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25 pages, 55171 KiB  
Article
Characterization of Laser-Textured Surfaces of Parts of a Biodegradable Polymer
by Petronela-Daniela Rusu (Ostahie), Oktawian Bialas, Anna Wozniak, Marcin Adamiak, Augustine Appiah, Catalin Tampu, Simona-Nicoleta Mazurchevici, Panagiotis Kyratsis, Anastasios Tzotzis, Alexandra Nedelcu, Teodor-Daniel Mindru and Dumitru Nedelcu
Coatings 2025, 15(2), 246; https://doi.org/10.3390/coatings15020246 - 19 Feb 2025
Viewed by 32
Abstract
Surface texturing entails surface alteration through forming, microgrooving, microdimpling, and microchanneling. This is achieved by laser micromachining, in addition to other related methods, of a substrate surface. The present paper describes the surface characteristics obtained after the laser texturing of a biodegradable polymer [...] Read more.
Surface texturing entails surface alteration through forming, microgrooving, microdimpling, and microchanneling. This is achieved by laser micromachining, in addition to other related methods, of a substrate surface. The present paper describes the surface characteristics obtained after the laser texturing of a biodegradable polymer (Arbofill Fichte) with four and six passes in hexagonal and square patterns. The results of the wettability test indicate that this biodegradable polymer has a surface with a weak hydrophobic characteristic (contact angle near 90°), regardless of the type of texture that is obtained. The underlying material’s wear behavior changes as a result of the surface alteration due to laser surface texturing (LST). The coefficient of friction (COF) values thus increase for all samples. The hexagonal geometry offers greater stability and consistency compared to square geometry, independent of the number of passes. Square geometry is more susceptible to variations, particularly along the Y axis, and may need additional adjustment of the process parameters. The hexagonal structure naturally promotes more uniform leveling due to its tighter and more evenly spread arrangement, even at four texturing passes (4x). However, at six texturing passes (6x), the advantages become more pronounced because of the repeated overlaps in the laser trajectories. The overlap in the hexagonal configuration guarantees that each area of the material receives a relatively consistent energy dose, reducing localized discrepancies. The possibility of using this method to texture surfaces is viable; thus, based on the obtained results, there is the possibility that it can replace non-biodegradable polymers in different sectors. Full article
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<p>Microscopic observation of biodegradable biopolymer after laser texturing process: (<b>a</b>) 4x_H x300, (<b>b</b>) 4x_S x300.</p>
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<p>Microscopic observation of biodegradable biopolymer after laser texturing process: (<b>a</b>) 6x_H x300, (<b>b</b>) 6x_S x300.</p>
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<p>Contact angle diagram for the experiment: (<b>a</b>,<b>b</b>) initial state; (<b>c</b>,<b>d</b>) hexagonal-textured pattern with 4 passes; (<b>e</b>,<b>f</b>) square-textured pattern with 4 passes; (<b>g</b>,<b>h</b>) hexagonal-textured pattern with 6 passes; (<b>i</b>,<b>j</b>) square-textured pattern with 6 passes.</p>
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<p>Contact angle diagram for the experiment: (<b>a</b>,<b>b</b>) initial state; (<b>c</b>,<b>d</b>) hexagonal-textured pattern with 4 passes; (<b>e</b>,<b>f</b>) square-textured pattern with 4 passes; (<b>g</b>,<b>h</b>) hexagonal-textured pattern with 6 passes; (<b>i</b>,<b>j</b>) square-textured pattern with 6 passes.</p>
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<p>Results of COF tests for biodegradable biopolymer: (<b>a</b>) base material, (<b>b</b>) 4x_H, (<b>c</b>) 4x S, (<b>d</b>) 6x_H, (<b>e</b>) 6x_S.</p>
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<p>Wear track morphology of biodegradable biopolymer samples: (<b>a</b>) base material x100; (<b>b</b>) 4x_H x100; (<b>c</b>) 4x_S x100; (<b>d</b>) 6x_H x100; (<b>e</b>) 6x_S x100.</p>
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<p>Wear track morphology of biodegradable biopolymer samples: (<b>a</b>) base material x100; (<b>b</b>) 4x_H x100; (<b>c</b>) 4x_S x100; (<b>d</b>) 6x_H x100; (<b>e</b>) 6x_S x100.</p>
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<p>Microscopic observation of laser-untextured biodegradable polymer in initial state after degradation test.</p>
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<p>Microscopic observation of laser-textured Arbofill Fichte after degradation test: (<b>a</b>) 4x_H; (<b>b</b>) 4x_S.</p>
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<p>Microscopic observation of laser-textured biodegradable polymer after degradation test: (<b>a</b>) 6x_H; (<b>b</b>) 4x_S.</p>
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<p>Heat flow variation with temperature during heating for all samples: 1, base material; 2, hexagonal (4x); 3, square (4x); 4, hexagonal (6x); 5, square (6x).</p>
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<p>Maximum Rz value of three sections of Arbofill Fichte 4x_H: slice 1 (Sl.1); slice 2 (Sl.2); slice 3 (Sl.3).</p>
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<p>Flatness deviation after texturing—Arbofill Fichte: 4x_H.</p>
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<p>Roughness value Ra for three reference lines of Arbofill Fichte 4x_H.</p>
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<p>Interstial values for three reference lines—Arbofill Fichte: 4x_H, different geometric shapes.</p>
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<p>Maximum Rz value from the analysis of three sections—Arbofill Fichte: 6x_H, for different geometric shapes: slice 1 (Sl.1); slice 2 (Sl.2); slice 3 (Sl.3).</p>
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<p>Flatness deviation after texturing—Arbofill Fichte: 6x_H.</p>
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<p>Roughness value Ra for three reference lines—Arbofill Fichte: 6x_H, with a geometric shape.</p>
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<p>Gap value for three reference lines—Arbofill Fichte: 6x_H, with geometric shape.</p>
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<p>The maximum Rz value from the analysis of three sections—Arbofill Fichte: 4x_S, with geometric shape: slice 1 (Sl.1); slice 2 (Sl.2); slice 3 (Sl.3).</p>
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<p>Flatness deviation after texturing—Arbofill Fichte: 4x_S.</p>
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<p>Roughness value Ra for three reference lines—Arbofill Fichte: 4x_S, with geometric shape.</p>
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<p>Rz value for three reference lines—Arbofill Fichte: 4x_S, with geometric form.</p>
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<p>The maximum Rz value from the analysis of three sections—Arbofill Fichte: 6x_S, with geometric shape: slice 1 (Sl.1); slice 2 (Sl.2); slice 3 (Sl.3).</p>
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<p>Flatness deviation after texturing—Arbofill Fichte: 6x_S.</p>
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<p>Roughness value Ra for three reference lines—Arbofill Fichte: 6x_S, with geometric form.</p>
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<p>Interstitial values for three reference lines—Arbofill Fichte: 6x_S, with geometric shape.</p>
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15 pages, 7060 KiB  
Article
Investigation of Microjet Engine Inlet Pressure Distortions at Angled Inflow Velocity Conditions
by Santiago Sanchez Villacreses, Jun Yao, Yufeng Yao and Budi Chandra
Fluids 2025, 10(2), 49; https://doi.org/10.3390/fluids10020049 - 13 Feb 2025
Viewed by 329
Abstract
The Armfield CM14 microjet axial flow turbine engine has been tested in open space at ambient conditions with engine inlet pressure at the aerodynamic interface plane (AIP) measured by a built-in pressure sensor for validating computational fluid dynamics (CFD) studies. A three-dimensional computational [...] Read more.
