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28 pages, 13595 KiB  
Article
Research on Optimization of Diesel Engine Speed Control Based on UKF-Filtered Data and PSO Fuzzy PID Control
by Jun Fu, Shuo Gu, Lei Wu, Nan Wang, Luchen Lin and Zhenghong Chen
Processes 2025, 13(3), 777; https://doi.org/10.3390/pr13030777 - 7 Mar 2025
Abstract
With the continuous development of industrial automation, diesel engines play an increasingly important role in various types of construction machinery and power generation equipment. Improving the dynamic and static performance of the speed control system of single-cylinder diesel engines can not only significantly [...] Read more.
With the continuous development of industrial automation, diesel engines play an increasingly important role in various types of construction machinery and power generation equipment. Improving the dynamic and static performance of the speed control system of single-cylinder diesel engines can not only significantly improve the efficiency of the equipment, but also effectively reduce energy consumption and emissions. Particle swarm optimization (PSO) fuzzy PID control algorithms have been widely used in many complex engineering problems due to their powerful global optimization capability and excellent adaptability. Currently, PSO-based fuzzy PID control research mainly integrates hybrid algorithmic strategies to avoid the local optimum problem, and lacks optimization of the dynamic noise suppression of the input error and the rate of change of the error. This makes the algorithm susceptible to the coupling of the system uncertainty and measurement disturbances during the parameter optimization process, leading to performance degradation. For this reason, this study proposes a new framework based on the synergistic optimization of the untraceable Kalman filter (UKF) and PSO fuzzy PID control for the speed control system of a single-cylinder diesel engine. A PSO-optimized fuzzy PID controller is designed by obtaining accurate speed estimation data using the UKF. The PSO is capable of quickly adjusting the fuzzy PID parameters so as to effectively alleviate the nonlinearity and uncertainty problems during the operation of diesel engines. By establishing a Matlab/Simulink simulation model, the diesel engine speed step response experiments (i.e., startup experiments) and load mutation experiments were carried out, and the measurement noise and process noise were imposed. The simulation results show that the optimized diesel engine speed control system is able to reduce the overshoot by 76%, shorten the regulation time by 58%, and improve the noise reduction by 25% compared with the conventional PID control. Compared with the PSO fuzzy PID control algorithm without UKF noise reduction, the optimized scheme reduces the overshoot by 20%, shortens the regulation time by 48%, and improves the noise reduction effect by 23%. The results show that the PSO fuzzy PID control method with integrated UKF has superior control performance in terms of system stability and accuracy. The algorithm significantly improves the responsiveness and stability of diesel engine speed, achieves better control effect in the optimization of diesel engine speed control, and provides a useful reference for the optimization of other diesel engine control systems. In addition, this study establishes the GT-POWER model of a 168 F single-cylinder diesel engine, and compares the cylinder pressure and fuel consumption under four operating conditions through bench tests to ensure the physical reasonableness of the kinetic input parameters and avoid algorithmic optimization on the distorted front-end model. Full article
(This article belongs to the Section Process Control and Monitoring)
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<p>Diesel engine speed control system schematic diagram.</p>
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<p>Diesel engine system schematic diagram.</p>
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<p>Schematic diagram of the overall architecture of the speed control system.</p>
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<p>Diesel engine test bench.</p>
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<p>GT-POWER model of 168 F single cylinder diesel engine.</p>
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<p>Comparison of cylinder pressure under different loads.</p>
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<p>Fuel consumption comparison chart under different loads.</p>
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<p>Schematic diagram of overall technical scheme.</p>
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<p>Schematic diagram of the PSO fuzzy PID controller based on UKF data.</p>
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<p>UKF algorithm flowchart.</p>
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<p>Unscented kalman filtering noise reduction effect diagram.</p>
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<p>Characteristic face of the fuzzy inference system: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>p</mi> </mrow> </msub> </mrow> </semantics></math> (Proportional term characteristic surface), (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </mrow> </semantics></math> (Integral term characteristic surface), (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> (Derivative term characteristic surface).</p>
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<p>Particle swarm optimization flowchart.</p>
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<p>Fitness value optimization results.</p>
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<p>Model of fuzzy PID control algorithm optimized by particle swarm optimization based on UKF in Matlab/Simulink (R2022b).</p>
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<p>Model of PID, Fuzzy PID, Fuzzy PID based on data of UKF, and PSO Fuzzy PID based on data of UKF in Matlab/Simulink (R2022b).</p>
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<p>Step response experiment results.</p>
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<p>Load disturbance experiment results.</p>
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12 pages, 6370 KiB  
Communication
A 24 GHz End-Fire Rod Antenna Based on a Substrate Integrated Waveguide
by Yanfei Mao, Shiju E, Yu Zhang and Wen-cheng Lai
Sensors 2025, 25(5), 1636; https://doi.org/10.3390/s25051636 - 6 Mar 2025
Viewed by 172
Abstract
Most of the traditional rod antennas in the literature are in the shape of a cylinder or are conical, which are not suitable shapes for planar PCB technology or planar integrated CMOS or BiCMOS technology. In this paper, we present a 24 GHz [...] Read more.
Most of the traditional rod antennas in the literature are in the shape of a cylinder or are conical, which are not suitable shapes for planar PCB technology or planar integrated CMOS or BiCMOS technology. In this paper, we present a 24 GHz planar end-fire rod antenna based on an SIW (substrate integrated waveguide) suitable for planar PCB technology or planar integrated circuit technology. The antenna is made of PCB Rogers 4350 and utilizes the SIW to realize the end-fire rod antenna. The measurement results of the antenna are presented: its gain is 8.55 dB and its S11 bandwidth is 6.2 GHz. This kind of planar end-fire rod antenna possesses the characteristics of high gain, wide bandwidth, compactness, and simple design and structure. This type of antenna can also be used as a PCB antenna in other frequency bands, and it could also possibly be utilized in mm-wave and THz integrated antenna design in the future due to its very simple architecture. Full article
(This article belongs to the Special Issue Waveguide-Based Sensors and Applications)
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<p>(<b>a</b>) Architecture of the end-fire rod antenna and (<b>b</b>) 3D view of the rod antenna without the GSG structure.</p>
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<p>(<b>a</b>) Top view of the rod antenna and (<b>b</b>) top view of the antenna.</p>
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<p>(<b>a</b>) E field animation plot and (<b>b</b>) current plot (Jsurf plot) of the end-fire rod antenna in HFSS.</p>
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<p>The rod can be one kind of tapered shape: (<b>a</b>) trapezoid, (<b>b</b>) triangle, or (<b>c</b>) curved.</p>
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<p>Explanation of the reflection and refraction at the interface of the rod and air according to Snell’s law.</p>
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<p>(<b>a</b>) Top view, (<b>b</b>) bottom view, and (<b>c</b>) side view of the prototype of the end-fire rod antenna during the first fabrication (the coordinate <span class="html-italic">X</span>-<span class="html-italic">Y</span>-<span class="html-italic">Z</span> axis is also shown in (<b>c</b>)).</p>
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<p>(<b>a</b>) Top view, (<b>b</b>) bottom view, and (<b>c</b>) side view of the prototype of the end-fire rod antenna during the first fabrication (the coordinate <span class="html-italic">X</span>-<span class="html-italic">Y</span>-<span class="html-italic">Z</span> axis is also shown in (<b>c</b>)).</p>
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<p>Simulation and measurement results during the first fabrication of the rod end-fire antenna.</p>
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<p>(<b>a</b>) Top view, (<b>b</b>), bottom view, and (<b>c</b>) side view of the prototype of the end-fire rod antenna during the second fabrication (the coordinate <span class="html-italic">X</span>-<span class="html-italic">Y</span>-<span class="html-italic">Z</span> axis is also shown in (<b>c</b>)).</p>
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<p>Simulation and measurement results of the S parameter of the antenna during the second fabrication and measurement.</p>
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<p>Simulation and measurement results of the gain pattern of the antenna in the x-y plane (gain versus <math display="inline"><semantics> <mrow> <mi>φ</mi> </mrow> </semantics></math>).</p>
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<p>Simulation and measurement results of the gain pattern of the antenna in the x-z plane (gain versus θ).</p>
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20 pages, 7507 KiB  
Article
Experimental Validation of Exact Burst Pressure Solutions for Thick-Walled Cylindrical Pressure Vessels
by Xian-Kui Zhu
Appl. Mech. 2025, 6(1), 20; https://doi.org/10.3390/applmech6010020 - 5 Mar 2025
Viewed by 120
Abstract
Burst pressure is one of the critical strength parameters used in the design and operation of pressure vessels because it represents the maximum pressure that a vessel can withstand before failing. Historically, the Barlow formula was used as a design base for estimating [...] Read more.
