Engineering

Abstract: This research focuses on our bidirectional Greedy pairing of the mechanical vibrations of a Hydra-Rib basketball rim and backboard, which had an National Collegiate Athletic Association (NCAA) and Fédération Internationale de Basketball (FIBA) mandated Energy Rebound Testing Device (ERTD) suspended from it. The Experimental Modal Analysis (EMA) used Brüel & Kjær vibration instrumentation to gather vibration data which was then processed by the Spectral Dynamics STAR7 package into mode-shapes and frequencies. A MECWAY Finite Element Analysis (FEA) analytical model of the basketball rim, backboard, and frame was created using hexahedral elements, and the ERTD which hung from the outer end of the basketball rim was modeled as a 3kg truss element. The EMA and FEA mode-shapes were then exported for processing by our GNU Octave programming, which employed a bidirectional Greedy selection algorithm to pair those EMA and FEA modes which most closely matched, to generate our Cross Application Modal Assurance Criterion (CrossMAC). This CrossMAC showed high values along its main-diagonal, showing good agreement between like mode-shapes, and low off-diagonal values, indicating desired orthogonality, and we achieved a Frequency MAPE of 23.3% and a Mode-Shape MAPE of 5.974%.

Abstract: Surface defects strongly influence the fatigue strength of AlSi10Mg manufactured by Laser Powder Bed Fusion for Metals (PBF-LB/M), particularly for specimens with as-built surfaces. This work presents a non-destructive procedure for determining a fatigue relevant defect parameter from confocal measurements of the as-built surface before fatigue testing. Surface valleys were identified from the measured three-dimensional topography and projected onto the plane perpendicular to the loading direction, which enabled the determination of the projected defect area A_⊥ and the corresponding defect parameter √(A_⊥ ), comparable to the parameter √area. The procedure was evaluated on 36 specimens covering variation in PBF-LB/M process parameters, different orientations of the specimens in relation to the building direction and two heat-treatment conditions, i.e., T6 and not heat-treated. After fully reversed axial fatigue testing (R=-1), the sizes of the crack-initiating defects were determined by fracture surface analysis and were compared to the values obtained by confocal microscopy. The differently determined defect sizes were generally in the same range, showing similar trends in dependency with the variation in manufacturing process and orientation of the specimens. Accordingly, the fatigue strength estimation by means of √area approach resulted in only small deviations (within a factor of 1.2) between the conventional approach based on fracture surface analysis and the methodology proposed in this work. These results demonstrate the applicability of confocal surface measurements for determining fatigue-relevant surface-defect parameters for non-destructive assessment of the fatigue strength.

Abstract: To address the issues of lengthy vibration durability test cycles for seat frames and poor consistency of damage equivalence at different locations under multiaxial excitation in existing acceleration methods, this paper proposes a frequency-segmented accelerated vibration test method based on damage rate equivalence. The method derives an analytical relationship between damage rate and stress spectral moments based on the Dirlik broadband damage estimation, enabling frequency-selective amplification of the acceleration PSD, thereby compressing test duration while maintaining a constant damage rate ratio at critical nodes. The proposed method is implemented in three strategies—triaxial full-band, triaxial frequency-segmented, and uniaxial frequency-segmented—and compared with the Inverse Power Law (IPL) and Fatigue Damage Spectrum (FDS) methods. Through finite element analysis of a seat frame and dynamic force measurements on a six-degree-of-freedom hydraulic shaker, the damage rate ratios at four structural nodes are used as indicators to evaluate each method. Results show that when the triaxial frequency-segmented strategy (DRR-TP) achieves the target damage rate ratio of 0.25, the thrust increase is only 17.1 %, substantially lower than the 21.0 % increase from full-band acceleration, while displacement requirements remain nearly unchanged. At the calibrated node, DRR-TP provides the best accuracy, comparable to FDS and superior to IPL and the uniaxial strategy. However, deviations exist across all methods at non-calibrated nodes, with IPL and the uniaxial strategy being particularly pronounced. Furthermore, accelerated high-intensity road spectra may produce stresses approaching the yield limit, necessitating amplitude constraints. Overall, the DRR-TP method offers a favorable balance between efficiency and equipment feasibility, providing a practical framework for accelerated durability testing of seat frames.