The Armfield CM14 microjet axial flow turbine engine has been tested in open space at ambient conditions with engine inlet pressure at the aerodynamic interface plane (AIP) measured by a built-in pressure sensor for validating computational fluid dynamics (CFD) studies. A three-dimensional computational domain of the test engine intake duct configuration is defined, followed by mesh convergence studies. The latter results in a fine mesh of 5.7 million cells on which CFD-predicted engine inlet pressures are in good agreement with the experimental measurements at the AIP face for 20–100% throttles. CFD studies are continued to investigate the engine inlet pressure distortions at two inflow velocities of 35 m/s and 70 m/s, and various inflow angles ranging from 0° to 30° with a step of 5°, to evaluate their impacts on engine inlet pressure distortions. It is found that pressure distortions increase with the inflow angle, with severe pressure distortions occurring at higher inflow angles above 15°. At the same flow conditions of inflow angle and velocity, pressure distortions from an intake with a flat lip are overall higher than those of a bell-mouth round lip. This is primarily due to a rapid geometry change at the intake entrance causing large vortical flow motions, accompanied by local flow separations at higher inflow angles, therefore impacting the downstream flow field towards the engine inlet. Full article
(This article belongs to the Special Issue 10th Anniversary of Fluids—Recent Advances in Fluid Mechanics)
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<p>A sketch of the Armfield CM14 gas turbine engine with sensor points (not to scale).</p>
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<p>Original intake. (<b>a</b>) Injection nozzle with flat lip; (<b>b</b>) half a nozzle with inner geometry shape.</p>
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<p>Bell-mouth intake. (<b>a</b>) Injection nozzle with round lip; (<b>b</b>) half a nozzle with inner geometry shape.</p>
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<p>A 2D cross-section plane of 3D CFD domain (not to scale). (<b>a</b>) Case 1—flat lip; (<b>b</b>) case 2—bell-mouth round lip.</p>
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<p>Polyhedral meshes at cross-section plane for 3D intake with flat lip.</p>
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<p>Polyhedral mesh at cross-section plane for 3D intake with bell-mouth round lip.</p>
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<p>CFD-predicted static gauge pressure variation with number of mesh elements at 100% engine throttle and ambient conditions. (<b>a</b>) Case 1—flat lip; (<b>b</b>) case 2—bell-mouth round lip.</p>
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<p>The ratio of averaged static gauge pressure and ambient pressure at the AIP face as a function of throttle. Comparison of the experimental data and CFD results: (<b>a</b>) flat lip (case 1); (<b>b</b>) bell-mouth round lip (case 2).</p>
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<p>Pressure contours at the AIP face with flat lip intake at various inflow angles and a velocity of 35 m/s.</p>
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<p>Pressure contours at the AIP face with flat lip intake at various inflow angles and a velocity of 70 m/s.</p>
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<p>Pressure contours at the AIP face with a bell-mouth round lip intake at various inflow angles and a velocity of 35 m/s.</p>
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<p>Pressure contours at the AIP face with a bell-mouth round lip intake at various inflow angles and a velocity of 70 m/s.</p>
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<p>Comparison of distortion coefficient DC60 at the AIP face with two inflow velocities and various inflow angles from 0° to 30°. (<b>a</b>) Intake with flat lip; (<b>b</b>) intake with bell-mouth round lip.</p>
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15 pages, 3856 KiB  
Article
Analyzing Cutting Temperature in Hard-Turning Technique with Standard Inserts Through Both Simulation and Experimental Investigations
by Pham Minh Duc, Le Hieu Giang and Van Thuc Nguyen
Appl. Sci. 2025, 15(2), 983; https://doi.org/10.3390/app15020983 - 20 Jan 2025
Viewed by 562
Abstract
The cutting temperature in hard turning is extremely high, which reduces tool life, lowers machined-surface quality, and affects dimensional control. However, hard turning differs greatly from conventional turning in that the cutting process mainly happens at the tool-nose radius due to the extremely [...] Read more.
The cutting temperature in hard turning is extremely high, which reduces tool life, lowers machined-surface quality, and affects dimensional control. However, hard turning differs greatly from conventional turning in that the cutting process mainly happens at the tool-nose radius due to the extremely shallow depth of the cut. This paper provides a comprehensive and systematic analysis of this issue based on an evaluation of tool geometry in hard turning via finite element analysis (FEA) simulations and experiments. The effect of tool angles on cutting temperature in hard turning is analyzed. The impacts of cutting-edge angle, rake angle, inclination angle, and average local rake angle on the cutting temperature are investigated via central composite design (CCD). The simulated results and the empirically measured cutting temperature exhibit comparable patterns, with a minor 2% difference. Increasing the cutting-edge angle, negative rake angle and negative inclination angle enhances the local negative rake angles of the cutting-edge elements at the tool-nose radius involved in the cutting process. Notably, the most important component influencing cutting temperature in hard turning is the inclination angle, as opposed to normal turning, where the rake angle dominates the heat generation. Following this is the cutting-edge angle and the rake angle, which each contribute 40.75%, 32.39%, and 7.03%. These findings could enhance the application of the hard-turning technique by improving tool life and surface quality by focusing on optimizing the inclination angle. Full article
(This article belongs to the Special Issue Advances in Machining Process for Hard and Brittle Materials)
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<p>Mechanisms of heat generation and conduction in hard machining.</p>
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<p>(<b>a</b>) Hard-turning configuration; (<b>b</b>) Cutting-edge element geometry <span class="html-italic">j</span> at <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>θ</mi> </mrow> <mrow> <mi>j</mi> </mrow> </msup> </mrow> </semantics></math> = 31.59°; (<b>c</b>) Local rake angles; (<b>d</b>) Local uncut chips.</p>
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<p>Set up of hard-turning simulation process.</p>
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<p>Flow diagram of the hard-turning research process.</p>
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<p>The cutting process at the tool-nose radius in hard turning as determined from (<b>a</b>) simulation and (<b>b</b>) experimental results.</p>
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<p>Main effect plots for average local rake angle.</p>
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<p>Temperature distributions at the chip–tool interface, as determined through 3D finite element modeling (FEM).</p>
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<p>Comparison of measured and predicted temperatures.</p>
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<p>Main effect plots for FEM cutting temperature.</p>
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<p>Main effect plots for experimental cutting temperature.</p>
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<p>Cutting temperature vs. rake and inclination angles’ response surface in hard turning.</p>
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18 pages, 5510 KiB  
Article
Towards an Automated Design Evaluation Method for Wire Arc Additive Manufacturing
by Johannes Pusicha, Henrik Stromberg, Markus Quanz and Armin Lohrengel
Appl. Sci. 2025, 15(2), 938; https://doi.org/10.3390/app15020938 - 18 Jan 2025
Viewed by 714
Abstract
Freedom of design and the cost-effective production of structural parts have led to much research interest in Wire Arc Additive Manufacturing (WAAM). Nevertheless, WAAM is subject to design constraints and fundamentally differs from other additive manufacturing processes. Consequently, design guidelines and supporting design [...] Read more.
Freedom of design and the cost-effective production of structural parts have led to much research interest in Wire Arc Additive Manufacturing (WAAM). Nevertheless, WAAM is subject to design constraints and fundamentally differs from other additive manufacturing processes. Consequently, design guidelines and supporting design evaluation tools adapted to WAAM are needed. One geometric approach to design evaluation is the use of a three-dimensional medial axis transformation (3D-MAT) to derive local geometry indicators. Previous works define the thickness and radius indicators. In this work, the angle between opposing faces and a mass gradient indicator are added. To apply the literature design rules regarding wall thickness, clearance, bead angle, and edge radius to specific geometry regions, features are classified by the indicators. Following a literature suggestion, wall and corner regions are differentiated by the angle indicator. An angle of 65° is identified as an effective separation limit. Additionally, the analogy of Heuvers’ spheres to the MAT helps estimate a limit of kH1kH+1 for the mass gradient (kH: Heuvers’ factor). Finally, tests on example parts demonstrate the method’s effectiveness in verifying compliance to the specified rules. With a numerical complexity of O(n2), this method is more efficient than finite element analyses, providing early feedback in the design process. Full article
(This article belongs to the Section Mechanical Engineering)
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<p>Example for Heuvers’ circles with different diameters <span class="html-italic">D</span> and <span class="html-italic">d</span>.</p>
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<p>Medial axis and medial surface as dual representation of a geometry delivering its local symmetry axis or plane. The medial axis and the medial surface are defined by the set of all midpoints of maximally inscribed circles and spheres, respectively.</p>
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<p>Dimensions of the 3D-MAT: <math display="inline"><semantics> <mi mathvariant="bold">p</mi> </semantics></math>, <math display="inline"><semantics> <mi mathvariant="bold">b</mi> </semantics></math>: tangent points; <math display="inline"><semantics> <msub> <mi mathvariant="bold">n</mi> <mi>p</mi> </msub> </semantics></math>, <math display="inline"><semantics> <msub> <mi mathvariant="bold">n</mi> <mi>b</mi> </msub> </semantics></math>: normal vectors; <math display="inline"><semantics> <mi>α</mi> </semantics></math>: wall angle; <span class="html-italic">s</span>: secant; <math display="inline"><semantics> <msub> <mi>g</mi> <mi>r</mi> </msub> </semantics></math>: 2D gradient.</p>
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<p>Different applications of Heuvers’ sphere.</p>
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<p>Comparison of various outer and inner angles and the secant used (red). Sections with an enclosed angle of <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>≤</mo> <mi>α</mi> <mo>≤</mo> <msup> <mn>65</mn> <mo>°</mo> </msup> </mrow> </semantics></math> can be considered as tapered wall.</p>
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<p>Overview of the implemented software architecture.</p>
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<p>Example bar part to verify our implementation. Design flaws on the left-hand side, and corresponding corrections on the right-hand side. All dimensions are indicated in millimeters.</p>
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<p>Approximations of the medial surfaces of the example part. The center points of the inscribed spheres are color-coded by their radius in millimeters.</p>
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<p>Evaluation results on the example part. For each feature, non-manufacturable faces are highlighted with a color scale from yellow to red with ascending constraint violation.</p>
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<p>Some testing results on three benchmark geometries. Note that some color scales and feature limits have been adjusted to better represent the recognition of the feature. In general, the features are measured correctly, despite the above described classification issues with thin walled regions.</p>
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<p>Some testing results on three benchmark geometries. Note that some color scales and feature limits have been adjusted to better represent the recognition of the feature. In general, the features are measured correctly, despite the above described classification issues with thin walled regions.</p>
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12 pages, 1962 KiB  
Article
Lattice Structure for Improving Cooling Uniformity in HPDC Mould Corners
by Essam Abo-Serie and Samuel K. Koranteng-Agyarko
Appl. Sci. 2025, 15(1), 427; https://doi.org/10.3390/app15010427 - 5 Jan 2025
Viewed by 662
Abstract
Conformal cooling channels have demonstrated significant advantages for cast parts and 3D-printed moulds in the high-pressure die casting (HPDC) process. However, the complex geometry of moulds, characterised by small intrusions, sharp corners, and fins, often results in nonuniform cooling in certain regions, leading [...] Read more.