Burst pressure is one of the critical strength parameters used in the design and operation of pressure vessels because it represents the maximum pressure that a vessel can withstand before failing. Historically, the Barlow formula was used as a design base for estimating burst pressure. However, it does not consider the plastic flow response for ductile steels and is applicable only to thin-walled cylinders (i.e., the diameter to thickness ratio D/t ≥ 20). A new multiaxial plastic yield theory was developed to consider the plastic flow response, and the associated theoretical (i.e., Zhu–Leis) solution of burst pressure was obtained and has gained extensive applications in the pipeline industry because it was validated by different full-scale burst test datasets for large-diameter, thin-walled pipelines in a variety of steel grades from Grade B to X120. The Zhu–Leis flow theory of plasticity was recently extended to thick-walled pressure vessels, and the associated exact flow solution of burst pressure was obtained and is applicable to both thin and thick-walled cylindrical shells. Many full-scale burst tests are available for thin-walled line pipes in the pipeline industry, but limited pressure burst tests exist for thick-walled vessels. To validate the newly developed exact solutions of burst pressure for thick-walled cylinders, this paper conducts a series of burst pressure tests on small-diameter, thick-walled pipes. In particular, six burst tests are carried out for three thick-walled pipes in Grade B carbon steel. These pipes have a nominal diameter of 2.375 inches (60.33 mm) and three nominal wall thicknesses of 0.154, 0.218, and 0.344 inches (3.91, 5.54, and 8.74 mm), leading to D/t = 15.4, 10.9, and 6.9, respectively. With the burst test data, comparisons show that the Zhu–Leis flow solution of burst pressure matches well the burst test data for thick-walled pipes. Thus, these burst tests validate the accuracy of the Zhu–Leis flow solution of burst pressure for thick-walled cylindrical vessels. Full article
(This article belongs to the Collection Fracture, Fatigue, and Wear)
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<p>Comparison of four geometry terms of ln(D<sub>o</sub>/D<sub>i</sub>), 2t/D<sub>m</sub>, 2t/D<sub>o</sub>, and 2t/D<sub>i</sub>.</p>
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<p>API 5L Grade B black carbon steel pipe.</p>
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<p>Tensile test specimens.</p>
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<p>Tensile specimen fixture, extensometer, and broken specimen.</p>
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<p>Engineering stress–strain curves of the three Grade B carbon steel pipes.</p>
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<p>Pressure burst test setup for SCH-40 Pipe 1.</p>
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<p>Pressure-time records for SCH-40 Pipe 1 burst test.</p>
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<p>Pressure-time records for the SCH-40 Pipe 2 burst test.</p>
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<p>Comparison of measured and predicted burst pressures.</p>
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<p>Variations of measured and predicted burst pressures with strain hardening exponent n for the thick-walled tubes.</p>
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<p>Comparison of predicted and measured burst pressures for the thick-walled tubes.</p>
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<p>Normalized Zhu–Leis burst pressure (P<sub>b</sub>/σ<sub>0</sub>) against ln(D<sub>o</sub>/D<sub>i</sub>) for the specific n values.</p>
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<p>Pressure pipe specimen design drawing.</p>
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<p>Schedule 40 Pipe 1 after bursting.</p>
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<p>Schedule 40 Pipe 2 after bursting.</p>
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<p>Schedule 80 Pipe 1 after bursting.</p>
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<p>Schedule 80 Pipe 2 after bursting.</p>
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<p>Schedule 160 Pipe 2 after bursting.</p>
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20 pages, 10436 KiB  
Article
FEM Study on Enhancing Crashworthiness of Cylindrical Li-Ion Battery Packs Using Spacers Between the Cells
by Adrian Daniel Muresanu and Mircea Cristian Dudescu
Appl. Sci. 2025, 15(5), 2720; https://doi.org/10.3390/app15052720 - 4 Mar 2025
Viewed by 164
Abstract
This study proposes a novel approach to improving the crashworthiness of lithium-ion cylindrical cell packs by strategically placing spacers between the cells. The spacers transform the initial line contacts into broader surface contacts, enhancing the overall stiffness of the pack and reducing radial [...] Read more.
This study proposes a novel approach to improving the crashworthiness of lithium-ion cylindrical cell packs by strategically placing spacers between the cells. The spacers transform the initial line contacts into broader surface contacts, enhancing the overall stiffness of the pack and reducing radial deformation during compression. The concept was evaluated using finite element analysis (FEA), leveraging established material models to efficiently assess the concept’s potential prior to physical testing. To validate the robustness of the homogenized cell material and its application in a full pack, a compression experiment was performed on a pack of nine cells. The experimental results aligned closely with the simulation data, underlining the reliability of the material model and simulation methodology. Across all configurations and load cases—quasi-static compression using a plate or cylinder, and dynamic impact tests simulating crash indentation with a ball—the inclusion of spacers resulted in significant reductions in cell deformation and pack intrusion. The study also examined three spacer materials: aluminum, printed PLA, and printed PLA conditioned at 60 °C. The results showed that stiffer spacers, such as those made of aluminum, were the most effective in improving crash performance. However, even the conditioned PLA spacer, despite its lower stiffness, delivered meaningful benefits by enhancing structural integrity and reducing deformation. This demonstrates the versatility of the spacer concept, which can accommodate a range of materials based on specific performance and manufacturing requirements. These findings establish a solid foundation for the practical implementation of spacers in electric vehicle battery packs. Future research should include experimental validation under real-world crash conditions and explore spacer design and material optimization to maximize crashworthiness without compromising energy density or thermal performance. Full article
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<p>Graphical representation of the concept.</p>
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<p>Cell packing configuration: (<b>a</b>) V1; (<b>b</b>) V2; (<b>c</b>) V3.</p>
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<p>Impactors used for compression: (<b>a</b>) compression plate; (<b>b</b>) compression cylinder.</p>
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<p>Spacers for different configurations tested in this paper: (<b>a</b>) V1; (<b>b</b>) V2; (<b>c</b>) V3.</p>
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<p>Cell pack compression experiment: (<b>a</b>) no spacers; (<b>b</b>) printed spacers.</p>
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<p>Compression force–displacement validation curves.</p>
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<p>Compression plate load–displacement curve for different cells configurations: (<b>a</b>) V1; (<b>b</b>) V2; (<b>c</b>) V3.</p>
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<p>Compression plate, cell configuration V1, center-cut deformation for different spacers material: (<b>a</b>) aluminum; (<b>b</b>) printed PLA; (<b>c</b>) printed PLA at 60 °C.</p>
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<p>Compression plate, cell configuration V2, center-cut deformation for different spacer’s material: (<b>a</b>) aluminum; (<b>b</b>) printed PLA; (<b>c</b>) printed PLA at 60 °C.</p>
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<p>Compression plate, cell configuration V3, center-cut deformation for different spacer’s material: (<b>a</b>) aluminum; (<b>b</b>) printed PLA; (<b>c</b>) printed PLA at 60 °C.</p>
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<p>Compression cylinder load–displacement curve for different cells configurations: (<b>a</b>) V1; (<b>b</b>) V2; (<b>c</b>) V3.</p>
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<p>Compression cylinder, cell configuration V1, center-cut deformation for different spacer materials: (<b>a</b>) aluminum; (<b>b</b>) printed PLA; (<b>c</b>) printed PLA at 60 °C.</p>
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<p>Compression cylinder, cell configuration V2, center-cut deformation for different spacer materials: (<b>a</b>) aluminum; (<b>b</b>) printed PLA; (<b>c</b>) printed PLA at 60 °C.</p>
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<p>Compression cylinder, cell configuration V3, center-cut deformation for different spacer materials: (<b>a</b>) aluminum; (<b>b</b>) printed PLA; (<b>c</b>) printed PLA at 60 °C.</p>
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<p>Dynamic loading intrusion in V1 cell configuration: (<b>a</b>) no spacers; (<b>b</b>) aluminum; (<b>c</b>) printed PLA; (<b>d</b>) printed PLA at 60 °C.</p>
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<p>Dynamic loading intrusion in V2 cell configuration: (<b>a</b>) no spacers; (<b>b</b>) aluminum; (<b>c</b>) printed PLA; (<b>d</b>) printed PLA at 60 °C.</p>
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<p>Dynamic loading intrusion in V3 cell configuration: (<b>a</b>) no spacers; (<b>b</b>) aluminum; (<b>c</b>) printed PLA; (<b>d</b>) printed PLA at 60 °C.</p>
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<p>Dynamic loading stress in V1 cell configuration at center cut: (<b>a</b>) no spacers; (<b>b</b>) aluminum; (<b>c</b>) printed PLA; (<b>d</b>) printed PLA at 60 °C.</p>
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<p>Dynamic loading stress in V2 cell configuration at center cut: (<b>a</b>) no spacers; (<b>b</b>) aluminum; (<b>c</b>) printed PLA; (<b>d</b>) printed PLA at 60 °C.</p>
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<p>Dynamic loading stress in V3 cell configuration at center cut: (<b>a</b>) no spacers; (<b>b</b>) aluminum; (<b>c</b>) printed PLA; (<b>d</b>) printed PLA at 60 °C.</p>
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18 pages, 3605 KiB  
Article
Proteo-Transcriptomic Analysis of the Venom Gland of the Cone Snail Cylinder canonicus Reveals the Origin of the Predatory-Evoked Venom
by Zahrmina Ratibou, Anicet E. T. Ebou, Claudia Bich, Fabrice Saintmont, Gilles Valette, Guillaume Cazals, Dominique K. Koua, Nicolas Inguimbert and Sébastien Dutertre
Toxins 2025, 17(3), 119; https://doi.org/10.3390/toxins17030119 - 2 Mar 2025
Viewed by 234
Abstract
Cone snails are carnivorous marine predators that prey on mollusks, worms, or fish. They purposefully inject a highly diversified and peptide-rich venom, which can vary according to the predatory or defensive intended use. Previous studies have shown some correlations between the predation- and [...] Read more.
