Search Results (2,845)

Magnetorheological (MR) fluids are smart materials widely used in applications requiring controllable braking torque and force generation. The optimization of such devices often relies on the finite element method (FEM) combined with a numerical optimization algorithm, incurring high computational cost due to the large number of required evaluations. This study investigates the geometric optimization of a spherical MR actuator using Differential Evolution (DE), Artificial Bee Colony (ABC), and Teaching–Learning-Based Optimization (TLBO). To reduce computational effort, Short-Term Memory Assistance (STMA) and Long-Term Memory Assistance (LTMA) were integrated into DE and TLBO. The performance of all approaches was evaluated based on optimization time, the number of fitness evaluations, and objective function values. The results show that all algorithms used are capable of finding comparable objective function values; however, substantial differences were observed in computational times, with both DE and TLBO significantly outperforming ABC. The incorporation of memory assistance reduced computational time without degrading solution quality. Unexpectedly, STMA achieved greater time reduction than LTMA. The proposed approach represents a simple and effective strategy for reducing computational cost in the FEM-based optimization of MR actuators. The proposed approach shows potential for application to other computationally intensive electromagnetic design problems, which are common in engineering. Full article

The development of multifunctional cosmetic creams requires balancing functional performance with consumer acceptability. This study aimed to develop cream formulations containing aloe vera gel, eucalyptus essential oil, and vitamin E. Their relative proportions were optimized using mixture-design methodology. Ten formulations were prepared, and antioxidant activity was evaluated using the DPPH radical scavenging assay. A special cubic mixture model was fitted to the experimental data, followed by numerical optimization. The formulations were further characterized in terms of pH, microstructure, sensory attributes, and microbiological quality during refrigerated storage. Antioxidant activity varied among creams, with significant aloe vera × eucalyptus essential oil and aloe vera × vitamin E interactions. The model showed high explanatory capacity (R² = 93.14%) and predicted an optimum mixture of 30.3% aloe vera gel, 29.3% eucalyptus essential oil, and 40.4% vitamin E. The pH of the creams remained within 4.74–5.18, while most sensory attributes were comparable among formulations. Odor and cooling sensation were formulation-dependent, while willingness to use exceeded 60% for several formulations and reached approximately 71% for BIO8. Microbial counts remained below the applicable quantitative acceptance criterion during the 60-day refrigerated storage assessment, while the specified target microorganisms were not detected under the microbiological methods employed. The findings support further investigation of ternary formulations under formulation and stability conditions relevant to cosmetic use. Full article

This study evaluated the effects of misfit type, magnitude, and location on the stress distribution in full-arch screw-retained implant frameworks. A maxillary finite element model with four implants was analyzed under 16 scenarios, characterized by horizontal misfits of 10, 50, 100, and 200 µm; vertical misfits of 10 and 100 µm; and combined 10–10 and 100–100 µm misfits, each positioned anteriorly or posteriorly. Forced seating was simulated using prescribed displacement; no occlusal load or screw preload was applied. Von Mises stresses were evaluated in the framework, occlusal screws, and implants, and principal stresses were assessed in peri-implant bone. Framework stress increased with horizontal misfit magnitude. When the same numerical misfit value (10 or 100 µm) was applied at the same location under otherwise identical model conditions, vertical misfit produced higher framework stress than horizontal misfit, indicating a direction-dependent response associated with different seating deformation modes. The posterior 100–100 µm combined misfit produced the maximum framework (356 MPa), occlusal screw (193 MPa), and implant (250 MPa) stresses. In contrast, the maximum principal stress peaked at the posterior bone site with the anterior 200 µm horizontal misfit (V0 H200 A; 77 MPa), while the most negative minimum principal stress occurred at the posterior bone site with the posterior 200 µm horizontal misfit (V0 H200 P; −52 MPa). Among the tested scenarios, combined misfits yielded the highest framework and screw stresses, whereas implant and bone responses depended on the magnitude and location of the misfit. These findings indicate that the types, magnitudes, and locations of misfits should be considered during framework-fit assessments, with particular attention to combined misfits, before definitive seating. Full article