Conformal cooling channels have demonstrated significant advantages for cast parts and 3D-printed moulds in the high-pressure die casting (HPDC) process. However, the complex geometry of moulds, characterised by small intrusions, sharp corners, and fins, often results in nonuniform cooling in certain regions, leading to overcooling or overheating. This study proposes integrating lattice structures within specific regions of 3D-printed moulds or inserts as an additional control parameter to enhance cooling uniformity by increasing thermal resistance in targeted areas. A validated three-dimensional Computational Fluid Dynamics (CFD) model was employed to incorporate three types of lattice structures, aiming to limit local heat flux in overcooled areas. The model specifically addresses the cooling of an aluminium alloy profile with 90-degree-angled corners, using H13 steel mould properties. The results indicate that implementing a lattice structure as a sleeve around the cooling pipe at the corner two sides improved temperature uniformity by over 42%. However, this increased thermal resistance also led to a 16 °C rise in corner temperature. These findings suggest that implementing lattice structures in the mould can improve cooling uniformity. However, they should be positioned away from the thickest regions of the mould to avoid increasing the modelling time. Full article
(This article belongs to the Topic Applied Heat Transfer)
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<p>Sketch showing the three computational regions and the lattice structure sleeves around the cooling pipe.</p>
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<p>Polyhedral mesh distribution in the three regions.</p>
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<p>Sketch of the available area for cooling the mould corner and heat flux distribution in the cast and mould. (<b>a</b>) available cooling area; (<b>b</b>) heat flux distribution.</p>
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<p>Baseline temperature distribution: (<b>a</b>) contours of temperature at the cast/mould interface, pipe surface, and a central section. (<b>b</b>) temperature at different probe points starting from the part corner.</p>
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<p>Temperature distribution in the cast, interface, lattice structure, and pipe surfaces. (<b>a</b>) Baseline cooling—no lattice structure; (<b>b</b>) cooling pipe with 1.5 mm lattice structure; (<b>c</b>) cooling pipes with 3 mm lattice structure; (<b>d</b>) two 1.5 mm lattice structures.</p>
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<p>Temperature variation at the cast interface along the two sides of the corners for various lattice structure configurations.</p>
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14 pages, 3665 KiB  
Article
An Irregular Pupil Localization Network Driven by ResNet Architecture
by Genjian Yang, Wenbai Chen, Peiliang Wu, Jianping Gou and Xintong Meng
Mathematics 2024, 12(17), 2703; https://doi.org/10.3390/math12172703 - 30 Aug 2024
Viewed by 713
Abstract
The precise and robust localization of pupils is crucial for advancing medical diagnostics and enhancing user experience. Currently, the predominant method for determining the center of the pupil relies on the principles of multi-view geometry, necessitating the simultaneous operation of multiple sensors at [...] Read more.
The precise and robust localization of pupils is crucial for advancing medical diagnostics and enhancing user experience. Currently, the predominant method for determining the center of the pupil relies on the principles of multi-view geometry, necessitating the simultaneous operation of multiple sensors at different angles. This study introduces a single-stage pupil localization network named ResDenseDilateNet, which is aimed at utilizing a single sensor for pupil localization and ensuring accuracy and stability across various application environments. Our network utilizes near-infrared (NIR) imaging to ensure high-quality image output, meeting the demands of most current applications. A unique technical highlight is the seamless integration of the efficient characteristics of the Deep Residual Network (ResNet) with the Dense Dilated Convolutions Merging Module (DDCM), which substantially enhances the network’s performance in precisely capturing pupil features, providing a deep and accurate understanding and extraction of pupil details. This innovative combination strategy greatly improves the system’s ability to handle the complexity and subtleties of pupil detection, as well as its adaptability to dynamic pupil changes and environmental factors. Furthermore, we have proposed an innovative loss function, the Contour Centering Loss, which is specifically designed for irregular or partially occluded pupil scenarios. This method innovatively calculates the pupil center point, significantly enhancing the accuracy of pupil localization and robustness of the model in dealing with varied pupil morphologies and partial occlusions. The technology presented in this study not only significantly improves the precision of pupil localization but also exhibits exceptional adaptability and robustness in dealing with complex scenarios, diverse pupil shapes, and occlusions, laying a solid foundation for the future development and application of pupil localization technology. Full article
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<p>Diagram of the ResDenseDilateNet architecture.</p>
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<p>Principle Diagram of Dilated Convolution. (<b>a</b>) The outcome of a 1-dilated convolution; (<b>b</b>) The effect of a 2-dilated convolution; (<b>c</b>) The impact of a 4-dilated convolution.</p>
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<p>Schematic diagram illustrating the principle of the DDCM.</p>
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<p>Diagram illustrating the principles of Contour Centering Loss. The blue lines represent tangents, and the red lines represent normals.</p>
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<p>Examples of images from the dataset.</p>
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<p>Schematic diagram of the human eye data collection process.</p>
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<p>Comparative analysis of ablation experiments on the RPE.</p>
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14 pages, 7290 KiB  
Article
Optimizing Trapezoidal Labyrinth Weir Design for Enhanced Scour Mitigation in Straight Channels
by Ahmed H. Shehata, Tahani F. Youssef, Hamada A. Hamada, Ibrahim M. M. and Abeer Samy
Water 2024, 16(17), 2443; https://doi.org/10.3390/w16172443 - 29 Aug 2024
Viewed by 1050
Abstract
Designing hydraulic structures requires careful consideration of local scouring downstream. This study investigated the performance of trapezoidal labyrinth weirs in controlling flow and mitigating scour in straight channels through physical model experiments. Sixty configurations were examined, using weir apex angles of 20°, 45°, [...] Read more.