Cone snails are carnivorous marine predators that prey on mollusks, worms, or fish. They purposefully inject a highly diversified and peptide-rich venom, which can vary according to the predatory or defensive intended use. Previous studies have shown some correlations between the predation- and defense-evoked venoms and specific sections of the venom gland. In this study, we focus on the characterization of the venom of Cylinder canonicus, a molluscivorous species collected from Mayotte Island. Integrated proteomics and transcriptomics studies allowed for the identification of 108 conotoxin sequences from 24 gene superfamilies, with the most represented sequences belonging to the O1, O2, M, and conkunitzin superfamilies. A comparison of the predatory injected venom and the distal, central, and proximal sections of the venom duct suggests mostly distal origin. Identified conotoxins will contribute to a better understanding of venom–ecology relationships in cone snails and provide a novel resource for potential drug discovery. Full article
(This article belongs to the Special Issue Conotoxins: Evolution, Classifications and Targets)
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<p>Shells of molluscivorous cones that belong to the same clade (subgenus) <span class="html-italic">Cylinder</span>.</p>
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<p>LC-MS total ion current (TIC) chromatograms of predatory-evoked venoms from three different specimens of <span class="html-italic">Cylinder canonicus</span>. TIC chromatograms represent a summed intensity of all ions detected on the mass spectrometer detector depending on the time (minutes) and are normalized according to the most intense peak (relative intensity %). Chromatogram peaks were annotated with the molecular monoisotopic base peak mass (most intense peak on the mass spectrum in Dalton, Da). In this figure, molecular masses of the largest peaks in predatory venoms were colored blue. The Venn diagram on the top right represents the complexity and diversity of predatory-evoked venoms of three specimens of <span class="html-italic">C. canonicus</span> (MV1, MV2, MV4).</p>
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<p>Venom diversity across the venom gland. (<b>A</b>) Schematic representation of the venom gland of a cone snail adapted from Prashanth et al. (2016) [<a href="#B15-toxins-17-00119" class="html-bibr">15</a>]. The venom bulb functions as a muscle that allows the venom to be expelled by muscle contraction through the venom gland. The venom duct was dissected in four separate sections: the proximal and proximal-central sections, which are closer to the venom bulb, and the distal-central and distal sections, which are further from the bulb and closer to the proboscis end, where venom injection occurs [<a href="#B4-toxins-17-00119" class="html-bibr">4</a>,<a href="#B18-toxins-17-00119" class="html-bibr">18</a>]. (<b>B</b>) LC-MS chromatogram overlay of dissected venoms extracted from four different sections of the venom gland and a predatory venom (CAN MV4) of a cone snail, <span class="html-italic">Cylinder canonicus</span>. Chromatogram peaks were annotated with the molecular monoisotopic base peak mass (most intense peak on the mass spectrum in Dalton, Da). In this figure, molecular masses of largest peaks in the distal and proximal venoms were respectively colored green and blue. (<b>C</b>) Diagrams illustrate mass distribution across the venom gland. The Venn diagram on the bottom-left represents shared masses between pooled predatory CAN MV1 + MV2 + MV4 milking venoms (MVs) and pooled dissected distal D + DC (Ds) and proximal P + PC (Ps) venoms. Proximal venoms display higher number of detected masses, followed by milkings and Distal. A total of 34 shared masses between MVs, Ds, and Ps venoms, with more shared masses between MVs and Ps venoms. The diagram on the bottom right represents the distribution of detected masses in the venom gland sections. Proximal venoms display 122 unique masses, whereas the distal section presents 71 unique masses, while 46 masses were common to both.</p>
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<p>MALDI-TOF-MS spectra of the predatory milked venoms from three specimens of <span class="html-italic">Cylinder canonicus</span> (MV1, MV2, and MV4) aligned with dissected venoms from the distal (D, DC) and proximal (PC, P) duct sections. Matrix-assisted desorption of venom samples (dried spots) was performed at a frequency of 5000 Hz, by adding 3 × 1500 shots of a laser at a laser power (LP) of 30%. Peaks were recorded in positive reflectron mode, for the mass range 500–8000 Da in HCCA matrix. The seven mass spectra were aligned and the window was zoomed to display all detected peaks, mainly 1000–4000 Da.</p>
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<p>Distribution of the identified conopeptide gene superfamilies in the transcriptome of <span class="html-italic">Cylinder canonicus</span> venom gland. The pie chart represents proportion in number and percentage of each gene superfamilies in the transcriptome. A total of 98 conopeptides were distributed in 22 gene superfamilies.</p>
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<p>Diversity of <span class="html-italic">C. canonicus</span> venoms evaluated through proteomics. (<b>A</b>) The Venn diagram shows shared proteins between distal, proximal, and predatory venoms of <span class="html-italic">C. canonicus</span>. The figure on the bottom-left lays out size proportion of each sample and the part of shared proteins in at least two samples. (<b>B</b>) The pie chart represents total venom contribution of all venom samples assessed through blast annotation. A total of 76% of 466 proteins correspond to non-venom-related proteins (354 proteins), 18% to venom-related proteins (84 proteins), and 5% to conotoxins (25 proteins). (<b>C</b>) The histogram on the left represents the gene superfamily distribution of conotoxins validated through proteomics. Nine gene superfamilies are ordered from most to least abundant according to the number of conotoxins detected. B. The Venn diagram on the top right of the histogram represents distribution of detected conotoxins across distal and proximal venom gland sections and predatory-milked venoms of <span class="html-italic">C. canonicus</span>. All conotoxins, and proteins, identified through proteo-transcriptomics are presented in the <a href="#app1-toxins-17-00119" class="html-app">supplemental files</a> (<a href="#app1-toxins-17-00119" class="html-app">Tables S1–S4</a>, <a href="#app1-toxins-17-00119" class="html-app">Supplemental File S2</a>).</p>
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<p>Example of proteomics results. (<b>A</b>) Protein contig containing the precursor of the peptide Can102 is detected in the predatory venom of <span class="html-italic">C. canonicus</span>. A total of 79 spectra were matched (not all shown in the figure for clarity), corresponding to a coverage of the mature sequence of &gt;90%. Blue lines below the sequence represent peptide matches aligned to the protein. PTMs are also displayed on the figure with colored letters, such as c (carbamidomethylation), r (ion adducts), etc. (<b>B</b>) Example of the MS/MS spectrum automatically annotated with the b- and y-ions. (<b>C</b>) Table presenting some of the post-translational modifications (PTMs) detected in predatory-milked and dissected venoms. PTMs are quantified based on the number of peptide-spectra matches (PSM) which represent computed matches between MS/MS spectrum sequence prediction and database sequence. Of note, as they were automatically generated, some of these PTMs are likely artifacts. Only the 10 most represented PTMs are shown.</p>
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42 pages, 4769 KiB  
Review
A Comprehensive Analysis of Characteristics of Hydrogen Operation as a Preparation for Retrofitting a Compression Ignition Engine to a Hydrogen Engine
by Máté Zöldy, Márton Virt, Kristóf Lukács and György Szabados
Processes 2025, 13(3), 718; https://doi.org/10.3390/pr13030718 - 2 Mar 2025
Viewed by 280
Abstract
Hydrogen is a carbon-neutral fuel, so in theory it holds enormous potential. The use of hydrogen as a fuel for traditional internal combustion engines is becoming increasingly prominent. The authors now have the opportunity to retrofit a single-cylinder diesel research engine to an [...] Read more.