Plant chemodiversity is generally evaluated through metabolite richness, relative abundance, compositional dissimilarity, and biosynthetic organization. However, these descriptors characterize chemical states without explicitly identifying which metabolites, chemical classes, or biosynthetic pathways gain or lose relative representation during transitions between states. Here, we introduce Chemical Game Theory as an operational analogy inspired by the relative-performance principle of replicator dynamics. Metabolites are treated as elementary chemical strategies, biosynthetic pathways constitute higher-order strategies, and normalized chromatographic abundances define their frequencies within a mixture. A centered log-ratio quantity, termed realized chemical payoff within this framework, retrospectively quantifies whether a component gained or lost proportional representation relative to the abundance-weighted mean log change in the system. It is not inferred from a payoff matrix and does not represent Darwinian fitness, interaction strength, or absolute biosynthetic production. Shannon diversity describes metabolite-level coexistence, whereas the General Biosynthetic Diversity Index, GBDI, characterizes abundance-weighted pathway organization and intrapathway diversification. The framework was applied to previously published GC-MS and GC-FID profiles of essential oils from leaves and four developmental stages of the reproductive organ of Piper mollicomum Kunth, sampled over five months. Leaves had the highest numerical mean Shannon diversity and GBDI, although the Shannon difference was not statistically significant. The reproductive stages followed temporally variable compositional trajectories. Across the five descriptive monthly blocks, the terpenoid route gained relative representation during the Stage I to II and Stage III to IV transitions, whereas the mixed category declined. Chemical dominance, Shannon diversity, GBDI, and realized payoff captured related but non-equivalent dimensions of relative chemical organization. As a proof of concept, Chemical Game Theory provides a quantitative language for retrospective analysis of compositional redistribution. Its proposed use for prioritizing plant material and its transferability to other chromatographic platforms require validation with independent datasets, biological replication, absolute quantification, and bioactivity-guided experiments. Full article

For the wingtip-connected combined UAV considered here, the proposed constraint-based assessment demonstrates that the clearance margin changes sign between the sampled 5° and 6° angles of attack, thereby bracketing the clearance transition within this interval. This study presents a deterministic, constraint-based assessment framework for the separation of wingtip-connected combined unmanned aerial vehicles (UAVs). The previously developed torque-driven compliant interface is treated as the existing physical platform rather than as a new mechanism contribution. Structural-strength, roll-control, and collision-clearance requirements are formulated as individual limit-state margins and linked by a non-compensatory minimum operator, so that failure of one quantified constraint cannot be offset by favorable performance in another. Previously reported aerodynamic, finite-element, multibody-dynamics, and ground-test records are reanalyzed as case-study inputs; they are not presented as independent validation of the complete classifier. The verified stress contours show that parametric refinement reduces the maximum equivalent von Mises stress from 17.2 MPa to 10.4 MPa (39.5%). Ground measurements acquired at 1000 Hz yield R² = 0.96 for a descriptive sinusoidal fit, supporting response smoothness but not proving the complete low-impact safety hypothesis. The framework therefore provides a traceable requirement-checking route; with the presently retained records, its demonstrated implementation is a clearance-decision template rather than a numerically complete three-channel safety index. Full article

Equivalent-circuit models (ECMs) are widely used in battery management systems. However, scheduled resistance and capacitance changes can make numerical histories inconsistent with physical polarisation states. This paper introduces BATTLM, a Transmission-Line Modelling (TLM) realisation of lithium-ion battery ECMs. Each capacitor in a resistor–capacitor (RC) branchcapacitor is represented by an open-circuit TLM stub using incident and reflected variables. When parameters change, the incident history is reconstructed from the endpoint polarisation voltage. The fixed-step algebraic formulation extends from 1RC to arbitrary nRC order and reproduces the corresponding trapezoidal update. Assessment uses Panasonic 18650PF and Stanford second-life cell data. Among 1RC, 2RC, 3RC, and 4RC candidates, frequency-point testing favours 4RC for all 180 Stanford spectra, whereas the corrected Akaike information criterion selects 4RC for 108 spectra and 3RC for 72. Median impedance test root-mean-square error (RMSE) values are 2.166, 1.146, 0.912, and 0.848 mΩ, respectively. Electrochemical impedance spectroscopy (EIS)-derivedparameters are applied to 177 measured pulses without pulse-domain fitting. Median voltage RMSE values, referenced to the measured pre-pulse voltage, are 5.359, 1.656, 0.884, and 0.623 mV. The results support state-consistent TLM implementation while identifying application-dependent model-order trade-offs. On a dedicated Panasonic temperature-rise record excluded from parameter identification, scheduling with measured battery temperature reduced terminal-voltage RMSE from 177.55 to 86.92 mV relative to freezing the temperature dependence at the initial condition. Full article

