Search Results (2,121)

Closing resistors in ultra-high-voltage (UHV) gas-insulated circuit breakers (GCBs) are critical components designed to suppress inrush currents and transient overvoltages during switching operations. However, in practical service, these resistors are subjected to repeated mechanical impacts and transient electrical stresses, leading to degradation of their electrical contact interfaces, fluctuating resistance values, and potential failure of the entire breaker assembly. Existing studies mostly simplify the closing resistor as a constant resistance element, neglecting the coupled electro-thermal–mechanical effects that occur during transient events. In this work, a comprehensive modeling framework is developed to investigate the dynamic electrical contact characteristics of a 750 kV GCB closing resistor under transient closing impacts. First, an electromagnetic transient model is built to calculate the combined inrush and power-frequency currents flowing through the resistor during its pre-insertion period. A full-scale mechanical test platform is then used to capture acceleration signals representing the mechanical shock imparted to the resistor stack. These measured signals are fed into a finite element model incorporating the Cooper–Mikic–Yovanovich (CMY) electrical contact correlation to simulate stress evolution, current density distribution, and temperature rise at the resistor interface. The simulation reveals pronounced skin effect and current crowding at resistor edges, leading to localized heating, while transient mechanical impacts cause contact pressure to fluctuate dynamically—resulting in a temporary decrease and subsequent recovery of contact resistance. These findings provide insight into the real-time behavior of closing resistors under operational conditions and offer a theoretical basis for design optimization and lifetime assessment of UHV GCBs. Full article

This study develops a thermo-mechanical damage (TMD) model for predicting damage evolution in heterogeneous rock materials after heat treatment. The TMD model employs a Weibull distribution to characterize the spatial heterogeneity of the mechanical properties of rock materials and develops a framework that incorporates thermal effects into a nonlocal gradient damage model, thereby overcoming the mesh dependency issue inherent in homogeneous local damage models. The model is validated by numerical simulations of a notched cruciform specimen subjected to combined mechanical and thermal loading, confirming its capability in thermo-mechanical coupled scenarios. Sensitivity analysis shows increased material heterogeneity promotes localized, X-shaped shear-dominated failure patterns, while lower heterogeneity produces more diffuse, network-like damage distributions. Furthermore, the results demonstrate that thermal loading induces micro-damage that progressively spreads throughout the specimen, resulting in a significant reduction in both overall stiffness and critical strength; this effect becomes increasingly pronounced at higher heating temperatures. These findings demonstrate the model’s ability to predict the mechanical behavior of heterogeneous rock materials under thermal loading, offering valuable insights for safety assessments in high-temperature geotechnical engineering applications. Full article

To address thermal management challenges in CR400BF high-speed EMU electrical cabinets—stemming from heterogeneous component integration, multi-condition dynamic thermal loads, and topological configuration variations—a dual-metric-driven finite element model calibration method is proposed using ANSYS Workbench. A multi-objective optimization function, constructed via the coefficient of determination ($R^2$) and root mean square error ($RMSE$), integrates gradient descent to inversely solve key parameters, achieving precise global–local model matching. This establishes an equivalent model library of 52 components, enabling rapid development of multi-physical-field coupling models for electrical cabinets via parameterization and modularization. The framework supports temperature field analysis, thermal fault prediction, and optimization design for multi-topology cabinets under diverse operating conditions. Validation via simulations and real-vehicle tests demonstrates an average temperature prediction error $\le 10\%$, verifying reliability. A thermal management optimization scheme is further developed, constructing a full-process technical framework spanning model calibration to control for electrical cabinet thermal design. This advances precision thermal management in rail transit systems, enhancing equipment safety and energy efficiency while providing a scalable engineering solution for high-speed train thermal design. Full article

To elucidate the mechanisms governing hydrocarbon accumulation and phase evolution in the deep–ultradeep reservoirs of the Mo-Yong area, this study integrated 2D basin modeling and multi-component phase state simulation techniques, investigating the differences in maturity and hydrocarbon generation history between the Fengcheng Formation (P₁f) and the Lower Wuerhe Formation (P₂w) source rocks, as well as their coupling relationship with fault activity in controlling hydrocarbon migration, accumulation, and phase evolution. The results indicate that the P₁f and P₂w in the Mo-Yong area source rocks differ in thermal maturity and hydrocarbon generation evolution. The dual-source charging from both the P₁f and P₂w significantly enhances hydrocarbon accumulation number, volume, and saturation. The temporal-spatial coupling between peak hydrocarbon generation and multi-stage fault reactivation not only facilitates extra-source accumulation but also drives condensate reservoir formation through gas-oil ratio elevation and light-component enrichment. Based on these results, a model of hydrocarbon accumulation and phase evolution of deep reservoirs was proposed. The model elucidates the fundamental geological principle that source-fault spatiotemporal coupling controls hydrocarbon enrichment degree, while phase differentiation determines reservoir fluid types. Full article

