Search Results (1,557)

During the laser cladding process, the distribution of the temperature field directly influences the morphology, microstructure, and residual stress state of the cladding layer. However, the process involves transient characteristics of rapid heating and cooling, making it challenging to study temperature field variations directly through experimental methods. Therefore, numerical simulation has become a crucial tool for gaining a deeper understanding of the laser cladding mechanism, providing theoretical basis and guidance for optimizing process parameters. This study systematically integrates COMSOL Multiphysics coupling simulation with Jmatpro material thermal property data to perform simulations of temperature field evolution, melt pool flow behavior, and Marangoni effects during laser cladding of nickel-based alloy (IN718) onto an EA4T steel substrate. It highlights the influence patterns of different process parameters (e.g., laser power, scanning speed) on the temperature gradient and flow characteristics of the molten pool, providing an in-depth theoretical basis for understanding the formation mechanism of the molten pool and microstructure control. Full article

Coalbed methane (CBM) development involves multiple interacting physical fields, and different coupling schemes can lead to distinctly different production behaviors. A thermo-hydro-mechanical model accounting for gas–water two-phase flow and matrix dynamic diffusion (TP-D-THM) is developed and validated, achieving an error rate below 10%. By embedding the numerically estimated reservoir physical parameters of the Qinshui Basin into the numerical model, multi-field couplings during CBM production, the evolution of physical parameters, and the depth-dependent effects on production characteristics were revealed. The main findings are as follows: The inhibitory effect of water on CBM recovery consistently exceeds the promoting effect of temperature. As burial depth expands, the inhibitory effect first diminishes, then intensifies, ranging from 19.73% to 28.41%, while the thermal promotion effect exhibits a monotonically increasing trend, fluctuating between 8.55% and 16.33% and stabilizing below 1000 m. Temperature and burial depth do not alter the trend in gas production rate. For equilibrium permeability, reproducing a decrease–increase–decrease rate pattern requires explicit inclusion of water and matrix-fracture mass exchange terms, which can explain why different scholars obtained varying gas production rate trends using the THM model. Matrix adsorption-induced strain is the primary control on permeability evolution, and temperature amplifies the magnitude of permeability change. The critical depth essentially reflects the statistical characteristics of reservoir petrophysical properties. A dimensionless critical depth criterion has been proposed, which comprehensively considers reservoir pressure, permeability, and a fractional coverage index. For burial depths ranging from 650 to 1350 m, the TP-D-THM model can be simplified to the gas-mechanical model accounts for matrix dynamic diffusion (D-HM) with an error below 5%, indicating that thermal and water effects nearly cancel each other. Full article

The air-gap airflow significantly influences the performance of high-speed slotless permanent magnet synchronous motors (HSSPMSM), yet this critical factor is frequently overlooked during the design phase, resulting in performance deviations. This paper presents the design and multi-physical analysis of a 10 kW/40,000 rpm HSSPMSM, explicitly accounting for air-gap airflow effects. A comprehensive coupling model integrating electromagnetic, thermal, mechanical, and airflow fields is established to guide the motor design. Based on this analysis, the motor dimensions and parameters are determined, and a prototype is fabricated. Experimental validation demonstrates that the developed HSSPMSM successfully meets the design specifications. Considering air-gap airflow can obtain more accurate thermal design results with an accuracy improvement of 6.8% compared to not considering air-gap airflow. The close agreement between the simulated and measured performance confirms the effectiveness of the proposed design methodology that incorporates airflow effects. Full article

Laboratory astrophysics is an emerging interdisciplinary field bridging high-energy-density plasma physics and astrophysics. Optical diagnostic techniques offer high spatiotemporal resolution and the unique capability for simultaneous multi-field measurements. These attributes make them indispensable for deciphering extreme plasma dynamics in laboratory astrophysics. This review systematically elaborates on the physical principles and inversion methodologies of key optical diagnostics, including Nomarski interferometry, shadowgraphy, and Faraday rotation. Highlighting frontier progress by our team, we showcase the application of these techniques in analyzing jet collimation mechanisms, turbulent magnetic reconnection, collisionless shocks, and particle acceleration. Future trajectories for optical diagnostic development are also discussed. Full article