Designing hydraulic structures requires careful consideration of local scouring downstream. This study investigated the performance of trapezoidal labyrinth weirs in controlling flow and mitigating scour in straight channels through physical model experiments. Sixty configurations were examined, using weir apex angles of 20°, 45°, 60°, and 80°, heights of 30 cm, 35 cm, and 40 cm, and flow rates of 50–200 L/s. A linear weir served as a reference. The results showed that the 60° apex angle consistently outperformed other configurations, reducing scour depth by up to 41% and scour length by up to 50% compared to the linear weir. It also decreased deposition depth by 40% and length by 50%. Lowering weir height from 40 cm to 30 cm led to reductions of 35% in scour depth and 40% in scour length at low discharges. These improvements remained significant even at higher flow rates, with a 29% reduction in scour depth and 25% in scour length at 200 L/s. This study provides evidence-based recommendations for optimizing labyrinth weir designs to define the relationship between hydraulic efficiency and erosion control. It offers valuable insights into weir geometry, flow conditions, and the resulting scour and deposition patterns. These findings contribute to the optimization of labyrinth weir designs to minimize downstream bed configurations. The tests were conducted under limited flow conditions. Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
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<p>General layout of the physical model (20.5 m long, 2 m width, and 0.85 m depth), (<b>a</b>) an upper view of the physical model, (<b>b</b>) a side view of the model showing its longitude, (<b>c</b>) a view of the upstream entrance, and (<b>d</b>) a view of the downstream outlet.</p>
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<p>Schematic diagram for the weir model, and experimental setup: (<b>a</b>) side view, (<b>b</b>) plan.</p>
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<p>The schematic diagram for the trapezoidal labyrinth weir with four different apex angles (20°, 45°, 60°, and 80°)—“the red line shows the borders of one cycle of the weir from the schematic diagram to the natural view in the flume”.</p>
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<p>Grain size distribution of the bed material downstream of the solid apron.</p>
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<p>The calibrated point gauges to measure (<b>a</b>) the upstream water level, (<b>b</b>) the developed bed configurations, and (<b>c</b>) the tailgate water level.</p>
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<p>Scour developed downstream of the apron: (<b>a</b>) before the test run, (<b>b</b>) after the test run, and (<b>c</b>) a side view of the resulting scour and deposition.</p>
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<p>The relation between flow discharge and relative scour/deposition parameters (D<sub>s</sub>/Y<sub>t</sub>), (L<sub>s</sub>/Y<sub>t</sub>), (D<sub>d</sub>/Y<sub>t</sub>), and (L<sub>d</sub>/Y<sub>t</sub>) for the linear case and the other apex angles at different weir heights: (<b>a</b>) P = 40 cm, (<b>b</b>) P = 35 cm, and (<b>c</b>) P = 30 cm.</p>
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<p>The relation between flow discharge and relative scour/deposition parameters (D<sub>s</sub>/Y<sub>t</sub>), (L<sub>s</sub>/Y<sub>t</sub>), (D<sub>d</sub>/Y<sub>t</sub>), and (L<sub>d</sub>/Y<sub>t</sub>) for the linear case and the other apex angles at different weir heights: (<b>a</b>) P = 40 cm, (<b>b</b>) P = 35 cm, and (<b>c</b>) P = 30 cm.</p>
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<p>Relationship between passing discharge and scour/deposition parameters (D<sub>s</sub>/y<sub>t</sub>), (L<sub>s</sub>/y<sub>t</sub>), (D<sub>d</sub>/y<sub>t</sub>), and (L<sub>d</sub>/y<sub>t</sub>), for a weir apex angle of 60° and different weir heights (P = 40 cm, 35 cm, and 30 cm).</p>
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20 pages, 14212 KiB  
Article
ReLoki: A Light-Weight Relative Localization System Based on UWB Antenna Arrays
by Joseph Prince Mathew and Cameron Nowzari
Sensors 2024, 24(16), 5407; https://doi.org/10.3390/s24165407 - 21 Aug 2024
Cited by 1 | Viewed by 1022
Abstract
Ultra Wide-Band (UWB) sensing has gained popularity in relative localization applications. Many localization solutions rely on using Time of Flight (ToF) sensing based on a beacon–tag system, which requires four or more beacons in the environment for 3D localization. A lesser researched option [...] Read more.
Ultra Wide-Band (UWB) sensing has gained popularity in relative localization applications. Many localization solutions rely on using Time of Flight (ToF) sensing based on a beacon–tag system, which requires four or more beacons in the environment for 3D localization. A lesser researched option is using Angle of Arrival (AoA) readings obtained from UWB antenna pairs to perform relative localization. In this paper, we present a UWB platform called ReLoki that can be used for ranging and AoA-based relative localization in 3D. To enable AoA, ReLoki utilizes the geometry of antenna arrays. In this paper, we present a system design for localization estimates using a Regular Tetrahedral Array (RTA), Regular Orthogonal Array (ROA), and Uniform Square Array (USA). The use of a multi-antenna array enables fully onboard infrastructure-free relative localization between participating ReLoki modules. We also present studies demonstrating sub-50cm localization errors in indoor experiments, achieving performance close to current ToF-based systems, while offering the advantage of not relying on static infrastructure. Full article
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<p>Illustration of the relative localization problem. On the left, we show ReLoki attached to an existing motion platform and capable of relative localization based on fully onboard sensing. Here, the RX agent senses the relative positions <math display="inline"><semantics> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </semantics></math> of the TX agents w.r.t its body frame whenever a message is received from <span class="html-italic">j</span>. On the right, we show the scenario where ReLoki can act as a mobile beacon. All beacons are capable of localizing a transmitting agent in 3D and adding more beacons will improve estimates.</p>
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<p>Illustration of the 4-antenna configurations that can be used with ReLoki. Here, we show the ROA, where the antennas are placed orthogonal w.r.t the central antenna, the RTA, where the antennas are placed at the vertices of a regular tetrahedron, and the USA, where the antennas are placed as a square on the same plane.</p>
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<p>Illustration of angle of incidence for RTA, ROA, and USA Antennas. The angle of incidence measured is used for bearing estimates based on the specific geometry of the antenna array.</p>
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<p>Angle of incidence measured for the redundant pairs. Here, the measured value is the average of 20 readings. The plot shows the saturation of the angle of incidence measured over <math display="inline"><semantics> <mrow> <msup> <mn>60</mn> <mo>∘</mo> </msup> </mrow> </semantics></math> in one pair and under <math display="inline"><semantics> <mrow> <mo>−</mo> <msup> <mn>60</mn> <mo>∘</mo> </msup> </mrow> </semantics></math> in the other.</p>
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<p>Timing diagram showing the different phases of transmissions. Message Transfer phase is shown in red, TWR Ranging phase in blue, and AoA Blink phase in green.</p>
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<p>Single-antenna design for ReLoki. (<b>a</b>) Finished PCB antenna along with the copper plane showing the circular patch antenna and the ground plane. (<b>b</b>) Return loss for the designed antenna showing less than <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>10</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math> return loss in almost all the UWB band for Ch. 1, 2, and 3. (<b>c</b>) Center frequency and the bandwidth of the UWB bands supported by proposed antenna and DW1000.</p>
Full article ">Figure 6 Cont.
<p>Single-antenna design for ReLoki. (<b>a</b>) Finished PCB antenna along with the copper plane showing the circular patch antenna and the ground plane. (<b>b</b>) Return loss for the designed antenna showing less than <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>10</mn> <mspace width="3.33333pt"/> <mi>dB</mi> </mrow> </semantics></math> return loss in almost all the UWB band for Ch. 1, 2, and 3. (<b>c</b>) Center frequency and the bandwidth of the UWB bands supported by proposed antenna and DW1000.</p>
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<p>ReLoki controller design. (<b>a</b>) ReLoki hardware block diagram showing the components. Here, we start with the host <span class="html-italic">i</span> initiating a communication request. ReLoki connects to host <span class="html-italic">i</span> and transmits the data. The information is transferred to the receiving ReLoki where it is then combined with the estimated localization data. Finally, the data are sent to the receiving host <span class="html-italic">j</span>. (<b>b</b>) ReLoki PCB design showcasing the different components mentioned in the block diagram.</p>
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<p>ReLoki experimental setup for covariance measurement. On the left, we have the pan and tilt mechanism and on the right we have the test setup for the <math display="inline"><semantics> <mrow> <mn>1.5</mn> <mspace width="3.33333pt"/> <mi mathvariant="normal">m</mi> </mrow> </semantics></math> range from source.</p>
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<p>Covariance maps for RTA and ROA antennas. In the top left we have RTA and in the top right we have the ROA array. A darker color means lower error. On the bottom, we show the comparison of RTA antenna array to the ROA antenna array. Here, green boxes represent lower errors for RTA and red represents lower errors for ROA. Yellow a represents comparable performance (combined azimuth and elevation difference within <math display="inline"><semantics> <mrow> <msup> <mn>10</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>) between both.</p>
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<p>Covariance map for USA antenna. On the top, we have the covariance maps, with darker colors showing lower errors in localization and lighter colors showing higher errors in localization. On the bottom, we show the average of measured vs actual values for azimuth and elevation for 50 readings at a given pan–tilt pair.</p>
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<p>Localization experiment with RTA antenna on ReLoki. On the left, we have the composite of overlayed frames from the video captured during the experiment. Agent 1 is executing a rectangular motion and Agent 2 is executing a straight-line motion. On the right, we have the output from ReLoki as seen by Agent 3 as well as the Opti-Track data captured. We show both the raw estimation data, in a lighter color, and filtered data using a low-pass filter in a darker color.</p>
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<p>ReLoki beacon test. On the top, we show the experimental setup. Two beacons are placed <math display="inline"><semantics> <mrow> <mn>8</mn> <mspace width="3.33333pt"/> <mi mathvariant="normal">m</mi> </mrow> </semantics></math> apart and the human operator moves the tag in a hour glass pattern. On the bottom, we show plots of the localization data along with the captured MoCAP data. Here, we show localization data with only one beacon active on the right side and both beacons active on the left. The unused beacon is marked with an “X”. We show the localization errors in both cases.</p>
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20 pages, 15846 KiB  
Article
Modelling the Control of Groundwater on the Development of Colliery Spoil Tip Failures in Wales
by Lingfeng He, John Coggan, Patrick Foster, Tikondane Phiri and Matthew Eyre
Land 2024, 13(8), 1311; https://doi.org/10.3390/land13081311 - 19 Aug 2024
Viewed by 1021
Abstract
Legacy colliery spoil tip failures pose a significant hazard that can result in harm to persons or damage to property and infrastructure. In this research, the 2020 Wattstown tip landslide caused by heavy rainfall was examined to investigate the likely mechanisms and developmental [...] Read more.
