Search Results (177)

The bearingless induction motor (BIM) relies on accurate displacement feedback to maintain stable magnetic suspension, but sensor faults, degradation, and noise can distort feedback and induce transients during branch switching. This paper proposes a confidence-fusion-based fault-tolerant displacement measurement method for the BIM suspension feedback chain. A four-channel asymmetric redundant sensor configuration is developed, and channel state evaluation functions are constructed from sampling-difference terms and geometric-consistency residuals. A decreasing Sigmoid mapping with first-order smoothing generates continuous confidence coefficients to represent channel health. Combined with discrete fault flags of the primary channels, four reconstruction branches, AB, BC, AC, and CD, are adaptively weighted to obtain the reconstructed displacement, which is connected to the original suspension controller through a smooth feedback access mechanism. A MATLAB/Simulink closed-loop suspension model is used to evaluate the method under fault-free operation, an abrupt fault of primary channel A, simultaneous and sequential faults of primary channels A and B, abrupt and gradual degradation, constant bias, intermittent signal dropouts, and noise disturbance of primary channel B. Results show that the method identifies abnormal primary channels, redistributes reconstruction weights according to sensor conditions, and maintains a fallback path through the CD branch under dual-primary-channel failure. Under channel-B degradation, the confidence coefficient tracks the deterioration and supports the subsequent AB-to-AC branch transfer, whereas under noise disturbance, the fault flag remains inactive and unnecessary branch switching is avoided. The method improves feedback continuity without changing the main suspension controller. Full article

Audio deepfake detection systems often achieve excellent internal validation performance but fail to generalize under real-world inference conditions involving synthetic speech generated with previously unseen AI tools. To address this limitation, this work proposes the Spectral Multi-Representation Fusion (SMRF) framework, which integrates multiple spectral representations and decision-level fusion strategies to improve robustness under cross-domain conditions. Additionally, a Stability-Aware Multi-Metric Selection (SAMMS) strategy is introduced to select architectures by jointly considering predictive performance and cross-representation stability. The proposed framework was evaluated using four spectral representations (log-magnitude spectrogram (LOG), Mel spectrogram (MEL), Discrete Wavelet Transform (DWT), and Constant-Q Transform (CQT)) combined with multiple convolutional architectures and complementary voting strategies. The experiments revealed that isolated models exhibiting validation metrics above 95% may still produce very poor synthetic-audio detection rates during external inference (even lower than 10%). In contrast, fusion-based strategies substantially improved robustness by exploiting complementary synthetic evidence across spectral domains. The results also demonstrated that both the voting strategy and the SAMMS stability parameter $\lambda$ strongly affect the final behavior of the system. In particular, hybrid fusion using One-Hard Voting with two architectures selected using $\lambda \ge 0.25$ achieved the best balance between synthetic-audio detection and real-audio preservation, outperforming individual models under cross-domain inference conditions, with detection rates close to 75% for both synthetic and real audio. These findings suggest that stability-aware fusion strategies constitute a promising direction for improving robustness in realistic audio deepfake detection scenarios. Full article

This paper studies the stability properties of a class of Hopfield-type neural networks involving conformable derivatives and piecewise constant arguments. By constructing an associated discrete-time formulation, the continuous system is expressed in a form that is more suitable for analysis. A Lyapunov-based approach is then developed to investigate the asymptotic and exponential stability of the equilibrium point of the resulting discrete system. The analysis provides conditions that depend on the system parameters and the conformable derivative order, offering insight into the convergence behavior of solutions. The proposed approach treats the discrete formulation as an analytical tool for studying the original model. A numerical example is included to illustrate the theoretical results. Full article

This study examines a discrete fractional-order predator–prey system incorporating a Holling type-III functional response. The Caputo fractional derivative is employed because it naturally incorporates memory and hereditary effects while preserving biologically meaningful initial conditions. The system is formulated from a biologically relevant continuous fractional-order framework through the application of the piecewise constant argument approach, enabling an analysis of how memory-dependent effects and discrete dynamics influence predator–prey interactions. The existence and local stability of fixed points are determined by using the Jacobian matrix and eigenvalue conditions. The bifurcation of the positive fixed point is analyzed by using the center manifold and normal form methods. Numerical simulations, including bifurcation diagrams, phase portraits, and maximum Lyapunov exponent plots, confirm our analytical results and reveal periodic, quasiperiodic, and chaotic behavior. The findings of this study reveal that the combined influence of memory-dependent dynamics, nonlinear predator–prey interactions, and discrete-time effects can generate rich and complicated behaviors in fractional-order predator-prey systems. Full article