Deep lacustrine–fluvial soft ground at the Songyanghu Terminal (Phase III), Yueyang Chenglingji Port, was treated using vacuum wellpoint dewatering combined with dynamic compaction. A two-dimensional coupled solid-mechanics-Darcy model in coupled COMSOL Multiphysics 6.3 model was used to examine deformation and excess pore-water-pressure response, while an archived 360-day settlement series was used to evaluate three empirical prediction methods. The field dataset contains 12 settlement observations at a constant 30-day interval from Day 30 to Day 360. The numerical outputs indicate surface settlement approaching approximately 100 mm by Day 100; at Day 10, localised excess pore-water pressure remained at roughly 100 kPa near the mid-depth drainage zone, while most of the model domain was substantially lower. To avoid treating the same observations as both fitting and validation data, the Asaoka, hyperbolic and exponential methods were recalibrated using data ending at Days 180, 240 and 300 and then evaluated against the subsequent withheld observations. Across these three windows, the mean RMSE values were 0.02, 0.59 and 0.19 mm for the Asaoka, hyperbolic and exponential methods, respectively. The Day-360 measurement of 108.84 mm is therefore used as a reference observation rather than as a proven final settlement. For this single site and dataset, the Asaoka method produced the lowest numerical withheld-data errors; however, the differences between the Asaoka and exponential predictions are smaller than the stated ±1 mm levelling accuracy and therefore do not establish statistically or physically significant superiority. Broader applicability requires validation at additional sites and with independent monitoring datasets. These results provide a case-specific basis for post-construction settlement assessment of similarly treated soft ground. Full article

This study examines a non-autonomous quadratic map driven by a logarithmic cooling schedule (${\mu }_n\sim 1/{ln}^{2}n$, a phenomenological ansatz), building on our recent published result that the logistic map’s symbolic dynamics at its band-merging point is isomorphic to the prime sieve. From its trajectories, we construct an empirical, non-normal, dissipative transfer matrix and compares its complex eigenphases to the non-trivial Riemann zeros after calibrating a few free parameters against the same low-order zeros—an in-sample numerical correspondence, not an independent prediction. We quantify this gap directly: fitting on the first $M\in \{50,70,80\}$ zeros and evaluating on the rest gives a held-out MSE one to two orders of magnitude larger than the training error, with the fitted coupling drifting across M but remaining comparatively stable across ten random seeds at fixed $M=70$ (CV $\approx 4.7\%$). At low order ($N\lesssim 20$), an unselected re-computation shows a qualitative rank correlation ($\rho =0.56$, $p=0.010$) with, but no significant joint co-location ($p=0.099$) of, a residual feature reported in recent ion-trap quantum simulations of the same zeros. At larger N ($N\ge 1000$), the model matches a globally rescaled GUE surrogate’s mean counting-function trend better once conjugate eigenphases are restored, though this partly follows from the construction’s own symmetry; a separate, standard unfolded local-statistics test shows the model’s own eigenphase spacings do not match GUE, unlike the true zeros. These are numerical observations on a heuristic model, not a proof or Hilbert–Pólya-type operator construction; a dedicated table tabulates the epistemic status of every main claim. Full article

Accurate prediction of ship roll motion is essential for maritime safety and stability assessment. Physics-based methods can provide physically interpretable predictions, but high-fidelity numerical simulations usually require considerable computational resources, limiting their application to efficient and long duration roll motion prediction. In contrast, purely data driven models are computationally efficient but may lack physical consistency. To address these limitations, this study develops a physics-informed neural network (PINN) framework with an adaptive loss-balancing strategy for ship roll motion prediction. An adaptive loss balancing strategy is incorporated to dynamically regulate the relative contributions of the governing equation loss and the data fitting loss during training, thereby integrating physical constraints with available roll response data. The DTMB 5415 hull is selected as a benchmark case, in which the roll motion equation is incorporated as a physical constraint, and time series data under both regular and irregular wave conditions are generated through numerical simulations. Comparative results demonstrate that the proposed PINN-BP (Adaptive) framework achieves the lowest RMSE and MAE among the evaluated models, while maintaining an R² comparable to that of the standard PINN. The computational results further show that its training cost remains comparable to that of the standard PINN and is substantially lower than that of the LSTM model, while the inference time remains at a low level. The results demonstrate that incorporating adaptive loss balancing into the physics-informed BP neural-network framework can improve roll motion prediction accuracy without introducing a substantial additional computational burden. The proposed framework provides a physically informed and computationally efficient approach for ship roll motion prediction under the investigated wave conditions. Full article