Legacy colliery spoil tip failures pose a significant hazard that can result in harm to persons or damage to property and infrastructure. In this research, the 2020 Wattstown tip landslide caused by heavy rainfall was examined to investigate the likely mechanisms and developmental factors contributing to colliery spoil tip failures in Welsh coalfields. To achieve this, an integrated method was proposed through the combination of remote sensing mapping, stability chart analysis, 2D limit equilibrium (LE) modelling, and 3D finite difference method (FDM) analysis. Various water table geometries were incorporated into these models to ascertain the specific groundwater condition that triggered the occurrence of the 2020 landslide. In addition, sensitivity analyses were carried out to assess the influence of the colliery spoil properties (i.e., cohesion, friction angle, and porosity) on the slope stability analysis. The results indicate that the landslide was characterised by a shallow rotational failure mode and spatially constrained by the critical water table and an underlying geological interface. In addition, the results also imply that the landslide was triggered by the rise of water table associated with heavy rainfall. Through sensitivity analysis, it was found that the properties of the colliery spoil played an important role in confining the extent of the landslide and controlling the process of its development. The findings underscore the detrimental effects of increased pore pressures, induced by heavy rainfall, on the stability of colliery tips, highlighting the urgent needs for local government to enhance water management strategies for this region. Full article
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<p>Study area—Wattstown tip which is south of Wattstown in the county borough of Rhondda Cynon Taf, Wales, and displayed on ESRI world imagery.</p>
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<p>Images of Wattstown standard tip. (<b>a</b>) A Google satellite image prior to the landslide (05/2020), (<b>b</b>) a Google satellite image after the landslide (07/2021), (<b>c</b>) delineation of the landslide boundary.</p>
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<p>Daily rainfall located at the study area from November 2020 to December 2020 (Met Office Hadley Centre, 2023).</p>
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<p>Remote-sensing mapping of the Wattstown standard tip prior to the 2020 landslide occurrence. (<b>a</b>) Hillshade map, (<b>b</b>) aspect map, and (<b>c</b>) slope angle map.</p>
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<p>Methodology of this research, including the input part to collect data for landslide analysis, the methods part of different methods used for landslide analysis, the output part of the final results obtained using these methods, and the validation process using post-landslide satellite images.</p>
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<p>Slope models for numerical analysis. (<b>a</b>) A 3D model and 9 monitoring points, (<b>b</b>) a satellite image showing the position of the 9 points, (<b>c</b>) a 2D model constructed along an N–S profile in the 3D model.</p>
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<p>A representative Hoek and Bray circular failure chart to estimate the FS of a soil slope where the surface water is 8×H behind the toe of the slope.</p>
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<p>FS values of the slope angle of 30° (grey line), 35° (red line), and 40° (blue line) in response to different groundwater conditions.</p>
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<p>Results of 2D LE analysis based on the simplified Bishop method, showing FS estimation corresponding to the slip surface. (<b>a</b>) Dry slope, (<b>b</b>) partially saturated slope (regime_1).</p>
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<p>FDM modelling result showing the total displacement of a dry slope (regime_1). (<b>a</b>) overview of the modelling result, (<b>b</b>) an N–S cross section of the total displacement contour.</p>
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<p>The curves of total displacement at 9 monitoring points when the slope is in a dry condition.</p>
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<p>FDM modelling result of a partially saturated slope (regime_1). (<b>a</b>) Contour of slope displacement and modelled displacement vectors of the unstable zone, (<b>b</b>) an N–S cross section of the slope displacement contour, (<b>c</b>) close-up image of the N–S cross section showing the geometry of the unstable zone and monitoring points P1, P6, and P8 on the slope.</p>
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<p>The curves of total displacement at 9 monitoring points when the slope is in the regime_1 water condition.</p>
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<p>The curves of total displacement at 9 monitoring points. (<b>a</b>) c = 0, (<b>b</b>) c = 20 kPa.</p>
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<p>Results of sensitivity analysis associated with the cohesion of colliery spoil. (<b>a</b>) c = 0, (<b>b</b>) c = 20 kPa, (<b>c</b>) N–S cross section of the cohesionless modelling result, (<b>d</b>) N–S cross section of the 20 kPa modelling result.</p>
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<p>The curves of total displacement at 9 monitoring points. (<b>a</b>) Φ = 32°, (<b>b</b>) Φ = 42°.</p>
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<p>Results of sensitivity analysis associated with the friction angle of colliery spoil. (<b>a</b>) Φ = 32°, (<b>b</b>) Φ = 42°, (<b>c</b>) N–S cross section of the 32° friction angle modelling result, (<b>d</b>) N–S cross section of the 42° friction angle modelling result.</p>
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<p>The curves of total displacement at 9 monitoring points. (<b>a</b>) φ = 10%, (<b>b</b>) φ = 30%.</p>
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<p>Results of sensitivity analysis associated with the porosity of colliery spoil. (<b>a</b>) φ = 10%, (<b>b</b>) φ = 30%, (<b>c</b>) N–S cross section of the 10% porosity modelling result, (<b>d</b>) N–S cross section of the 30% porosity modelling result.</p>
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<p>UKCP18 daily precipitation projection of a 5 km grid located in the study area from 1 July 2024 to 31 December 2028.</p>
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18 pages, 3123 KiB  
Article
A Method to Evaluate Forchheimer Resistance Coefficients for Permeable Screens and Air Louvers Modelled as a Porous Medium
by Yuriy Marykovskiy, Giulia Pomaranzi, Paolo Schito and Alberto Zasso
Fluids 2024, 9(7), 147; https://doi.org/10.3390/fluids9070147 - 22 Jun 2024
Viewed by 983
Abstract
Porous medium models are commonly used in Computational Fluid Dynamics (CFD) to simulate flow through permeable screens of various types. However, the setup of these models is often limited to replicating a pressure drop in cases where fluid inflow is orthogonal to the [...] Read more.
Porous medium models are commonly used in Computational Fluid Dynamics (CFD) to simulate flow through permeable screens of various types. However, the setup of these models is often limited to replicating a pressure drop in cases where fluid inflow is orthogonal to the screen. In this work, a porous medium formulation that employs a non-diagonal Forchheimer tensor is presented. This formulation is capable of reproducing both the pressure drop and flow deflection under varying inflow angles for complex screen geometries. A general method to determine the porous model coefficients valid for both diagonal and non-diagonal Forchheimer tensors is proposed. The coefficients are calculated using a nonlinear least-squares optimisation based on an analytical solution of a special case of the Navier–Stokes equations. The applicability of the proposed method is evaluated in four different scenarios supplemented by local CFD simulations of permeable screens: wire mesh, perforated screens, air louvers, and expanded mesh panels. The practical application of this method is demonstrated in the modelling of windbreaks and permeable double-skin facades, which typically employ the aforementioned types of porous screens. Full article
(This article belongs to the Section Mathematical and Computational Fluid Mechanics)
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<p>Permeable screen types on building facades: perforated screens, louvers, expanded mesh (left to right).</p>
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<p>Computational domain and coordinate systems.</p>
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<p>Resolved portions of the permeable screens.</p>
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<p>Wired mesh: analytical, FVM porous vs. resolved geometry CFD solutions in the Case 1 flow.</p>
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<p>Perforated panels: analytical, FVM porous vs. resolved geometry CFD solutions in the Case 1 flow; (<b>a</b>) 0 mm thickness, (<b>b</b>) 2 mm thickness, (<b>c</b>) 4 mm thickness.</p>
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<p>Louvers: analytical, FVM porous vs. resolved geometry CFD solutions in the Case 1 flow.</p>
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<p>Expanded Mesh: analytical, FVM porous vs. resolved geometry CFD solutions for Fx and Fy in the Case 1 flow.</p>
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<p>Expanded mesh: analytical, FVM porous vs. resolved CFD solutions for Fz in the Case 2 flow.</p>
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17 pages, 1309 KiB  
Article
Timelike Constant Axis Ruled Surface Family in Minkowski 3-Space
by Areej A. Almoneef and Rashad A. Abdel-Baky
Symmetry 2024, 16(6), 677; https://doi.org/10.3390/sym16060677 - 31 May 2024
Viewed by 545
Abstract
A timelike (TL) constant axis ruled surface in E13 (Minkowski 3-space), as determined by its ruling, forms a constant dual angle with its Disteli-axis (striction axis or curvature axis). In this article, we employ the symmetry through point geometry [...] Read more.
