Search Results (313)

Long-distance free-surface water-conveyance tunnels require a spatially continuous representation of transient water depth, yet in practice flow is monitored at only a few sections. This study develops a physics-informed neural network (PINN) that reconstructs the transient water-depth field of unsteady free-surface flow in such tunnels from two- or three-point sensors. The one-dimensional Saint-Venant equations, closed with a Darcy–Weisbach steady friction term in hydraulic-radius form, are embedded as a soft constraint in the training loss, so that sparse depth observations are combined with the governing conservation laws to recover the field at unobserved interior and downstream locations. High-resolution finite-volume (FVM) solutions of a 500 m circular tunnel under a flood-rise scenario provide the reference data. The PINN reduces the relative L₂ error at unobserved sections to approximately one-quarter of that of an otherwise identical, physics-free ANN (2.50% versus 10.05% at an interior section; 4.77% versus 13.69% at an extrapolation section). Runs repeated with different random seeds confirm statistical stability at zero noise, while revealing that a minority of trainings at 10% noise converge to spurious solutions. Sensor-placement experiments, including layouts anchored at the true domain boundaries (x = 0 and 500 m), show that boundary anchoring—particularly of the upstream boundary—governs both accuracy and noise robustness: boundary-anchored two-sensor layouts remain accurate in most runs under 10–20% observation noise, whereas interior-only layouts degrade sharply. The method is presented as an offline reconstruction tool; its extension to streaming data assimilation is discussed as future work. Full article

Extreme spatial intensification in affordable housing exposes the structural limitations of conventional room-based zoning, yet existing generative design methods often fail to deeply couple spatial automation with volatile occupant behavioral logic. This study proposes a generalizable Structure–Behavior–Function (SBF)-based generative framework to realize the transition from top-down rigid zoning to bottom-up behavioral adaptation. The framework deconstructs traditional rooms into three coupled layers: minimal ergonomic action domains (structural), 3D Design Structure Matrix-based activity correlation quantification (behavioral), and multi-objective optimization metrics encoding (functional). A discrete grid-based evolutionary approach with a hard–soft dual-constraint mechanism is introduced, combining geometric collision detection for physical feasibility and behavioral correlation rules for spatial zoning reward–punishment. Layout performance is validated via pedestrian circulation simulations. Using a representative megacity affordable housing standard as a case study, controlled computational experiments reveal an empirical power-law scaling boundary between minimum viable area and occupancy size. We establish an Adaptability Surcharge Index (ASI) to quantify the 3.0–7.2% spatial efficiency degradation from rigid structural constraints. The framework achieves 30.3–45.7% floor area reduction versus traditional benchmarks while maintaining comparable circulation efficiency. Validation using an existing residential case further confirms the practical applicability of the proposed framework. This work provides a scalable computational methodology for hyper-dense spatial optimization and a quantitative foundation for future residential space standard formulations. Full article

We model the vacuum as a discrete face-centered-cubic ($K=12$) tensor network with Bell-pair bonds and use it to predict a two-step quantum-to-classical threshold for macroscopic center-of-mass superpositions. A reversible dispersive deformation of the center-of-mass mode sets in at $m_{\mathrm{soft}}\approx 13.1$$\mu$g, and coherence becomes geometrically unsustainable at $m_{\mathrm{hard}}\approx 22.6\mu$g. The two scales are separated by the exact, parameter-free ratio $\sqrt{3}$, fixed by the edge-to-circumradius ratio of the cuboctahedral triangular face. Gravitational-collapse models predict a single scale of the same order, so the distinctive, falsifiable content is the two-step structure and the exact $\sqrt{3}$ separation, testable by a mass scan across the window; the recent $16.2\mu$g cat-state oscillator of Bild et al. falls between the thresholds, where coherence is not ruled out. The absolute window depends on the bond length $L=\sqrt{4ln2}{\mathsf{\ell }}_P\approx 1.665{\mathsf{\ell }}_P$, fixed by one calibration against the Bekenstein–Hawking area law. This calibration and the Compton representability hypothesis—that a mass excitation remains coherent only while its reduced Compton wavelength is resolvable by the lattice—are stated model inputs rather than derivations, motivated by the Compton frequency internal clock of massive excitations, the mass cutoff generic to lattice-regularized field theories, and the total-mass dependence observed in composite-object interferometry. Open problems are stated explicitly. Full article

