Search Results (22,499)

Three-dimensional spatial effects in deep excavations critically govern the mechanical response of retaining structures and adjacent soils, yet their quantitative characterization remains a challenge. This study systematically investigates the spatial behavior of row-pile-supported foundation pits through an integrated approach combining model tests, theoretical analysis, and numerical simulations. A novel formulation for the spatial effect influence coefficient K is derived from limit equilibrium principles and subsequently validated via ABAQUS-based finite element simulations. Model test results reveal pronounced spatial heterogeneity in earth pressure and bending moment distributions along the pit perimeter: lateral earth pressure at corner regions exceeds that at mid-side locations at equivalent depths, whereas bending moments in mid-side piles are substantially larger than those at corners. Displacement field measurements further demonstrate that corner zones, constrained bidirectionally, undergo minimal deformation, while maximum displacement occurs at the midpoints of the long sides. These observations collectively confirm the existence of a marked corner effect and a subdued side-midpoint effect under three-dimensional confinement. Complementary numerical analyses indicate that the coefficient K decreases monotonically with increasing half-angle corners and distance from the corner, thereby quantitatively capturing the decay of spatial constraint intensity. Together, these findings establish a theoretical framework for assessing excavation-induced spatial effects and provide actionable guidance for the rational design of deep foundation pit support systems. Full article

Numerous safety hazards in construction projects can readily cause safety accidents. While collaborative governance among stakeholders is vital for construction safety, it is hampered by interest-related factors. Evolutionary game theory is an excellent tool for analyzing participants’ behavioral decisions based on interest factors, and it is employed in this study to explore strategies for promoting collaborative governance. However, existing studies rarely mention the concept of collaborative governance of construction safety risks, seldom focus on construction payment disputes between owners and contractors, and barely take into account the differences in interests and decisions faced by stakeholders under projects of varying costs. Based on this, an evolutionary game model among the government, owner and contractor is established by taking China’s construction industry as an example, and MATLAB numerical simulation is conducted. First, the heterogeneity of the laws of strategy evolution under different cost levels was verified. Subsequently, cost levels were divided into two major categories and four subcategories based on strategy evolution results, and sensitivity analysis was conducted for each corresponding scenario. It was found that rewards for owners and contractors are barely effective, while cutting government regulatory costs and boosting positive governmental incentives generally play a positive role. The effects of penalties for inadequate safety investment and safety accidents on collaboration differ across project costs. Nevertheless, collaborative governance can be achieved via reasonable parameter optimization. This study addresses the critical issue of interest factors hindering collaborative governance, and provides a critical perspective for promoting construction safety and the sustainability of the construction industry. Cost-stratified analysis reduces overly definitive suggestions, offering valuable insights for both theory and practice. Full article

In the state estimation problem for nonlinear systems, the Unscented Kalman Filter (UKF) has gained attention as an algorithm capable of accurate state estimation based on high-fidelity discretization for strongly nonlinear systems. Furthermore, for applying the UKF to continuous-time state–space models, a method employing the Runge–Kutta method in the time-update equation for sigma points has already been proposed to achieve high-precision state estimation. While this method uses high-order numerical approximations, the associated decrease in computational efficiency due to processing time becomes problematic. It is thus unsuitable for the state estimation of relatively fast-moving objects, such as autonomous vehicles and drones, which require high sampling frequencies. In this study, to reduce computational load while achieving relatively high estimation accuracy, we newly apply the Adams–Bashforth method to the UKF algorithm. The effectiveness of the proposed method is demonstrated by first explaining a low-dimensional model’s state estimation problem, followed by a comparison of estimation accuracy and computation time in state estimation simulations for the UAV model of an Osprey-type drone. Full article

Solar radiation, longwave radiation, sensible heat flux, and latent heat flux constitute the primary forms of air–sea heat exchange, serving as crucial computational parameters in numerical simulations of thermal discharge. This study investigates a coastal nuclear power plant and employs a modified Morris screening method to quantitatively assess the contribution rates of various air–sea heat exchange processes to the spatial distribution of temperature rise under different operating conditions. The results indicate that the influence of air–sea heat exchange processes on the thermal discharge envelope exhibits a nonlinear pattern. The individual parameter sensitivity of shortwave radiation, sensible heat flux and latent heat flux is higher in the low temperature rise region ($∆\mathrm{T} \ge 1 °\mathrm{C}$) than in the high temperature rise region ($∆\mathrm{T} \ge 4 °\mathrm{C}$), with the individual parameter sensitivities of longwave radiation and latent heat flux displaying distinct threshold effects. The dominant heat exchange mechanisms vary across temperature rise regions: longwave radiation predominates in the high temperature rise region ($∆\mathrm{T} \ge 4 °\mathrm{C}$), contributing approximately 74.71%, whereas latent and sensible heat fluxes dominate in the low temperature rise region ($∆\mathrm{T} \ge 1 °\mathrm{C}$), accounting for a combined contribution of about 88.58%. These findings provide a scientific basis for model simplification and targeted parameterization. Full article