A timelike (TL) constant axis ruled surface in E13 (Minkowski 3-space), as determined by its ruling, forms a constant dual angle with its Disteli-axis (striction axis or curvature axis). In this article, we employ the symmetry through point geometry of Lorentzian dual curves and the line geometry of TL ruled surfaces. This produces the capability to expound a set of curvature functions that specify the local configurations of TL ruled surfaces. Then, we gain some new constant axis ruled surfaces in Lorentzian line space and their geometrical illustrations. Further, we also earn several organizations among a TL constant axis ruled surface and its striction curve. Full article
(This article belongs to the Section Mathematics)
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<p>The hyperbolic and Lorentzian <math display="inline"><semantics> <mi mathvariant="script">DU</mi> </semantics></math> spheres.</p>
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<p><math display="inline"><semantics> <mrow> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mrow> <mo>(</mo> <mi>v</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo form="prefix">cosh</mo> <mover accent="true"> <mi>ω</mi> <mo>^</mo> </mover> <msub> <mover accent="true"> <mi mathvariant="bold">z</mi> <mo>^</mo> </mover> <mn>1</mn> </msub> <mo>+</mo> <mo form="prefix">sinh</mo> <mover accent="true"> <mi>ω</mi> <mo>^</mo> </mover> <msub> <mover accent="true"> <mi mathvariant="bold">z</mi> <mo>^</mo> </mover> <mn>3</mn> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> cylindroid.</p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> Archimedes helicoid with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="normal">Γ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mi>μ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> Archimedes helicoid with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="normal">Γ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mi>μ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> Archimedes helicoid with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="normal">Γ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mi>μ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mi>ϰ</mi> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> Archimedes helicoid with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="normal">Γ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mi>μ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mi>ϰ</mi> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> tangential surface with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mn>0</mn> <mo>.</mo> </mrow> </semantics></math></p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> tangential surface with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mn>0</mn> <mo>.</mo> </mrow> </semantics></math></p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> binormal surface with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="normal">Γ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mn>0</mn> <mo>.</mo> </mrow> </semantics></math></p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> binormal surface with <math display="inline"><semantics> <mrow> <msup> <mi>ω</mi> <mo>*</mo> </msup> <mo>=</mo> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="normal">Γ</mi> <mo>(</mo> <mi>ϰ</mi> <mo>)</mo> <mo>=</mo> <mn>0</mn> <mo>.</mo> </mrow> </semantics></math></p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> cone.</p>
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<p><math display="inline"><semantics> <mi mathvariant="script">TL</mi> </semantics></math> cylinder with <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>=</mo> <mn>1</mn> <mo>.</mo> </mrow> </semantics></math></p>
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23 pages, 11342 KiB  
Article
Geometric Implications of Photodiode Arrays on Received Power Distribution in Mobile Underwater Optical Wireless Communication
by Tharuka Govinda Waduge, Boon-Chong Seet and Kay Vopel
Sensors 2024, 24(11), 3490; https://doi.org/10.3390/s24113490 - 28 May 2024
Cited by 2 | Viewed by 1181
Abstract
Underwater optical wireless communication (UOWC) has gained interest in recent years with the introduction of autonomous and remotely operated mobile systems in blue economic ventures such as offshore food production and energy generation. Here, we devised a model for estimating the received power [...] Read more.
Underwater optical wireless communication (UOWC) has gained interest in recent years with the introduction of autonomous and remotely operated mobile systems in blue economic ventures such as offshore food production and energy generation. Here, we devised a model for estimating the received power distribution of diffused line-of-sight mobile optical links, accommodating irregular intensity distributions beyond the beam-spread angle of the emitter. We then used this model to conduct a spatial analysis investigating the parametric influence of the placement, orientation, and angular spread of photodiodes in array-based receivers on the mobile UOWC links in different Jerlov seawater types. It revealed that flat arrays were best for links where strict alignment could be maintained, whereas curved arrays performed better spatially but were not always optimal. Furthermore, utilizing two or more spectrally distinct wavelengths and more bandwidth-efficient modulation may be preferred for received-signal intensity-based localization and improving link range in clearer oceans, respectively. Considering the geometric implications of the array of receiver photodiodes for mobile UOWCs, we recommend the use of dynamically shape-shifting array geometries. Full article
(This article belongs to the Special Issue Underwater Vision Sensing System)
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<p>(<b>a</b>) The polar distribution of the emitter’s optical intensity is non-uniform, especially for diffused line-of-sight optical links; the received power is contingent on multiple factors. (<b>b</b>) a miniaturized visual of a typical transmitter–receiver alignment expected for a mobile UOWC. Here, <math display="inline"><semantics> <mrow> <mi>θ</mi> </mrow> </semantics></math> is the beam divergence angle and <math display="inline"><semantics> <mrow> <mi>d</mi> </mrow> </semantics></math> is the separation between the transmitter and the receiver.</p>
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<p>Spectral attenuation variation of Jerlov water types [<a href="#B25-sensors-24-03490" class="html-bibr">25</a>].</p>
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<p>Relative intensity distribution over annuli concentric about the LED center axis.</p>
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<p>Array configuration and naming convention. Array center axis is orthogonal to the tangent to curve at the middle PD, with coordinate <math display="inline"><semantics> <mrow> <mfenced separators="|"> <mrow> <msub> <mrow> <mi>x</mi> </mrow> <mrow> <mi>c</mi> </mrow> </msub> <mo>,</mo> <mo> </mo> <msub> <mrow> <mi>y</mi> </mrow> <mrow> <mi>c</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math>. C-type and D-type arrays observe the light from the outside and inside of the curve, respectively. Orange circles and purple squares are representative of the PD placements of the 3PD and 5PD arrays, respectively. Each PD is equidistantly placed along the curve starting from the array center.</p>
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<p>Each array is moved within the positive quadrant of a cartesian coordinate plane with the origin centered at the location of the light source. The results are generated for horizontal and vertical displacements.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <msub> <mrow> <mi>r</mi> </mrow> <mrow> <mi>t</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> for 5PD arrays at: (<b>a</b>–<b>c</b>) <span class="html-italic">β</span> = 90°; (<b>d</b>–<b>f</b>) <span class="html-italic">β</span> = 60°; (<b>g</b>–<b>i</b>) <span class="html-italic">β</span> = 0°; (<b>j</b>–<b>l</b>) <span class="html-italic">β</span> = −60°; (<b>m</b>–<b>o</b>) <span class="html-italic">β</span> = −90° for Jerlov I; <math display="inline"><semantics> <mrow> <mi>c</mi> <mo>=</mo> <mn>0.022</mn> </mrow> </semantics></math> m<sup>−1</sup>. Red and green lines are 10- and 0-dB contours, respectively.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <msub> <mrow> <mi>r</mi> </mrow> <mrow> <mi>t</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> for 5PD arrays at: (<b>a</b>–<b>c</b>) <span class="html-italic">β</span> = 90°; (<b>d</b>–<b>f</b>) <span class="html-italic">β</span> = 60°; (<b>g</b>–<b>i</b>) <span class="html-italic">β</span> = 0°; (<b>j</b>–<b>l</b>) <span class="html-italic">β</span> = −60°; (<b>m</b>–<b>o</b>) <span class="html-italic">β</span> = −90° for Jerlov III; <math display="inline"><semantics> <mrow> <mi>c</mi> <mo>=</mo> <mn>1.045</mn> </mrow> </semantics></math> m<sup>−1</sup>. Red and green lines show 10- and 0-dB contours, respectively.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <msub> <mrow> <mi>r</mi> </mrow> <mrow> <mi>t</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> for 5PD arrays at: (<b>a</b>–<b>c</b>) <span class="html-italic">β</span> = 90°; (<b>d</b>–<b>f</b>) <span class="html-italic">β</span> = 60°; (<b>g</b>–<b>i</b>) <span class="html-italic">β</span> = 0°; (<b>j</b>–<b>l</b>) <span class="html-italic">β</span> = −60°; (<b>m</b>–<b>o</b>) <span class="html-italic">β</span> = −90° for Jerlov 3C; <math display="inline"><semantics> <mrow> <mi>c</mi> <mo>=</mo> <mn>1.142</mn> </mrow> </semantics></math> m<sup>−1</sup>. Red and green lines show 10- and 0-dB contours, respectively.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <msub> <mrow> <mi>r</mi> </mrow> <mrow> <mi>t</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> for respective 3PD arrays at <span class="html-italic">β</span> = 60° rotation in: (<b>a</b>–<b>c</b>) Jerlov I (<span class="html-italic">λ</span> = 450 nm); (<b>d</b>–<b>f</b>) Jerlov III (<span class="html-italic">λ</span> = 550 nm) and (<b>g</b>–<b>i</b>) Jerlov 3C (<span class="html-italic">λ</span> = 550 nm). Red and green lines show 10- and 0-dB contours, respectively.</p>
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<p>BER analysis for respective 5PD arrays in: (<b>a</b>–<b>c</b>) Jerlov I; (<b>d</b>–<b>f</b>) Jerlov III; and (<b>g</b>–<b>i</b>) Jerlov 3C. A wavelength of 450 nm was used for Jerlov I and 550 nm was used for Jerlov III and 3C, respectively, due to them being the least attenuated light wavelengths in the respective water types, as per <a href="#sensors-24-03490-t003" class="html-table">Table 3</a>. Jerlov I was modeled for a 15 m vertical displacement, and Jerlov III and 3C at a 1 m vertical displacement.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <msub> <mrow> <mi>r</mi> </mrow> <mrow> <mi>t</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> for 5PD arrays of: (<b>a</b>,<b>b</b>) type F; (<b>c</b>,<b>d</b>) type C25; and (<b>e</b>,<b>f</b>) type C55; at <math display="inline"><semantics> <mrow> <mi>β</mi> <mo>=</mo> <mo>{</mo> </mrow> </semantics></math>−60°, 0°, 60°} respectively, for Jerlov I, III, 1C, and 3C, for <math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mo>{</mo> </mrow> </semantics></math>450, 500, 550} nm.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <msub> <mrow> <mi>r</mi> </mrow> <mrow> <mi>t</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> for 5PD arrays of: (<b>a</b>,<b>b</b>) type F; (<b>c</b>,<b>d</b>) type C25; and (<b>e</b>,<b>f</b>) type C55; at <math display="inline"><semantics> <mrow> <mi>β</mi> <mo>=</mo> <mo>{</mo> </mrow> </semantics></math>−60°, 0°, 60°} respectively, for Jerlov I, III, 1C, and 3C, for <math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mo>{</mo> </mrow> </semantics></math>450, 500, 550} nm.</p>
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25 pages, 6814 KiB  
Article
Study on the Seismic Response of a Water-Conveyance Tunnel Considering Non-Uniform Longitudinal Subsurface Geometry and Obliquely Incident SV-Waves
by Erlei Yao, Yu Rao, Meishan Liu, Zhifang Liu and Ang Cao
Appl. Sci. 2024, 14(11), 4398; https://doi.org/10.3390/app14114398 - 22 May 2024
Cited by 1 | Viewed by 793
Abstract
The longitudinal seismic response characteristics of a shallow-buried water-conveyance tunnel under non-uniform longitudinal subsurface geometry and obliquely incident SV-waves was studied using the numerical method, where the effect of the non-uniform longitudinal subsurface geometry due to the existence of a local one-sided rock [...] Read more.