Sequential resource allocation has long been a central problem in operations research, yet ongoing technological developments, particularly in cloud and high-performance computing and in multi-channel marketing, are giving rise to new structural constraints that classical methods were not designed to handle. Semi-Bandit Feedback (SBF) has emerged as the dominant framework for these modern settings. This paper introduces an alternative that recasts the allocation problem within the Bayesian Optimization (BO) paradigm. All three proposed BO algorithms consistently outperform SBF, with BORAw_SE showing a particularly clear advantage under time-varying budget settings, while CBO achieves comparable rewards under constant budget conditions. The core methodological contribution is a reformulation in which each candidate allocation is represented as a discrete probability distribution over the available options, making the probability simplex the natural search domain. Grounding the search in this space calls for a geometry that respects the structure of distributions: we adopt the optimal transport (Wasserstein) distance, which allows both the Gaussian process surrogate and the acquisition function to be extended as functionals over the simplex. A further practical advantage of the proposed method is its applicability to problem instances where SBF cannot be used without modification. The approach is evaluated on two case studies: the benchmark computing-resource allocation scenario from the original SBF paper, and a budget allocation problem across marketing channels. Full article

Insulated concrete sandwich panels (ICSPs) are widely utilized in modern building structures due to their excellent combination of energy efficiency and structural load-bearing capacity. However, compared to their mechanical and thermal properties, the sound insulation characteristics of ICSPs remain insufficiently studied, presenting a scientific deficit. In practical engineering, insufficient consideration of these acoustic properties—particularly the “acoustic bridging” induced by connectors—often leads to unpredictable noise transmission, making it difficult for building envelopes to meet stringent modern acoustic codes. To further investigate their acoustic characteristics, this paper extends existing theories on infinite periodic ICSPs to study the airborne sound insulation performance of finite-sized ICSPs. First, analytical models for ICSPs under simply supported on all edges (SS) and clamped on all edges (CC) boundary conditions are derived, wherein the connectors are equivalently modeled as elastic media and discrete elastic springs, respectively. Subsequently, the accuracy and applicability of the analytical models are verified through finite element (FE) models and an airborne sound insulation experiment. Finally, based on the analytical models, a parametric study is conducted to explore the effects of the stiffness of connectors, boundary conditions, and the thickness of the core layer on the sound insulation performance of the ICSPs. The results indicate that connector stiffness has a non-monotonic influence on the sound insulation performance of ICSPs. As the connector stiffness increases, the R_w first decreases and then increases, and the sound insulation performance gradually stabilizes when the connector stiffness becomes sufficiently high. Boundary conditions have a significant effect on the acoustic response. For the reference ICSPs, changing the boundary condition from SS to CC increases the R_w from 49 dB to 62 dB, corresponding to an increment of 13 dB and an approximately 95.0% reduction in the equivalent sound transmission coefficient. When the total panel thickness is kept constant, reducing the core layer thickness from 80 mm to 40 mm increases the R_w from 49 dB to 55 dB under SS boundary conditions and from 62 dB to 66 dB under CC boundary conditions, corresponding to increments of 6 dB and 4 dB, respectively. These improvements are equivalent to reductions of approximately 74.9% and 60.2% in the sound transmission coefficient, though this must be weighed against the inevitable reduction in thermal insulation capacity. Although the sound insulation performance of ICSPs is inferior to that of solid concrete panels (SCPs) of equivalent thickness, with reasonable parameter optimization, their sound insulation indices can significantly exceed the latest requirements of current building codes. By fully accounting for boundary effects in practical engineering, this study provides an analytical basis for the acoustic performance prediction and engineering-oriented optimization of finite-sized ICSPs. Full article