Abstract: Wide-cut heavy disc harrows are widely used for tillage of perennial grass sod, summer fallow, and stubble fields; however, imported implements commonly used in Kazakhstan are not always sufficiently adapted to local soil and operating conditions, which may re-sult in incomplete sod undercutting, uneven crop residue incorporation, and increased draft resistance. This study aimed to substantiate the configuration, design parameters, and operating conditions of a wide-cut heavy disc harrow for traction class 5–6 tractors under the soil and field conditions of Northern Kazakhstan. Field experiments were conducted to evaluate the effects of disc arrangement, disc angle, operating speed, and support and finishing elements on tillage quality, draft resistance, and energy consump-tion. The developed configuration consisted of a central frame with folding side wings, eight disc sections arranged in two rows, support and transport wheels, an adjustable hitch, and a rear rod roller, with a 7.0 m working width, 660 mm notched discs, and 210 mm disc spacing. Under the investigated conditions, the harrow operated at speeds of up to 11.5 km h⁻¹ and, at disc section angles of 12°, 15°, and 18°, achieved a surface roughness of 3–5 cm, eliminated clods larger than 100 mm, and required 63.8–78.3 MJ ha⁻¹ of specific energy. The results provide experimental evidence for the suitability of the investigated structural configuration and operating parameters for heavy disc harrowing under the field conditions of Northern Kazakhstan.

Abstract: There is renewed interest in the phenomenon of limiting shear stress (LSS); an essential component of friction modelling in elastohydrodynamic lubrication (EHL), perhaps because it is thought to be detectable and measurable by a simple friction measurement. In a sense, this is true, but only with knowledge of the viscosity under the conditions of the friction data. The LSS dependence on pressure may be extracted from EHL traction only if the LSS is operating over nearly all the contact area. Otherwise, the value of the LSS will be understated. Recent attempts have utilized contact pressures that are insufficient to achieve the LSS over enough of the contact and the resulting pressure dependence erroneously appears to make the LSS go to zero at a large positive pressure. The current work discusses precautionary measures for a proper extraction of LSS from traction measurements, to be used in EHL friction modelling.

Abstract: This comprehensive research article presents the empirical validation of a strategic maintenance engineering model through the systematic testing of 100 hypotheses (H1-H100) examining the complex interrelationships between external environmental factors, internal operational conditions, mediating results, and final organizational outcomes in physical asset maintenance management. The study employs a mixed-methods approach combining quantitative survey data from 124 organizations with qualitative inter-views, utilizing structural equation modeling and T-Student tests for hypothesis validation. The research investigates twelve dis-tinct relationship domains: (1) indirect external conditions and internal controls, (2) direct external conditions and internal controls, (3) internal mechanisms and controls, (4) indirect external conditions and mediating results, (5) direct external conditions and me-diating results, (6) internal conditions and mediating results, (7) mediating results between environment and internal, (8) mediating results and political management outcomes, (9) mediating results and operational outcomes, (10) political management and opera-tional outcomes, (11) final results, and (12) final results with control variables. The findings reveal that 78% of hypotheses were confirmed, demonstrating significant relationships between strategic maintenance management and organizational performance indicators including cost management, quality strategies, availability optimization, and overall productivity. The study proposes a five-stage strategic maintenance model: diagnostic analysis, strategic conditioning, implementation, evaluation, and strategic feedback. This research contributes to the theoretical development of maintenance engineering by integrating resource depen-dency theory, strategic management theory, and chaos theory into a unified framework for physical asset management. The im-plications extend to Industry 4.0 contexts, where IoT-based predictive maintenance and digital twin technologies are transforming traditional maintenance paradigms.

Abstract: Accurate prediction of wind speed percentiles is essential for diverse applications, including wind energy assessment, infrastructure resilience to extreme winds, and the reliable operation of wind turbines. Among these, the 25th percentile—commonly referred to as the first quartile—plays a key role in characterizing low-wind conditions. A previous statistical model, originally developed for wind speed probability distributions, showed poor performance in predicting the 25th percentile when applied to urban environments, with significant underestimation and scatter relative to reference data. In this study, an optimization of that statistical model is undertaken to improve its predictive capability specifically for the 25th percentile. Large Eddy Simulation (LES) data from a wind tunnel experiment representing a typical urban morphology are used as a reference. The original model’s predictions are first evaluated against the LES-derived 25th percentiles, confirming persistent underestimation (fractional bias FB = 0.25). To address this, correlations between the 25th percentiles and key statistical descriptors—namely mean, standard deviation, skewness, kurtosis, and maximum wind speed—are systematically examined. Linear and power-law fits are developed, revealing strong linear relationships with the mean and skewness, and a robust power-law relationship with the maximum wind speed. No meaningful correlations are found with standard deviation or kurtosis. The proposed corrections offer a simple yet effective physical scaling framework to mitigate internal model bias for the 25th wind speed percentile within the investigated urban setup. While further out-of-sample validation across varied topologies is required, the modified approach demonstrates promising potential for future integration into urban wind resource assessment, microclimate planning, and environmental risk tools.