The longitudinal seismic response characteristics of a shallow-buried water-conveyance tunnel under non-uniform longitudinal subsurface geometry and obliquely incident SV-waves was studied using the numerical method, where the effect of the non-uniform longitudinal subsurface geometry due to the existence of a local one-sided rock mountain on the seismic response of the tunnel was focused on. Correspondingly, a large-scale three-dimensional (3D) finite-element model was established, where different incidence angles and incidence directions of the SV-wave were taken into consideration. Also, the non-linearity of soil and rock and the damage plastic of the concrete lining were incorporated. In addition, the wave field of the site and the acceleration response as well as damage of the tunnel were observed. The results revealed the following: (i) a local inclined subsurface geometry may focus an obliquely incident wave due to refraction or total reflection; (ii) a tunnel in a site adjacent to a rock mountain may exhibit a higher acceleration response than a tunnel in a homogeneous plain site; and (iii) damage in the tunnel in the site adjacent to a rock mountain may appear in multiple positions, and the effect of the incidence angle on the mode of compressive deformation and damage of the lining is of significance. Full article
(This article belongs to the Special Issue Earthquake Engineering and Seismic Risk)
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Figure 1
<p>The spatial location relationship between the tunnel and the mountain for the Kunming interval of the Dianzhong Water Diversion Project.</p>
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<p>Schematic diagram for the local one-sided mountain–plain site tunnel model: (<b>a</b>) left side incidence; and (<b>b</b>) right side incidence.</p>
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<p>Dimensions of the one-sided mountain tunnel model.</p>
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<p>Mesh of the one-sided mountain tunnel model.</p>
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<p>Simulated ground motions: (<b>a</b>) acceleration time–history; (<b>b</b>) velocity time–history; (<b>c</b>) displacement time–history; and (<b>d</b>) the PSD of the simulated ground motion.</p>
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<p>Wave propagation diagram for SV-waves: (<b>a</b>) left-side incidence; and (<b>b</b>) right-side incidence.</p>
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<p>Displacement contour under incident SV–wave for (<b>a</b>) plain site and left-side incidence at t = 0.27 s; (<b>b</b>) plain–mountain site and left–side incidence at t = 0.27 s; (<b>c</b>) plain site and right–side incidence at t = 0.36 s; and (<b>d</b>) plain–mountain site and right-side incidence at t = 0.36 s. (Unit: m).</p>
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<p>Displacement contour under incident SV–wave for (<b>a</b>) plain site and left-side incidence at t = 0.27 s; (<b>b</b>) plain–mountain site and left–side incidence at t = 0.27 s; (<b>c</b>) plain site and right–side incidence at t = 0.36 s; and (<b>d</b>) plain–mountain site and right-side incidence at t = 0.36 s. (Unit: m).</p>
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<p>Seismic response at the arch vault of the tunnel: (<b>a</b>) acceleration response in the horizontal direction; and (<b>b</b>) acceleration response in the vertical direction.</p>
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<p>Seismic response at the arch bottom of the tunnel: (<b>a</b>) acceleration response in the horizontal direction; and (<b>b</b>) acceleration response in the vertical direction.</p>
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<p>Seismic response at the left arch of the tunnel: (<b>a</b>) acceleration response in the horizontal direction; and (<b>b</b>) acceleration response in the vertical direction.</p>
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<p>Seismic response at the right arch of the tunnel: (<b>a</b>) acceleration response in the horizontal direction; and (<b>b</b>) acceleration response in the vertical direction.</p>
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<p>Diagram of the wave field for (<b>a</b>) left-side-incident SV-wave and (<b>b</b>) right-side-incident SV-wave with an incidence angle = 11.31° in the plain–mountain site.</p>
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<p>Diagram of the wave field for (<b>a</b>) left-side-incident SV-wave and (<b>b</b>) right-side-incident SV-wave with an incidence angle = 33.69° in the plain–mountain site.</p>
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<p>Tensile damage of tunnel lining under right-side-incident SV-wave: (<b>a</b>) incidence angle = 33.69° and t = 2.25 s; (<b>b</b>) incidence angle = 33.69° and t = 20 s; (<b>c</b>) incidence angle = 26.57° and t = 2.31 s; (<b>d</b>) incidence angle = 26.57° and t = 20 s; (<b>e</b>) incidence angle = 18.43° and t = 2.26 s; (<b>f</b>) incidence angle = 18.43° and t = 20 s; (<b>g</b>) incidence angle = 11.31° and t = 2.21 s; and (<b>h</b>) incidence angle = 11.31° and t = 20 s.</p>
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<p>Tunnel lining deformation at the time when damage initially shows up for right-side-incident SV-wave with the following incidence angles: (<b>a</b>) 33.69°; (<b>b</b>) 26.57°; (<b>c</b>) 18.43°; and (<b>d</b>) 11.31° (scaling factor = 300; unit: m).</p>
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<p>Tunnel lining deformation at t = 6.0 s for right-side-incident SV-wave with the following incidence angles: (<b>a</b>) 33.69°; (<b>b</b>) 26.57°; (<b>c</b>) 18.43°; and (<b>d</b>) 11.31° (scaling factor = 300; unit: m).</p>
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<p>Tensile damage of tunnel lining under left-side-incident SV-wave: (<b>a</b>) incidence angle = 33.69° and t = 2.25 s; (<b>b</b>) incidence angle = 33.69° and t = 20 s; (<b>c</b>) incidence angle = 26.57° and t = 2.31 s; (<b>d</b>) incidence angle = 26.57° and t = 20 s; (<b>e</b>) incidence angle = 18.43° and t = 2.26 s; (<b>f</b>) incidence angle = 18.43° and t = 20 s; (<b>g</b>) incidence angle = 11.31° and t = 2.21 s; and (<b>h</b>) incidence angle = 11.31° and t = 20 s.</p>
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<p>Tunnel lining deformation at the time when damage initially shows up for left-side-incident SV-wave with the following incidence angles: (<b>a</b>) 33.69°; (<b>b</b>) 26.57°; (<b>c</b>) 18.43°; and (<b>d</b>) 11.31° (scaling factor = 300; unit: m).</p>
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16 pages, 4660 KiB  
Article
Elastic Critical Buckling Coefficients for Skew Plates of Steel Structures under Biaxial Normal Stress
by Kazuya Mitsui, Kikuo Ikarashi and Keiichiro Sada
Buildings 2024, 14(4), 901; https://doi.org/10.3390/buildings14040901 - 26 Mar 2024
Viewed by 1039
Abstract
In steel structures, skew thin steel plates serve as panel zones in structures spanning large spaces (e.g., warehouses and gymnasiums). Considerable research has been conducted on the shear buckling of panels due to seismic loads acting on a structure. Conversely, under snow or [...] Read more.