To advance our understanding of atmospheric processes and climate dynamics, improved knowledge of outgoing long-wave radiation (OLR) spectral emission is essential. The FORUM mission, selected for the ninth cycle of the European Space Agency’s Earth Explorer programme, is specifically designed to address the long-standing observational gap in the far-infrared (FIR) spectral region. When combined with measurements from the IASI-NG instrument, FORUM will provide complete spectral coverage of Earth’s OLR emission (spanning 100 to 2760 cm⁻¹ wavenumber, or 3.62 to 100 μm wavelength), thereby enabling robust climate model validation and enhanced understanding of climate change processes. While IASI-NG’s primary mission is to support numerical weather prediction, FORUM is designed to measure key climate variables, which also enable the retrieval of atmospheric parameters in the troposphere and lower stratosphere. In this study, we assess the information content of FORUM and IASI-NG measurements for atmospheric profiling through a simulation-based approach. Synthetic retrieval products are generated using a linearized formulation of the retrieval transfer function, allowing an efficient and physically consistent evaluation of the sensitivity of the two instruments to atmospheric temperature and water vapor profiles. The analysis reveals a non-negligible sensitivity of FORUM to atmospheric temperature extending into the stratosphere, resulting in significant information content at altitudes higher than previously reported. This finding highlights the potential of far-infrared observations to contribute to atmospheric temperature profiling beyond the lower troposphere. The complementary capabilities of FORUM and IASI-NG suggest that their combined use can enhance the characterization of the atmospheric thermal structure. These results represent a first step toward evaluating the potential role of FORUM Level-2 products in future numerical weather prediction applications. Full article

In this study, we examine the effectiveness of combining interleukin-2 (IL-2) with highly active antiretroviral therapy (HAART) in controlling HIV replication. A mathematical model of the immune system is developed to analyze immune recovery when IL-2 is administered alongside HAART. We investigate the stability of the endemic equilibrium and Hopf bifurcation and determine the direction and stability of periodic solutions using center manifold theory. Numerical simulations are conducted to support the theoretical findings. The results show that the disease-free equilibrium is stable when the basic reproduction number $R_0<1$, while the endemic equilibrium exists when $R_0>1$. Our results also reveal the presence of a subcritical Hopf bifurcation in the system. An optimal control problem is also studied, showing that the combined therapy of IL-2 and HAART improves treatment outcomes, reduces side effects, and has a unique optimal control pair. Sensitivity analysis further highlights the importance of system parameters in influencing treatment effectiveness. Full article

Despite its importance in modeling subdiffusion in fractal and heterogeneous media, a rigorous and computational scheme for solving the fractional diffusion equation on generalized comb structures over unbounded domains has remained elusive, mainly due to the nonlocal memory effect and slow spatial decay of solutions. To the best of our knowledge, we address this long-standing gap by presenting a fully integrated framework that simultaneously resolves both challenges. We derive the governing equation from constitutive relations and establish exact absorbing boundary conditions (ABCs) for the multi-skeleton comb model, a result absent in prior work. A transparent Dirichlet-to-Neumann (DtN) map, constructed via Laplace analysis, rigorously handles skeletal Dirac delta singularities and eliminates spurious reflections without empirical parameters. Furthermore, we propose a novel structure-preserving finite difference scheme that applies the sum-of-exponentials (SOE) approximation not only to the interior Caputo derivative but also to the convolution kernels arising from the ABCs. This yields a dramatic reduction in computational complexity, from quadratic $O\left(N_t^2\right)$ to quasi-linear $O(N_{t}log{N}_t)$, while preserving the physics of anomalous transport. We prove the well-posedness, unconditional stability, and convergence of the method. Numerical results confirm theoretical error estimates and show excellent agreement between simulated particle distributions, mean square displacement profiles, and exact asymptotics, validating both accuracy and robustness. The speedup (CPU time ratio Direct/Fast) is about $1.00\times$–$1.23\times$ for $N_t=5000$ in our tests. Our approach sets a new benchmark for simulating anomalous dynamics in fractal-inspired media. Full article

