最新刊期
卷 59 ， 期 10 ， 2025
- 摘要：Abstract:The motor is the most critical component among the “three electric systems” (motor, battery, and electronic control) of new energy vehicles (NEVs).However, there is currently a lack of systematic and in-depth discussion and classification regarding the types of main drive motors used in modern NEVs and their key technical issues. To address this, this study first investigates and categorizes the types of drive motors for NEVs, identifying four dominant types currently in use: DC motors, AC permanent magnet synchronous motors (PMSMs), reluctance motors, and AC asynchronous induction motors. Furthermore, a comprehensive explanation of the current status and key technologies of these four types of drive motors is provided. The specific mechanical structures of each motor, the automotive manufacturers and vehicle models that employ them, as well as their respective advantages and disadvantages are discussed. This detailed analysis thoroughly presents the design philosophy behind NEV electric drive systems and related technologies. The research results indicate that AC radial-flux PMSMs, axial-flux PMSMs, and AC asynchronous motors exhibit superior comprehensive performance and are likely to dominate as the main types of drive motors for future NEVs. Additionally, the characteristics of 4-pole and 8-pole variable-pole AC asynchronous copper-rotor induction motors are briefly examined, demonstrating their promising application prospects. Finally, through a systematic and in-depth analysis of the development trends of main drive motors, this study clearly concludes that future NEV drive motors should evolve in the following directions: higher supply voltages, increasingly higher rotational speeds, lower noise vibration and harshness (NVH), greater power density, use of high-strength and high-permeability materials, integration of motors with gear reducers and drive controllers, cost-effective and highly reliable motor speed sensing, and highfrequency, high-efficiency drive controllers.关键词：new energy vehicle;AC permanent magnet synchronous motor;high-voltage;high speed;high power density472|48|0更新时间：2025-09-28
- 摘要：Abstract:To address the limited applicability of traditional small language models and the unsatisfactory diagnostic effects caused by the multi-dimensional heterogeneity of state parameters and data loss in power transformers, a multi-agent large language model framework for transformer fault diagnosis is proposed. The framework establishes a collaborative reasoning system with fault cases knowledge graph and three agents. The fault cases knowledge graph constraint mechanism significantly enhances the large language model's understanding of power engineering expertise while effectively mitigating machine hallucination. Three agents simulate expert diagnostic processes by decomposing complex transformer fault diagnosis tasks. Primary diagnostic agents perform preliminary fault identification through feature threshold analysis, expert diagnostic agents conduct uncertainty reasoning on typical fault patterns using probabilistic graphical models, and case analysis agents access a historical fault case database to enable knowledge retrieval and diagnostic result validation. Validation results show that the proposed model achieves excellent performance in diagnosing 100 fault cases, with an accuracy rate of 86%, representing a 33% improvement over the BERT model. The integration of the fault cases knowledge graph enhances the large language model's output in terms of completeness, semantic consistency, and professional depth, with an expert rating average performance increase of 50%.This multi-agent large language model demonstrates superior performance in reducing misjudgment rates compared to monolithic large language models, and can provide technical support for intelligent fault diagnosis and operation and maintenance of power transformers.关键词：power transformer;fault diagnosis;multi-agent;knowledge graph;large language model281|22|0更新时间：2025-09-28
- 摘要：Abstract:To address the challenges of coordinating multiple frequency regulation resources in permanent magnet synchronous（PMS）wind farms and mitigating excessive reactive power fluctuations during frequency regulation，a model predictive control（MPC）-based coordinated predictive control strategy is proposed.First，based on the structural block diagram of the underlying controller in PMS wind farms，a dynamic model of multiple frequency regulation resources is established，elucidating their mechanism for participating in main grid frequency regulation.Then，combined with the power system swing equation，a grid frequency response model is constructed to accurately predict the system's frequency dynamics during active power disturbances.Finally，with the optimization objective of suppressing main grid frequency deviations，the coordinated control of multiple frequency regulation resources is achieved while comprehensively considering the physical safety constraints of each type of regulation resource.Validation using a two-area system demonstrates that，compared to traditional droop control methods，the proposed coordinated predictive control strategy increases the lowest frequency point of the main grid by 0.06Hz and reduces the wind farm's reactive power by 2.4Mvar，confirming its superiority in enhancing main grid frequency stability.This study provides theoretical insights for the comprehensive utilization of multiple frequency regulation resources in renewable energy power stations.关键词：permanent magnet synchronous wind farm;multiple frequency regulation resources;predictive control;coordinated control67|11|0更新时间：2025-09-28
