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>b). The position of the reference cross-sections (<a href="#geosciences-15-00037-f004" class="html-fig">Figure 4</a>) and the maximum aerial extension of relief generations R1 to R4 (Rre = R2 landforms are patchily preserved as relics on R3) determined based upon the vertical sinuosity—valley (VeSi<sub>val</sub>) index are displayed by red full, stippled, and dashed-stippled lines. (<b>g</b>) Geological index map (for legend, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a). The position of the reference cross-sections (<a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>g) and the maximum aerial extension of relief generations R1 to R4 (Rre = R2 landforms are patchily preserved as relics on R3) determined based upon the vertical sinuosity—valley (VeSi<sub>val</sub>) index are displayed by red full, stippled, and dashed-stippled line.</p>
Full article ">Figure 3 Cont.
<p>Geomorphological overview of the washboard landscape and the study areas defined by the two paleosurfaces, I and II. (<b>a</b>) Cartoon showing two paleosurfaces. Paleosurface I is gently dipping off the FLFZ (Franconian Line Fault Zone) as a presumed architectural planar element covering the Franconian Scarpland. Paleosurface II is a presumed surface covering the basement and the immediate foreland affected by the FLFZ. It is a tripartite curved surface covering three plains [<a href="#B29-geosciences-15-00037" class="html-bibr">29</a>] (<b>b</b>) Cartoon providing an idealized cross-section of the tripartite paleosurface II. For geology, see key of <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a. Dotted line marks the modern-day surface and longitudinal profile of the talweg with its knickpoints. (<b>c</b>) Digital terrain model of the study area showing the controlling linear tectonic elements of the main anticline of the MGC. (<b>d</b>) Topographic map showing the altitude of the study area in meters a.m.s.l. (<b>e</b>) Thematic map showing the slope angle values of the various land forms under consideration in degrees. (<b>f</b>) Geomorphological index map showing the morphotectonic units currently on display: 1 = paleoplain undissected, 2 = paleoplain dissected, 3 = step-fault plain inclined, 4 = foreland plain inclined off the basement, and 5 = foreland plain towards the basement (<a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>b). The position of the reference cross-sections (<a href="#geosciences-15-00037-f004" class="html-fig">Figure 4</a>) and the maximum aerial extension of relief generations R1 to R4 (Rre = R2 landforms are patchily preserved as relics on R3) determined based upon the vertical sinuosity—valley (VeSi<sub>val</sub>) index are displayed by red full, stippled, and dashed-stippled lines. (<b>g</b>) Geological index map (for legend, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a). The position of the reference cross-sections (<a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>g) and the maximum aerial extension of relief generations R1 to R4 (Rre = R2 landforms are patchily preserved as relics on R3) determined based upon the vertical sinuosity—valley (VeSi<sub>val</sub>) index are displayed by red full, stippled, and dashed-stippled line.</p>
Full article ">Figure 3 Cont.
<p>Geomorphological overview of the washboard landscape and the study areas defined by the two paleosurfaces, I and II. (<b>a</b>) Cartoon showing two paleosurfaces. Paleosurface I is gently dipping off the FLFZ (Franconian Line Fault Zone) as a presumed architectural planar element covering the Franconian Scarpland. Paleosurface II is a presumed surface covering the basement and the immediate foreland affected by the FLFZ. It is a tripartite curved surface covering three plains [<a href="#B29-geosciences-15-00037" class="html-bibr">29</a>] (<b>b</b>) Cartoon providing an idealized cross-section of the tripartite paleosurface II. For geology, see key of <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a. Dotted line marks the modern-day surface and longitudinal profile of the talweg with its knickpoints. (<b>c</b>) Digital terrain model of the study area showing the controlling linear tectonic elements of the main anticline of the MGC. (<b>d</b>) Topographic map showing the altitude of the study area in meters a.m.s.l. (<b>e</b>) Thematic map showing the slope angle values of the various land forms under consideration in degrees. (<b>f</b>) Geomorphological index map showing the morphotectonic units currently on display: 1 = paleoplain undissected, 2 = paleoplain dissected, 3 = step-fault plain inclined, 4 = foreland plain inclined off the basement, and 5 = foreland plain towards the basement (<a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>b). The position of the reference cross-sections (<a href="#geosciences-15-00037-f004" class="html-fig">Figure 4</a>) and the maximum aerial extension of relief generations R1 to R4 (Rre = R2 landforms are patchily preserved as relics on R3) determined based upon the vertical sinuosity—valley (VeSi<sub>val</sub>) index are displayed by red full, stippled, and dashed-stippled lines. (<b>g</b>) Geological index map (for legend, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a). The position of the reference cross-sections (<a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>g) and the maximum aerial extension of relief generations R1 to R4 (Rre = R2 landforms are patchily preserved as relics on R3) determined based upon the vertical sinuosity—valley (VeSi<sub>val</sub>) index are displayed by red full, stippled, and dashed-stippled line.</p>
Full article ">Figure 4
<p>The reference cross-sections provide the link between the landscape and the lithological composition. For lithology, see key of <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>b, and for their position, see <a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>d. In the rectangles, the vertical sinuosity—valley (VeSi<sub>val</sub>) index of the landform series portrayed by the reference cross-section is given. It is the landscape roughness index of regional scale (for more information see text). (<b>a</b>) M1-M2, (<b>b</b>) L1-L2, (<b>c</b>) Pe1-Pe2, (<b>d</b>) K1-K2, (<b>e</b>) Ku1-Ku2, (<b>f</b>) We1-We, (<b>g</b>) J3-J4, (<b>h</b>) H1-I2, (<b>i</b>) H1-H2, (<b>j</b>) G1-G2, (<b>k</b>) F1-E2, (<b>l</b>) E1-E2, (<b>m</b>) D1-D2, (<b>n</b>) C1-C2, (<b>o</b>) B1-B2, (<b>p</b>) A1-A2, (<b>q</b>) Lu1-Lu2, (<b>r</b>) Wü1-Wü2, (<b>s</b>) A3-A4, (<b>t</b>) A3-A4 FW, (<b>u</b>) A1-A2 FW, (<b>v</b>) J1-J2, and (<b>w</b>) J5-J6.</p>
Full article ">Figure 4 Cont.
<p>The reference cross-sections provide the link between the landscape and the lithological composition. For lithology, see key of <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>b, and for their position, see <a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>d. In the rectangles, the vertical sinuosity—valley (VeSi<sub>val</sub>) index of the landform series portrayed by the reference cross-section is given. It is the landscape roughness index of regional scale (for more information see text). (<b>a</b>) M1-M2, (<b>b</b>) L1-L2, (<b>c</b>) Pe1-Pe2, (<b>d</b>) K1-K2, (<b>e</b>) Ku1-Ku2, (<b>f</b>) We1-We, (<b>g</b>) J3-J4, (<b>h</b>) H1-I2, (<b>i</b>) H1-H2, (<b>j</b>) G1-G2, (<b>k</b>) F1-E2, (<b>l</b>) E1-E2, (<b>m</b>) D1-D2, (<b>n</b>) C1-C2, (<b>o</b>) B1-B2, (<b>p</b>) A1-A2, (<b>q</b>) Lu1-Lu2, (<b>r</b>) Wü1-Wü2, (<b>s</b>) A3-A4, (<b>t</b>) A3-A4 FW, (<b>u</b>) A1-A2 FW, (<b>v</b>) J1-J2, and (<b>w</b>) J5-J6.</p>
Full article ">Figure 4 Cont.