Abstract: This study investigates the role of shots on shot peening of austenitic steel AISI 304 as a function of shot peening cycles when the conventional steel shots are compared with the ceramic ones. The surface state is analysed in terms of dislocation density, stress state, and the phase transformation of the metastable paramagnetic austenite into the ferromagnetic strain-induced martensite. The sharp transition in magnetic state is monitored via Barkhausen noise emission. It was found that the height of the surface irregularities is nearly unaffected by the number of shot peening cycles and by the different shots. On the other hand, an increasing number of shot peening cycles leads to greater surface damage, as evidenced by the strain-induced martensite fraction and dislocation density. The use of steel shots results in greater microstructural alterations at greater penetration depths due to their higher mass and lower shot velocity. In contrast, ceramic shots produce a higher amplitude of surface stress. Barkhausen noise emission from the steel shots is stronger, which is linked to the higher fraction of strain-induced martensite, especially in the deeper regions. The application of steel shots can initiate and accelerate surface corrosion due to shot contamination, in contrast to the unaffected corrosion resistance of ceramic shots.

Abstract: Predicting the interaction and competition of multiple hydraulic fractures is essential for designing efficient stimulation treatments in shale reservoirs. This study develops a two-dimensional hydro-mechanical finite-discrete element method (FDEM) framework that couples Biot poroelasticity, Darcy flow in the rock matrix, cubic-law flow in fractures, Carter-type leak-off, cohesive-zone damage, and post-failure block contact. The model is verified against the classical KGD solution; the relative errors in fracture half-length and maximum aperture remain below 3%. A parametric study is then performed to quantify the effects of horizontal principal stress difference, cluster spacing, injection rate, and fracturing-fluid viscosity on multi-cluster fracture growth. Increasing the horizontal stress difference suppresses deflection and branching and promotes nearly planar fracture growth. Increasing cluster spacing weakens stress-shadow interference, and the middle-fracture length increases from 18.5 m at 5 m spacing to 39.8 m at 20 m spacing. Increasing the injection rate from 6 to 12 m3/min raises the maximum fracture aperture from 1.4 to 3.2 mm and promotes secondary branching. Low-viscosity fluid enhances leak-off and shear-dominated branching, whereas high-viscosity fluid favors wider, tensile-dominated fractures; at 100 mPa·s, the branching frequency is 72% lower than in the 1 mPa·s case. The combined results indicate that a high injection rate, moderate cluster spacing, and subsequent low-viscosity slickwater displacement provide a favorable strategy for enhancing fracture-network development. The framework provides a process-oriented numerical basis for parameter screening and hydraulic-fracturing design in shale reservoirs.

Abstract: This study investigates fully developed stratified gas–liquid magnetohydrodynamic (MHD) flow of an electrically conducting liquid and a nonconducting gas in inclined rectangular ducts subjected to a vertical magnetic field. Analytical and numerical solutions for the velocity and induced magnetic fields are obtained in terms of the governing dimensionless parameters for concurrent upward, concurrent downward, and countercurrent flows. Unlike single-phase MHD flow, duct inclination strongly affects two-phase flow by altering the liquid holdup and the relative contributions of gravitational, frictional, and electromagnetic forces.The results reveal a complex interplay among gravity, Lorentz forces, and wall and interfacial shear stresses. These interactions govern the liquid holdup, pressure gradient, multiple steady solutions, flooding limits, local backflow, jet-like velocity structures, and pumping requirements. Wall conductivity critically affects the induced magnetic field and Lorentz-force distribution and therefore cannot be neglected, even at very small magnetic Reynolds numbers. Fully insulating ducts generally exhibit the weakest electromagnetic effects and behavior closest to non-MHD flow. Configurations with a conducting bottom wall exhibit substantially stronger electromagnetic effects and greater sensitivity to side-wall conductivity, leading to pronounced changes in the velocity field, liquid holdup, pressure gradient, gas-lubrication effect, and overall pumping-power requirements.