Accurate and efficient analysis of embankment seepage is of vital importance for scientific assessment of embankment safety. Conventional numerical simulation techniques for embankment seepage analysis suffer from high computational cost and low efficiency. To address this issue, this paper proposes an embankment seepage response analysis method based on physical information neural network (PINN). Initially, this method considering the fluid–solid coupling and spatial variability of soil parameters of the embankment. Consequently, a numerical simulation method was developed using the finite difference method to analyze the seepage response. On this basis, a neural network loss function for the surrogate model is introduced by integrating the governing equations for fluid–solid coupling of embankments with boundary conditions. This integration incorporates physical restrictions into the seepage analysis, hence improving its interpretability. Furthermore, a feature sequence is derived from the soil parameter field via a Variational Autoencoder (VAE) to diminish input dimensionality and improve training accuracy. The feature sequence and hydraulic loading function as the model input, while the output is the piezometric head obtained from the pore water pressure. The PINN model is trained by numerical simulation results to establish the surrogate model for seepage responses analysis. A case study on the practical embankment engineering is employed to confirm the feasibility and efficacy of the proposed strategy. Comparative tests demonstrate that the PINN surrogate model markedly enhances computational accuracy relative to conventional baseline models. Overall, this approach offers a trustworthy and effective method for rapid and accurate assessment of embankment seepage characteristics. Full article

With the rapid development of electrified railways in high-altitude regions, section insulators in catenary systems frequently experience gap breakdown and surface flashover under low atmospheric pressure conditions, posing serious threats to safe train operation. This paper investigates the discharge mechanisms of section insulators in high-altitude environments and conducts research on discharge characteristics under extremely non-uniform electric fields, along with structural optimization. First, the physical mechanisms of gap discharge and surface flashover in section insulators are analyzed. A three-dimensional electric field simulation model of the section insulator is established, and numerical analysis is performed to reveal the electric field distribution characteristics. The results indicate that the electric field is predominantly concentrated at the junction between metal electrodes and insulators, as well as at the tip of the arcing horn. The local maximum field strength reaches 3.84 × 10⁵ V/m, exceeding the corona inception field strength of air, which readily induces discharge. Subsequently, power frequency and lightning impulse discharge tests are conducted in both plain region and regions at an altitude of 4300 m. The results show that under high-altitude conditions, the power frequency breakdown voltage decreases by 28%, and the 50% lightning impulse breakdown voltage decreases by 42%. The discharge voltages under standard atmospheric conditions are obtained through correction. Finally, optimization schemes involving arcing horn structural modification and surface coating application are proposed. Adjusting the arcing horn angle to 55° and adding a grading ring structure with a radius of 70 mm reduces the local maximum field strength by 26%. After applying an RTV insulating coating, the field strength at the junction decreases by 35.9%, effectively enhancing the insulation performance of section insulators in high-altitude regions. Full article

We introduce the one-parameter bounded p-exponential distribution on $(0, p+1)$, which includes the uniform model as a special case and converges pointwise to the exponential law as $p\to \infty$. Closed-form expressions are derived for the CDF and PDF, the survival function, an explicit increasing-failure-rate hazard function, the quantile function (enabling inversion-based simulation), moments, and entropy, along with a constructive scaled beta or Kumaraswamy representation. We also establish stochastic ordering with respect to p in stop-loss and increasing convex order, formalizing how dispersion varies with the parameter while preserving the mean scale. Inference is discussed under parameter-dependent support, a non-regular setting, and we develop and compare several estimation procedures, including a likelihood-based boundary MLE, a variance-matching method-of-moments estimator, and Bayesian estimation under a gamma prior implemented via numerical quadrature or MCMC. Monte Carlo simulation studies evaluate finite-sample performance and interval behavior, and two real-world applications in survival and reliability analysis illustrate competitive goodness-of-fit relative to standard benchmark models. Full article

This paper addresses the speed control problem of a DC motor in the presence of nonlinearities, disturbances, and unmodeled dynamics by proposing a neural backstepping control scheme based on a Recurrent High-Order Neural Network (RHONN). The proposed RHONN serves as an online approximator to compensate for uncertain nonlinear dynamics in a PD-based backstepping controller, enabling the system to handle disturbances, modeling errors, and unmodeled dynamics. Instead of relying on the traditional Extended Kalman Filter (EKF) for RHONN weight adaptation, the neural parameters are updated online using a Super-Twisting Algorithm (STA). As a result, the proposed STA-based learning law provides a simpler and robust covariance-free adaptation mechanism with practical finite-time convergence properties, making it suitable for real-time embedded implementations. The proposed method was evaluated through numerical simulations and implemented on an embedded microcontroller to assess its real-time performance. Simulation results show reductions between 0.04% and 2.04% in steady-state and integral error metrics compared with a tuned PD controller, and improvements up to 25.66% and 23.82% over LQR and MPC in the IMSE index. Experimental results demonstrate good tracking performance, robustness under varying load conditions, and low computational requirements, confirming the practical feasibility. Full article