<p>The reference cross-sections provide the link between the landscape and the lithological composition. For lithology, see key of <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>b, and for their position, see <a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>d. In the rectangles, the vertical sinuosity—valley (VeSi<sub>val</sub>) index of the landform series portrayed by the reference cross-section is given. It is the landscape roughness index of regional scale (for more information see text). (<b>a</b>) M1-M2, (<b>b</b>) L1-L2, (<b>c</b>) Pe1-Pe2, (<b>d</b>) K1-K2, (<b>e</b>) Ku1-Ku2, (<b>f</b>) We1-We, (<b>g</b>) J3-J4, (<b>h</b>) H1-I2, (<b>i</b>) H1-H2, (<b>j</b>) G1-G2, (<b>k</b>) F1-E2, (<b>l</b>) E1-E2, (<b>m</b>) D1-D2, (<b>n</b>) C1-C2, (<b>o</b>) B1-B2, (<b>p</b>) A1-A2, (<b>q</b>) Lu1-Lu2, (<b>r</b>) Wü1-Wü2, (<b>s</b>) A3-A4, (<b>t</b>) A3-A4 FW, (<b>u</b>) A1-A2 FW, (<b>v</b>) J1-J2, and (<b>w</b>) J5-J6.</p>
Full article ">Figure 5
<p>X–Y diagrams of the variation in slope angle altitude (VaSlAn<sub>alti</sub>) index with the X-axis giving the mean slope angle in degrees and the Y-axis giving the altitude in meters above mean sea level. R2 = correlation coefficient. (<b>a</b>) M1-M2, (<b>b</b>) L1-L2, (<b>c</b>) Pe1-Pe2, (<b>d</b>) K1-K2, (<b>e</b>) Ku1-Ku2, (<b>f</b>) We1-We, (<b>g</b>) J3-J4, (<b>h</b>) H1-I2, (<b>i</b>) H1-H2, (<b>j</b>) G1-G2, (<b>k</b>) F1-E2, (<b>l</b>) E1-E2, (<b>m</b>) D1-D2, (<b>n</b>) C1-C2, (<b>o</b>) B1-B2, (<b>p</b>) A1-A2, (<b>q</b>) Lu1-Lu2, (<b>r</b>) Wü1-Wü2, (<b>s</b>) A3-A4, (<b>t</b>) A3-A4 FW, (<b>u</b>) A1-A2 FW, (<b>v</b>) J1-J2, and (<b>w</b>) J5-J6.</p>
Full article ">Figure 5 Cont.
<p>X–Y diagrams of the variation in slope angle altitude (VaSlAn<sub>alti</sub>) index with the X-axis giving the mean slope angle in degrees and the Y-axis giving the altitude in meters above mean sea level. R2 = correlation coefficient. (<b>a</b>) M1-M2, (<b>b</b>) L1-L2, (<b>c</b>) Pe1-Pe2, (<b>d</b>) K1-K2, (<b>e</b>) Ku1-Ku2, (<b>f</b>) We1-We, (<b>g</b>) J3-J4, (<b>h</b>) H1-I2, (<b>i</b>) H1-H2, (<b>j</b>) G1-G2, (<b>k</b>) F1-E2, (<b>l</b>) E1-E2, (<b>m</b>) D1-D2, (<b>n</b>) C1-C2, (<b>o</b>) B1-B2, (<b>p</b>) A1-A2, (<b>q</b>) Lu1-Lu2, (<b>r</b>) Wü1-Wü2, (<b>s</b>) A3-A4, (<b>t</b>) A3-A4 FW, (<b>u</b>) A1-A2 FW, (<b>v</b>) J1-J2, and (<b>w</b>) J5-J6.</p>
Full article ">Figure 5 Cont.
<p>X–Y diagrams of the variation in slope angle altitude (VaSlAn<sub>alti</sub>) index with the X-axis giving the mean slope angle in degrees and the Y-axis giving the altitude in meters above mean sea level. R2 = correlation coefficient. (<b>a</b>) M1-M2, (<b>b</b>) L1-L2, (<b>c</b>) Pe1-Pe2, (<b>d</b>) K1-K2, (<b>e</b>) Ku1-Ku2, (<b>f</b>) We1-We, (<b>g</b>) J3-J4, (<b>h</b>) H1-I2, (<b>i</b>) H1-H2, (<b>j</b>) G1-G2, (<b>k</b>) F1-E2, (<b>l</b>) E1-E2, (<b>m</b>) D1-D2, (<b>n</b>) C1-C2, (<b>o</b>) B1-B2, (<b>p</b>) A1-A2, (<b>q</b>) Lu1-Lu2, (<b>r</b>) Wü1-Wü2, (<b>s</b>) A3-A4, (<b>t</b>) A3-A4 FW, (<b>u</b>) A1-A2 FW, (<b>v</b>) J1-J2, and (<b>w</b>) J5-J6.</p>
Full article ">Figure 5 Cont.
<p>X–Y diagrams of the variation in slope angle altitude (VaSlAn<sub>alti</sub>) index with the X-axis giving the mean slope angle in degrees and the Y-axis giving the altitude in meters above mean sea level. R2 = correlation coefficient. (<b>a</b>) M1-M2, (<b>b</b>) L1-L2, (<b>c</b>) Pe1-Pe2, (<b>d</b>) K1-K2, (<b>e</b>) Ku1-Ku2, (<b>f</b>) We1-We, (<b>g</b>) J3-J4, (<b>h</b>) H1-I2, (<b>i</b>) H1-H2, (<b>j</b>) G1-G2, (<b>k</b>) F1-E2, (<b>l</b>) E1-E2, (<b>m</b>) D1-D2, (<b>n</b>) C1-C2, (<b>o</b>) B1-B2, (<b>p</b>) A1-A2, (<b>q</b>) Lu1-Lu2, (<b>r</b>) Wü1-Wü2, (<b>s</b>) A3-A4, (<b>t</b>) A3-A4 FW, (<b>u</b>) A1-A2 FW, (<b>v</b>) J1-J2, and (<b>w</b>) J5-J6.</p>
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<p>Overview of the variation in slope angle altitude (VaSlAn<sub>alti</sub>) index as facies marker.</p>
Full article ">Figure 7
<p>Overview of the petrophysical–geomorphological parameters vertical sinuosity—lithology (VeSi<sub>lith</sub>) of the landform and variation in normalized slope angle (VaSlAn<sub>norm</sub>) of the landform.</p>
Full article ">Figure 8
<p>Meta-sedimentary, meta-intrusive, and meta-volcanic magmatic rocks and their landforms featuring different values of VaSlAn<sub>norm</sub> and VeSi<sub>lith</sub>. For numerical, compositional, topographic, and more detailed geomorphological data, see <a href="#geosciences-15-00037-t002" class="html-table">Table 2</a>. (<b>a</b>) Mica gneiss with subhorizontal jointing on top of a hillock of a large and shallow valley. The top slope is strewn with boulders undergoing creep and solifluction. (<b>b</b>) Close-up view of one of the boulders which displays a lens-shaped and strong foliation. (<b>c</b>) A well-rounded paragneiss-hornfels boulder similar in outward appearance and internal texture but of rock strength twice as much as the mica gneiss. (<b>d</b>) Layered phyllite exposed on the mid-slope of a V-shaped valley. (<b>e</b>) Tightly foliated and folded phyllite as an allochthonous block. See ignition key for scale. Dashed line highlights wrinkled folding. (<b>f</b>) Alternating beds of chert, forming ledges and slates with the beginning of disintegration into debris of flakes at the footslope of a V-shaped valley. (<b>g</b>) Plates of (roof)slate in the D horizon of the pedosphere. The argillaceous rocks are transformed into individual slaps of slate preserving the original siting of the rocks with the slaty cleavage. (<b>h</b>) Completely disintegrated pencil slates randomly scattered along the footslope of a V-shaped valley while forming a talus apron of flakey gravel. See hammer for scale. (<b>i</b>) Augengneiss ledges protruding out of the top slope of a V-shaped valley. The inset displays the tight arrangement of layers composed of quartz, K feldspar, and plagioclase with dark micaceous layers. (<b>j</b>) Meta-granite-to granodiorite showing a massive texture devoid of any strong foliation. (<b>k</b>) Steeply-dipping layers of tightly foliated epidote amphibolite (prasinite). (<b>l</b>) Layers of meta-basalt with narrowly-spaced joints near the escarpment of the inclined step-and-fault plain which is identical to the highland-boundary fault FLFZ (see <a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>b,c). The inset shows the disintegration of the meta-basalt (diabase) as a consequence of weathering. (<b>m</b>) Amphibolite with a vaguely expressed layering which is intruded by an alkaline feldspar pegmatoid rimmed by a stippled line. It constitutes the edge of a V-shaped valley (wide angle) passing into a large and shallow valley. See geologists for scale. (<b>n</b>) Monadnock with subrounded exposures of bronzite-serpentinite displaying typical rillen features of “silica karst”. (<b>o</b>) Disharmonic tight folding of alkaline feldspar—quartz mobilisates in massive layered amphibolite gneiss. (<b>p</b>) A monadnock made of massive eclogite and eclogite amphibolite surrounded by a blockmeer of the same lithology. Inset shows a slightly weathered massive eclogite with red Fe-Al-Mn garnet and green omphacitic pyroxene.</p>
Full article ">Figure 9
<p>Longitudinal sections along the talweg of drainage systems. The X-axis denotes the station points, and the Y-axis denotes the dip angle of the talweg in degree. The station points are characterized by Arabic numerals. The third variable is the wall rock or bedrock lithology of the host rocks exposed in the river banks and the river bed which, when different from each other on the left- and right-hand bank, are given by more than one numeral which refers to the notation in <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>b, e.g., profile X7-X9 13 + 12 + 14 = phyllite &gt; epidote amphibolite &gt; talc schist (for lithology, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>b). The correlation coefficient R2 between the two data sets is given in the upper right-hand corner of the diagram. (<b>a</b>) X–Y plot showing the inclination of the talweg (IncTal<sub>lith/grad</sub> index) in degrees. <span class="html-italic">Y</span>-axis versus the station point downstream of longitudinal profile X15-X16 FW. The knickpoints intensity can be directly assessed by the length of the various intervals of the graph and the type of knickpoint (see text) by its upward and downward directions. At station point 11, the longitudinal section is intersected by the cross-section A3-A4 FW (<a href="#geosciences-15-00037-f005" class="html-fig">Figure 5</a>t). The red rectangle marks the IncTal<sub>lith/grad</sub> index fluvial facies in the close-up view of <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>b. (<b>b</b>) Incision of an acute-angle single-channel non-alluvial V-shaped valley into the Devonian chert unit (slope angle 30° ⇒ 35°, talweg angle 2.7° ⇒ 0.7°). See reference profile with steps and pools in (stippled white line = strike of bedding). (<b>c</b>) Geological index map (for more detail and key, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a) with horizontal sinuosity—lithology plus gradient index (HoSi<sub>lith/grad</sub>) given in the white boxes; the knickpoint types 1 and 2 and the start and end points of longitudinal sections are displayed in <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>d–i by X–Y diagrams plotting the station points and inclinations data. The red dots mark mines of talc—(purple), pegmatoid—(dark blue), and Cu-(Au) deposits (yellow). (<b>d</b>) X1-X2, (<b>e</b>) X2-X3, (<b>f</b>) X5-X6, (<b>g</b>) X7-X8, (<b>h</b>) X9-X10, and (<b>i</b>) X11-X12 (for color symbols, see <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>c).</p>
Full article ">Figure 9 Cont.