Amid the global energy transition, geothermal energy, as a clean, stable, and renewable energy source, serves as a core direction for energy structure optimization. The development of medium-deep geothermal reservoirs is dominated by thermo–hydro–mechanical (THM) multi-physics coupling effects, yet the quantitative regulation laws of their operational parameters remain unclear. In this study, a numerical model for geothermal extraction considering THM multi-physics coupling was established. Using the single-factor variable method, simulations were conducted within the set parameter ranges of injection–production pressure difference, well spacing, and injection temperature. The spatiotemporal evolution characteristics of the temperature field, the dynamic temperature–pressure responses at the midpoint of injection–production wells and production wells, and efficiency indicators, such as instantaneous heat extraction power and cumulative heat extraction, were analyzed and quantified. The results show that a larger pressure difference accelerates the expansion of the cold zone in the reservoir, which improves short-term heat extraction efficiency but increases the risk of long-term thermal depletion; a smaller well spacing leads to higher initial heat production power but results in lower long-term cumulative heat extraction due to rapid heat consumption; within the normal temperature range of 16–24 °C, the injection temperature has a negligible impact on heat extraction efficiency. This study clarifies the regulatory laws of operational parameters and provides theoretical support for well pattern design and injection–production process optimization in medium-deep geothermal development. Full article

Informal settlements accommodate more than one billion people worldwide, yet their intricate urban forms are frequently perceived as chaotic, which impedes the formulation of sustainable upgrading strategies. The main objective of this research is to bridge a major methodological gap by developing analytical tools that can systematically decode the inherent spatial logic of such environments. This paper develops and applies an integrated four-part morphological framework designed to provide a deep, form-based reading of informal urbanism. The framework’s indicators were systematically derived from an extensive review of the literature and subsequently validated through the Fuzzy Delphi Method (FDM) with a panel of 15 experts, ensuring analytical robustness. The validated framework was then applied to the Saadi neighborhood, a representative informal settlement in Shiraz, Iran, using a multi-scalar, mixed-methods approach that integrated GIS, remote sensing, and in-depth field surveys. The analysis produced a comprehensive analytical atlas, culminating in a detailed morphological profile. The findings identify Saadi’s urban form not as disordered, but as a ‘consolidating, low-rise, fine-grained fabric shaped by topography,’ revealing a clear, self-organized spatial logic. The study concludes that the proposed framework is a robust and replicable tool for moving beyond pejorative descriptions of informality. By providing an evidence-based method to read the physical language of these settlements, the approach offers a crucial foundation for developing more context-sensitive and sustainable urban upgrading strategies. Full article

The outer sheath of power cables is prone to mechanical damage and environmental stress during long-term operation, and early defects are often difficult to detect accurately using conventional methods. To address this challenge, this paper proposes an outer sheath defect identification method based on leakage current features and graph neural networks. An electro–thermal coupling physical model was first proposed to simulate the electric field distribution and thermal effects under typical defects, thereby revealing the mechanisms by which defects influence leakage current and harmonic components. A power-frequency high-voltage experimental platform was then constructed to collect leakage current signals under conditions such as scratches, indentations, moisture, and chemical corrosion. Multi-scale frequency band features were extracted using wavelet packet decomposition to construct correlation graphs, which were further modeled through a combination of graph convolutional networks and long short-term memory networks for spatiotemporal analysis. Experimental results demonstrate that the proposed method effectively improves defect type and severity identification. By integrating physical mechanism analysis with data-driven modeling, this approach provides a feasible pathway for condition monitoring and refined operation and maintenance of cable outer sheaths. Full article

Background: Over the past several decades, the prevalence of gestational diabetes mellitus (GDM) has risen markedly worldwide, posing serious threats to both maternal and child health by increasing adverse pregnancy outcomes and long-term metabolic risks. Developing effective risk prediction tools for early detection and intervention has become the most important clinical priority in this field. The current GDM prediction models primarily rely on non-modifiable factors, for example age and body mass index, while modifiable factors such as lifestyle and health literacy, although strongly associated with GDM, have not been fully utilized in risk assessment. This study sought to establish and validate a nomogram prediction model combining modifiable and non-modifiable risk factors, with the goal of identifying high-risk Chinese pregnant women with GDM at an early stage and promoting targeted prevention and personalized prenatal management. Methods: A multicenter study was conducted across 7 maternal health institutions in Southern China (2021–2023), enrolling 806 singleton pregnant women (14–23⁺⁶ weeks). The collected data included sociodemographic, clinical history, and modifiable factors collected through validated questionnaires: dietary quality, physical activity level, sleep quality, and nutrition and health literacy. GDM was diagnosed via 75 g oral glucose tolerance test at 24–28 weeks. Predictive factors were identified through multi-variable logistic regression. A nomogram model was developed (70% modeling group) and validated (30% validation group). Receiver operator characteristic curves, calibration curves, and decision curve analysis were used to evaluate the prediction ability, the degree of calibration, and the clinical benefit of the model, respectively. Results: The finalized risk prediction model included non-modifiable factors such as maternal age, pre-pregnancy weight, and maternal polycystic ovary syndrome, as well as modifiable factors including dietary quality, physical activity level, sleep quality, nutrition and health literacy. The application of the nomogram in the modeling group and the validation groups showed that the model had high stability, favorable predictive ability, good calibration effect and clinical practicality. Conclusions: Overall, the integrated model demonstrates significant clinical utility as it facilitates the prompt identification of individuals at heightened risk and offers actionable targets for personalized interventions. In terms of future implementation, this model can be integrated into prenatal care as a rapid scoring table during early pregnancy consultations or incorporated into mobile health applications. This approach fosters precise prevention strategies for GDM in maternal health by emphasizing nutrition and health literacy, supplemented by coordinated adjustments in diet, physical activity, and sleep. Full article