Hardware sizing and energy management for hybrid energy storage systems are usually designed sequentially, hiding the interactions between them. This paper proposes an MPC-informed dynamic screening framework in which every candidate configuration is simulated under one model predictive control law over a complete driving cycle, so that operational behaviour, not static metrics, determines selection. A fully documented post-evaluation criterion aggregates tracking, battery electrical stress, soft constraint violations and design overhead into one score normalised against an exact baseline anchor. Because one evaluation costs about 60 ms, the complete exact Pareto front of an electric transit bus case study is screened, not a sample. The static design cost proves almost uninformative regarding dynamic performance: the rank correlation between the two orderings is statistically indistinguishable from zero, the sets that they rank highest share no member, and the statically cheapest design falls far down the dynamic ranking, ending below the baseline. The cause is structural opposition on the pack voltage, which improves the dynamic performance but raises the static cost. The framework returns a leading design family that improves on the baseline overall, quantifies the battery stress that its leaner supercapacitor incurs, and shows the verdict to be robust to controller tuning but dependent on the duty and control strategy. Full article

To investigate the mechanical response and energy-damage evolution of argillaceous sandstone under coupled hydro-softening and confining pressure effects, triaxial compression tests were conducted under different water contents (0%, 3.1%, 6.2%, and 9.3%) and confining pressures (0, 3, 6, 10, and 15 MPa). The stress–strain characteristics, failure modes, strength criteria, and energy evolution laws were systematically analyzed. The results show that argillaceous sandstone exhibits a pronounced hydro-softening effect. When the water content increased from 0% to 9.3%, the peak strength decreased by 28.5–50.3% under different confining pressures, with more significant deterioration at the low-water-content stage. Increasing the confining pressure from 0 to 15 MPa increased the peak strength by 180–240% and enhanced the plastic deformation capacity, partly offsetting the weakening induced by hydro-softening. Regression analyses indicate that the exponential strength criterion provides the best applicability for the triaxial strength of argillaceous sandstone. The proposed water-content-modified exponential strength criterion can characterize both hydro-softening and confining pressure effects, with an average relative error of 2.11% and a maximum relative error of 4.70%. Energy analysis shows that increasing water content reduced the elastic energy storage capacity; under uniaxial compression, the peak elastic strain energy at 9.3% water content was 64.4% lower than that in the dry state. The energy-based damage model can describe the pre-peak damage evolution and stress response of argillaceous sandstone. The results can provide a theoretical basis for the stability evaluation of surrounding rock in water-rich soft rock underground engineering. Full article

Foot-worn electromagnetic harvesters are driven by irregular rigid-body motion, while their response is limited by mechanical stroke, coil geometry, mounting direction, and the electrical interface. This paper presents a reproducible numerical design study of a finite-stroke magnetic quasi-zero-stiffness (QZS) moving-magnet harvester. Two public three-axis foot-IMU records are processed with stated gyroscope-bias estimation, six-axis attitude estimation, gravity removal, residual-offset correction, filtering, and angular-acceleration calculation. Three explicit axes are used in the design screen, and the selected candidate is then evaluated over a 62-direction spherical grid. Rigid-body angular-acceleration and centripetal terms are included for specified sensor-to-harvester offsets. Two normalized magnetic force laws are compared. The electrical model uses position-dependent flux linkage, explicit series connection and polarity of coil sections, winding-derived resistance, and a position-dependent electromagnetic reaction force. A fixed-seed random screen evaluates 720 geometry-constrained candidates. The highest-ranked nominal candidate is a 150 mm external foot-worn module with a 40.6 g moving mass, a 30 mm hard half-stroke, 1649 turns in two series sections, and a 25.27 mm coil outer diameter. Across 72 design-screen cases formed from 12 five-second windows, three mounting axes, and two magnetic laws, this candidate remained hard-stroke- and design-stroke-safe. Its conditional ideal load-side power had a 10th percentile of 1.38 mW and a median of 2.03 mW. In the 62-direction check, all 1488 cases remained hard-stroke-safe; two opposite directions each produced one design-stroke exceedance, with a maximum displacement of 24.15 mm. Re-ranking all 30 Stage-2 candidates under coupling and magnetic-stiffness changes retained the long geometry family, although a 30% coupling reduction changed the highest-ranked candidate from 600 to 632. Soft-stop sensitivity, equation-level consistency, and multi-case Runge–Kutta convergence are also reported. The results support finite-stroke design screening, but they do not constitute prototype, finite-element, or delivered-power validation. Full article