<p>Longitudinal sections along the talweg of drainage systems. The X-axis denotes the station points, and the Y-axis denotes the dip angle of the talweg in degree. The station points are characterized by Arabic numerals. The third variable is the wall rock or bedrock lithology of the host rocks exposed in the river banks and the river bed which, when different from each other on the left- and right-hand bank, are given by more than one numeral which refers to the notation in <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>b, e.g., profile X7-X9 13 + 12 + 14 = phyllite &gt; epidote amphibolite &gt; talc schist (for lithology, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>b). The correlation coefficient R2 between the two data sets is given in the upper right-hand corner of the diagram. (<b>a</b>) X–Y plot showing the inclination of the talweg (IncTal<sub>lith/grad</sub> index) in degrees. <span class="html-italic">Y</span>-axis versus the station point downstream of longitudinal profile X15-X16 FW. The knickpoints intensity can be directly assessed by the length of the various intervals of the graph and the type of knickpoint (see text) by its upward and downward directions. At station point 11, the longitudinal section is intersected by the cross-section A3-A4 FW (<a href="#geosciences-15-00037-f005" class="html-fig">Figure 5</a>t). The red rectangle marks the IncTal<sub>lith/grad</sub> index fluvial facies in the close-up view of <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>b. (<b>b</b>) Incision of an acute-angle single-channel non-alluvial V-shaped valley into the Devonian chert unit (slope angle 30° ⇒ 35°, talweg angle 2.7° ⇒ 0.7°). See reference profile with steps and pools in (stippled white line = strike of bedding). (<b>c</b>) Geological index map (for more detail and key, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a) with horizontal sinuosity—lithology plus gradient index (HoSi<sub>lith/grad</sub>) given in the white boxes; the knickpoint types 1 and 2 and the start and end points of longitudinal sections are displayed in <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>d–i by X–Y diagrams plotting the station points and inclinations data. The red dots mark mines of talc—(purple), pegmatoid—(dark blue), and Cu-(Au) deposits (yellow). (<b>d</b>) X1-X2, (<b>e</b>) X2-X3, (<b>f</b>) X5-X6, (<b>g</b>) X7-X8, (<b>h</b>) X9-X10, and (<b>i</b>) X11-X12 (for color symbols, see <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>c).</p>
Full article ">Figure 10
<p>Quantification of fluvial and mass wasting deposits as well as their ratios (quantification of fluvial–mass wasting index (Quant<sub>flu/mas</sub>). For geomorphological background, see <a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>f. 1 + 2: Mass wasting deposits: 2.302 to 0.768 per km<sup>2</sup>, fluvial deposits: 0.888 to 0.135 per km<sup>2</sup>. 3: Mass wasting deposits: 0.457 to 0.061 per km<sup>2</sup>, fluvial deposits: 0.335 to 0.017 per km<sup>2</sup>. 4: Mixed type (mass wasting and fluvial): 3.443 to 0.393 per km<sup>2</sup>, mass wasting deposits 3.132 to 0.393 per km<sup>2</sup>, fluvial deposits: 2.798 to 0.028 per km<sup>2</sup>. 5: Mass wasting deposits 0.019 per km<sup>2</sup>, fluvial deposits: 0.076 per km<sup>2</sup>. In the case of very small quantities of the landform-related mass wasting and fluvial deposits, only the ratio of the deposits is presented as a sector diagram. In the case of very high quantities of these unconsolidated deposits, columnar diagram are used instead.</p>
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<p>Composition of siliciclastic deposits of the study area. For geology of the sampling sites, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a. The mineralogical and petrological composition is given by sector diagrams (100%). (<b>a</b>) Abundance of sand-sized light minerals (Quant<sub>san/ligh</sub>). (<b>b</b>) Abundance of sand-sized heavy minerals (Quant<sub>san/heav</sub>). (<b>c</b>) Abundance of gravel-sized debris (Quant<sub>grav/lith</sub>).</p>
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<p>Composition of siliciclastic deposits of the study area. For geology of the sampling sites, see <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a. The mineralogical and petrological composition is given by sector diagrams (100%). (<b>a</b>) Abundance of sand-sized light minerals (Quant<sub>san/ligh</sub>). (<b>b</b>) Abundance of sand-sized heavy minerals (Quant<sub>san/heav</sub>). (<b>c</b>) Abundance of gravel-sized debris (Quant<sub>grav/lith</sub>).</p>
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<p>Landforms hosting gravel-sized debris accumulations subjected to GMS analyses (granulometry–morphometry–situmetry). For sampling sites, see the geological setting presented in <a href="#geosciences-15-00037-f011" class="html-fig">Figure 11</a> and the legend on display in <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a,b. (<b>a</b>) A V-shaped valley (acute angle 22 to 25°) with a small floodplain narrowing upstream towards a gorge (alluvial to non-alluvial). The inset situgram shows a bimodal clast orientation. Sampling site 7. (<b>b</b>) Non-alluvial V-shaped valley (acute angle 25 to 30°) chocked with gravel-sized clast and concentrated in side- and mid-channel longitudinal bars. Sampling site 15. (<b>c</b>) V-shaped valley with a small raised side bar on the slip bank (wide angle 5 to 11°) Sampling site 2. (<b>d</b>) Wide valley (angle 5 to 15°) showing a floodplain with gallery forests lined up along the meander belts, S = 1.407. Sampling site 12. (<b>e</b>) Two valleys telescoped into each other. The large and shallow valley (angle &lt;&lt; 10°) is cut by an acute V-shaped valley near the FLFZ. Sampling site 13 photography facing towards the W with the scarpland on the horizon. (<b>f</b>) A polymodal clast orientation representative of different landscape-forming processes superimposed on each other. Situgram of sampling site 15. (<b>g</b>) Unimodal clast orientation preserved on the raised sidebar of a slip bank. Situgram of sampling site 2.</p>
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<p>Landforms hosting gravel-sized debris accumulations subjected to GMS analyses (granulometry–morphometry–situmetry). For sampling sites, see the geological setting presented in <a href="#geosciences-15-00037-f011" class="html-fig">Figure 11</a> and the legend on display in <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>a,b. (<b>a</b>) A V-shaped valley (acute angle 22 to 25°) with a small floodplain narrowing upstream towards a gorge (alluvial to non-alluvial). The inset situgram shows a bimodal clast orientation. Sampling site 7. (<b>b</b>) Non-alluvial V-shaped valley (acute angle 25 to 30°) chocked with gravel-sized clast and concentrated in side- and mid-channel longitudinal bars. Sampling site 15. (<b>c</b>) V-shaped valley with a small raised side bar on the slip bank (wide angle 5 to 11°) Sampling site 2. (<b>d</b>) Wide valley (angle 5 to 15°) showing a floodplain with gallery forests lined up along the meander belts, S = 1.407. Sampling site 12. (<b>e</b>) Two valleys telescoped into each other. The large and shallow valley (angle &lt;&lt; 10°) is cut by an acute V-shaped valley near the FLFZ. Sampling site 13 photography facing towards the W with the scarpland on the horizon. (<b>f</b>) A polymodal clast orientation representative of different landscape-forming processes superimposed on each other. Situgram of sampling site 15. (<b>g</b>) Unimodal clast orientation preserved on the raised sidebar of a slip bank. Situgram of sampling site 2.</p>
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<p>GMS indices (granulometry–morphology–situmetry) and their fluvial networks of the X1-X2 drainage system and its tributaries X3-X4 and X7-X8. For more details on the numerical parameters of the drainage systems, see <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>, and for geology, <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>. (<b>a</b>) Granulometry of gravel-sized debris illustrated by the numerical index QuantSed<sub>gran/sort</sub> with a cumulative frequency grain-size distribution of all samples from the study area above represented by the blue shaded area. (<b>b</b>) The regional variation in the minimum values of the QuantSed<sub>morp/roun</sub> of gravel-sized debris (map above) and a reference site showing the QuantSed<sub>morp/roun</sub> compared with the QuantSed<sub>morp/cycl</sub> numerically and visually for the most widespread lithology of the study area, the muscovite-biotite gneisses. (<b>c</b>) Situmetry of gravel-sized debris illustrated by 360° circle diagrams showing the true orientation of the river course and of various maxima of the longest axis of gravel clasts (<b>above</b>). The reference samples show a topographically non-oriented semi-circle rose diagram with a trimodal arrangement of gravel clasts with a sharpness of maximum as follows: first maximum 60.0, second maximum 19.4, and third maximum 19.0.</p>