Quantile functions provide a natural representation of probability distributions and offer direct advantages for random variate generation, simulation, and quantile-based statistical analysis. In this paper, we develop a quantile-differential construction in which a probability model is characterized through a differential equation satisfied directly by its quantile function. Within this framework, we introduce a one-parameter continuous model, termed the quadratic quantile distribution (QQD), whose explicit quantile representation leads to a simple and analytically tractable probability model. Closed-form expressions are obtained for the cumulative distribution function, probability density function, survival function, hazard rate, and cumulative hazard function. Several structural properties are also investigated, including shape characteristics, stochastic ordering, entropy measures, fractional moments, and quantile-based descriptive measures. Particular attention is devoted to the upper-tail behavior. The survival function is regularly varying with index $-1$, so that the QQD has a Pareto-type tail with tail index one. Consequently, the ordinary mean is infinite, whereas fractional moments exist only for orders less than one. This feature makes quantile-, survival-, and tail-based summaries more appropriate than conventional moment-based descriptions. Maximum likelihood estimation is developed for the model parameter, and its finite-sample behavior is examined through an extensive Monte Carlo study. The simulation results show a progressive reduction in bias, root mean squared error, and mean absolute error as the sample size increases, providing numerical evidence consistent with the expected large-sample behavior of the estimator without treating simulation as a proof of asymptotic consistency. The empirical performance of the QQD is examined using three right-skewed datasets from reliability and biomedical applications. Comparisons with established one- and two-parameter distributions show that the QQD can provide a competitive likelihood-based fit while retaining the simplicity of a single unknown parameter. Graphical comparisons further complement the numerical criteria, particularly in assessing the behavior of the fitted models in the upper tail. Overall, the results suggest that the QQD offers a parsimonious and analytically convenient alternative for selected strongly right-skewed positive data, while its suitability should be assessed on a case-by-case basis in view of its heavy-tailed structure. Full article

When submarine pipelines are placed on erodible sandy beds, the interaction between the surrounding flow, the pipeline, and the sediment can induce local scour. While two-dimensional simulations have been extensively performed to capture the scour process in a two-dimensional cross-sectional plane, they cannot simulate the three-dimensional (3D) spanwise propagation of the scour hole, which leads to free-span development. This study presents 3D numerical simulations of current-induced scour propagation in the spanwise direction beneath a subsea pipeline using an open-source Eulerian two-phase flow solver. Systematic simulations are performed under four distinct Shields parameters. The results indicate a close spatial association between the evolving 3D scour hole and regions of localized shear stress amplification and sediment flux near the span shoulder. For low Shields parameters, the scour hole retains pronounced 3D features with steady spanwise propagation, which is also characterized by skewed wake flow structures and oblique downstream dunes. At higher Shields parameters, the scour front propagates rapidly across the domain, causing the morphology and flow streamlines to transition to a quasi-2D state. Furthermore, the scour slope at the span shoulder remains approximately constant across the investigated flow conditions. The spanwise propagation speed is approximately constant during the fitted propagation stage for the selected four simulated conditions. Full article

This study numerically investigates unsteady natural convection and Soret–Dufour double-diffusion in a two-dimensional sinusoidally wavy porous cavity saturated with an Al₂O₃–Cu/Water hybrid nanofluid (φ = 0.02), using a Darcy–Brinkman formulation with temperature-dependent viscosity and Rosseland thermal radiation. The governing equations are solved on a boundary-fitted grid; an independent Method of Manufactured Solutions verification confirms second-order accuracy, with a finest-grid (120 × 120) L₂ error of 2.6807 × 10⁻⁵ and a fine-grid GCI of 0.013225%. Within the investigated dimensionless range, Nu_avg increases with the Rayleigh number, wall-wave amplitude, radiation parameter, and viscosity-thinning magnitude, while the hybrid nanofluid yields a 2.8–3.2% enhancement over pure water. Because no independent experimental measurements or complete dimensional operating envelope are available, the reported engineering implications are presented as model-based guidance rather than validated design prescriptions. Full article