During the preparation of gallium nitride (GaN) single crystals by Hydride Vapor Phase Epitaxy (HVPE), variations in growth pressure within the reaction chamber can easily lead to a mismatch between vapor transport dynamics and surface reaction processes, thereby affecting crystal growth rate and uniformity. To address this issue, this study established a multi-physics coupled simulation model based on the HVPE equipment structure. By integrating reaction gas flow, heat transfer, chemical reactions, and mass transport mechanisms, systematic finite element analysis was employed to simulate the flow field distribution, thermal field stability, and precursor concentration field evolution within the reaction chamber under different growth pressures (91–141 kPa). The simulation results indicate that, on one hand, the growth rate exhibits a nearly linear increase trend with rising pressure. At lower pressures (<100 kPa), vapor transport is limited, leading to a significant decrease in growth rate, while at higher pressures (>110 kPa), growth uniformity deteriorates. Optimizing the pressure parameter can enhance both the growth rate and thickness uniformity of GaN single crystals, providing a basis for process control in the preparation of high-performance GaN devices. Full article

Lightning-induced backflashovers pose significant risks to high-voltage transmission systems, particularly in high lightning activity regions. Conventional backflashover rate (BFR) estimation methods rely on simplified empirical formulas that lack accuracy in complex scenarios. This paper presents a comprehensive simulation framework integrating (i) a Simulation-Based Leader Progression Model (SB-LPM) implemented in COMSOL Multiphysics–MATLAB to evaluate lightning attachment through detailed electrostatic field analysis and streamer-leader dynamics, (ii) ATP-EMTP electromagnetic transient simulations incorporating multi-component Heidler function current waveforms, calibrated to regional lightning measurements, and (iii) a Monte Carlo analysis for statistical assessment of backflashover susceptibility. Applied to a representative 138 kV transmission line in Minas Gerais, Brazil, the framework shows that BFR results are highly sensitive to tower-footing impedance and attachment model selection. The SB-LPM yields systematically different predictions compared to traditional electrogeometric models, yielding approximately 10% lower BFR estimates at 20 Ω grounding impedance relative to the widely used Eriksson model. The framework enables comprehensive lightning performance assessment by incorporating geometry-sensitive attachment modeling, realistic current waveform synthesis, and detailed system transient response, providing valuable insights for transmission line insulation coordination studies. Full article

As a zero-carbon energy carrier, hydrogen is playing an increasingly vital role in the decarbonization of maritime transportation. The hydrogen pressure reducing valve (PRV) is a core component of ship-borne hydrogen storage systems, directly influencing the safety, efficiency, and reliability of hydrogen-powered vessels. However, the marine environment—characterized by persistent vibrations, salt spray corrosion, and temperature fluctuations—poses significant challenges to PRV performance, including material degradation, flow instability, and reduced operational lifespan. This review comprehensively summarizes and analyzes recent advances in the study of high-pressure hydrogen PRVs for marine applications, with a focus on transient flow dynamics, turbulence and compressible flow characteristics, multi-stage throttling strategies, and valve core geometric optimization. Through a systematic review of theoretical modeling, numerical simulations, and experimental studies, we identify key bottlenecks such as multi-physics coupling effects under extreme conditions and the lack of marine-adapted validation frameworks. Finally, we conducted a preliminary discussion on future research directions, covering aspects such as the construction of coupled multi-physics field models, the development of marine environment simulation experimental platforms, the research on new materials resistant to vibration and corrosion, and the establishment of a standardized testing system. This review aims to provide fundamental references and technical development ideas for the research and development of high-performance marine hydrogen pressure reducing valves, with the expectation of facilitating the safe and efficient application and promotion of hydrogen-powered shipping technology worldwide. Full article