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<p>GMS indices (granulometry–morphology–situmetry) and their fluvial networks of the X1-X2 drainage system and its tributaries X3-X4 and X7-X8. For more details on the numerical parameters of the drainage systems, see <a href="#geosciences-15-00037-f009" class="html-fig">Figure 9</a>, and for geology, <a href="#geosciences-15-00037-f002" class="html-fig">Figure 2</a>. (<b>a</b>) Granulometry of gravel-sized debris illustrated by the numerical index QuantSed<sub>gran/sort</sub> with a cumulative frequency grain-size distribution of all samples from the study area above represented by the blue shaded area. (<b>b</b>) The regional variation in the minimum values of the QuantSed<sub>morp/roun</sub> of gravel-sized debris (map above) and a reference site showing the QuantSed<sub>morp/roun</sub> compared with the QuantSed<sub>morp/cycl</sub> numerically and visually for the most widespread lithology of the study area, the muscovite-biotite gneisses. (<b>c</b>) Situmetry of gravel-sized debris illustrated by 360° circle diagrams showing the true orientation of the river course and of various maxima of the longest axis of gravel clasts (<b>above</b>). The reference samples show a topographically non-oriented semi-circle rose diagram with a trimodal arrangement of gravel clasts with a sharpness of maximum as follows: first maximum 60.0, second maximum 19.4, and third maximum 19.0.</p>
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<p>The manual from fieldwork (geological, geomorphological, and lithological mapping) to numerical geomorphology &gt; geomorphometry (genetic geosciences) and economic and environmental geology (applied geosciences). The landform indices are the missing links. See also <a href="#geosciences-15-00037-t001" class="html-table">Table 1</a>.</p>
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<p>The evolution of landscape and re-orientation of the drainage system from the ancient Donau River to the modern Rhein River systems on display as a series of landscape contours true to scale as a function of altitude and distance based upon the VeSi<sub>val</sub>, VaSlAn<sub>alti</sub>, IncTal<sub>lith/grad</sub>, and geochronological data (for reference, see text). Periods correspond to the relief generations shown in plan view in <a href="#geosciences-15-00037-f003" class="html-fig">Figure 3</a>f,g. For the geology and landforms of each cross-section, see <a href="#geosciences-15-00037-f004" class="html-fig">Figure 4</a> and <a href="#geosciences-15-00037-f005" class="html-fig">Figure 5</a>. (<b>a</b>) Stage of peneplanation at full swing (Ro). (<b>b</b>) Stage of peneplanation (R1) transitioning into pediplanation (R2) (fossiliferous badlands). (<b>c</b>) Stage of the re-orientation of the paleogradientaccompanied by river piracy (R2e) and linear erosion (R3). (<b>d</b>) Stage of the re-direction of the fluvial regime from dip to strike stream and perched pedimentation (R4).</p>
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<p>Clay minerals (QuantClaSil), sand-sized light minerals (QuantSan<sub>/ligh</sub>), heavy minerals (QuantSan<sub>heav</sub>), and gravel (QuantGrav<sub>lith</sub>) of different lithologies represented by the range of dispersal off their source rocks.</p>
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<p>The “graphical conclusions” to underscore what the compositional terrain analysis is all about. The tripartite subdivision of the geoscientific disciplines involved: (<b>a</b>) A digital terrain model showing the interrelationship between morphotectonic linear architectural elements (fold axis), and hydrography (strike stream vs. dip stream). (<b>b</b>) The sedimentological GMS technology encompassing <b>g</b>ranulometry, morphometry, and <b>s</b>itumetry. (<b>c</b>) The pie-chart diagram commonly used in sediment petrography to quantify the lithological changes during transport.</p>
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23 pages, 25801 KiB  
Article
A Large-Scale Focused Fluid Flow Zone Between Atolls in the Xisha Islands (South China Sea): Types, Characteristics, and Evolution
by Jixiang Zhao, Benjun Ma, Zhiliang Qin, Wenjian Lan, Benyu Zhu, Shuyi Pang, Mingzhe Li and Ruining Wang
J. Mar. Sci. Eng. 2025, 13(2), 216; https://doi.org/10.3390/jmse13020216 - 23 Jan 2025
Viewed by 356
Abstract
A large number of seabed depressions, covering an area of 2500 km2 in the Xisha Massif of the South China Sea, are investigated using newly collected high-resolution acoustic data. By analyzing the morphological features and seismic attributes of the focused fluid flow [...] Read more.
A large number of seabed depressions, covering an area of 2500 km2 in the Xisha Massif of the South China Sea, are investigated using newly collected high-resolution acoustic data. By analyzing the morphological features and seismic attributes of the focused fluid flow system, five geological structures are recognized and described in detail, including pockmarks, volcanic mounds, pipes, faults, and forced folds. Pockmarks and volcanic mounds occur as clustered groups and their distributions are related to two large-scale volcanic zones with chaotic seismic reflections. Pipes, characterized by disordered seismic reflections, mainly occur within the focused fluid flow zone (FFFZ) and directly link with the large-scale deep volcano and its surrounding areas. Faults and fractures mainly occur along pipes and extend to the seafloor, commonly presenting lateral walls of mega-pockmarks. Forced folds are primarily clustered above volcanic zones and commonly restricted between faults or pipes, characterized by sediment deformations as indicated in seismic profiles. By comprehensive analysis of the above observations and a simplified simulation model, the volcanism-induced hydrothermal fluid activities are argued herein to contribute to these focused fluid flow structures. In addition, traces of suspected submarine instability disasters such as landslides have been found in this sea area, and more observational data will be needed to determine whether seafloor fluid flow zones can be used as a predictor of seafloor instability in the future. Full article
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<p>(<b>A</b>–<b>C</b>) Series of neritic carbonate platforms in the Xisha waters. The data are sourced from the General Bathymetric Chart of the Oceans (GEBCO).</p>
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<p>The overall research process.</p>
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<p>The seafloor morphologies (<b>A</b>), where box a represents the main research area of the seabed depression; box b represents the main research area of the submarine volcanos and mounds; (<b>B</b>) shows the slope in the study area, and (<b>C</b>) (refer to [<a href="#B23-jmse-13-00216" class="html-bibr">23</a>]) shows the simplified stratigraphic column of the study area with depositional units the basin evolution of the Qiongdongnan Basin (QDNB), and the lithology of a well in the Xisha uplift zone.</p>
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<p>The seabed depressions identified in the study area a, where (<b>A</b>) is a two-dimensional overall schematic diagram of this region, while (<b>B</b>) is three-dimensional. (<b>C</b>) is detail diagram of the area showing the shapes of crescentic depressions. (<b>D</b>) is detail diagram of the area mainly showing the shapes of polygonal depressions.</p>
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<p>Topographic depression profile map of the research area (Line 3 in <a href="#jmse-13-00216-f003" class="html-fig">Figure 3</a>A), where P<sub>1</sub>–P<sub>6</sub> represent different pockmarks, respectively, while V<sub>1</sub> represents volcano I and V<sub>2</sub> represents volcano II. (<b>A</b>) shows the water depth and slope on the Line 3. (<b>B</b>) shows the dimensions and shape of the identified depression.</p>