This paper investigates the fractal dynamical behavior of a discrete Caputo fractional-order hepatitis C virus model. First, we analyze the stability of the system by using spectral radius and design the fractional-order controller based on coordinate transformation. Then, a nonlinear coupling controller is constructed to achieve synchronization between two fractional-order models with different parameters and different fractional orders, and the synchronization is supported by rigorous mathematical proof. Numerical simulations are used to verify the effectiveness of control and synchronization. Full article

Dynamic umbilicals, as critical components connecting offshore platforms to subsea production systems, can effectively decouple platform motions through a lazy-wave configuration, thereby reducing top tension and fatigue damage. To address the engineering challenges of numerous configuration design variables and time-consuming dynamic analyses for dynamic umbilicals, an efficient design optimization framework based on surrogate modeling and multi-objective optimization is proposed. An integrated finite-element model of a lazy-wave dynamic umbilical–offshore platform system is developed in OrcaFlex, incorporating environmental loads, material properties, and geometric parameters. The arrangement parameters of clump weights and buoyancy modules are selected as design variables, and the dynamic responses and parameter sensitivities of multiple configurations are investigated. Using simulation data, surrogate models for predicting tension and curvature are constructed via random forest regression, achieving coefficients of determination (R²) of 0.9948 and 0.9121 on the test set, respectively. Based on the surrogate predictors, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to solve a multi-objective optimization problem that minimizes the maximum tension and curvature, yielding a set of Pareto-optimal solutions. The proposed approach effectively improves the stability and reliability of the dynamic umbilical system under complex sea states. Full article

For deep-draft cylindrical platforms with a large annular column boot, the influence of the column boot diameter-to-height ratio (d/h) on motion performance remains unclear. This study investigates the effect of d/h on platform hydrodynamics while keeping the main body geometry, displacement, and draft unchanged. A hybrid numerical model validated against tests is adopted: STAR-CCM+ free-decay simulations identify equivalent linear damping, and ANSYS AQWA predicts hydrodynamic coefficients, response amplitude operators, and coupled time-domain responses under a 100-year survival sea state in the western South China Sea. Increasing d/h substantially increases heave added mass and added pitch moment of inertia, leading to longer natural periods and higher damping in heave and pitch. However, its effect on motion responses is non-monotonic and strongly response-dependent. As d/h increases, the responses are initially reduced markedly. The minimum surge and heave responses occur at d/h = 2.39 and 4.67, with reductions of about 34.0% and 87.2%, respectively, while the pitch response is already reduced by about 67.3% at d/h = 7.22. Further increases in d/h may weaken surge and heave mitigation while providing limited additional benefit for pitch. These findings provide qualitative understanding and quantitative guidance for response-oriented column boot design and optimization of similar platforms. Full article

High-temperature carburization (HTC, 950–1050 °C) has emerged as a pivotal low-carbon, energy-efficient manufacturing technology for gear steels, accelerating carbon diffusion for reducing processing cycles by over 60% while achieving significant energy savings and emission reductions. However, the inherent contradiction between HTC efficiency and microstructural stability, specifically austenite grain coarsening, severely degrades mechanical properties (e.g., strength, toughness, fatigue resistance) and limits widespread application. This review systematically synthesizes recent advances in austenite grain size regulation during HTC of gear steels, focusing on the core scientific framework of “grain coarsening mechanism—regulation strategy—performance enhancement”. It elaborates on thermodynamic and kinetic mechanisms of austenite grain growth, ripening behavior of microalloying precipitates (Nb(C,N), Ti(C,N), AlN, etc.), and their synergistic grain-refining effects. Comprehensive coverage of regulatory strategies (microalloying design, pretreatment technologies, process optimization, and integrated regulation) and characterization techniques is provided, along with a quantitative correlation between grain size, microstructure, and surface performance (wear resistance, corrosion resistance, and fatigue life). Numerical simulation and predictive models (empirical, theoretical, multiphysics coupling, machine learning-based) are critically analyzed, and current challenges (temperature-grain stability trade-off, multifactor synergy understanding, industrial scalability) and future research directions (advanced microalloying systems, intelligent process optimization, cross-scale modeling, green technology integration) are proposed. This review aims to provide theoretical guidance and technical support for optimizing the HTC performance of gear steels, catering to the demands of high-power-density transmission systems in automotive, aerospace, and heavy machinery industries. Full article