Hydrogen is a carbon-neutral fuel, so in theory it holds enormous potential. The use of hydrogen as a fuel for traditional internal combustion engines is becoming increasingly prominent. The authors now have the opportunity to retrofit a single-cylinder diesel research engine to an engine with hydrogen operation. For this reason, before that conversion, they prepared a comprehensive review study regarding hydrogen. Firstly, the study analyzes the most essential properties of hydrogen in terms of mixture formation and combustion compared to diesel. After that, it deals with indirect and direct injection, and what kind of combustion processes can occur. Since there is a possibility of pre-ignition, backfire, and knocking, the process can be dangerous in the case of indirect mixture formation, and so a short subsection is devoted to these uncontrolled combustion phenomena. The next subsection shows how important, in many ways, a special spark plug and ignition system are for hydrogen operation. The next part of the study provides a detailed presentation of the possible combustion chamber design for operation with hydrogen fuel. The last section reveals how many parameters can be focused on analyzing the hydrogen’s combustion process. The authors conclude that intake manifold injection and a Heron-like combustion chamber design, with a special spark plug with an ignition system, would be an appropriate solution. Full article
(This article belongs to the Section Environmental and Green Processes)
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<p>Main characteristics of compared fuels (on the basis of [<a href="#B26-processes-13-00718" class="html-bibr">26</a>]) ((1) at pressure 1.013 bar; (2) at temperature 0 °C; (3) at temperature 25 °C; (4) at λ = 1; (5) in air; (6) at pressure 250 bar and at temperature 280 K).</p>
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<p>Combustion processes can be implemented with hydrogen (on the basis of [<a href="#B38-processes-13-00718" class="html-bibr">38</a>]) (HCCI stands for homogenaous charge compression ignition).</p>
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<p>A typical pressure function during the pre-ignition process [<a href="#B41-processes-13-00718" class="html-bibr">41</a>] (black line—backfire, dash line—normal process) (reproduced with permission from Verhelst, S., and Wallner, T., Progress in Energy and Combustion Science, Elsevier, 2009).</p>
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<p>Pressure functions over the crankshaft angle in the cylinder and in the intake manifold in case of a backfire (black line—backfire, dash line—normal process) [<a href="#B41-processes-13-00718" class="html-bibr">41</a>] (reproduced with permission from Verhelst, S., and Wallner, T., Progress in Energy and Combustion Science, Elsevier, 2009).</p>
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<p>Frequency curves of low- and high-intensity knocking [<a href="#B59-processes-13-00718" class="html-bibr">59</a>] (reproduced with permission from Luo, Q. H., and Sun, B. G., International Journal of Hydrogen Energy, Elsevier, 2016).</p>
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<p>Drawing of a spark plug registered at the Deutsches Patent und Markenamt (Patent number: DE 10 2006 041 161 A1) [<a href="#B65-processes-13-00718" class="html-bibr">65</a>].</p>
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<p>Combustion chambers of the Erren hydrogen engine (<b>left</b>) and the MAN small-series hydrogen engine (<b>right</b>) (on the basis of [<a href="#B26-processes-13-00718" class="html-bibr">26</a>]).</p>
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<p>Cross-section of a hydrogen-fuelled research engine [<a href="#B74-processes-13-00718" class="html-bibr">74</a>].</p>
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<p>Meshed model of the combustion chamber [<a href="#B76-processes-13-00718" class="html-bibr">76</a>] (Blue color lines form the mesh) (reproduced with permission from Yuan, C. et al., International Journal of Hydrogen Energy, Elsevier, 2016).</p>
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<p>Combustion chamber of the VW hydrogen engine (on the basis of [<a href="#B30-processes-13-00718" class="html-bibr">30</a>]).</p>
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<p>Counter drawing of the main combustion chamber (on the basis of [<a href="#B78-processes-13-00718" class="html-bibr">78</a>]).</p>
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<p>CAD model of engine combustion chamber including intake and exhaust ducts, valves and spark plug [<a href="#B84-processes-13-00718" class="html-bibr">84</a>].</p>
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<p>The Heron combustion chamber of Volvo 900/700 [<a href="#B87-processes-13-00718" class="html-bibr">87</a>] (yellow—combustion chamber; blue—other engine parts).</p>
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<p>Chamber geometries: simple design (<b>top left</b>), Heron-type geometry (<b>top right</b>), MR-type geometry (<b>bottom left</b>), plate-type geometry (<b>bottom right</b>) [<a href="#B88-processes-13-00718" class="html-bibr">88</a>].</p>
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<p>Engine model in GT-Power (<b>left side</b>) and cylinder pressure functions at different hydrogen mixing ratios (<b>right side</b>) [<a href="#B95-processes-13-00718" class="html-bibr">95</a>] (explanation of model color marking: blue arrows—fluid flow between engine components; yellow—yellow—physical spaces, spatial connections; green—model inputs and outputs; red—notation of the author of the original article about each component) (reproduced with permission from Cho, J., and Song, S., Applied Thermal Engineering, Elsevier, 2020).</p>
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23 pages, 27451 KiB  
Article
Adapted Speed Control of Two-Stroke Engine with Propeller for Small UAVs Based on Scavenging Measurement and Modeling
by Yifang Feng, Tao Chen, Qinwang Liu and Heng Zhao
Aerospace 2025, 12(3), 202; https://doi.org/10.3390/aerospace12030202 - 28 Feb 2025
Viewed by 177
Abstract
The speed of the engine–propeller directly determines the power output for Unmanned Aerial Vehicles (UAV) with internal combustion engines. However, variable air pressure can impact the engine’s air exchange and combustion processes, causing minor changes that affect the engine speed and result in [...] Read more.
The speed of the engine–propeller directly determines the power output for Unmanned Aerial Vehicles (UAV) with internal combustion engines. However, variable air pressure can impact the engine’s air exchange and combustion processes, causing minor changes that affect the engine speed and result in variations in propeller thrust. A single-loop control strategy was proposed incorporating a feed-forward air-intake model with throttle feedback for small UAVs equipped with a two-stroke scavenging internal combustion engine and propeller. The feed-forward model was built with a simplified model of the airpath based on the scavenging measurement, which combined the tracer gas method and CFD simulation by a two-zone combustion chamber model. The feed-forward control strategy was built by a simplified crankcase–scavenging–cylinder model with CFD results under different air pressures, demonstrating a 1% error compared with CFD simulation. An iterative method of feed-forwarding was suggested for computing efficiency. A feedback controller was constructed using fuzzy PID for minimal instrumentation in engine control for small aircraft. Finally, the single-loop control strategy was validated through simulation and experimentation. The results indicate an 89% reduction in average speed error under varying air pressure and an 83.7% decrease in average speed overshoot in continuous step speed target experiments. Full article
(This article belongs to the Special Issue UAV System Modelling Design and Simulation)
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<p>Engine test bench.</p>
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<p>Structure of the engine controller.</p>
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<p>Three-dimensional grid for CFD simulation: (<b>a</b>) three-dimensional engine structure, (<b>b</b>) calculation region with speed distribution (m/s), (<b>c</b>) independence of the grid concentration by in-cylinder pressure at EPC, (<b>d</b>) independence of the grid concentration by in-cylinder maximum pressure, and (<b>e</b>) mesh view at the top dead center.</p>
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<p>Three-dimensional grid for CFD simulation: (<b>a</b>) three-dimensional engine structure, (<b>b</b>) calculation region with speed distribution (m/s), (<b>c</b>) independence of the grid concentration by in-cylinder pressure at EPC, (<b>d</b>) independence of the grid concentration by in-cylinder maximum pressure, and (<b>e</b>) mesh view at the top dead center.</p>
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<p>Characteristics of heat release rate with/without methane at 6500 rpm and 50% throttle opening.</p>
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<p>The trapping and scavenging efficiency at different engine speeds and throttle opening.</p>
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<p>The pressure in the cylinder at 6500 rpm and 50% throttle opening from Experiment and Simulation.</p>
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<p>The pressure in the Crankcase at 6500 rpm and 50% throttle opening from Experiment and Simulation.</p>
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<p>Comparison of heat release rate between experiment and simulation at 6500 rpm and 50% throttle opening.</p>
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<p>The schematic of the flame front (1000 K isotherm) in the cylinder from simulation.</p>
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<p>Comparison of heat release rate between 2-zone combustion model with experiment.</p>
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<p>The sweep curve under different engine speeds and intake pressure.</p>
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<p>The calculation process of the intake prediction model.</p>
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<p>The verification of intake mass calculation under different intake pressure.</p>
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<p>Calculation flow chart of feed-forward throttle opening.</p>
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<p>Convergence Effect of Reverse Solution.</p>
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<p>Membership function of speed deviation e.</p>
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<p>The comparison of the effect of speed control under climbing and descending.</p>
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<p>The comparison of the effect of speed control under step speed target.</p>
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<p>Experiment result of model feed-forward + fuzzy PI feedback speed step control.</p>
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<p>Experiment results of MAP feed-forward + PID feedback speed step control.</p>
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18 pages, 290 KiB  
Article
The Compactified D-Brane Cylinder Amplitude and T Duality
by Jian-Xin Lu
Mod. Math. Phys. 2025, 1(1), 3; https://doi.org/10.3390/mmphys1010003 - 28 Feb 2025
Viewed by 202
Abstract
In this paper, we address how to implement T-duality to the closed string tree cylinder amplitude between a Dp brane and a Dp′ brane with pp=2n. To achieve this, we compute the closed string tree cylinder [...] Read more.
In this paper, we address how to implement T-duality to the closed string tree cylinder amplitude between a Dp brane and a Dp′ brane with pp=2n. To achieve this, we compute the closed string tree cylinder amplitude, for the first time, between these two D-branes with common longitudinal and transverse circle compactifications. We then show explicitly how to perform a T-duality for this amplitude along either a longitudinal or a transverse compactified direction to both branes. At the decompactification limit, we show that either the compactified cylinder amplitude or the T dual compactified cylinder gives the known non-compactified one as expected. Full article
21 pages, 50829 KiB  
Article
Strengthening the Cavitation Resistance of Cylinder Liners Using Surface Treatment with Electroless Ni-P (ENP) Plating and High-Temperature Heat Treatment
by Wenjuan Zhang, Hao Gao, Qianting Wang, Dong Liu and Enlai Zhang
Materials 2025, 18(5), 1087; https://doi.org/10.3390/ma18051087 - 28 Feb 2025
Viewed by 170
Abstract
As internal combustion engines (ICEs) develop towards higher explosion pressures and lower weights, their structures need to be more compact; thus, the wall thickness of their cylinder liners is reducing. However, intense vibrations in the cylinder liner can lead to coolant cavitation and, [...] Read more.