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<p>Topographic depression profile map of the research area a, where (<b>A</b>) is a two-dimensional overall schematic diagram of this region, and (<b>B</b>,<b>C</b>) are detail diagrams with seismic lines.</p>
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<p>Submarine volcanos and mounds in the study area b, where (<b>A</b>) is a two-dimensional overall schematic diagram of this region, while (<b>B</b>) is three-dimensional. (<b>C</b>,<b>D</b>) are detail diagrams of some areas, mainly showing the shapes of volcanic mounds and the depressions around them.</p>
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<p>The shallow submarine formations’ stratigraphic profile (line 1 in <a href="#jmse-13-00216-f003" class="html-fig">Figure 3</a>A) between the volcanic mounds around submarine volcano II, where V<sub>2</sub> represent volcano II. (<b>A</b>) shows the terrain near the seismic line. (<b>B</b>) is the unannotated seismic section. (<b>C</b>) is a seismic section annotated after manual interpretation.</p>
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<p>The shallow submarine formations’ stratigraphic profile (line 2 in <a href="#jmse-13-00216-f003" class="html-fig">Figure 3</a>A) in the study area, where P<sub>7</sub>–P<sub>9</sub> represent different pockmarks, respectively. (<b>A</b>) shows the terrain near the seismic line. (<b>B</b>) is the unannotated seismic section. (<b>C</b>) is a seismic section annotated after manual interpretation.</p>
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<p>The shallow submarine formations’ stratigraphic profile (line 3 in <a href="#jmse-13-00216-f003" class="html-fig">Figure 3</a>A) between submarine volcano I and submarine volcano II, where P1–P6 represent different pockmarks, respectively, while V<sub>1</sub> represents volcano I and V<sub>2</sub> represents volcano II. (<b>A</b>) shows the terrain near the seismic line. (<b>B</b>) is the unannotated seismic section. (<b>C</b>) is a seismic section annotated after manual interpretation.</p>
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<p>Shape and structure of the seabed after hydrothermal activity based on simulation models. (<b>A</b>–<b>C</b>,<b>E</b>) show the simulation results after a period of volcanic activity. (<b>C</b>) shows the details of (<b>D</b>), and (<b>F</b>) show the details of (<b>E</b>).</p>
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<p>Evolutionary pattern for the morphological structure of the focused fluid flow structural units in the study area. (<b>A</b>–<b>D</b>) are simplified schematic diagrams of the changes in the morphological structure of the focused fluid flow structural units. (<b>a</b>–<b>d</b>) show the three-dimensional changes in the morphological structure of the focused fluid flow structural units at different stages.</p>
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17 pages, 12602 KiB  
Article
Demagnetization Analysis and Optimization of Bonded Nd-Fe-B Magnet Rings in Brushless DC Motors
by Yinan Wang, Hao Zhan, Yanyan Gong, Mingxu Wang, Juntao Yu, Ze Zhang, Yuanfei Yang and Li Wang
Machines 2025, 13(2), 75; https://doi.org/10.3390/machines13020075 - 22 Jan 2025
Viewed by 276
Abstract
Bonded Nd-Fe-B magnets have greater freedom of shape than sintered Nd-Fe-B magnets. The ring structure is one of the typical structures of bonded Nd-Fe-B materials. In this paper, we analyzed the generation and spread of demagnetization fault (DMF) and changes in motor performance. [...] Read more.
Bonded Nd-Fe-B magnets have greater freedom of shape than sintered Nd-Fe-B magnets. The ring structure is one of the typical structures of bonded Nd-Fe-B materials. In this paper, we analyzed the generation and spread of demagnetization fault (DMF) and changes in motor performance. Meanwhile, a BLDC fitted with a bonded Nd-Fe-B magnet ring was analyzed for DMF under actual overload conditions. DMF occurred with obvious localization and variability, which was mainly concentrated on the side of each pole opposite to the direction of the motor’s operation, near the weak magnetic zones. The experimental results show that back electromotive force (EMF) and its harmonic had the same variation trends as the surface radial flux density of the magnet ring. The analysis with the EMF waveform and total harmonic distortion (THD) were proposed as a method for diagnosing the DMF. Finally, this paper presents a modified magnet ring. The anti-demagnetization capability of the modified magnet ring is effectively improved. This research can provide a reference for the design analysis of BLDCs using bonded Nd-Fe-B magnet rings. Full article
(This article belongs to the Section Electrical Machines and Drives)
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<p>Irreversible demagnetization: (<b>a</b>) disregarding temperature; (<b>b</b>) considering temperature; (<b>c</b>) different magnetization positions.</p>
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<p>Schematic of the experimental motor using a bonded magnet ring.</p>
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<p>Voltage source inverter circuit.</p>
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<p>Magnetization rate for magnet rings (normalization).</p>
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<p>Schematic diagram of single pole magnetization.</p>
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<p>Flux maps of motor magnetic flux density for different load cases: (<b>a</b>) normal load, (<b>b</b>) 1.5 times load, (<b>c</b>) double load.</p>
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<p>Demagnetization ratio maps in different load cases: (<b>a</b>) normal load, (<b>b</b>) 1.5 times load, (<b>c</b>) double load.</p>
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<p>Comparison of B<sub>s</sub> after DMF with different loads.</p>
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<p>Harmonic comparison of B<sub>s</sub> in different DMF cases.</p>
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<p>Waveform comparison of back EMF after DMF in different loads.</p>
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<p>Harmonic comparison of back EMF for different DMF cases.</p>
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<p>Experiment protype: (<b>a</b>) test motor, (<b>b</b>) magnet ring rotor.</p>
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<p>Test platforms: (<b>a</b>) load test, (<b>b</b>) single-phase back EMF test.</p>
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<p>B<sub>s</sub> distribution after demagnetization with different loads: (<b>a</b>) normal load, (<b>b</b>) 1.5 times load, (<b>c</b>) double load.</p>
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<p>Comparison of B<sub>s</sub> at the axial mid-position of the magnet ring.</p>
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<p>Harmonic analysis of the Bs in the axial mid-position of the magnet ring.</p>
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<p>Back EMF after different load tests.</p>
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<p>Harmonic analysis of back EMF after different load tests.</p>
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<p>Modified inner diameter magnet ring.</p>
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<p>Parametric optimization search for <span class="html-italic">H</span> values.</p>
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<p>Comparison of demagnetization results in double load case: (<b>a</b>) original magnet ring, (<b>b</b>) modified magnet ring.</p>
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<p>Comparison of B<sub>s</sub> after demagnetization of the original and modified magnet ring.</p>
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<p>Comparison of back EMF after demagnetization of the original and modified magnet ring.</p>
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26 pages, 14152 KiB  
Article
Evaluation of Water Inrush Risk in the Fault Zone of the Coal Seam Floor in Madaotou Coal Mine, Shanxi Province, China
by Shuai Yu, Hanghang Ding, Moyuan Yang and Menglin Zhang
Water 2025, 17(2), 259; https://doi.org/10.3390/w17020259 - 17 Jan 2025
Viewed by 391
Abstract
As coal seams are mined at greater depths, the threat of high water pressure from the confined aquifer in the floor that mining operations face has become increasingly prominent. Taking the Madaotou mine field in the Datong Coalfield as the research object, in [...] Read more.