Abstract: Accurate dimensional and deformation measurement of mechanical components is central to manufacturing quality control and experimental mechanics. Contact-based instruments such as Vernier calipers, micrometers, and coordinate measuring machines (CMMs) are widely used but introduce measurement loading and cannot simultaneously capture multi-point displacements. Commercial optical alternatives, such as Vic-2D and GOM Aramis for Digital Image Correlation (DIC) and HALCON for machine vision, provide high accuracy but carry license costs that restrict adoption in academic laboratories and small engineering workshops. This review examines two freely available, open-source platforms that together provide comprehensive non-contact 2D measurement of planar mechanical components: Python OpenCV, which enables camera calibration, homography-based planar reconstruction, adaptive Gaussian thresholding for metallic surfaces, and sub-pixel edge detection; and MATLAB NCORR, an open-source Digital Image Correlation (DIC) package that computes full-field displacement and strain maps from random speckle patterns. The review is directed at general planar mechanical components as: flat rectangular parts, cylindrical fasteners, threaded screws, gears, and beam specimens.Experimental results obtained using a mobile phone camera and the Python-OpenCV pipeline demonstrate dimensional measurement errors below 1.5% relative to Vernier caliper measurements for a flat rectangular component (scientific calculator) and below 1% for length and outer diameter of a metallic machine screw, confirming sub-millimetre accuracy for components in the 10–200 mm size range. Thread pitch measurement via horizontal edge projection is reported as a specific limitation at standard mobile phone image magnification, with error exceeding 89%, and a Hough Transform solution is proposed. An integrated two-tool workflow combining OpenCV discrete-point tracking with NCORR full-field DIC strain mapping is proposed for comprehensive mechanical component characterization at near-zero software cost.

Abstract: Conventional valve-controlled hydraulic excavator boom drive systems suffer from low energy conversion efficiency and severe throttling losses. To address this issue, this paper proposes a pump-controlled digital hydraulic drive system based on a Direct Energy Recovery Digital Pump (DERDP). The DERDP integrates hydraulic pumping and boom potential energy recovery within a single unit, enabling both energy recuperation and precise flow regulation. An AMESim simulation model of the system is developed and validated against experimental measurements from a dedicated hardware-in-the-loop test bench. Using the validated model, the operational characteristics are investigated under varying boom load pressures, pump displacement fractions, and motor displacement fractions; the drive and energy recovery efficiencies are systematically evaluated across different operating conditions. Simulation results show that the boom energy recovery efficiency reaches 50%–60%. These findings offer practical guidance for implementing digital hydraulic solutions in construction machinery.

Abstract: The current pattern of energy utilization relies primarily on fossil fuels, and countries around the world are faced with the dual pressures of resource scarcity and environmental pollution. The development of series-connected hydraulic hybrid vehicles represents one of the key approaches to reducing energy consumption and emissions in the automotive industry today. In this paper, aiming at a certain type of series-connected hydraulic hybrid vehicle, the models are developed for the vehicle’s power and transmission systems as well as its driving dynamics, and also a forward simulation model is created for the entire vehicle using Matlab/Simulink. An energy management strategy based on rules for engine multi-point control is proposed. The simulation results show that, compared with conventional vehicles before any modifications, this control strategy improves the fuel efficiency of the hydraulic hybrid vehicle by 26.46%. In comparison with an energy management strategy based on rule-based engine single-point control, it increases the vehicle’s fuel efficiency by 8.48%. The study finds that, for series-connected hydraulic hybrid vehicles, using the coordinated operation of the engine and the accumulator instead of relying solely on the accumulator for propulsion not only eliminates unnecessary engine idling but also helps to improve fuel efficiency.

Abstract: The diversity of modern structural glasses is immense, and their mechanical properties vary significantly. Reliable evaluation of glass fracture toughness enables the rational design of structural elements, accurate prediction of their service life, and guaranteed operational safety. This study introduces a novel specimen configuration for determining the static fracture toughness of glass. The specimen design incorporates a stabilizing zone, which reduces its sensitivity to loading device stiffness and ensures straight crack propagation. Specimen preparation is simple and requires no specialized, expensive equipment. Utilizing this approach, static fracture toughness testing of glass can be performed on a standard tensile testing machine. This specimen configuration enables the analysis of crack deceleration and arrest stages. At these stages, the crack tip is fully formed, and the crack front exhibits a natural, rectilinear profile. Consequently, the quality of initial crack preparation in the specimen becomes non-critical. The application of numerical simulation in experimental data processing yielded the dependence of the critical stress intensity factor on the crack propagation velocity. The developed specimen was successfully tested on silicate glass. The advantages of the proposed approach are demonstrated by comparing the results with data obtained using a traditional compact tension specimen.