Frequent building fires seriously threaten the safety of steel structures. According to the data, fire accidents account for about 35% of the total number of production safety accidents. The collapse of steel structures accounted for 42% of the total collapse. The early warning problem of steel structure fire collapse is imminent. This study aims to address this challenge by establishing a novel early warning framework, which is used to quantify the critical early warning threshold of steel frames based on elastic modulus degradation and its correlation with ultrasonic wave velocity under different collapse modes. The sequential thermal–mechanical coupling numerical method is used in the study. Firstly, Pyrosim is used to simulate the high-fidelity fire to obtain the real temperature field distribution, and then it is mapped to the Abaqus finite element model as the temperature load for nonlinear static analysis. The critical point of structural instability is identified by monitoring the mutation characteristics of the displacement and the change rate of the key nodes in real time. The results show that when the steel frame collapses inward as a whole, the three-level early warning elastic modulus thresholds of the beam are 153.6 GPa, 78.6 GPa, and 57.5 GPa, respectively. The column is 168.7 GPa, 122.4 GPa, and 72.6 GPa. Then the three-level warning threshold of transverse and longitudinal wave velocity is obtained. The three-stage shear wave velocity warning thresholds of the fire column are 2828~2843 m/s, 2409~2434 m/s, and 1855~1874 m/s, and the three-stage longitudinal wave velocity warning thresholds are 5742~5799 m/s, 4892~4941 m/s, and 3804~3767 m/s. The core innovation of this study is to quantitatively determine a three-level early warning threshold system, which corresponds to the three stages of significant degradation initiation, local failure, and critical collapse. Based on the theoretical relationship, these elastic modulus thresholds are converted into corresponding ultrasonic wave velocity thresholds. The research results provide a direct and reliable scientific basis for the development of new early warning technology based on acoustic emission real-time monitoring and fill the gap between the mechanism research and engineering application of steel structure fire resistance design. Full article

In this study, the impact resistance of WUF-B steel frame beam–column joints under fire was investigated using ABAQUS finite element software through a sequential thermal–mechanical coupling approach. By integrating a room-temperature impact model with a single-sided fire field applied to the lower flange of the steel beam, the multi-parameter influence mechanisms—including temperature (150–750 °C), fire area distribution, and impact momentum—were systematically analyzed. Results indicate that elevated temperatures significantly degrade structural impact resistance. At 750 °C, the peak impact force decreases by 73.3% compared to room temperature, while the mid-span bending moment increases by 63.3%. When the fire zone is near the impact point, localized thermal softening further reduces the peak impact force. Under constant impact energy, lower momentum (i.e., higher velocity) accelerates the rebound of the falling mass, revealing the role of momentum transfer efficiency in governing the transient response of high-temperature structures. Additionally, an analytical prediction model based on Timoshenko beam theory and thermo-mechanical stiffness degradation is developed. By introducing a segmented temperature reduction function, the model significantly enhances the accuracy of mid-span displacement predictions for steel structures under fire. Full article

The technical study of the presented manuscript is to investigate the thermal vibration of thick functionally graded material (FGM) conical shells with fully-homogeneous equations coupled in third-order shear-deformation theory (TSDT). The method in the generalized-differential quadrature (GDQ) approach is used to calculate the dynamic numerical data of FGM conical shells subjected to thermal-vibration only. Some parametric effects of minor middle-surface radius, environment temperature, and FGM power-law index on thermal stress and displacement of thick FGM conical shells are investigated with the frequency approach of the fully homogeneous equation. The novelties and main contributions of the present paper are that the thermal vibration GDQ study is original in thick FGM conical shells and contains some contributions to science and physics, by using the higher-order analysis of the TSDT displacement model and GDQ numerical results to obtain more accurate data in the thermal analyses of displacements and stresses for the thick FGM conical shells. Full article

To further improve the economic benefits of operators and the low-carbon performance within the system, this paper proposes a hierarchical distributed low-carbon economic dispatch strategy for regional integrated energy systems (RIESs) based on the Alternating Direction Method of Multipliers (ADMM). First, the energy coupling relationships among conversion devices in RIESs are analyzed, and a structural model of RIES incorporating an energy generation operator (EGO) and multiple load aggregators (LAs) is established. Second, considering the stepwise carbon trading mechanism (SCTM) and the average thermal comfort of residents, economic optimization models for operators are developed. To ensure optimal energy trading strategies between conflicting stakeholders, the EGO and LAs are embedded into a master–slave game trading framework, and the existence of the game equilibrium solution is rigorously proven. Furthermore, considering the processing speed of the optimization problem by the operators and the operators’ data privacy requirement, the optimization problem is solved in a hierarchical distributed manner using ADMM. To ensure the convergence of the algorithm, the non-convex feasible domain of the subproblem bilinear term is transformed into a convex polyhedron defined by its convex envelope so that the problem can be solved by a convex optimization algorithm. Finally, an example analysis shows that the scheduling strategy proposed in this paper improves the economic efficiency of energy trading participants by 3% and 3.26%, respectively, and reduces the system carbon emissions by 10.5%. Full article