- 摘要：Abstract:To meet the demand for rapid risk assessment in power systems under massive operational scenarios and investigate the role of flexible resources in power-energy balance, this study introduces the concept of flexible operation domain for renewable energy and proposes a construction method that accounts for the system's potential balance risks. By transforming the challenging decision-dependent uncertainty set into a decision-independent uncertainty set, a twolayer robust optimization model that considers potential balance risks is established. The upperlayer model aims to minimize operational costs and balance risks under forecasted scenarios while determining the upper and lower boundaries of the flexible operation domain for renewable energy. The lower-layer model verifies the system's worst-case balance conditions within the boundaries of the flexible operation domain for renewable energy derived from the upper layer. The C&CG algorithm is employed for effective solving. Case study results demonstrate that the proposed method can delineate the balance risk boundaries of the system under the impact of the randomness of new energy. The obtained flexible operation domain covers 99% of potential deviations in most time periods, thereby assisting in quickly identifying risk-free renewable energy operation modes and providing warnings about imbalanced time periods and quantities for risky operation modes. Furthermore, the introduction of energy storage devices can expand the flexible operation domain for renewable energy, effectively enhancing the system's renewable energy accommodation capability and load supply capacity. Storage capacities of 10%, 20%, and 40% increase the flexible operation domain for renewable energy by 1.93%, 7.82%, and 10.44%, respectively.关键词：renewable energy flexible operation region;power and energy balance;balance risks;bi-level robust optimization model64|12|0更新时间：2025-09-28
- 摘要：Abstract:To address the challenges of weak fault features and severe fundamental frequency interference in motor rotor bar breakage, which makes fault feature extraction particularly difficult, an adaptive sparse Fourier transform (ASFT) method is proposed. First, the sparse Fourier transform (SFT) is employed to remove the fundamental frequency component from the original signal, with the sparsity parameter adaptively selected using an improved golden eagle optimizer (IGEO).Subsequently, SFT is reapplied to the fundamental frequency-suppressed signal to accurately extract the rotor bar fault features. Finally, a feature-reconstruction-based extraction method is introduced to mitigate the large fluctuations of fault components under high-load conditions. To validate the effectiveness of ASFT, it is applied to both simulated and experimental signals of rotor bar breakage. The results demonstrate that when conventional methods are significantly affected by the fundamental frequency, ASFT achieves a 100% energy proportion for the extracted fault feature components, effectively resolving the issues of high diagnostic difficulty and strong concealment in rotor bar breakage faults.关键词：rotor broken bars;adaptive fault diagnosis;sparse Fourier transform19|12|0更新时间：2025-09-28
- 摘要：Abstract:To optimize catalyst geometric structures in packed beds and enhance hydrogen production efficiency, the effects of triple-periodic minimal surface (TPMS) structured catalysts on methane steam reforming reactions is investigated. The solid particle method is employed for numerical simulations comparing the flow, heat transfer, and reaction performance among TPMS-structured catalyst particles, conventional through-hole catalyst particles, and spherical catalyst particles. By analyzing reactive catalyst particles and incorporating classical thermal resistance theory, a novel thermal resistance evaluation method is developed to evaluate hydrogen production performance from the perspective of heat transfer and conversion. Results demonstrate that: The proposed thermal resistance evaluation method effectively reflects hydrogen production performance characteristics；the TPMS-structured spherical catalysts reduce flow energy loss by 22.97% compared to conventional spherical structures；in terms of heat transfer performance, they achieve the highest outlet temperature, showing a 4.48K increase over conventional spherical structures while reducing convective heat transfer resistance by 28.68%；regarding reaction performance, they exhibit the maximum hydrogen production rate, which is 49.93% higher than that of conventional spherical structures, along with a 27.45% reduction in chemical reaction thermal resistance；overall, they achieve 28.03% reduction in total thermal resistance. These findings demonstrate the superior efficiency of TPMS structures in methane steam reforming and provide a novel analytical approach for performance evaluation in packed beds.关键词：methane steam reforming;hydrogen production;triply periodic minimal surfaces;catalyst geometry structure;thermal resistance evaluation method31|8|0更新时间：2025-09-28