As internal combustion engines (ICEs) develop towards higher explosion pressures and lower weights, their structures need to be more compact; thus, the wall thickness of their cylinder liners is reducing. However, intense vibrations in the cylinder liner can lead to coolant cavitation and, in severe cases, penetration of the liner, posing a significant reliability issue for ICEs. Therefore, research on cylinder liner cavitation has attracted increasing interest. Gray cast iron is widely used in cylinder liners for its hardness and wear resistance; however, additional surface plating is necessary to improve cavitation resistance. This study developed a novel surface-modification technology using electroless Ni-P plating combined with high-temperature heat treatment to create cylinder liners with refined grains, low weight loss rate, and high hardness. The heat-treatment temperature ranged from 100 to 600 °C. An ultrasonic cavitation tester was used to simulate severe cavitation conditions, and we analyzed and compared Ni-P-plated and heat-treated Ni-P-plated surfaces. The findings showed that the combination of Ni-P plating with high-temperature heat treatment led to smoother, more refined surface grains and the formation of cellular granular structures. After heat treatment, the plating structure converted from amorphous to crystalline. From 100 to 600 °C, the weight loss of specimens was within the range of 0.162% to 0.573%, and the weight loss (80.2% lower than the plated surface) and weight loss rate at 600 °C were the smallest. Additionally, cavitation resistance improved by 80.1%. The microhardness of the heat-treated plated surface reached 895 HV at 600 °C, constituting a 306 HV (65.8%) increase compared with that of the unplated surface, and a 560 HV increase compared with that of the maximum hardness of the plated surface without heat treatment of 335 HV, with an enhancement rate of 62.6%. Full article
(This article belongs to the Special Issue Research on Performance Improvement of Advanced Alloys)
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<p>Vibration of piston cylinder liner causes coolant pressure fluctuation and bubble formation.</p>
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<p>Unplated cylinder liner cavitation location and plated cylinder liner specimen location dimensions: (<b>a</b>) unplated cavitation, (<b>b</b>) ENP plated specimen location and geometry.</p>
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<p>Ultrasonic cavitation test device: (<b>a</b>) Schematic diagram of the test device; (<b>b</b>) Partial enlargement.</p>
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<p>The surface topography of the unplated specimens after cavitation testing: (<b>a</b>) 50×, (<b>b</b>) 100×, (<b>c</b>) 500×.</p>
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<p>The energy spectra of the uncavitated and cavitated regions of the unplated specimens: (<b>a</b>) region without cavitation, (<b>b</b>) cavitation region.</p>
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<p>SEM of Ni-P plating in plated state and after heat treatment, (<b>a</b>) plated state, (<b>b</b>) 200 °C, (<b>c</b>) 300 °C.</p>
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<p>EDS of Ni-P plating in plated state.</p>
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<p>SEM of cavitation of Ni-P plated specimens without heat-treatment; (<b>a</b>) initial cavitation pit; (<b>b</b>) cavitation pits connection; (<b>c</b>) cavitation pit size; (<b>d</b>) cavitation cracks.</p>
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<p>Metallographic microstructure of the Ni-P plated section without heat treatment: (<b>a</b>) cavitation in the plated section, (<b>b</b>) cavitation penetrating the plating.</p>
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<p>SEM of cavitation of Ni-P-plated after different heat treatments: (<b>a</b>) 100, (<b>b</b>) 200, (<b>c</b>) 300, (<b>d</b>) 400, (<b>e</b>) 500, and (<b>f</b>) 600 °C.</p>
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<p>EDS and percentages of elemental compositions of plated layers at different temperatures, (<b>a</b>) EDS, (<b>b</b>) 100 °C, (<b>c</b>) 200 °C, (<b>d</b>) 300 °C, (<b>e</b>) 400 °C, (<b>f</b>) 500 °C, (<b>g</b>) 600 °C.</p>
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<p>Variation in the weight loss and weight loss rate of plated cylinder liner with different temperature heat treatments.</p>
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<p>Comparison of hardness of heat-treated Ni-P plated and unplated specimens.</p>
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<p>Effect of phosphorus content heat treatment time on the hardness of plated layer [<a href="#B65-materials-18-01087" class="html-bibr">65</a>].</p>
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20 pages, 4257 KiB  
Article
Sensitivity Analysis of 3D Printing Parameters on Mechanical Properties of Fused Deposition Modeling-Printed Polylactic Acid Parts
by Marta Mencarelli, Mattia Sisella, Luca Puggelli, Bernardo Innocenti and Yary Volpe
Appl. Mech. 2025, 6(1), 17; https://doi.org/10.3390/applmech6010017 - 28 Feb 2025
Viewed by 198
Abstract
This study investigates the influence of various printing parameters on the tensile, compressive, and bending stiffness of fused deposition modeling (FDM)-printed polylactic acid (PLA) parts through a comprehensive full factorial design of experiment. Key factors, including infill percentage, infill pattern, number of outer [...] Read more.
This study investigates the influence of various printing parameters on the tensile, compressive, and bending stiffness of fused deposition modeling (FDM)-printed polylactic acid (PLA) parts through a comprehensive full factorial design of experiment. Key factors, including infill percentage, infill pattern, number of outer shells, and part orientation, were systematically varied to quantify their impact on mechanical performance. A total of 36 parameter combinations, selected based on a literature review and experimental feasibility, were tested using standardized specimens: beams for bending, cylinders for compression, and dogbones for tensile testing. Mechanical tests were performed according to ISO 5893:2019, employing a 1 kN load cell to determine stiffness and elastic modulus. The results indicate that the number of outer shells and infill density are the most influential parameters, whereas infill pattern and part orientation have a minor effect, depending on the loading condition. This study provides a novel and robust evaluation of the interactions between key printing parameters, offering new insights into optimizing the mechanical properties of FDM-printed parts. These findings establish a foundation for further optimization and material selection in future additive manufacturing research. Full article
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<p>Different infill patterns included in this study: (<b>a</b>) gyroid, (<b>b</b>) 3D honeycomb, and (<b>c</b>) cubic. Source: <a href="http://www.prusa3d.com" target="_blank">www.prusa3d.com</a> (accessed on 27 February 2025).</p>
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<p>Geometry and dimensions (expressed in mm) of tensile (<b>a</b>), compression (<b>b</b>), and bending (<b>c</b>) specimens.</p>
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<p>(<b>a</b>) Spatial arrangement of the specimens on the printing plate (kept constant for each configuration), (<b>b</b>) preview of the print once the supports are automatically generated, and (<b>c</b>) specimen fabrication completed. Brim was added to improve adhesion to the printing plate.</p>
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<p>Test machine set up for tensile (<b>a</b>), compression (<b>b</b>), and bending test (<b>c</b>).</p>
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<p>Specimens after tensile (<b>a</b>), compression (<b>b</b>), and bending (<b>c</b>) testing.</p>
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<p>Examples of computation of stiffness from the linear section of the force–displacement curve for tensile (<b>a</b>), compression (<b>b</b>), and bending tests (<b>c</b>). The four curves are obtained by testing the four copies of the same specimen.</p>
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<p>Main effect plot for tensile (<b>a</b>), compressive (<b>b</b>), and bending (<b>c</b>) stiffness for the different printing parameters considered in this study. H, C, and G, respectively, stand for 3D honeycomb, cubic, and gyroid patterns.</p>
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<p>Main effect plot for tensile (<b>a</b>), compressive (<b>b</b>), and bending (<b>c</b>) elastic modulus (E) for the different printing parameters considered in this study. H, C, and G, respectively, stand for 3D honeycomb, cubic, and gyroid patterns.</p>
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<p>Interaction plot for tensile (<b>a</b>), compressive (<b>b</b>), and bending (<b>c</b>) stiffness for the different printing parameters considered in this study. H, C, and G, respectively, stand for 3D honeycomb, cubic, and gyroid patterns.</p>
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<p>Interaction plot for tensile (<b>a</b>), compressive (<b>b</b>), and bending (<b>c</b>) stiffness for the different printing parameters considered in this study. H, C, and G, respectively, stand for 3D honeycomb, cubic, and gyroid patterns.</p>
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<p>Interaction plot for tensile (<b>a</b>), compressive (<b>b</b>), and bending (<b>c</b>) E for the different printing parameters considered in this study. H, C, and G, respectively, stand for 3D honeycomb, cubic, and gyroid patterns.</p>
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<p>Interaction plot for tensile (<b>a</b>), compressive (<b>b</b>), and bending (<b>c</b>) E for the different printing parameters considered in this study. H, C, and G, respectively, stand for 3D honeycomb, cubic, and gyroid patterns.</p>
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16 pages, 5306 KiB  
Article
On the Identification of Mobile and Stationary Zone Mass Transfer Resistances in Chromatography
by Alessandra Adrover and Gert Desmet
Separations 2025, 12(3), 59; https://doi.org/10.3390/separations12030059 - 28 Feb 2025
Viewed by 255
Abstract
A robust and elegant approach, based on the Two-Zone Moment Analysis (TZMA) method, is proposed to assess the contributions of the mobile and stationary zones, HCm and HCs, to the C term HC in the van Deemter [...] Read more.