This study investigates the non-equilibrium radiation characteristics during the high-speed re-entry of a lunar-return-type capsule under rarefied atmospheric conditions. A line-by-line spectral model was developed to compute atomic emission and absorption coefficients for excited nitrogen and oxygen atoms. Coupled with the Direct Simulation Monte Carlo (DSMC) method, the Photon Monte Carlo (PMC) method was employed to solve the radiative energy transport equation. The model was validated against the FIRE II flight experiment at 1631 s and 1634 s, showing improved agreement with experimental heat flux data compared to previous numerical results. A detailed sensitivity analysis was conducted to examine the influence of spectral discretization and the number of emitted photons per computational cell. Results indicate that low spectral resolution can cause non-physical fluctuations in wall heat flux, while increasing the number of photons improves local smoothness. Optimal parameters were identified as 50,000 spectral points and 5000 photons per cell. The model was further applied to a lunar-return-type capsule re-ntering at 90 km and 95 km altitudes. It was found that radiative heating is spatially decoupled from aerodynamic heating and primarily governed by excited species concentration and line-of-sight geometry. At 90 km, radiative heating accounted for over $15.31\%$ of the aerodynamic heating, more than double that at 95 km. These results underscore the necessity of considering radiation effects in the design of thermal protection systems, particularly at high re-entry velocities and large angles of attack. Full article

During the service life of steel bridges, the structural stress histories display combined cyclic characteristics due to the superposition of low-frequency thermal loading and high-frequency vehicle loading. To investigate the fatigue performance under such loading patterns, a series of constant-amplitude and high-low frequency superimposed loading fatigue (HLSF) tests were conducted on notched specimens fabricated from Q355D bridge steel. The influence of HLSF waveform parameters on fatigue life was systematically investigated. Based on the fracture evolution mechanism, a concept of low-frequency periodic damage acceleration factor was proposed to effectively model the block nonlinear damage effects, and the applicability of existing fatigue life prediction models was discussed. The results show that the effect of average stress on the fatigue life under HLSF can be effectively considered by Walker’s formula. Low-amplitude ratios and low-frequency ratios indicate unfavorable loading conditions that may accelerate the Q355D fatigue damage accumulation, and these conditions are not adequately accounted for in current life prediction models. Compared to constant amplitude loading, HLSF can lead to a 66% and 46% reduction in high-frequency life when the amplitude ratio reaches 0.12 and the frequency ratio reaches 100. Compared to Miner’s rule, the proposed damage correction method reduces the life prediction error for HLSF by 11%. These findings provide valuable references for the fatigue assessment of bridge steel structures under the coupled effects of temperature and vehicle loading. Full article

Neuromedin U receptors (NMURs) represent a class of evolutionarily conserved G-protein-coupled receptors that play a pivotal role in a variety of physiological processes. However, the role of NMURs in the heat shock response has yet to be elucidated. Using the nematode Caenorhabditis elegans as a model system, we demonstrate herein that functional loss of NMUR-3 results in reduced survival upon heat shock. The regulation of thermal tolerance by NMUR-3 is dependent on AMPK. Furthermore, our data demonstrate that NMUR-3 activates autophagy via AMPK, thereby contributing to protection against heat shock. The results of this study suggest that NMUR-3 is crucial for thermal tolerance in C. elegans. Full article

With the progressive depletion of conventional oil and gas resources and the increasing demand for alternative energy, organic-rich sedimentary rock—oil shale—has attracted widespread attention as a key unconventional hydrocarbon resource. Pyrolysis is the essential process for converting the organic matter in oil shale into recoverable hydrocarbons, and a detailed understanding of its behavior is crucial for improving development efficiency. This review systematically summarizes the research progress on the pyrolysis characteristics of oil shale under laboratory conditions. It focuses on the applications of thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) in identifying pyrolysis stages, extracting kinetic parameters, and analyzing thermal effects; the role of coupled spectroscopic techniques (e.g., TG-FTIR, TG-MS) in elucidating the evolution of gaseous products; and the effects of key parameters such as pyrolysis temperature, heating rate, particle size, and reaction atmosphere on product distribution and yield. Furthermore, the mechanisms and effects of three distinct heating strategies—conventional heating, microwave heating, and autothermic pyrolysis—are compared, and the influence of inherent minerals and external catalysts on reaction pathways is discussed. Despite significant advances, challenges remain in quantitatively describing reaction mechanisms, accurately predicting product yields, and generalizing kinetic models. Future research should integrate multiscale experiments, in situ characterization, and molecular simulations to construct pyrolysis mechanism models tailored to various oil shale types, thereby providing theoretical support for the development of efficient and environmentally friendly oil shale conversion technologies. Full article