The accuracy of spectro-temporal features for Makhaarij al-Huroof and Sifaat distinguishes between the ten canonical Qiraát recitation styles of the Holy Quran. However, real-world room reverberations blur formant contours and corrupt inter-word energies, thus making Qiraat discrimination difficult. The current dereverberation methods were designed to work under ordinary speech conditions and are not capable of preserving phonetic qualities for domain-specific purposes. This paper introduces a four-step, phase-consistent signal-processing approach prioritizing phonetic preservation over direct reverberation suppression. The four steps are: (1) adaptive noise-floor attenuation; (2) soft-voice activity detection using power-law boundary decay; (3) application-specific spectral contour adjustment from clean Quranic reference audio; and (4) Griffin–Lim algorithm-based phase correction. A total of 48 real-world room recordings were utilized for the evaluation of this approach based on Energy Ratio (ER), Spectral Contrast (SC), and Spectral Contour Stability (SCS)—measures specific to the Quran audio domain—alongside conventional speech-quality metrics. The proposed approach yielded the highest scores in three of seven metrics, namely SC (+40.11), SCS (+822.94), and PESQ (+1.251), alongside the second-highest Energy Ratio (+19.58 dB), while being superior to Spectral Subtraction, Wiener Filtering, and WPE Dereverberation approaches. Moreover, the perceptual enhancement was verified in a synthetic controlled experiment where the proposed approach scored an improved PESQ metric (+2.495; SNR −1.874 dB). The results illustrate the fact that an optimization for general-purpose metrics does not necessarily ensure phonetic preservation required for specific classification. Full article

V-shaped riblets are widely studied shark-skin-inspired microstructures, but their continuous high-fidelity replication on soft hyperelastic substrates remains challenging because large substrate deformation complicates complete profile filling. This study establishes an Abaqus-based finite-element process-window and morphology-screening method for roll-to-roll (R2R) hot embossing of 100 $\mathsf{\mu }$m-scale V-shaped riblets on a fluoroelastomer (FKM) sheet as a model hyperelastic substrate. A Yeoh hyperelastic law calibrated from room-temperature uniaxial tension was implemented in a three-dimensional large-deformation contact simulation. Embossing temperature T and imposed nip-compression depth D were examined as screening variables, with formed riblet height, filling ratio, and auxiliary field indicators used to evaluate the forming response. The simulated filling ratio increased from about 69% to 76% as T increased from 120 to 180 °C and from about 39% to 76% as D increased from 60 to 120 $\mathsf{\mu }$m, indicating that nip-compression depth exerted the stronger geometric control over profile filling. R2R hot embossing experiments and laser-confocal profilometry evaluated the retained riblet morphology. For the 160 °C D-series, the measured retained morphology followed the simulated filling trend, with a filling-ratio RMSE of 3.09 percentage points and top-width RMSE of 2.01 $\mathsf{\mu }$m. The integrated numerical–experimental framework provides an experimentally supported manufacturing basis for process-window selection and retained-morphology control in the R2R hot embossing of riblet-textured hyperelastic sheets. Full article