As coal seams are mined at greater depths, the threat of high water pressure from the confined aquifer in the floor that mining operations face has become increasingly prominent. Taking the Madaotou mine field in the Datong Coalfield as the research object, in the context of mining under pressure, for the main coal seams in the mining area, first of all, an improved evaluation method for the vulnerability of floor water inrush is adopted for hazard prediction. Secondly, numerical simulation is used to conduct a simulation analysis on the fault zones in high-risk areas. By using the fuzzy C-means clustering method (FCCM) to improve the classification method for the normalized indicators in the original variable-weight vulnerability evaluation, the risk zoning for water inrush from the coal seam floor is determined. Then, through the numerical simulation method, a simulation analysis is carried out on high-risk areas to simulate the disturbance changes of different mining methods on the fault zones so as to put forward reasonable mining methods. The results show that the classification of the variable-weight intervals of water inrush from the coal seam floor is more suitable to be classified by using fuzzy clustering, thus improving the prediction accuracy. Based on the time effect of the delayed water inrush of faults, different mining methods determine the duration of the disturbance on the fault zones. Therefore, by reducing the disturbance time on the fault zones, the risk of karst water inrush from the floor of the fault zones can be reduced. Through prediction evaluation and simulation analysis, the evaluation of the risk of water inrush in coal mines has been greatly improved, which is of great significance for ensuring the safe and efficient mining of mines. Full article
(This article belongs to the Special Issue Engineering Hydrogeology Research Related to Mining Activities)
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<p>The runoff directions from west to east.</p>
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<p>Flowchart of the methodology used in this study.</p>
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<p>State–variable-weight vector diagram ([<a href="#B36-water-17-00259" class="html-bibr">36</a>]).</p>
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<p>Geological conceptual model of the study area.</p>
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<p>Numerical model of fluid–structure interaction.</p>
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<p>Fuzzy C-mean variable-weight evaluation division of the No. 3–5 coal seam floor.</p>
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<p>Risk assessment zone of the water inrush coefficient of No. 3–5 coal.</p>
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<p>Model initial equilibrium state.</p>
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<p>Development law of the plastic zone at different advancing distances in the working face. (<b>a</b>) Advance 20 m. (<b>b</b>) Advance 40 m. (<b>c</b>) Advance 80 m. (<b>d</b>) Advance 120 m. (<b>e</b>) Advance 160 m. (<b>f</b>) Advance 200 m. (<b>g</b>) Advance 240 m. (<b>h</b>) Advance 280 m.</p>
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<p>Distribution law of stress field at different advancing distances in working face. (<b>a</b>) Advance 20 m. (<b>b</b>) Advance 40 m. (<b>c</b>) Advance 80 m. (<b>d</b>) Advance 120 m. (<b>e</b>) Advance 160 m. (<b>f</b>) Advance 200 m. (<b>g</b>) Advance 240 m. (<b>h</b>) Advance 280 m.</p>
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<p>Variation law of the seepage field at different advancing distances in the working face. (<b>a</b>) Advance 20 m. (<b>b</b>) Advance 40 m. (<b>c</b>) Advance 80 m. (<b>d</b>) Advance 120 m. (<b>e</b>) Advance 160 m. (<b>f</b>) Advance 200 m. (<b>g</b>) Advance 240 m. (<b>h</b>) Advance 280 m.</p>
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<p>Local seepage diagram of the fault zone during forward mining.</p>
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<p>Development law of the plastic zone at different advancing distances in the working face. (<b>a</b>) Advance 20 m. (<b>b</b>) Advance 40 m. (<b>c</b>) Advance 80 m. (<b>d</b>) Advance 120 m. (<b>e</b>) Advance 160 m. (<b>f</b>) Advance 200 m. (<b>g</b>) Advance 240 m. (<b>h</b>) Advance 280 m.</p>
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<p>Distribution law of the stress field at different advancing distances in the working face. (<b>a</b>) Advance 20 m. (<b>b</b>) Advance 40 m. (<b>c</b>) Advance 80 m. (<b>d</b>) Advance 120 m. (<b>e</b>) Advance 160 m. (<b>f</b>) Advance 200 m. (<b>g</b>) Advance 240 m. (<b>h</b>) Advance 280 m.</p>
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<p>Variation law of the seepage field at different advancing distances in the working face. (<b>a</b>) Advance 20 m. (<b>b</b>) Advance 40 m. (<b>c</b>) Advance 80 m. (<b>d</b>) Advance 120 m. (<b>e</b>) Advance 160 m. (<b>f</b>) Advance 200 m. (<b>g</b>) Advance 240 m. (<b>h</b>) Advance 280 m.</p>
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<p>Local seepage diagram of the fault zone during retreat mining.</p>
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20 pages, 34237 KiB  
Article
Spatiotemporal Analysis of Atmospheric Chemical Potential Anomalies Associated with Major Seismic Events (Ms ≥ 7) in Western China: A Multi-Case Study
by Qijun Jiao, Qinqin Liu, Changgui Lin, Feng Jing, Jiajun Li, Yuxiang Tian, Zhenxia Zhang and Xuhui Shen
Remote Sens. 2025, 17(2), 311; https://doi.org/10.3390/rs17020311 - 16 Jan 2025
Viewed by 440
Abstract
Focusing on major earthquakes (EQs; MS ≥ 7) in Western China, this study primarily analyzes the fluctuation in Atmospheric Chemical Potential (ACP) before and after the Wenchuan, Yushu, Lushan, Jiuzhaigou, and Maduo EQs via Climatological Analysis of Seismic Precursors Identification (CAPRI). The distribution [...] Read more.
Focusing on major earthquakes (EQs; MS ≥ 7) in Western China, this study primarily analyzes the fluctuation in Atmospheric Chemical Potential (ACP) before and after the Wenchuan, Yushu, Lushan, Jiuzhaigou, and Maduo EQs via Climatological Analysis of Seismic Precursors Identification (CAPRI). The distribution of vertical ACP revealed distinct altitude-dependent characteristics. The ACP at lower atmospheric layers (100–2000 m) exhibited a high correlation, and this correlation decreased with increasing altitude. Anomalies were detected within one month prior to each of the five EQs studied, with the majority occurring 14 to 30 days before the events, followed by a few additional anomalies. The spatial distribution of anomalies is consistent with the distribution of fault zones, with noticeable fluctuation in surrounding areas. The ACP at an altitude of 200 m gave a balance between sensitivity to seismic signals and minimal surface interference and proved to be optimal for EQ monitoring in Western China. The results offer a significant reference for remote sensing studies related to EQ monitoring and the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) model, thereby advancing our understanding of pre-seismic atmospheric variations in Western China. Full article
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<p>The epicenters, average altitudes, and associated fault zones of the five selected earthquakes (EQs) in this study. The average altitude data were derived by calculating the mean value within a 700 km half-side length centered on the epicenter, using the mid-layer height data from each model layer of MERRA-2. The red dots represent the epicenters, the blue solid lines represent the fault zones, and the yellow solid lines represent the provincial boundaries.</p>
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<p>During the Wenchuan (<b>a</b>), Yushu (<b>b</b>), Lushan (<b>c</b>), Jiuzhaigou (<b>d</b>), and Maduo (<b>e</b>) EQs, Atmospheric Chemical Potential (ACP) variations were observed across eight distinct altitudinal strata during the EQ period, with data points recorded every 3 h. The ACP values in the figure represent the spatial average with the epicenter as the center and a half-side length of 700 km. The red dashed vertical line on the right represents the EQ occurrence.</p>
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<p>PCC (Pearson Correlation Coefficient) of ACPs at eight distinct altitudinal strata during the Wenchuan (<b>a</b>), Yushu (<b>b</b>), Lushan (<b>c</b>), Jiuzhaigou (<b>d</b>), and Maduo (<b>e</b>) EQ periods.</p>
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<p>Monitoring maps of ACP anomalous (200 m) response at 18:00 during the EQ periods for Wenchuan (<b>a</b>), Yushu (<b>b</b>), Lushan (<b>c</b>), Jiuzhaigou (<b>d</b>), and Maduo (<b>e</b>) after removing the global warming effect using the CAPRI algorithm. Comparison of the time series (dashed red line) concerning the historical mean (continuous blue line). The stripes indicate 1.0 (cyan), 1.5 (green), and 2.0 (yellow) times the standard deviation. The red vertical line on the right represents EQ occurrence. The red circles indicate that anomalies greater than 2<math display="inline"><semantics> <mi>σ</mi> </semantics></math> appeared.</p>
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<p>ACP anomaly distribution maps during the period of the 2008 Wenchuan EQ. These maps were obtained by subtracting the spatial distribution on the reference date (5 May) from the distributions on the anomaly dates 28 February (<b>a</b>), 1 March (<b>b</b>), and 24 April (<b>c</b>). “Mean” represents the spatial average of the figure. The epicenter is indicated by an asterisk in the figure, and grey lines indicate major faults in the study area.</p>