With the increase in energy density of power batteries, the risk of thermal runaway significantly increases under extreme working conditions. Therefore, this article proposes a biomimetic liquid cooling plate design based on the fractal structure of fir needle leaf veins, combined with Murray’s mass transfer law, which has significantly improved the heat dissipation performance under extreme working conditions. A multi-field coupling model of electrochemistry fluid heat transfer was established using ANSYS 2022 Fluent, and the synergistic mechanism of environmental temperature, coolant parameters, and heating power was systematically analyzed. Research has found that compared to traditional serpentine channels, leaf vein biomimetic structures can reduce the maximum temperature of batteries by 11.78 °C at a flow rate of 4 m/s and 5000 W/m³. Further analysis reveals that there is a critical flow rate threshold of 2.5 m/s for cooling efficiency (beyond which the effectiveness of temperature reduction decreases by 86%), as well as a thermal saturation temperature of 28 °C (with a sudden increase in temperature rise slope by 284%). Under low-load conditions of 2600 W/m ³, the system exhibits a thermal hysteresis plateau of 40.29 °C. To predict the battery temperature in advance and actively intervene in cooling the battery pack, based on the experimental data and thermodynamic laws of the biomimetic liquid cooling system mentioned above, this study further constructed a support vector machine (SVM) prediction model to achieve real-time and accurate prediction of the highest temperature of the battery pack (validation set average relative error 1.57%), providing new ideas for intelligent optimization of biomimetic liquid cooling systems. Full article

Regulatory changes related to the policy of reducing CO₂ emissions from natural gas are leading to an increase in the share of hydrogen in gas transmission and utilization systems. In this context, the impact of the change in composition on thermal radiation zones should be assessed for flaring during startups, scheduled shutdowns, maintenance, and emergency operations. Most existing models are calibrated for hydrocarbon flare gases. This study assesses how the CH₄–H₂ blends affect thermal radiation zones using a developed solver based on the Brzustowski–Sommer methodology with composition-dependent fraction of heat radiated (F) and range-dependent atmospheric transmissivity. Five blends, 0–50% (v/v) H₂, were analyzed for a 90 m stack at wind speeds of 3 and 5 m·s⁻¹. Comparisons were performed at constant molar (standard volumetric) throughput to isolate composition effects. Adding H2 contracted the radiation zones and reduced peak ground loads. Superposition analysis for a multi-flare layout indicated that replacing one 100% (v/v) CH₄ flare with a 10% (v/v) H₂ blend reduced peak ground radiation. Emission-factor analysis (energy basis) showed reductions of 3.24/3.45% at 10% (v/v) H₂ and 7.01/7.44% at 20% (v/v) H₂ (LHV/HHV); at 50% (v/v) H₂, the decrease reached 22.18/24.32%. Hydrogen blending provides coupled safety and emissions co-benefits, and the developed framework supports screening of flare designs and operating strategies as blends become more prevalent. Full article

Magnetic components serve as critical energy conversion elements in power conversion systems, with their performance directly determining overall system efficiency and long-term operational reliability. The development of accurate core loss frameworks and multi-objective optimization strategies has emerged as a pivotal technical bottleneck in power electronics research. This study develops an integrated framework combining physics-informed modeling and multi-objective optimization. Key findings include the following: (1) a square-root temperature correction model (exponent = 0.5) derived via nonlinear least squares outperforms six alternatives for Steinmetz equation enhancement; (2) a hybrid Bi-LSTM-Bayes-ISE model achieves industry-leading predictive accuracy (R² = 96.22%) through Bayesian hyperparameter optimization; and (3) coupled with NSGA-II, the framework optimizes core loss minimization and magnetic energy transmission, yielding Pareto-optimal solutions. Eight decision-making strategies are compared to refine trade-offs, while a crow search algorithm (CSA) improves NSGA-II’s initial population diversity. UFM, as the optimal decision strategy, achieves minimal core loss (659,555 W/m³) and maximal energy transmission (41,201.9 T·Hz) under 90 °C, 489.7 kHz, and 0.0841 T conditions. Experimental results validate the approach’s superiority in balancing performance and multi-objective efficiency under thermal variations. Full article