Abstract: Infrared thermography provides non-contact access to spatially resolved wall-temperature information, but large flow-boiling archives require traceable separation of physically meaningful variations from measurement artefacts. This study develops a physics-guided workflow for quality assessment of longitudinal infrared temperature profiles extracted from the central line of an externally observed heated foil in rectangular minichannels. The frozen dataset comprised 143,821 complete profiles, 35,666,447 spatial points, 447 source files, and 20 grid families. Leakage-safe source-file-level partitioning was used. Controlled evaluation covered eight local synthetic anomaly morphologies at three intensities and a separate global-offset challenge. A Random Forest using 64 engineered profile descriptors was compared with a five-channel masked residual one-dimensional convolutional neural network operating directly on complete profiles. On the locked test set, the Random Forest achieved an area under the precision-recall curve of 0.915, sensitivity of 0.731, and false-positive rate of 0.082, compared with 0.871, 0.452, and 0.063 for the neural model. Both models deteriorated under external grid-family transfer and remained near chance for uniform temperature offsets. The Random Forest is retained as the preferred supervised benchmark; geometry and grid-family transfer remain the principal unresolved limitation.

Abstract: The curing state of polyolefin elastomer (POE) encapsulants affects the mechanical interaction between constituent layers of laminated photovoltaic (PV) structures and is therefore relevant to their manufacturing quality and long-term structural performance. Gel content (GC), commonly used as an indicator of encapsulant crosslinking, is conventionally determined using destructive laboratory procedures. This study investigates the feasibility of vibration-based modal characterization as a non-destructive approach for distinguishing different POE curing states in simplified glass–POE–glass laminate specimens relevant to photovoltaic module structures. Specimens with POE gel contents of 25%, 35%, 49%, 68%, and 75% were experimentally investigated. Modal parameters were identified from acceleration responses using Frequency Domain Decomposition (FDD) and Enhanced Frequency Domain Decomposition (EFDD), and the first six vibration modes were evaluated. The results revealed a measurable but non-monotonic dependence of natural frequency on gel content. For most modes, the frequencies decreased as GC increased from 25% to approximately 68%, followed by a partial recovery at 75% GC. Higher-order modes exhibited larger absolute frequency variations than the first global bending mode, indicating greater sensitivity to changes in the effective mechanical state of the POE interlayer. Finite element analysis supported the correspondence between the experimentally identified and numerically predicted modal characteristics, while a calibrated partial-composite-action model provided a structural interpretation of incomplete shear coupling between the glass layers. The results demonstrate the potential of modal characterization as a rapid and non-destructive screening approach for differentiating POE curing states, while quantitative prediction of unknown gel content requires further validation using larger independent datasets.

Abstract: This work introduces PCREM, a Principal Component Analysis/Artificial Neural Network-guided methodology for identifying candidate reduced ethanol-combustion mechanism topologies from high-fidelity two-dimensional OpenFOAM pool-fire simulations. The high-fidelity database is generated using The San Diego Mechanism, while the reduced-state analysis is organized around the modified Millán-Merino retained-species set containing 17 chemical species, including dynamically retained CH₃CHOH. Principal Component Analysis (PCA) is applied to the pool-fire thermochemical state, and the first 10 principal components (PCs) are retained, capturing 99.9390% of the cumulative variance and yielding reconstruction errors of approximately 2% for the selected thermochemical scalars. Artificial neural networks (ANN) are then trained to reconstruct temperature and species mass fractions from the retained principal components, with validation losses of 3.4716e-06 for temperature, 2.0333E-06 for major species (avg of CO₂, H₂O, C₂H₅OH), and 2.4943E-6 for selected radicals/intermediates (avg of CH₃, CO, H). A PCA-ANN-based sensitivity and species-ranking framework is subsequently developed to quantify the influence of each retained thermochemical scalar on key quantities of interest, including temperature, fuel, O₂, CO₂, H₂O, CO, and principal-component source terms. Using unity-weighted quantities of interest, the cumulative species-importance analysis indicates that the top 13, 15, and 16 species retain approximately 91.91%, 97.83%, and 99.40% of the total importance, respectively. Based on these thresholds, three candidate reduced mechanism topologies are proposed: PCREM-16, a conservative candidate that removes only CH₃ CH₂O; PCREM-15, an intermediate candidate that removes CH₃CH₂O and CH₃CHOH; and PCREM-13, an aggressive candidate that additionally removes HO₂ and C₂H₂. Reaction-consistency analysis is used to identify which pathways remain directly closed and which require ANN reconstruction, QSS treatment, or future reduced-rate re-derivation.The proposed PCREM framework is not intended as an arbitrary truncation of the Millán-Merino mechanism. Rather, it provides a data-informed, pool-fire-specific, a priori methodology for identifying compact candidate reduced mechanisms suitable for future ANN-closed principal-component transport simulations. The results establish the foundation for subsequent a posteriori OpenFOAM implementation and validation of PCREM-16, PCREM-15, and PCREM-13.