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<p>ACP anomaly distribution maps during the period of the 2010 Yushu EQ. These maps were obtained by subtracting the spatial distribution on the reference date (8 April) from the distributions on the anomaly dates 15 March (<b>a</b>), 18 March (<b>b</b>), 20 March (<b>c</b>), 7 April (<b>d</b>), 26 April (<b>e</b>), and 27 April (<b>f</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2013 Lushan EQ. These maps were obtained by subtracting the spatial distribution on the reference date (26 March) from the distributions on the anomaly dates 4 March (<b>a</b>), 7 March (<b>b</b>), and 12 March (<b>c</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2017 Jiuzhaigou EQ. These maps were obtained by subtracting the spatial distribution on the reference date (14 August) from the distributions on the anomaly dates of 9 July (<b>a</b>), 10 July (<b>b</b>), and 9 August (<b>c</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2017 Maduo EQ. These maps were obtained by subtracting the spatial distribution on the reference date (25 May) from the distributions on the anomaly dates of 14 March (<b>a</b>), 21 March (<b>b</b>), 22 March (<b>c</b>), and 7 May (<b>d</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>Monitoring maps of ACP anomalous (200 m) response at 18:00 in 2020 during the EQ periods for Wenchuan (<b>a</b>), Yushu (<b>b</b>), Lushan (<b>c</b>), Jiuzhaigou (<b>d</b>), and Maduo (<b>e</b>) after removing the global warming effect using the CAPRI algorithm. Labeled as shown in <a href="#remotesensing-17-00311-f004" class="html-fig">Figure 4</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2008 Wenchuan EQ. These maps were obtained by subtracting the spatial distribution on the reference date (7 March) from the distributions on the anomaly dates of 28 February (<b>a</b>), 1 March (<b>b</b>), and 24 April (<b>c</b>). “Mean” represents the spatial average of the figure. Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2010 Yushu EQ. These maps were obtained by subtracting the spatial distribution on the reference date (27 February) from the distributions on the anomaly dates of 15 March (<b>a</b>), 18 March (<b>b</b>), 20 March (<b>c</b>), 7 April (<b>d</b>), 26 April (<b>e</b>), and 27 April (<b>f</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2013 Lushan EQ. These maps were obtained by subtracting the spatial distribution on the reference date (20 March) from the distributions on the anomaly dates of 4 March (<b>a</b>), 7 March (<b>b</b>), and 12 March (<b>c</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2017 Jiuzhaigou EQ. These maps were obtained by subtracting the spatial distribution on the reference date (3 July) from the distributions on the anomaly dates of 9 July (<b>a</b>), 10 July (<b>b</b>), and 9 August (<b>c</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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<p>ACP anomaly distribution maps during the period of the 2017 Maduo EQ. These maps were obtained by subtracting the spatial distribution on the reference date (28 March) from the distributions on the anomaly dates of 14 March (<b>a</b>), 21 March (<b>b</b>), 22 March (<b>c</b>), and 7 May (<b>d</b>). Labeled as shown in <a href="#remotesensing-17-00311-f005" class="html-fig">Figure 5</a>.</p>
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31 pages, 31280 KiB  
Article
Three-Dimensional Digital Documentation for the Conservation of the Prambanan Temple Cluster Using Guided Multi-Sensor Techniques
by Anindya Sricandra Prasidya, Irwan Gumilar, Irwan Meilano, Ikaputra Ikaputra, Rochmad Muryamto and Erlyna Nour Arrofiqoh
Heritage 2025, 8(1), 32; https://doi.org/10.3390/heritage8010032 - 16 Jan 2025
Viewed by 533
Abstract
The Prambanan Temple cluster is a world heritage site that has significant value for humanity, a multiple zone cluster arrangement of highly ornamented towering temples, and a Hindu architectural pattern design. It lies near the Opak Fault, at the foothills of Mount Merapi, [...] Read more.
The Prambanan Temple cluster is a world heritage site that has significant value for humanity, a multiple zone cluster arrangement of highly ornamented towering temples, and a Hindu architectural pattern design. It lies near the Opak Fault, at the foothills of Mount Merapi, on an unstable ground layer, and is surrounded by human activities in Yogyakarta, Indonesia. The site’s vulnerability implies the necessity of 3D digital documentation for its conservation, but its complexity poses difficulties. This work aimed to address this challenge by introducing the utilization of architectural pattern design (APD) to guide multi-sensor line-ups for documentation. First, APDs were established from the literature to derive the associated multiple detail levels; then, multiple sensors and modes of light detection and ranging (Lidar) scanners and photogrammetry were utilized according to their detail requirements and, finally, point cloud data were processed, integrated, assessed, and validated by the proof of the existence of an APD. The internal and external qualities of each sensor result showed the millimeter- to centimeter-range root mean squared error, with the terrestrial laser scanner (TLS) having the best accuracy, followed by aerial close-range and terrestrial-mode photogrammetry and nadiral Lidar and photogrammetry. Two relative cloud distance analyses of every point cloud model to the reference model (TLS) returned the millimeter and centimeter ranges of the mean distance values. Furthermore, visually, every point cloud model from each sensor successfully complemented each other. Therefore, we can conclude that our approach is promising for complex heritage documentation. These results provide a solid foundation for future analyses, particularly in assessing structural vulnerabilities and informing conservation strategies. Full article
(This article belongs to the Special Issue 3D Reconstruction of Cultural Heritage and 3D Assets Utilisation)
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<p>The Prambanan Temple cluster’s location and its concentric layout arrangement.</p>
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<p>The proposed workflow. Solid arrows represent the main data flow, while the dashed arrows represent the supporting data flow.</p>
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<p>Data acquisition concept for three different scale levels. Darker colors represent larger scale levels, while lighter colors represent smaller scale levels. Google Earth and SketchUp 3D Warehouse provide background images for the left and center illustrations, respectively.</p>
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<p>Distribution of GDCPs (<b>a</b>) and FDCPs (<b>b</b>).</p>
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<p>Summary of the quality assessment of each sensor processing result.</p>
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<p>Orthophoto result of the sites that cover the first and second courtyards.</p>
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<p>Registered and georeferenced 3D point clouds from (<b>a</b>) TLS 2020 and (<b>b</b>) TLS 2023.</p>
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<p>Point cloud model from aerial UAV Lidar.</p>
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<p>Dense point cloud model from CR-UAVP integrated with terrestrial photogrammetry.</p>
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<p>Point cloud results from multiple sensors and their combinations (the example of the Brahma Temple). (<b>a</b>) Nadiral UAV Lidar; (<b>b</b>) TLS; (<b>c</b>) CR-UAV photogrammetry; (<b>d</b>) terrestrial photogrammetry; (<b>e</b>) combination of each sensor point clouds. The true color and texture of the temple are presented by (<b>b</b>–<b>d</b>), while (<b>a</b>) only displays the scalar color scale based on the Z coordinate.</p>
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<p>C2C and M3C2 Euclidean distance analysis results of the six main temples of interest.</p>
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<p>C2C results of the corridor part of the Shiva Temple.</p>
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<p>Four sample measurements captured on the base part (Bhurloka) of a single temple.</p>
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<p>Rectangular-based planimetric proportions of the Garuda, Nandhi, and Hamsha Temples.</p>
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<p>The parameter of the Cartesian–cruciform-based planimetric proportion.</p>
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<p>Cartesian–cruciform planimetric proportion of the Shiva, Vishnu, and Brahma Temples (Bhurloka part).</p>
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<p>Cartesian–cruciform planimetric proportion of the Shiva, Vishnu, and Brahma Temples (Bhuvarloka part).</p>
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<p>Cartesian–cruciform planimetric proportion of the Garuda, Nandhi, and Hamsha Temples (Bhuvarloka part).</p>
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<p>Cartesian–cruciform planimetric proportion of the Shiva, Vishnu, and Brahma Temples (Svarloka part).</p>
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<p>Cartesian–cruciform planimetric proportion of the Garuda, Nandhi, and Hamsha Temples (Svarloka part).</p>
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14 pages, 5030 KiB  
Article
Strength Prediction Model for Cohesive Soil–Rock Mixture with Rock Content
by Yang Sun, Jianyong Xin, Junchao He, Junping Yu, Haibin Ding and Yifan Hu
Appl. Sci. 2025, 15(2), 843; https://doi.org/10.3390/app15020843 - 16 Jan 2025
Viewed by 451
Abstract
Fault fracture zones, characterized by high weathering, low strength, and a high degree of fragmentation, are common adverse geological phenomena encountered in tunneling projects. This paper performed a series of large-scale triaxial compression tests on the cohesive soil–rock mixture (SRM) samples with dimensions [...] Read more.