A robust and elegant approach, based on the Two-Zone Moment Analysis (TZMA) method, is proposed to assess the contributions of the mobile and stationary zones, HCm and HCs, to the C term HC in the van Deemter equation for plate height. The TZMA method yields two formulations for HCm and HCs, both fully equivalent in terms of HC, yet offering different decompositions of the contributions from the mobile and stationary zones. The first formulation proposes an expression for the term HCs that has strong similarities, but also significant differences, from the well-known and widely used one proposed by Giddings. While it addresses the inherent limitation of Giddings’ approach—namely, the complete decoupling of transport phenomena in the moving and stationary zones—it introduces the drawback of a non-unique decomposition of HC. Despite this, it proves highly valuable in highlighting the limitations and flaws of Giddings’ method. In contrast, the second formulation not only properly accounts for the interaction between the moving and stationary zones, but provides a unique and consistent decomposition of HC into its components. Three different geometries are investigated in detail: the 2D triangular array of cylinders (pillar array columns), the 2D array of rectangular pillars (radially elongated pillar array columns) and the 3D face-centered cubic array of spheres. It is shown that Giddings’ approach significantly underestimates the HCs term, especially for porous-shell particles. Its accuracy is limited, being reliable only when intra-particle diffusivity (Ds) and the zone retention factor (k) are very low, or when axially invariant systems are considered. Full article
(This article belongs to the Section Chromatographic Separations)
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<p>(<b>a</b>) Intensity <span class="html-italic">I</span> of the normalized velocity field <math display="inline"><semantics> <mrow> <mi>I</mi> <mo>=</mo> <msqrt> <mrow> <msubsup> <mi>v</mi> <mi>x</mi> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi>v</mi> <mi>y</mi> <mn>2</mn> </msubsup> </mrow> </msqrt> <mo>/</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> </mrow> </semantics></math> and streamlines within the unit cell of the square array of fully porous cylinders. The figure highlights the fluid macro-porous region <math display="inline"><semantics> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi>m</mi> </msub> </semantics></math>, the meso-porous zone <math display="inline"><semantics> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi>s</mi> </msub> </semantics></math> (the stationary phase where adsorption takes place) and the three reference points. (<b>b</b>–<b>d</b>) Surface of the normalized <math display="inline"><semantics> <msub> <mi>b</mi> <mi>s</mi> </msub> </semantics></math> field <math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> for <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> <mo>=</mo> <mn>4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>=</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math> in three different cases, namely <math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mi>m</mi> </msub> <mo>=</mo> <msub> <mi>b</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> in point 1 (<b>b</b>), in point 2 (<b>c</b>), and in point 3 (<b>d</b>).</p>
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<p>Normalized total plate height <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mi>H</mi> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>=</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> </mrow> </semantics></math> (black dot–dashed curve) of the square array of fully porous cylinders for <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> <mo>=</mo> <mn>4</mn> </mrow> </semantics></math>, and the three different splits in <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mi>m</mi> </msub> <mo>=</mo> <msub> <mi>H</mi> <mi>m</mi> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>=</mo> <msub> <mi>H</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> depending on the point at which the constraint <math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mi>m</mi> </msub> <mo>=</mo> <msub> <mi>b</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> is enforced.</p>
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<p>(<b>a</b>) <math display="inline"><semantics> <mi>θ</mi> </semantics></math> evaluated from Giddings’ equations, Equations (<a href="#FD22-separations-12-00059" class="html-disp-formula">22</a>) and (<a href="#FD23-separations-12-00059" class="html-disp-formula">23</a>). (<b>b</b>–<b>f’</b>) <math display="inline"><semantics> <msub> <mi>θ</mi> <mrow> <mi>T</mi> <mi>Z</mi> </mrow> </msub> </semantics></math> evaluated from Equation (<a href="#FD25-separations-12-00059" class="html-disp-formula">25</a>) and the <math display="inline"><semantics> <msub> <mi>b</mi> <mi>s</mi> </msub> </semantics></math> field, Equations (<a href="#FD9-separations-12-00059" class="html-disp-formula">9</a>)–(<a href="#FD12-separations-12-00059" class="html-disp-formula">12</a>), thus enforcing the proper boundary condition <math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mi>s</mi> </msub> <msub> <mrow> <msub> <mo>|</mo> <mrow> <mo>∂</mo> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi>s</mi> </msub> </mrow> </msub> <mo>=</mo> <msub> <mi>b</mi> <mi>m</mi> </msub> <mo>|</mo> </mrow> <mrow> <mo>∂</mo> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi>s</mi> </msub> </mrow> </msub> </mrow> </semantics></math>. (<b>b</b>–<b>f</b>) refer to <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>. (<b>b’</b>–<b>f’</b>) refer to <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>.</p>
Full article ">Figure 4
<p>(<b>a</b>) Geometry of the square array of porous-shell cylindrical particles, <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>=</mo> <msub> <mi>R</mi> <mi>i</mi> </msub> <mo>/</mo> <msub> <mi>R</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math>. (<b>b</b>–<b>i</b>) Comparison between <math display="inline"><semantics> <mi>θ</mi> </semantics></math> evaluated from Giddings equations, Equations (<a href="#FD22-separations-12-00059" class="html-disp-formula">22</a>) and (<a href="#FD23-separations-12-00059" class="html-disp-formula">23</a>) (gray surfaces), and <math display="inline"><semantics> <msub> <mi>θ</mi> <mrow> <mi>T</mi> <mi>Z</mi> </mrow> </msub> </semantics></math> (colored surfaces) evaluated from Equation (<a href="#FD25-separations-12-00059" class="html-disp-formula">25</a>) and the <math display="inline"><semantics> <msub> <mi>b</mi> <mi>s</mi> </msub> </semantics></math> field, Equations (9)–(13). (<b>b</b>–<b>e</b>) refer to <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math>. (<b>f</b>–<b>i</b>) refer to <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>.</p>
Full article ">Figure 5
<p>The 2D and 3D geometries investigated. (<b>a</b>) Array of 2D cylindrical pillars arranged on an equilateral triangular mesh, <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math> (<b>b</b>) Array of 2D rectangular pillars, aspect ratio <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>. (<b>c</b>,<b>d</b>) Face-centered cubic array of spheres, <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>. Color plots indicate the intensity <span class="html-italic">I</span> of the normalized velocity field <math display="inline"><semantics> <mrow> <mi>I</mi> <mo>=</mo> <mrow> <mo>|</mo> <mo>|</mo> <mi mathvariant="bold">v</mi> <mo>|</mo> <mo>|</mo> </mrow> <mo>/</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> </mrow> </semantics></math>. Arrow plots indicate the streamlines.</p>
Full article ">Figure 6
<p><math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>H</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>=</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> </mrow> </semantics></math> for the array of 2D cylindrical pillars, for fully porous particles (<b>a</b>–<b>c</b>) and porous-shell particles (<b>d</b>–<b>f</b>) with <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>=</mo> <msub> <mi>d</mi> <mi>i</mi> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math>. Arrows indicate increasing values of <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> (<span class="html-italic">orange</span>), 0.2 (<span class="html-italic">blue</span>), 0.3 (<span class="html-italic">green</span>), 0.5 (<span class="html-italic">red</span>). Three different values of <math display="inline"><semantics> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> </semantics></math> have been considered, namely <math display="inline"><semantics> <mrow> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> <mo>=</mo> <mn>2</mn> <mo>,</mo> <mn>8</mn> <mo>,</mo> <mn>12</mn> </mrow> </semantics></math>. Continuous lines indicate results from the TZMA approach (Equation (<a href="#FD21-separations-12-00059" class="html-disp-formula">21</a>)). Dot–dashed lines indicate results from the Giddings’ approach (Equation (<a href="#FD3-separations-12-00059" class="html-disp-formula">3</a>)).</p>
Full article ">Figure 7
<p><math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>H</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>=</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> </mrow> </semantics></math> for the array of rectangular pillars, for fully porous particles (<b>a</b>,<b>b</b>) and porous-shell particles (<b>c</b>,<b>d</b>) with <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>=</mo> <msub> <mi>d</mi> <mi>i</mi> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>0.8</mn> </mrow> </semantics></math>. Arrows indicate increasing values of <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> (<span class="html-italic">orange</span>), 0.2 (<span class="html-italic">blue</span>), 0.3 (<span class="html-italic">green</span>), 0.5 (<span class="html-italic">red</span>). Two different values of <math display="inline"><semantics> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> </semantics></math> have been considered, namely <math display="inline"><semantics> <mrow> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> <mo>=</mo> <mn>2</mn> <mo>,</mo> <mn>8</mn> </mrow> </semantics></math>. (<b>a’</b>–<b>d’</b>) show the magnification of the corresponding (<b>a</b>–<b>d</b>) for <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>∈</mo> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>20</mn> <mo>]</mo> </mrow> </semantics></math>. Continuous lines indicate results from the TZMA approach (Equation (<a href="#FD21-separations-12-00059" class="html-disp-formula">21</a>)). Dotted lines indicate results from Giddings’ approach (Equation (<a href="#FD3-separations-12-00059" class="html-disp-formula">3</a>)).</p>
Full article ">Figure 8
<p><math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>H</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>C</mi> <mi>m</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>H</mi> <mrow> <mi>C</mi> <mi>m</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>=</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> </mrow> </semantics></math> for the array of fully porous rectangular pillars, for <math display="inline"><semantics> <mrow> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math>. (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>. (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>. Continuous lines indicate results from the TZMA approach (Equation (<a href="#FD21-separations-12-00059" class="html-disp-formula">21</a>)). Dot–dashed lines indicate results from the Giddings’ approach (Equation (<a href="#FD3-separations-12-00059" class="html-disp-formula">3</a>)).</p>
Full article ">Figure 9
<p><math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>H</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>C</mi> <mi>m</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>H</mi> <mrow> <mi>C</mi> <mi>m</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>=</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> </mrow> </semantics></math> for the face-centered cubic array of spheres, for <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>. (<b>a</b>,<b>b</b>) Fully porous particles. (<b>c</b>,<b>d</b>) Porous-shell particles, <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>=</mo> <msub> <mi>d</mi> <mi>i</mi> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math>. Three different values of <math display="inline"><semantics> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> </semantics></math> have been considered, namely <math display="inline"><semantics> <mrow> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>16</mn> </mrow> </semantics></math>. Continuous lines indicate results from the TZMA approach (Equation (<a href="#FD21-separations-12-00059" class="html-disp-formula">21</a>)). Dot–dashed lines indicate results from the Giddings’ approach (Equation (<a href="#FD3-separations-12-00059" class="html-disp-formula">3</a>)).</p>
Full article ">Figure 10
<p>(<b>a</b>) Axially invariant system with the main fluid flow component <math display="inline"><semantics> <msub> <mi>v</mi> <mi>x</mi> </msub> </semantics></math> parallel to the pillar symmetry axis. Colors indicate the normalized axial velocity <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>x</mi> </msub> <mo>/</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> </mrow> </semantics></math>. Arrows indicate the streamlines (straight lines). (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>H</mi> <mrow> <mi>C</mi> <mi>s</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>d</mi> <mi>p</mi> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>P</mi> <mi>e</mi> <mo>=</mo> <msub> <mi>U</mi> <mi>i</mi> </msub> <msub> <mi>d</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> </mrow> </semantics></math> for porous-shell pillars, <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msup> <mi>k</mi> <mrow> <mo>″</mo> </mrow> </msup> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math>. Arrow indicates increasing values of <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msub> <mi>D</mi> <mi>s</mi> </msub> <mo>/</mo> <msub> <mi>D</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>0.1</mn> <mo> </mo> <mrow> <mo>(</mo> <mi>o</mi> <mi>r</mi> <mi>a</mi> <mi>n</mi> <mi>g</mi> <mi>e</mi> <mo>)</mo> </mrow> <mo>,</mo> <mo> </mo> <mn>0.2</mn> <mo> </mo> <mrow> <mo>(</mo> <mi>b</mi> <mi>l</mi> <mi>u</mi> <mi>e</mi> <mo>)</mo> </mrow> <mo>,</mo> <mo> </mo> <mn>0.3</mn> <mo> </mo> <mrow> <mo>(</mo> <mi>g</mi> <mi>r</mi> <mi>e</mi> <mi>e</mi> <mi>n</mi> <mo>)</mo> </mrow> <mo>,</mo> <mo> </mo> <mn>0.5</mn> <mo> </mo> <mrow> <mo>(</mo> <mi>r</mi> <mi>e</mi> <mi>d</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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21 pages, 322 KiB  
Article
A Quasi-Explicit Method Applied to Missing Boundary Data Reconstruction for the Stokes System
by Abdulaziz H. Alharbi, Fadhel Jday, Abdulrahman B. Albidah and Ali M. Alhartomi
Axioms 2025, 14(3), 177; https://doi.org/10.3390/axioms14030177 - 27 Feb 2025
Viewed by 140
Abstract
In this paper, we study the data completion problem for the Cauchy–Stokes equation in a cylindrical domain, Ω. Neumann and Dirichlet boundary conditions are prescribed on part of the overdetermined boundary, Γ0, and the goal is to complete the data [...] Read more.