To reveal the stress transfer mechanism of overlying coal pillar loads in hard–soft composite floor strata during close-distance coal seam mining, this study comprehensively employed theoretical analysis, similar material simulation, and numerical simulation to systematically investigate the floor stress distribution characteristics under different pillar widths and rock combinations. This study focuses on the instantaneous elastic response of hard–soft composite floor strata under static coal pillar loading, providing a theoretical foundation for pillar design and roadway layout in multi-seam mining. The limitations and future research directions are also discussed. First, based on the elastic layered half-space theory, mechanical models for stress transfer in the floor under narrow coal pillars (unimodal load) and wide coal pillars (bimodal load) were established. Analytical expressions of stress at any point in the floor were derived, and the influence laws of key parameters, including Poisson’s ratio, interlayer spacing ratio, and shear modulus ratio, were clarified. Second, two typical physical models, namely “hard–soft–hard” and “soft–hard–soft”, were constructed. Experimental results revealed that the weak interlayer exhibits a significant “barrier effect” in the hard–soft–hard combination, causing the stress contours to contract in a “bulb-like” shape; whereas the hard rock layer plays a “bearing effect” in the soft–hard–soft combination, leading to stress contours diffusing in a “gourd-like” shape. Furthermore, numerical simulation revealed the controlling mechanisms of rock combination and thickness ratio: the hard rock layer dominates stress concentration, with the peak stress zone evolving from an “inverted water droplet” shape to a “platform” shape as the thickness increases; the soft rock layer governs stress diffusion and buffering. The depth of the plastic zone significantly decreases with increasing hard rock thickness ratio, achieving a reduction of 44.4%. Full article

The residual magnetic field of the magnetic shielding system is a key factor limiting the bias stability of high-precision atomic gyroscopes. Due to the temperature dependence of hysteresis in soft magnetic materials, variations in ambient temperature can cause drift in the residual magnetic field inside the shielding cavity, thereby introducing measurement errors. Existing studies mostly rely on time-consuming finite element methods (FEM), which struggle to efficiently characterize the temperature–magnetic coupling effect. To address this issue, this paper develops a theoretical model for a fast solution. First, a static magnetic field analytical model for the multilayer cylindrical magnetic shielding system is established. Second, nonlinear magnetization theory is introduced to correct the calculation errors caused by the nonlinear variation in material permeability under weak fields. On this basis, an improved Jiles-Atherton (J-A) model incorporating a temperature correction factor is constructed to accurately characterize the magnetic field distribution inside the shielding system at different temperatures. The results demonstrate that the proposed analytical model can independently and rapidly predict the residual magnetic field distribution at different temperatures, without requiring any calibration or fitting based on FEM simulations. After accounting for hysteresis nonlinearity, the deviation of the shielding factor at the center point between the analytical model and FEM simulations is approximately 5%. The static residual magnetic field at the center point exhibits a negative correlation with temperature variation. Within the actual operating temperature range of the atomic gyroscope from −40 °C to 60 °C, the measured results agree with the model predictions regarding the temperature-dependent trend of the radial residual magnetic field. The relative deviation of the radial residual magnetic field ranges from 2.78% to 7.69%, and that of the axial residual magnetic field ranges from 7.94% to 14.47%, thereby verifying the accuracy of the theoretical model. This model effectively predicts the residual magnetic field drift law of the magnetic shielding system under varying temperature conditions and can provide theoretical support for the analysis and active compensation of thermally induced magnetic errors in atomic gyroscopes. Full article

Aiming at the problem that strip surcharge in coastal soft soil foundations causes lateral squeezing and endangers the safety of adjacent existing bridge pile foundations, the traditional Boussinesq elastic theory cannot reflect the true elastoplastic characteristics of the soil and tends to underestimate the actual horizontal additional stress. This paper establishes a two-dimensional plane strain finite element model and, based on the calibration of pure elastic theoretical solutions, carries out extensive comparative analyses under elastoplastic foundation conditions. Through Pearson correlation and random forest sensitivity analyses, it is clarified that the internal friction angle, load ratio, and normalized distance ratio are the core control variables affecting the redistribution of horizontal additional stress, thereby demonstrating the limitations of the influence of elastic modulus and cohesion. The study reveals the nonlinear amplification mechanism of horizontal stress transfer caused by the penetration of the deep plastic zone within the foundation, as well as the physical evolution law of the stress correction factor, which initially exhibits a Gaussian peak enhancement and subsequently decays exponentially with spatial distance. Based on these mechanisms, a combined prediction formula for the horizontal additional stress correction factor is proposed, achieving an R² = 0.903, and a safety evaluation chart for the correction factor is constructed to quantify high-risk areas. The results indicate that when the normalized distance ratio is greater than or equal to 4, the elastoplastic squeezing effect essentially dissipates. The proposed modification method effectively delineates the applicable boundary of the elastic solution and provides a theoretical basis for the bearing capacity calculation and safety control of passively loaded pile foundations in soft soil regions. Full article