This paper investigates a discrete diffusion carbon emission-absorption model with periodic boundary conditions derived via the piecewise constant argument scheme. The existence of equilibrium points is established, and sufficient conditions for the local asymptotic stability of the positive equilibrium are derived through eigenvalue analysis. Then, uniform boundedness of positive solutions is proved, and the global asymptotic stability of the interior equilibrium is established by an iterative method and the comparison principle for difference equations. Furthermore, the model is shown to undergo a flip bifurcation when a critical parameter threshold is reached, leading to period-doubling dynamics and chaotic behavior. The influence of spatial diffusion is examined through a Turing instability analysis, yielding conditions for diffusion-driven instability and spatial pattern formation. Finally, Decision Tree and Random Forest classifiers are used as proof-of-concept tools to efficiently approximate the analytically derived stability regions using Monte Carlo-generated data. Both classifiers successfully reproduce the analytical stability structure, while the Random Forest classifier provides higher accuracy and smoother stability boundaries. Numerical simulations support the theoretical results and illustrate the stability and bifurcation phenomena exhibited by the model. These findings indicate that the proposed framework is useful for analyzing carbon emission-absorption dynamics and that machine learning can serve as an efficient computational surrogate for identifying stability regions in nonlinear dynamical systems. Full article

This paper considers a numerically stable discrete-time representation of the three-dimensional Constant Turn (CT) motion model within the Interacting Multiple Model (IMM) framework for radar tracking of maneuvering aerial targets. Classical discrete CT models used in Kalman-filter-based tracking contain singular expressions in the vicinity of zero and near-zero turn rates, which may degrade estimation accuracy and impair numerical robustness. To address this problem, a Maclaurin-series-based discretization of the three-dimensional CT model is developed, in which the state transition matrix and the process-noise-related matrices are approximated in polynomial form. Linear, quadratic, and cubic approximations are constructed and analyzed. The proposed CT model is integrated into a three-model IMM algorithm together with the Constant Velocity (CV) and Constant Acceleration (CA) models. The study includes both an internal comparison of Maclaurin approximations of different orders and an external comparison with the classical CT discretization and a Padé-based reference discretization. Numerical experiments are performed for representative three-dimensional maneuvering scenarios under radar measurement conditions. The obtained results show that the proposed discretization eliminates singular behavior near zero turn rate while preserving the tracking capability of the IMM estimator. The comparative analysis demonstrates that the quadratic Maclaurin approximation provides the most favorable trade-off between modeling accuracy, numerical stability, and computational cost. It yields tracking performance close to higher-order approximations and competitive with the Padé-based reference approach, while remaining simpler for practical implementation in real-time radar tracking systems. These results indicate that the proposed quadratic approximation is a suitable solution for maneuvering aerial target tracking in three-dimensional radar applications. Full article

This paper studies observer-based stabilization of a normalized incommensurate fractional-order discrete-time SI benchmark model for computer-virus propagation. The model is formulated with Caputo-like fractional-difference operators and allows the susceptible and infected compartments to have different memory orders. In contrast with a predictive malware-forecasting model, the proposed system is explicitly treated as a dimensionless benchmark for qualitative analysis and control design. To clarify how the benchmark can be connected to empirical cybersecurity data, the revised formulation includes a calibration and fractional-order selection procedure based on normalized infection telemetry, admissible parameter sets, and loss minimization. The incommensurate orders are therefore interpreted as identifiable modeling parameters, not as arbitrary constants. The plant, observer, and control laws are formulated on the integer update grid, and the memory terms are implemented through the equivalent Volterra-type convolution representation. A nonlinear Luenberger-type observer is proposed under infected-state measurements, which is justified as a detectability-based cyber-monitoring configuration rather than a full observability assumption. The observer gain design, the full-state feedback design, and the observer-based output-feedback design are derived from first-order linearized incommensurate fractional-order models. The resulting criteria are expressed through characteristic-root conditions associated with linear incommensurate Caputo-type fractional-order difference systems. The scope of the theoretical claims is made explicit: the results provide local linearized-design guarantees and do not establish global or semi-global nonlinear stabilization. The nonlinear residuals, measurement-noise channel, incomplete-measurement formulation, and limitations of the linearized characteristic-root approach are stated explicitly so that the numerical section can assess robustness, sensitivity, and the effective region of attraction of the nonlinear closed loop. Full article