In this paper, we study the data completion problem for the Cauchy–Stokes equation in a cylindrical domain, Ω. Neumann and Dirichlet boundary conditions are prescribed on part of the overdetermined boundary, Γ0, and the goal is to complete the data on the other part of the boundary, Γa. Here, Γ0 and Γa represent the side faces of the cylinder Ω. This problem is known to be ill-posed and is formulated as an optimal control problem with a regularized cost function. To directly approximate the missing data on Γa, we employ the method of factorization of elliptic boundary value problems. This technique allows the factorization of a boundary value problem into a product of parabolic problems. It is successfully applied to the optimality system in this work, yielding new and significant results. Full article
(This article belongs to the Special Issue Principles of Variational Methods in Mathematical Physics)
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Figure 1

Figure 1
<p>Schematic representation of the cylindrical domain <math display="inline"><semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics></math>.</p>
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<p>Schematic representation of the moving domain <math display="inline"><semantics> <msub> <mi mathvariant="sans-serif">Ω</mi> <mi>s</mi> </msub> </semantics></math>.</p>
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28 pages, 15824 KiB  
Article
Influence of Crank Angle Offset on the Mechanical Performance of Different Hydrogen-Fueled Opposed-Piston Engine Architectures
by Andrea Piergiacomi, Saverio Giulio Barbieri, Valerio Mangeruga and Matteo Giacopini
Appl. Sci. 2025, 15(5), 2537; https://doi.org/10.3390/app15052537 - 26 Feb 2025
Viewed by 262
Abstract
Decarbonization of the automotive sector is essential to achieve global climate goals, as passenger cars contribute a substantial share of CO2 emissions. This research project focuses on the preliminary design of an innovative 2-stroke hydrogen-fueled opposed-piston engine, offering a promising solution for [...] Read more.
Decarbonization of the automotive sector is essential to achieve global climate goals, as passenger cars contribute a substantial share of CO2 emissions. This research project focuses on the preliminary design of an innovative 2-stroke hydrogen-fueled opposed-piston engine, offering a promising solution for reducing emissions from passenger cars. Hydrogen enables clean combustion due to its carbon-free nature and allows the possibility of nearly-zero NOx emissions when burned in an ultra-lean mixture. Although the ultra-lean mixture inevitably leads to a significant drop in performance, the opposed-piston engine architecture offers a potential solution for maintaining power output and overall dimensions comparable to traditional internal combustion engines. The study addressed the global balancing of the engine. Unlike conventional engines, the opposed-piston engine presents non-trivial challenges, such as the interaction between the two crankshafts. Two engine architectures are addressed: 3-cylinder and 4-cylinder. Full article
(This article belongs to the Section Mechanical Engineering)
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Figure 1

Figure 1
<p>3D model of a generic OP crank mechanism.</p>
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<p>Configurations considered in the analysis; (<b>a</b>) 3-cylinder crankshaft with <math display="inline"><semantics> <mrow> <mi>β</mi> <mo>=</mo> <mn>120</mn> <mo>°</mo> </mrow> </semantics></math>; (<b>b</b>) 4-cylinder crankshaft with <math display="inline"><semantics> <mrow> <mi>β</mi> <mo>=</mo> <mn>90</mn> <mo>°</mo> </mrow> </semantics></math>.</p>
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<p>Crankshaft layouts of all configurations; (<b>a</b>) 3-cylinder co-rotating crankshafts; (<b>b</b>) 3-cylinder counter-rotating crankshafts; (<b>c</b>) 4-cylinder co-rotating crankshafts; (<b>d</b>) 4-cylinder counter-rotating crankshafts.</p>
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<p>Offset angle, α, between intake (left) and exhaust (right) crankshafts; (<b>a</b>) co-rotating shafts; (<b>b</b>) counter-rotating shafts.</p>
Full article ">Figure 5
<p>The resultant moment <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="bold-italic">M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> <mo>,</mo> <mi>t</mi> <mi>o</mi> <mi>t</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msubsup> </mrow> </semantics></math> generated by the rotating portion of the first-order alternating forces <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="bold-italic">F</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> <mo>,</mo> <mi>i</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msubsup> </mrow> </semantics></math> of each crank mechanism in the 3-cylinder co-rotating configuration, with and without offset.</p>
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<p>Pressure profile.</p>
Full article ">Figure 7
<p>Resultant moment under zero offset conditions for 3-cylinder configuration; (<b>a</b>) co-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced; (<b>b</b>) counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced; (<b>c</b>) co-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced; (<b>d</b>) counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced.</p>
Full article ">Figure 7 Cont.
<p>Resultant moment under zero offset conditions for 3-cylinder configuration; (<b>a</b>) co-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced; (<b>b</b>) counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced; (<b>c</b>) co-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced; (<b>d</b>) counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced.</p>
Full article ">Figure 8
<p>Resultant moment under zero offset conditions for 4-cylinder configuration; (<b>a</b>) co-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced; (<b>b</b>) counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced; (<b>c</b>) co-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced; (<b>d</b>) counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced.</p>
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<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced (scenario 2) and with different offset angles for 3-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 9 Cont.
<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced (scenario 2) and with different offset angles for 3-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 10
<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced (scenario 2) and with different offset angles for 4-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 10 Cont.
<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> unbalanced (scenario 2) and with different offset angles for 4-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 11
<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced (scenario 2) and with different offset angles for 3-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 11 Cont.
<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced (scenario 2) and with different offset angles for 3-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 12
<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced (scenario 2) and with different offset angles for 4-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 12 Cont.
<p>Resultant moment of co-rotating and counter-rotating shafts with <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>M</mi> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>c</mi> <mo>,</mo> <mi>r</mi> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math> balanced (scenario 2) and with different offset angles for 4-cylinder configuration; (<b>a</b>) co-rotating with 0° offset; (<b>b</b>) counter-rotating with 0° offset; (<b>c</b>) co-rotating with 5° offset; (<b>d</b>) counter-rotating with 5° offset; (<b>e</b>) co-rotating with 10° offset; (<b>f</b>) counter-rotating with 10° offset; (<b>g</b>) co-rotating with 15° offset; (<b>h</b>) counter-rotating with 15° offset.</p>
Full article ">Figure 13
<p>Output torque of a single cylinder; (<b>a</b>) 0° offset; (<b>b</b>) 5° offset; (<b>c</b>) 10° offset; (<b>d</b>) 15° offset.</p>
Full article ">Figure 13 Cont.