Deep excavations in composite “soft upper-hard lower” strata present significant deformation control challenges due to strong stiffness contrasts. This study investigates the deformation characteristics of a deep metro foundation pit in Jinan under zoned excavation conditions. A three-dimensional finite element model was developed to simulate the staged excavation process, and the spatiotemporal evolution of diaphragm wall deflection and ground settlement was analyzed, with particular focus on the influence of soft soil thickness. The results show clear spatial variation, with maximum lateral wall displacements exhibiting a typical “bulging” profile along the longer sides of the pit. The normalized maximum wall displacement (δ_hm/H_e) ranges from 0.051% to 0.090%, while the ratio of maximum ground settlement to wall displacement is 0.35–0.57, indicating lower deformation levels compared to homogeneous soft soils. As the soft soil thickness increases, the wall displacement increases and the location of maximum displacement migrates downward and outward. Under the investigated conditions, a transition toward a “kick-out” deformation mode occurs when the soft soil thickness reaches the transition range identified in the parametric analysis. These findings provide a quantitative basis for deformation prediction and support design in composite strata. Full article

Addressing uneven accuracy across multiple measurement sources and the insufficient adaptability of traditional data-driven models to topological changes, a data-driven state estimation method for distribution networks based on power-flow constraints is proposed. Firstly, historical prior information is used to supplement missing data, thereby constructing a complete measurement dataset and establishing a reliability index to assess the credibility of measurements from different sources. Secondly, according to the physical topological map structure of the distribution network, an improved graph neural network algorithm is proposed to realize state estimation. The bus power balance relationship is embedded as a soft constraint in the loss function to enhance the consistency between the estimation results and physical laws. Then, an adaptive method of topology change based on transfer learning is proposed to improve the adaptability of the model to the dynamic changes of distribution network topology. Finally, the proposed method is evaluated using various metrics on the IEEE 33 and IEEE 118 systems. The analysis results show that the method can maintain high estimation accuracy under multi-source measurements and exhibits good robustness to noise disturbances. Full article

The Federal Institute of Material Research and Testing has performed many impact tests, from very small laboratory tests to very big “free-field” tests with heavy containers on stiff foundations. The first measurements have been done on a big foundation where it should be guaranteed that the foundation is rigid and the container is tested properly. Later, a smaller drop-test facility has been built on the ground inside an existing building. It had to be controlled by prediction and measurements to ensure that the drop test will not damage the building. Tests from different heights on soft, medium, and stiff targets have been done to find out rules which allow to identify acceptable and unacceptable drop tests. Later, the biggest drop test facility has been built for masses up to 200 t. It was necessary for the design of the foundation to estimate the forces which occur during the drop tests. In addition, the acceptable tests should be selected and controlled by measurements where the impact duration is important. Different sensors, accelerometers, accelerometers with mechanical filters, geophones (velocity transducers), strain gauges, and pressure cells have been applied for these tasks. Signal transformations and model calculations have been used to check and understand the dynamic measurements. The simplest law is the conservation of the momentum which is a good approximation if the impact is short. If the soil under the foundation has an influence on the deceleration of the container, the maximum foundation velocity is lower than the simple estimation. Full article

Shape-memory polymers (SMPs) are gaining significant attention for their ability to recover predefined shapes via external stimuli. Among thermally activated systems, biodegradable blends of polylactic acid (PLA) and polycaprolactone (PCL) are particularly promising for biomedical devices and soft actuators. This study develops a thermo-mechanical theoretical model to investigate the shape-memory behavior of a PLA/PCL composite blend under controlled thermal cycling. The framework integrates transient heat transfer, temperature-dependent elasticity, and viscoelastic dynamics to predict temperature evolution, deformation, and internal stress. The thermal response is computed via Newton’s law of convection, while the mechanical transition is described by a sigmoidal temperature- and crystallinity-dependent Young’s modulus. Beam bending theory is employed to evaluate the spatial distribution of strain and stress. A parametric sensitivity analysis was performed to evaluate the influence of different parameters, including the crystallinity grade, convective heat transfer coefficient, glass transition temperature, and viscoelastic recovery constant. The theoretical study accurately reproduces the shape-memory cycle, quantifying performance through fixation and recovery ratios. This model provides a robust tool for the rational design and optimization of biodegradable smart polymer structures. Full article