We study the quantitative structure of the reciprocity gap method for inclusions with spatially varying conductivity. Motivated by the variable-coefficient reciprocity gap identity, we investigate the discrete approximation mechanism underlying the bounded/blow-up dichotomy for sampling points inside and outside the inclusion. The reciprocity gap functional is discretized by harmonic test functions, and the resulting ill-conditioned linear system is regularized by a Tikhonov term consistent with the $L^2(\partial D)$ trace norm appearing in the weighted formulation. The regularization parameter is selected by the L-curve criterion. For constant, radially varying, and angularly oscillating contrasts, the numerical results show that exterior sampling points exhibit an approximately exponential growth of $\parallel v_N{\left(z\right)\parallel }_{L^2(\partial D)}$ with respect to the harmonic order N, whereas interior points remain bounded. This behavior is quantified through fitted growth rates and contrast indicators, and its dependence on geometry and model parameters is examined. The results provide a quantitative description of the reciprocity gap approximation mechanism in heterogeneous media and show that the bounded/blow-up dichotomy remains numerically detectable beyond the constant-coefficient setting. Full article

Nanofluids, which are suspensions of nanoparticles within base fluids, are employed in industries such as electronics, automotives, nuclear power, and defense to enhance thermal management, mass transfer, and microchip cooling. This study investigates heat transfer generation on a stretching sheet incorporating aluminum oxide ${(\mathrm{A}\mathrm{l}}_2{\mathrm{O}}_3)$ and magnetite ${(\mathrm{F}\mathrm{e}}_3{\mathrm{O}}_4)$ nanoparticles under conditions of constant and varying wall temperatures. Key factors considered include variable viscosity, a periodic magnetic field, and thermal radiative flux, underscoring the thermal advantages of nanoparticles in nuclear reactor applications. The Crank–Nicolson method, an implicit finite difference technique, was utilized to solve the mathematical model, with partial differential equations discretized and approximated using an explicit method. An explicit iterative method was employed to solve the momentum and energy equations in a Python solver, while boundary values were analytically resolved based on discretized equations. In the explicit method, values at the subsequent time step (n + 1) were directly computed from the current time step (n) values. This approach necessitated a sufficiently small time step to satisfy the Courant–Friedrichs–Lewy (CFL) condition for numerical stability. The study examined the mass and heat transfer characteristics of a magnetizable nanofluid. While nanoparticles enhanced heat transfer, magnetic interactions, viscosity, and thermal radiation impeded it. A periodic magnetic field was applied perpendicularly to the plates with a constant pressure gradient, utilizing a magnetic phase angle to decelerate and control flow and heat convection modulation. Full article

This paper investigates a discrete-time fractional-order predator–prey model incorporating a double Allee effect in the prey population, derived from a fractional differential system via the piecewise constant argument method to capture both memory effects and density-dependent constraints. We establish the existence and local stability of all biologically meaningful equilibria and show that the interaction between fractional memory and the double Allee threshold significantly influences the stability of the coexistence state. Through the integration of linear stability analysis and center manifold reduction, we are able to obtain explicit conditions for Neimark–Sacker and period-doubling bifurcations. The system exhibits rich dynamics, including periodic oscillations, quasi-periodicity, and chaos. The double Allee effect plays a key role in shaping system stability. To suppress instability and chaotic behavior, feedback and hybrid control strategies are applied and shown to be effective. Numerical simulations are given to confirm the results obtained by the theoretical analysis and to show the transitions among different dynamical states, in which the fractional-order memory and multiple Allee effects play important roles. Full article

Gravel particles are widely developed and randomly distributed in deep reservoirs of the Tarim Oilfield, western China. The mechanical behavior of conglomerate, the main component of the gravel layer, under varying confining pressure and different gravel content, remains poorly understood, especially in terms of the microscopic aspect, which limits the analysis of the variation patterns of underground engineering parameters. This study conducts triaxial compression tests on outcrop specimens from various stress levels to analyze the effects of stress state and stress differences on the mechanical parameters and failure modes. After that, a kind of numerical modeling method based on the discrete element method (DEM) is proposed, which considers the random distribution of gravel particles, to study the microscopic observation of mechanical characteristics and crack propagation of conglomerate under different stress state conditions. The experimental and numerical simulation results indicate that the horizontal strain before failure remains nearly constant in the axial direction while increasing linearly for the horizontal stress. And, it was observed that the volumetric failure was accompanied by gravel fragmentation, sliding, and falling. Numerical simulations reveal that cementation strength and gravel content significantly influence mechanical properties and failure modes, which are the main factors. This study provides some useful references for further understanding of the mechanical behavior and failure mechanisms of rocks in the gravel layer, in particular, the numerical modeling method for heterogeneous materials. Full article