<p>Output torque of a single cylinder; (<b>a</b>) 0° offset; (<b>b</b>) 5° offset; (<b>c</b>) 10° offset; (<b>d</b>) 15° offset.</p>
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<p>Output torque profile of a 3-cylinder OP engine as the offset angle varies: (<b>a</b>) 0° offset; (<b>b</b>) 5° offset; (<b>c</b>) 10° offset; (<b>d</b>) 15° offset.</p>
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<p>Output torque profile of a 4-cylinder OP engine as the offset angle varies: (<b>a</b>) 0° offset; (<b>b</b>) 5° offset; (<b>c</b>) 10° offset; (<b>d</b>) 15° offset.</p>
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19 pages, 2917 KiB  
Article
Estimation of Upper Limb Motor Function and Its Use in Activities of Daily Living Based on the Performance Time Required for the Cylinder Transfer Task in Patients with Post-Stroke Mild Hemiparesis: A Cross-Sectional Study
by Daigo Sakamoto, Toyohiro Hamaguchi, Mina Yamamoto, Risa Aoki, Kenta Suzumura, Yasuhide Nakayama and Masahiro Abo
J. Clin. Med. 2025, 14(5), 1591; https://doi.org/10.3390/jcm14051591 - 26 Feb 2025
Viewed by 147
Abstract
Background/Objective: Evaluating the upper limb function of the paretic and non-paretic sides of patients post-stroke is important for predicting the efficient use of the upper limbs in activities of daily living. Although there are evaluation methods that can quantify bilateral upper limb function, [...] Read more.
Background/Objective: Evaluating the upper limb function of the paretic and non-paretic sides of patients post-stroke is important for predicting the efficient use of the upper limbs in activities of daily living. Although there are evaluation methods that can quantify bilateral upper limb function, they are insufficient for understanding the motor characteristics of individual patients. In this study, we aimed to quantitatively evaluate bilateral upper limb function from the performance time of the cylinder transfer task of The Southampton Hand Assessment Procedure and to estimate the use status of the paralyzed upper limb. Methods: This cross-sectional study included 88 participants with hemiparesis post-stroke. Performance time in the three phases of the cylinder transfer task and the total performance time of these phases were measured. Moreover, existing upper limb function assessments were made. Results: The total performance time of the paralyzed side showed a significant correlation with the existing upper limb function assessments. A regression model was calculated to estimate the score of the existing upper limb function assessment from the performance time of each phase. Conclusions: This new evaluation method is a useful tool for monitoring the recovery of motor paralysis in patients post-stroke. It is our hope that clinicians will use these objective performance data to provide more effective rehabilitation treatment for patients recovering from stroke. Full article
(This article belongs to the Section Clinical Rehabilitation)
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Figure 1
<p>Configuration of the instrument and method of measuring motion time. (<b>a</b>) Configuration and dimensions. (<b>b</b>) Methods of measuring performance time.</p>
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<p>Measurement setup and limb positions of the participants. The two conditions of the motor task were (<b>a</b>) the frontal task, in which the stand was placed 20 cm away from the bottom edge of the desk; and (<b>b</b>) the ipsilateral task, in which the stand was placed 20 cm away from the bottom edge of the desk and 30 cm away from the midline of the start and stop switches. (<b>c</b>) Participants’ limb positions.</p>
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<p>Patient selection procedure.</p>
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<p>Correlation between total performance time and functional assessment scores. Scatterplots show the relationship between total performance time and FMA-UE scores (<b>a</b>,<b>d</b>), as well as between the JASMID quantity (<b>b</b>,<b>e</b>) and quality (<b>c</b>,<b>f</b>) scores in frontal (<b>a</b>–<b>c</b>) and ipsilateral (<b>d</b>–<b>f</b>) tasks. The logarithmic trend lines illustrate significant negative correlations (<span class="html-italic">p</span> &lt; 0.001), indicating that longer performance times are associated with greater motor impairment and reduced upper limb use in daily activities. FMA-UE, Fugl–Meyer Assessment of the Upper Extremity; JASMID, Jikei Assessment Scale for Motor Impairment in Daily Living.</p>
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<p>Binomial logistic regression analysis for total performance time in frontal and ipsilateral tasks. The logistic regression models predict the probability of the upper limb being on the paretic side based on total performance time. (<b>a</b>) Shows the regression curve for the frontal, and (<b>b</b>) indicates that for the ipsilateral task. The vertical axis represents the probability that the limb is paretic, with higher values indicating a greater likelihood. Both models demonstrate significant predictive accuracy (<span class="html-italic">p</span> &lt; 0.001). ROC curve analysis was used to determine cut-off values for distinguishing between the paretic and non-paretic sides. FMA-UE; Fugl–Meyer Assessment of the Upper Extremity; JASMID, Jikei Assessment Scale for Motor Impairment in Daily Living; ROC, receiver operating characteristic.</p>
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<p>Research instrument. (<b>a</b>) Evaluation instrument set, (<b>b</b>) cylinder and stand, (<b>c</b>) inside of attache case, (<b>d</b>) attache case for storage of evaluation instrument.</p>
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13 pages, 1237 KiB  
Article
Toric Aberrometric Extended Depth of Focus Intraocular Lens: Visual Outcomes, Rotational Stability, Patients’ Satisfaction, and Spectacle Independence
by Erika Bonacci, Camilla Pagnacco, Marco Anastasi, Alessandra De Gregorio, Giorgio Marchini and Emilio Pedrotti
J. Pers. Med. 2025, 15(3), 88; https://doi.org/10.3390/jpm15030088 - 26 Feb 2025
Viewed by 133
Abstract
Objective: To evaluate visual outcomes, rotational stability, patients’ satisfaction, and spectacle independence after bilateral Toric extended depth of focus intraocular lens (EDOF IOL) implantation. Methods: Prospective observational study including cataract patients with bilateral corneal astigmatism between 0.75 and 3.00 D implanted with [...] Read more.
Objective: To evaluate visual outcomes, rotational stability, patients’ satisfaction, and spectacle independence after bilateral Toric extended depth of focus intraocular lens (EDOF IOL) implantation. Methods: Prospective observational study including cataract patients with bilateral corneal astigmatism between 0.75 and 3.00 D implanted with Toric EDOF IOLs. After three months distance corrected and uncorrected visual acuity at 4 m (DCVA and UDVA), 80 cm (DCI80VA and UI80VA), 67 cm (DCI67VA and UI67VA), and 40 cm (DCNVA and UNVA), IOL stability by Toric IOL Assistant tool (Osiris T, CSO, Florence, Italy), binocular defocus curves, contrast sensitivity (CS), halometry, reading performance, and subjective and objective (Root mean square-RMS, modulation transfer function-MTF, cut-off and point-spread-function-PSF-Strehl ratio) visual quality were evaluated. Results: Forty eyes from 20 astigmatic patients were enrolled. Mean refractive spherical equivalent and residual cylinder were −0.21 ± 0.74 D and 0.29 ± 0.31 D, respectively. No patients needed additional surgery due to IOL rotation. Binocular UDVA, UI80VA, UI67VA, and UNVA ≤ 0.2 logMAR was found in 90%, 95%, 85%, and 80%. Distance-corrected visual outcomes have overall shown higher performances. All visual acuities at defocus curves were ≤0.125 logMAR between +0.50 D and −2.00 D. PSF-Strehl ratio, MTF cut-off, RMS were 0.26 ± 0.28, 19.82 ± 12.35, 0.31 ± 0.17. Reading analysis reached 125.42 ± 27.21 words/minute, 92.56 ± 7.82, 0.17 ± 0.15 logMAR and 0.50 ± 0.11 logRAD for mean reading speed, visual acuity score, reading acuity, and critical print size, respectively. CS was higher in photopic conditions. Subjective spectacle independence was achieved in 80% of patients. Conclusions: Toric EDOF IOL showed rotational stability and reliable astigmatic correction. It provided spectacle independence and good performance from distance to near distance, reaching high patient satisfaction without undermining binocular quality of vision. Full article
(This article belongs to the Special Issue Current Trends in Cataract Surgery)
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Figure 1
<p>Postoperative spherical equivalent refractive accuracy and postoperative refractive cylinder. EDOF = extended depth of focus; D = diopter.</p>
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<p>Cumulative distribution of postoperative monocular (<b>A</b>,<b>B</b>) and binocular (<b>C</b>,<b>D</b>) visual outcomes for the Toric extended depth of focus (EDOF) Miniwell Toric intraocular lens (IOL). UDVA = uncorrected distance visual acuity; UI80VA = uncorrected intermediate (80 cm) visual acuity; UI67VA = uncorrected intermediate (67 cm) visual acuity; UNVA = uncorrected near visual acuity; DCVA = corrected distance visual acuity; DCI80VA = distance-corrected intermediate (80 cm) visual acuity; DCI67VA = distance-corrected intermediate (67 cm) visual acuity; DCNVA = distance-corrected near visual acuity.</p>
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<p>The graph shows the differences in logMAR between uncorrected visual acuity and DCVA, collected monocularly (blue) and binocularly (orange) at different distances. Monocular and binocular uncorrected (UDVA) versus corrected (DCVA) distance visual acuity. Monocular and binocular uncorrected (UI80VA) versus distance-corrected (DCI80VA) intermediate at 80 cm visual acuity. Monocular and binocular uncorrected (UI67VA) versus distance-corrected (DCI67VA) intermediate at 67 cm visual acuity. Monocular and binocular uncorrected (UNVA) versus distance-corrected (DCNVA) near visual acuity.</p>
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<p>Mean binocular defocus curve, contrast sensitivity function of the EDOF Toric IOL and its monofocal version measured under scotopic, mesopic, and photopic conditions and six-vertex halometry 3 months after bilateral Toric EDOF IOL implantation. D = diopters.</p>
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