In steel structures, skew thin steel plates serve as panel zones in structures spanning large spaces (e.g., warehouses and gymnasiums). Considerable research has been conducted on the shear buckling of panels due to seismic loads acting on a structure. Conversely, under snow or wind loads, the panel zone may experience compressive and tensile stresses simultaneously from two directions. Considering the economic preference for thin steel plates, evaluating the elastic critical local buckling stresses in the panel zone under biaxial normal stress may provide essential information to structural engineers. In this study, an elastic buckling analysis based on the energy method is performed to clarify the impact of panel geometry and boundary conditions on the elastic local buckling stresses of skew panel zones. As confirmed from the results, the local buckling stresses calculated using the energy method were consistent with those determined using finite element analysis. The findings indicate that a skew angle of up to 30° marginally affects the elastic buckling stress under uniaxial stress. Consequently, engineer-friendly design formulas were developed based on these findings. Comparisons with previous research demonstrated that the buckling loads reported were generally higher than those determined by finite element analysis. The study also established the correlation of the buckling stresses under biaxial stresses, which implied that the skew angle posed minimal influence on buckling stress for skew plates under biaxial stress. Additionally, a method for evaluating this correlation was presented. Engineers can utilize the provided design equations to more efficiently and accurately calculate buckling loads, facilitating a safer and more economical design of structures with skew plates. Full article
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Figure 1
<p>Stress state on panel zones varying with multiple loads.</p>
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<p>Skew plates under uniform biaxial normal stresses and its geometry: (<b>a</b>) Panel zone in moment frame; (<b>b</b>) Theoretical analysis model.</p>
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<p>Overview of FE model for skew plates under normal stress.</p>
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<p>Convergence study for mesh size.</p>
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<p>Graphical comparisons between present theoretical and FEA results and buckling modes under uniaxial compression where <span class="html-italic">θ</span> = 30°: (<b>a</b>) Under stress parallel to longitudinal direction; (<b>b</b>) Under stress perpendicular to longitudinal direction.</p>
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<p>Effect of geometries on the local buckling load: (<b>a</b>) Under stress parallel to longitudinal direction; (<b>b</b>) Under stress perpendicular to longitudinal direction.</p>
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<p>Effect of geometries on the local buckling modes with simply supported condition: (<b>a</b>) Under stress parallel to longitudinal direction; (<b>b</b>) Under stress perpendicular to longitudinal direction.</p>
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<p>Comparison between FEA results and calculations based on the proposed design equations: (<b>a</b>) Stress parallel to longitudinal direction; (<b>b</b>) Stress perpendicular to longitudinal direction.</p>
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<p>Correlation curve of buckling coefficient for simply supported condition: (<b>a</b>) <span class="html-italic">a</span>/<span class="html-italic">b</span> = 1.0; (<b>b</b>) <span class="html-italic">a</span>/<span class="html-italic">b</span> = 3.0; (<b>c</b>) <span class="html-italic">a</span>/<span class="html-italic">b</span> = 5.0.</p>
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<p>Correlation curve of buckling coefficient for clamped-supported condition: (<b>a</b>) <span class="html-italic">a</span>/<span class="html-italic">b</span> = 1.0; (<b>b</b>) <span class="html-italic">a</span>/<span class="html-italic">b</span> = 3.0; (<b>c</b>) <span class="html-italic">a</span>/<span class="html-italic">b</span> = 5.0.</p>
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32 pages, 8588 KiB  
Article
Heat Convection in a Channel-Opened Cavity with Two Heated Sources and Baffle
by Farhan Lafta Rashid, Asseel M. Rasheed Al-Gaheeshi, Hayder I. Mohammed and Arman Ameen
Energies 2024, 17(5), 1209; https://doi.org/10.3390/en17051209 - 3 Mar 2024
Cited by 2 | Viewed by 1207
Abstract
This study employs COMSOL software v 5.6 to investigate a novel approach to heat transfer via mixed convection in an open hollow structure with an unheated 90° baffle elbow. Two 20 W heat sources are strategically positioned on the cavity’s bottom and right-angled [...] Read more.
This study employs COMSOL software v 5.6 to investigate a novel approach to heat transfer via mixed convection in an open hollow structure with an unheated 90° baffle elbow. Two 20 W heat sources are strategically positioned on the cavity’s bottom and right-angled wall for this research. Notably, the orientation of the baffle perpendicular to the airflow is used to direct external, unrestricted flow into the square cavity. The research investigates a range of air velocities (0.1, 0.5, 1.0, and 1.5 m/s) and the intricate interaction between input air velocity, dual heated sources, and the presence of a right-angle baffle on critical thermodynamic variables, such as temperature distribution, isotherms, pressure variation, velocity profile, air density, and both local and mean Nusselt numbers. Validation of the applicable computational method is achieved by comparing it to two previous studies. Significant findings from numerical simulations indicate that the highest velocity profile is in the centre of the channel (2.3–2.68 m/s at an inflow velocity of 1.5 m/s), while the lowest profile is observed along the channel wall, with a notable disruption near the inlet caused by increased shear forces. The cavity neck temperature ranges from 380 to 640 K, with inflow air velocities varying from 0.1 to 1.5 m/s (Re is 812 to 12,182), respectively. In addition, the pressure fluctuates at the channel-cavity junction, decreasing steadily along the channel length and reaching a maximum at the intake, where the cavity neck pressure varies from 0.01 to 2.5 Pa with inflow air velocities changing from 0.1 to 1.5 m/s, respectively. The mean Nusselt number exhibits an upward trend as air velocity upon entry increases. The mean Nusselt number reaches up to 1500 when the entry air velocity reaches 1.5 m/s. Due to recirculation patterns, the presence of the 90° unheated baffle produces a remarkable cooling effect. The study establishes a direct correlation between input air velocity and internal temperature distribution, indicating that as air velocity increases, heat dissipation improves. This research advances our understanding of convective heat transfer phenomena in complex geometries and provides insights for optimising thermal management strategies for a variety of engineering applications. Full article
(This article belongs to the Special Issue New Challenges in Heat Transfer Enhancement)
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Figure 1
<p>Geometric passage flow diagram (all dimensions are measured in units of meters (m)).</p>
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<p>Mesh employed in this case study; (<b>a</b>) overview of the model and (<b>b</b>) a close up of the region of interest.</p>
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<p>Velocity contours comparison with the study by Salhi et al. (2020) [<a href="#B10-energies-17-01209" class="html-bibr">10</a>].</p>
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<p>Isotherm curve at various inlet velocities.</p>
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<p>Isotherm curve at various inlet velocities.</p>
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<p>Different inlet velocities’ contours of the 2D passage temperature.</p>
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<p>Different inlet velocities’ contours of the 2D passage temperature.</p>
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<p>Two-dimensional inlet velocity contours.</p>
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<p>Two-dimensional inlet velocity contours.</p>
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<p>Contours of the passage pressure streamline at various inlet velocities.</p>
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<p>Velocities distribution at various inlet velocities when the <span class="html-italic">y</span>-axis of the passage flow is positive.</p>
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<p>Pressure distribution along the <span class="html-italic">y</span>-axis for a range of inflow velocities.</p>
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<p>Pressure distribution along the <span class="html-italic">y</span>-axis for a range of inflow velocities.</p>
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<p>Upper side of the vertical position passage flow temperature distribution for different inlet flows.</p>
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<p>Upper side of the vertical position passage flow temperature distribution for different inlet flows.</p>
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<p>Cavity velocity profile along the lower side vertical position for various inflow speeds.</p>
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<p>Cavity velocity profile along the lower side vertical position for various inflow speeds.</p>
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<p>Cavity pressure distribution along the lower side vertical position for a range of inflow velocities.</p>
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<p>Cavity pressure distribution along the lower side vertical position for a range of inflow velocities.</p>
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<p>Cavity temperature distribution along the lower side vertical position for a range of input speeds.</p>
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<p>Cavity temperature distribution along the lower side vertical position for a range of input speeds.</p>
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<p>The local Nusselt number in the cavity along the lower side vertical position for a range of inflow velocities.</p>
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<p>The local velocity profile in the hollow neck at different intake speeds.</p>
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<p>Cavity neck pressure at various inflow velocities.</p>
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<p>Local temperature in cavity neck at various velocities.</p>
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<p>Cavity neck Nusselt number for different inflow velocities.</p>
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<p>Profile of velocity in outlet passage flow at various inlet velocities.</p>
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<p>Profile of Temperature in outlet passage flow at various inlet velocities.</p>
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<p>Profile of Density in outlet passage flow at various inlet velocities.</p>
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