Conventional maintenance models often neglect the impact of pre-existing rutting on sealcoat performance, particularly in high-temperature regions like Chongqing in China, where rut-related failures are common. Existing ruts impose geometric constraints that significantly alter stress redistribution within the new sealcoat layer, yet this constraint mechanism remains poorly understood due to limitations in laboratory observation. This study developed a mesoscopic AC16 + MS3 composite discrete element model to simulate the mechanical behavior of a sealcoat applied over a rutted pavement. To replicate real-world conditions, a constant pressure of 0.7 MPa, representing the standard tire ground pressure in JTG E20-2011, was applied at a temperature of 70 °C, reflecting extreme high-temperature stability limits. Virtual rutting tests and contact force chain analyses were conducted across varying existing pavement rut depths, including 0 mm, 3 mm, 6 mm, and 10 mm. The results indicate that existing ruts redirect stress transfer paths, causing vertical compressive force chains to densify within the rutted zone and tensile stress to concentrate at rut edges. Mastic-mastic contacts transmit over 65% of the load, identifying asphalt mortar as the primary load-transfer phase. Notably, a 10 mm existing rut depth induces a tensile vacuum zone at depths of 15–40 mm, disrupting the standard U-shaped stress distribution. These findings clarify how pre-existing geometries govern structural degradation, suggesting that maintenance in high-temperature regions must prioritize asphalt mortar performance to mitigate edge cracking and deformation. Full article

To address the technical challenges of difficult deduction, limited field measurement, and ambiguous instability determination of roof separation critical values in mining roadways within the weakly cemented coal-bearing strata of Xinjiang, this paper proposes a discrete element method that integrates the fracture of anchor bolt and anchor cable support materials with the damage degree of the surrounding rock. Taking a specific mine in the Hosh Tolgay coalfield as the research object, a systematic study was conducted. The research process was as follows. (1) Model parameter calibration was performed. Intact rock parameters were obtained through laboratory basic mechanical tests, and rock mass parameters were corrected based on reduction empirical formulas and the Hoek–Brown criterion. Numerical model verification showed that the errors between the simulated and theoretical values of the elastic modulus, compressive strength, and tensile strength of the rock mass were all less than 10%, indicating that the corrected parameters are reasonable. (2) The critical damage values of the rock mass considering a non-constant confining pressure environment were proposed. Through triaxial compression simulations, the differential evolution patterns of rapid damage increase in sandy mudstone under low confining pressure and stable damage accumulation in coal were revealed, thereby clarifying the damage thresholds for rock mass instability under different confining pressures. (3) A large-scale model was established to analyze the evolution laws of the fracture field, support field, and displacement field of the roadway surrounding rock. A comprehensive determination method for the instability of the roof anchored bearing structure was proposed. By comparing the damage thresholds of the scaled rock mass and the roadway surrounding rock and analyzing the fracture conditions of the roadway support system, a dual-criterion consisting of surrounding rock damage and support material fracture was constructed. Based on this criterion theory, the critical values for deep and shallow separation were obtained. The research results indicate that the evolution patterns of damage in coal and sandy mudstone differ with confining pressure. The sandy mudstone layers in the shallow part of the roof are more sensitive to mining-induced unloading disturbances. Consequently, the surrounding rock damage and support fracture of the mine roof exhibit distinct distribution characteristics: the dominant failure of the roadway is shear failure, with wide-range coalescence of shallow fractures and gradual development of deep fractures, alongside the concentrated failure of shallow anchor bolts and partial failure of deep anchor cables. Based on the instability state of the roof monitoring zones, the critical value for shallow separation was determined to be 90.7 mm, and the critical value for deep separation was 129.03 mm. These results are very close to the field measured values, verifying the engineering applicability of the method. This paper reveals the damage characteristics of the rock mass and surrounding rock in weakly cemented strata, as well as the mechanism of roof separation initiation and evolution. The proposed method for determining critical values provides a scientific and feasible practical reference for the support optimization and monitoring and early warning of roadway roofs in weakly cemented strata, possessing significant engineering value for ensuring safe and efficient mine production. Full article