Abstract: Particle–fluid flow in fluid catalytic cracking (FCC) standpipes depends on solids throughput, aeration, and valve throttling, which can redistribute pressure loading. This study combined a cold-flow experiment, an Eulerian–Eulerian gas–solid model, and structural finite-element analyses for a 150 mm regenerated-catalyst standpipe with a bend and butterfly valve at 30% opening. Sixteen cases combined solids mass flow rates of 5–20 kg s−1 and aeration velocities of 0–0.42 m s−1. At four matched conditions, the model overpredicted valve-upstream pressure (mean bias error, 0.802 kPa; root-mean-square error, 0.869 kPa; mean absolute percentage error, 32.5%) but reproduced the normalized response (r = 0.976; R²1:1 = 0.907; normalized root-mean-square error = 0.115). At 5 kg s−1, aeration decreased the valve-upstream-to-inlet pressure difference by 36.8% but increased the valve-upstream-to-outlet difference by 87.3%. At 10 kg s−1, the former reached a discrete minimum at 0.28 m s−1. At 15–20 kg s−1, both differences increased as valve restriction dominated. The first six natural frequencies were 22.766–158.390 Hz, and the bend–transition–valve assembly was structurally sensitive. These results identify operating-dependent pressure-load redistribution and priority monitoring locations for this standpipe geometry.

Abstract: Diabetic Foot Ulcers (DFUs) pose a serious health risk to people with diabetes, with a high risk of recurrence following the first DFU and a risk of foot amputation or death. It greatly impacts patient quality of life and costs the NHS up to 1% of its annual budget. Over the last 20 years, work has highlighted the link between DFU formation and normal forces. More recently, work has highlighted the importance of strain/shear forces, which are inherently coupled with normal forces. While limited lab-based in-shoe systems have been produced to detect shear, they alter the shoe-foot interface and are not commercially available. Additionally, consultation with people with diabetes highlighted that they may not wear shoes around the house, leaving long periods where in-shoe solutions cannot track forces. We, therefore, present the development of a novel plantar shear measuring system, the Shear Tracking for Enhanced Prevention Sock (STEPS), an instrumented garment to provide an accessible tool for people at risk with DFU. Integrating sensors within the sock provides a solution that seamlessly integrates within the foot-shoe environment, is suitable for shoeless use, and helps mitigate adherence issues. A prototype STEPS was produced, successfully integrating printed resistive strain sensors (proxy for shear) within custom-designed socks using conductive embroidery for flexible connectivity. The strain sensor has a low profile (<0.5 mm thickness) and remains unobtrusive. Preliminary testing shows the capacity for strain measurement of 12+%, with a resolution of 0.013 Ω across a 20 Ω range, demonstrating good sensitivity over 90 cycles. Proof-of-concept testing characterised the system’s ability to measure plantar strain. A single-participant pilot study demonstrated that STEPS captures repeatable, gait-synchronised strain signals during walking, with a signal-to-noise ratio exceeding 30 dB and between-repeat correlations of up to R=0.77, supporting its potential to detect strain (as proxy for shear) during daily activity.

Abstract: This study develops a fractional boundary element framework for the numerical analysis of nonlinear three temperature behavior in functionally graded magnetic thermoelectric materials. The formulation incorporates the coupled interactions among electron, ion, and phonon temperature fields together with magnetic, electric, and mechanical effects. A boundary element discretization is combined with fractional time modeling to provide an efficient computational strategy for problems involving complex geometries and strongly coupled material behavior. The proposed approach reduces the need for extensive domain discretization and therefore offers advantages in computational storage and solution efficiency. Numerical investigations demonstrate that the fractional order and material gradation significantly influence the magnitude and spatial distribution of thermal stresses. The computed results are also compared with established numerical approaches for representative limiting cases, showing close agreement and supporting the reliability of the proposed formulation. The developed methodology provides an effective computational tool for investigating coupled thermal, electromagnetic, and mechanical responses in advanced functionally graded thermoelectric structures.