The global energy transition, characterized by the proliferation of intermittent renewables and the evolution of electricity markets, has positioned virtual power plants (VPPs) as crucial aggregators of distributed energy resources. However, their participation in competitive markets is fraught with multifaceted uncertainties stemming from price volatility, renewable generation intermittency, and unpredictable prosumer behavior, which necessitate sophisticated, risk-averse bidding strategies to ensure financial viability. This review provides a comprehensive analysis of the state-of-the-art in risk-averse bidding for VPPs. It first establishes a resource-centric taxonomy, categorizing VPPs into four primary archetypes: DER-driven, demand response-oriented, electric vehicle-integrated, and multi-energy systems. The paper then delivers a comparative assessment of different optimization techniques—from stochastic programming with conditional value-at-risk and robust optimization to emerging paradigms such as distributionally robust optimization, game theory, and artificial intelligence. It critically evaluates their application contexts and effectiveness in mitigating specific risks across diverse market types. Finally, the review synthesizes these insights to identify persistent challenges—including computational bottlenecks, data privacy, and a lack of standardization—and outlines a forward-looking research agenda. This agenda emphasizes the development of hybrid AI–physical models, interoperability standards, multi-domain risk modeling, and collaborative VPP ecosystems to advance the field towards a resilient and decarbonized energy future. Full article

Gas injection displacement technology plays a critical role in enhancing coalbed methane (CBM) and mine gas extraction efficiency. Numerical simulation is essential for revealing multi-field coupling mechanisms and optimizing process parameters, effectively addressing challenges such as high field test costs and limited laboratory scalability. This study systematically reviews progress in modeling physical fields (e.g., flow and diffusion), focusing on multi-physical field coupling mechanisms and permeability model evolution. It conducts iterative numerical model analysis—from basic flow–diffusion to fully coupled THMC models—compares simulation software (COMSOL shows greater coupling depth and compatibility than COMET3), and characterizes key mechanisms. By systematically reviewing the key advancements in the fields of numerical simulation in recent years (including important achievements such as the Buddenberg–Wilke equation and the improved Palmer–Mansoori model), a decision-making framework was proposed based on these achievements, covering “Multi-physical Field Coupling Equation Selection, Key Parameter Calibration, Permeability Equation Selection, Model Validation and Error Correction” simulation error ≤10% in heterogeneous coal seams. Although general-purpose tools enable high-precision multi-physics coupling, improvements are still needed in modeling flow–diffusion mechanisms, heterogeneity, and chemical field integration. This study provides a systematic methodological reference for the engineering application of gas injection displacement numerical simulation, and the framework constructed hereby can also be extended to shale hydraulic fracturing and other related fields. Full article

Residual oil (RO) in terrigenous reservoirs formed after waterflooding can exceed 60% of the original oil in place; approximately 70% is trapped at the macro-scale in barriers and lenses, whereas about 30% remains at the micro-scale as film and capillary-held oil. This review aims to synthesize current knowledge of RO formation mechanisms, localization methods and chemical recovery technologies. It analyzes laboratory, numerical and field studies published from 1970 to 2025. The physical and technological factors governing RO distribution are systematized, and the effects of heterogeneities of various types, imperfections in pressure-maintenance (waterflood) systems and contrasts in oil–water properties are demonstrated. Instrumental monitoring techniques—vertical seismic profiling (VSP), well logging (WL), hydrodynamic well testing (WT) and geochemical well testing (GWT)—are discussed alongside indirect analytical approaches such as retrospective production-data analysis and neural-network forecasting. Industrial experience from more than 30,000 selective permeability-reduction operations, which have yielded over 50 Mt of additional oil, is consolidated. The advantages of gel systems of different chemistries are evaluated, and the prospects of employing waste products from agro-industrial, metallurgical and petroleum sectors as reagents are considered. The findings indicate that integrating multi-level neural-network techniques with instrumental monitoring and adaptive selection of chemical formulations is crucial for maximizing RO recovery. Full article

Aiming at the problem that obstacle avoidance flexibility and formation integrity are difficult to coexist in multi-robot formation motion, a path-deformation mapping mechanism is proposed, which deeply integrates artificial potential field and affine transformation, and drives formation adaptive adjustment in real time through path information. By using the non-uniform scaling characteristics of the affine transformation, the limitation of traditional conformal transformation is broken through, and the unity of flexibility and integrity is realized. The effectiveness of the algorithm is verified by experiments, which provide a practical solution for cooperative obstacle avoidance of multi-robot systems in complex environments. In order to verify the performance of the algorithm, a numerical simulation is carried out, and an experimental platform composed of seven omnidirectional mobile robots is built for physical verification. The simulation and experimental results show that the formation can complete the obstacle avoidance task in the complex static obstacle environment, and the average formation tracking error is maintained below 0.05 m. Compared with the traditional local obstacle avoidance or formation switching method, this algorithm significantly improves the fluency of the obstacle avoidance process and the integrity of the formation while ensuring a success rate of 100% obstacle avoidance. Full article