This study numerically investigated the applicability of the Forchheimer and Izbash equations for describing non-Darcian flow in three-dimensional (3D) rough-walled rock fractures. High-precision flow simulations were conducted on 52 synthetic 3D rough-walled fractures with varied apertures and surface roughness, generated from 56 combinations after excluding four cases with surface contact, under different hydraulic gradients. The simulation results captured transverse flow, back flow, and non-uniform streamlines on horizontal planes, which cannot be observed in conventional two-dimensional (2D) fracture models. The total eddy volume ratio negatively correlated with the aperture and positively correlated with roughness, and the 3D fractures exhibited a much smaller eddy volume ratio than the 2D fractures. Both equations provided excellent fits to the simulated data, with coefficients of determination R² > 0.996. Notably, the Forchheimer coefficients showed strong and monotonic correlations with the aperture and roughness and are therefore predictable and characterizable, whereas the Izbash coefficients showed weak and non-monotonic correlations. Since non-negligible prediction errors occurred at low Reynolds numbers when the equations were fitted over the entire flow range, a piecewise fitting strategy was proposed, which reduced the prediction errors of both equations to within 5% across the full range and quantitatively divided the flow into the Darcy, weak inertial, and strong inertial regimes. Double-parameter equations relating the critical Reynolds numbers to the aperture and roughness were then established, allowing the flow regime to be predicted directly from the geometric parameters without additional simulation. These findings facilitate reasonable flow regime division and accurate full-range flow characterization in rock fractures. Full article

Learning disabilities are traditionally conceptualized as domain-specific disorders arising from deficits in reading, attention, or numerical processing. Although these approaches have substantially advanced understanding of dyslexia, attention-deficit/hyperactivity disorder (ADHD), and dyscalculia, they do not fully explain the marked heterogeneity, developmental variability, frequent comorbidity, or changing learning trajectories observed across children. This conceptual review proposes a developmental timing framework in which learning disabilities emerge, in many cases, from maturational asynchrony among interacting neural, cognitive, linguistic, sensorimotor, and executive systems rather than from isolated deficits within a single domain. Drawing on evidence from developmental neuroscience, cognitive psychology, neuroeducation, developmental systems theory, and learning sciences, we synthesize research on the developmental coordination of language, executive function, attention, motor control, working memory, symbolic learning, and numerical cognition across childhood. Within this framework, dyslexia, ADHD-related learning difficulties, dyscalculia, and mixed learning profiles are interpreted as distinct developmental expressions of differing patterns of cross-system asynchrony interacting with the increasing cognitive demands of formal education. We distinguish maturational asynchrony from related concepts, including developmental variability, developmental cascades, and multiple-deficit models, and propose measurable indicators through which the framework may be empirically evaluated. The framework further generates testable predictions concerning longitudinal developmental trajectories, educational transitions, developmental fit, and timing-sensitive intervention. Rather than replacing established cognitive accounts of learning disabilities, the developmental timing framework provides an integrative developmental architecture within which existing theories can be understood while offering a basis for future longitudinal and intervention research. This perspective highlights the importance of aligning educational expectations and instructional practices with children’s evolving neurodevelopmental readiness rather than chronological age alone. Full article

Steep submarine canyons pose challenges to deep-water pipeline routing because of rugged terrain and slide-related hazards. This study integrates 3D seismic data, shipborne and autonomous underwater vehicle bathymetry, sub-bottom profiles, sediment testing, and numerical simulations to characterize engineering geological conditions and examine local terrain effects on slide–pipeline interaction in the Qiongdongnan Basin. Canyons, landslides/slumps, and scarps were identified as the principal engineering geological units, while high-resolution AUV data constrained representative depressions, ridges, and terrain asymmetry along the planned pipeline corridor. A post-failure fluidized mass was modeled using a Herschel–Bulkley relationship fitted to fully remolded site sediment. Thirty independent simulations compared five alternative fixed, non-buried pipeline locations under six field-informed terrain scenarios. The numerical framework was assessed through grid-sensitivity analysis and quantitative comparison with a published flume-derived drag relationship. Under fixed-pipeline and quiescent-water conditions, depressions confined moving material near the terrain base, whereas ridges produced more variable flow and loading patterns. Pipeline loading also varied with terrain asymmetry, approach direction, and relative pipeline position. The results provide screening-level guidance for identifying terrain-sensitive route sections requiring site-specific pipeline–soil–structure assessment. Full article