Fault fracture zones, characterized by high weathering, low strength, and a high degree of fragmentation, are common adverse geological phenomena encountered in tunneling projects. This paper performed a series of large-scale triaxial compression tests on the cohesive soil–rock mixture (SRM) samples with dimensions of 500 mm × 1000 mm to investigate the influence of rock content PBV (20, 40, and 60% by volume), rock orientation angle α, and confining pressure on their macro-mechanical properties. Furthermore, a triaxial numerical model, which takes into account PBV and α, was constructed by means of PFC3D to investigate the evolution of the mechanical properties of the cohesive SRM. The results indicated that (1) the influence of the α is significant at high confining pressures. For the sample with an α of 0°, shear failure was inhibited, and the rock blocks tended to break more easily, while the samples with an α of 30° and 60° exhibited fewer fragmentations. (2) PBV significantly affected the shear behaviors of the cohesive SRM. The peak deviatoric stress of the sample with an α of 0° was minimized at lower PBV (<20%), while both the deformation modulus and peak deviatoric stress were larger at high PBV (>60%). Based on these findings, an equation correlating shear strength and PBV was proposed under consistent α and matrix strength conditions. This equation effectively predicts the shear strength of the cohesive SRM with different PBV values. Full article
(This article belongs to the Special Issue Advances and Challenges in Rock Mechanics and Rock Engineering)
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<p>Artificial fault mud sample.</p>
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<p>Undrained shear strength of cohesive fault mud with different ratios.</p>
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<p>Artificial fault mud bentonite matrix sample.</p>
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<p>Soil matrix damage pattern.</p>
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<p>GSZ501 large triaxial compression tester for coarse-grained soil (size sample of Φ500 × 1000 mm).</p>
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<p>Stress–strain curves at a P<sub>BV</sub> of 40%.</p>
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<p>Stress-strain curves for samples with different P<sub>BV</sub> values.</p>
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<p>Relationship curve between P<sub>BV</sub> and shear strength.</p>
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<p>Calibration results.</p>
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<p>Failure modes.</p>
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<p>Simulated stress–strain curves of the cohesive SRM at a confining pressure of 400 kPa.</p>
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<p>Scatter plot of P<sub>BV</sub> vs. shear strength.</p>
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<p>Fitted graph.</p>
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<p>Relationship curve between P<sub>BV</sub> and shear strength.</p>
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16 pages, 5605 KiB  
Article
Stability Analysis of Surrounding Rock in Mining Tunnels Based on Microseismic Monitoring and Numerical Simulation
by Hao Wu, Qingfeng Li, Chuanqu Zhu and Pei Tang
Sustainability 2025, 17(2), 630; https://doi.org/10.3390/su17020630 - 15 Jan 2025
Viewed by 457
Abstract
In response to the safety hazards and environmental impacts caused by the decrease in the stability of the surrounding rock of the roadway and the frequent occurrence of microseismic activities during coal mining, the 4331 fully mechanized mining face of Nanpingdong Coal Mine [...] Read more.
In response to the safety hazards and environmental impacts caused by the decrease in the stability of the surrounding rock of the roadway and the frequent occurrence of microseismic activities during coal mining, the 4331 fully mechanized mining face of Nanpingdong Coal Mine was selected as a case study. Microseismic monitoring technology was used to analyze the spatial distribution of microseismic events in the surrounding rock during mining, and by establishing a FLAC3D numerical model, the displacement of surrounding rock and the evolution law of plastic zone during mining process are studied. The results confirmed that elastic strain energy in the rock is the primary source of microseismic energy. Using FISH language, a distribution cloud map of elastic strain energy was generated and compared with the microseismic event distribution and energy results. The findings indicate that as mining advances, the frequency and energy of microseismic events increase, particularly near faults, with roadway roof rupture exacerbating the events. The distribution of microseismic events correlates strongly with the depth of mining face advancement, highlighting the significant impact of mining activities on surrounding rock stability. The numerical simulation results closely align with on-site microseismic monitoring data, validating the simulation’s accuracy. This study proposes a method for dynamic monitoring and control of roadway surrounding rock stability through real-time microseismic monitoring and numerical simulation, aiming to mitigate surface environmental damage from underground mining. Full article
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<p>Comprehensive histogram of coal seams.</p>
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<p>Microseismic sensor measurement point deployment and control map.</p>
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<p>Distribution of microseismic events in the working face.</p>
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<p>Schematic diagram of numerical simulation scheme.</p>
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<p>Stress distribution cloud map under different grid densities.</p>
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<p>Distribution diagram of stress field evolution data in the working face.</p>
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<p>Contour map of the development of the plastic zone in the mining face.</p>
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<p>Comparison of numerical simulation results with microseismic and field exploration results.</p>
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22 pages, 17971 KiB  
Article
Experimental Study on Tunnel Failure Mechanism and the Effect of Combined Anti-Dislocation Measures Under Fault Dislocation
by Jiaxuan Du, Songhong Yan, Weiyu Sun, Mingxing Cao and Yuxiang Li
Appl. Sci. 2025, 15(2), 765; https://doi.org/10.3390/app15020765 - 14 Jan 2025
Viewed by 453
Abstract
Taking the tunnels crossing active faults in China’s Sichuan–Tibet Railway as the research background, experimental studies were conducted using a custom-developed split model box. The research focused on the cracking characteristics of the surrounding rock surface under the action of strike-slip faults, the [...] Read more.
Taking the tunnels crossing active faults in China’s Sichuan–Tibet Railway as the research background, experimental studies were conducted using a custom-developed split model box. The research focused on the cracking characteristics of the surrounding rock surface under the action of strike-slip faults, the progressive failure process of the tunnel model, and the mechanical response of the tunnel lining. In-depth analyses were performed on the tunnel damage mechanism under strike-slip fault action and the mitigation effects of combined anti-dislocation measures. The results indicate the following: Damage to the upper surface of the surrounding rock primarily occurs within the fault fracture zone. The split model box enables the graded transfer of fault displacement within this zone, improving the boundary conditions for the model test. Under a 50 mm fault displacement, the continuous tunnel experiences severe damage, leading to a complete loss of function. The damage is mainly characterized by circumferential shear and is concentrated within the fault fracture zone. The zone 20 cm to 30 cm on both sides of the fault plane is the primary area influenced by tunnel forces. The force distribution on the left and right sidewalls of the lining exhibits an anti-symmetric pattern across the fault plane. The left side wall is extruded by surrounding rock in the moving block, while the right side wall experiences extrusion from the surrounding rock in the fracture zone, and there is a phenomenon of dehollowing and loosening of the surrounding rock on both sides of the fault plane; the combination of anti-dislocation measures significantly enhances the tunnel’s stress state, reducing peak axial strain by 93% compared to a continuous tunnel. Furthermore, the extent and severity of tunnel damage are greatly diminished. The primary cause of lining segment damage is circumferential stress, with the main damage characterized by tensile cracking on both the inner and outer surfaces of the lining along the tunnel’s axial direction. Full article
(This article belongs to the Section Civil Engineering)
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<p>Test model box system. (<b>a</b>) Physical drawing. (<b>b</b>) Three-dimensional effect drawing. (<b>c</b>) Electric control system. (<b>d</b>) Fault dislocation frame. ① Moving block; ② fixed block; ③ fault dislocation frames; ④ servo motor; ⑤ reducer; ⑥ telescopic rod; ⑦ servo motor driver; ⑧ phase regulator; ⑨ resistance regulator; ⑩ switches.</p>
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<p>Schematic of the tunnel with combined anti-dislocation measures.</p>
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<p>Flowchart of the methodology.</p>
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<p>Tunnel support structure.</p>
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<p>Boundary error analysis.</p>
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<p>Schematic diagram of tunnel model burial depth.</p>
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<p>Schematic diagram of working condition 1 monitoring.</p>
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<p>Schematic diagram of working condition 2 monitoring.</p>
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<p>Experiment preparation. (<b>a</b>) Fault frame positioning. (<b>b</b>) Similar materials. (<b>c</b>) Similar material filling. (<b>d</b>) Building a physical model. (<b>e</b>) Flexible joint. (<b>f</b>) Bonding strain gauges.</p>
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<p>Surface damage of the surrounding rock and the final form of the fault frames.</p>
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<p>Damage characteristics inside the tunnel for different dislocation distances. (<b>a</b>) Initial state; (<b>b</b>) 19 mm; (<b>c</b>) 23 mm; (<b>d</b>) 30 mm; (<b>e</b>) 40 mm; (<b>f</b>) 45 mm; (<b>g</b>) 50 mm; (<b>h</b>) final damage form.</p>
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<p>External damage form of the tunnel.</p>
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<p>Distribution of lining cracks in working condition 1.</p>
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<p>Axial strain. (<b>a</b>) Vault. (<b>b</b>) Invert.</p>
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<p>Axial strain. (<b>a</b>) Left side wall. (<b>b</b>) Right side wall.</p>
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<p>Axial strain distribution at various locations in the tunnel.</p>
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<p>Circumferential strain. (<b>a</b>) 3#. (<b>b</b>) 4#.</p>
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<p>Longitudinal distribution of contact pressure increment. (<b>a</b>) Left side wall. (<b>b</b>) Right side wall.</p>
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<p>Final damage pattern of the tunnel with combined anti-dislocation measures.</p>
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<p>Distribution of lining cracks in working condition 2.</p>
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<p>Comparison of axial strains. (<b>a</b>) Vault. (<b>b</b>) Invert. (<b>c</b>) Right side wall. (<b>d</b>) Left side wall.</p>
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<p>Circumferential strain response. (<b>a</b>) 3#. (<b>b</b>) 4#. (<b>c</b>) 5#.</p>
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<p>Scan of post-earthquake lining of the Daliang Tunnel [<a href="#B21-applsci-15-00765" class="html-bibr">21</a>].</p>
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