- 摘要：Abstract:To clarify the effects of hydrogen-blended/full-hydrogen combustion-induced gas pulsation on the convective heat transfer and cooling characteristics of downstream turbine cascades, based on real hydrogen-blended/full-hydrogen combustion pulsation measurement data and transonic wind tunnel test data from a research institute and employing unsteady numerical methods, the influence of gas pulsation frequencies (1, 3, and 5kHz) on the endwall flow and film cooling performance of a turbine cascade under design operating conditions is investigated. The results show that pulsating inflow significantly reduces the endwall film cooling effectiveness, exhibiting non-monotonic frequency dependence. The smallest reduction in film cooling effectiveness (approximately 4.02%) occurs at 3kHz, while the largest reduction (approximately 11.28%) occurs at 5kHz. The fluctuation amplitude of film cooling effectiveness initially decreases and then increases with rising frequency, with the largest fluctuations observed downstream of the film cooling holes and near the cascade throat. The fluctuation frequency of film cooling effectiveness strictly synchronizes with the inlet pulsation frequency, indicating no attenuation of pulsation frequency within the cascade passage. As the pulsation frequency increases, the cavity vortex downstream of the step gradually expands toward the endwall. Under high-frequency (5kHz) pulsation, the intensities of the cavity vortex and horseshoe vortex significantly strengthen, destabilizing the secondary flow structures in the endwall region and leading to degraded film cooling performance and increased fluctuation amplitudes. This study reveals the coupled mechanism of flow and cooling as well as the pulsation characteristics in the endwall region of hydrogen-fueled turbine cascades, providing insights for the design of high-efficiency cooling configurations in endwall region.关键词：hydrogen-fired gas turbine;cascade endwall;pulsated flow;film cooling effectiveness29|13|0更新时间：2025-09-28
- 摘要：Abstract:To address the challenge of rapidly predicting transient thermal stress during the startup of turbomachinery rotors, which is difficult due to high computational costs, a compressor rotor surface temperature field and stress field prediction method based on temporal convolutional network (TCN) is proposed. The finite element method is utilized to compute the temperature field, stress field, and service life of the compressor rotor under cold startup conditions. A TCN model is then employed for temperature field and stress field prediction and life assessment of the rotor, and the results are compared with those obtained from three other neural network models: long short-term memory (LSTM), gated recurrent unit (GRU), and Transformer. Simulation results demonstrate that under cold startup conditions, the TCN model exhibits optimal performance in predicting transient thermal stress of the rotor. Compared to the Transformer, LSTM, and GRU models, the coefficient of determination for thermal stress predictions improves by 0.03%, 0.60%, and 0.36%, respectively, while the coefficient of determination for equivalent stress predictions under combined loading increases by 0.10%, 0.48%, and 0.02%.Moreover, the computational efficiency of the TCN model is significantly improved compared to traditional finite element thermo-mechanical coupled analysis, with a computation time only 0.25% that of the finite element method. This proposed method enhances prediction accuracy and provides technical support for the rapid prediction of transient thermal stresses and life assessment of turbomachinery rotors.关键词：temporal convolutional network;compressor rotor;thermal stress;lifespan assessment27|10|0更新时间：2025-09-28
- 摘要：Abstract:To address the unclear coupling mechanism of flow losses and the lack of optimization direction in supercritical carbon dioxide (SCO2) centripetal turbines, a 150kW SCO2centripetal turbine is concentrated in this paper. Based on entropy generation theory, different boundary condition settings, multiple numerical simulations, and vorticity analysis methods are employed to decompose flow losses, identify loss sources, and analyze loss characteristics. The simulation results indicate that under design conditions, the flow losses in the centripetal turbine occur in the following order, from largest to smallest: leakage losses, stator losses, mixing losses, and rotor losses, accounting for 44.43%, 31.82%, 11.98%, and 11.77% of the total losses, respectively. When deviating from the design conditions, the proportions of leakage losses and stator losses decrease, while the proportion of mixing losses increases, with little change in rotor losses. The primary cause of leakage losses is the relatively high clearance at the inlet tip of the rotor, which leads to significant leakage through the turbine；reducing the blade tip clearance can notably decrease the turbine's entropy generation and leakage losses. Stator losses predominantly occur in the mid-to-late regions of the passage, while rotor losses increase sharply at the mid-section of the rotor. The findings provide data support for the aerodynamic design and profile optimization of 100kW-class SCO2power cycle centripetal turbines.关键词：supercritical carbon dioxide;radial inflow turbine;decomposition of flow losses;entropy generation theory33|13|0更新时间：2025-09-28
- 摘要：Abstract:To address the issues of non-uniform inlet flow and volute tongue gap backflow caused by airflow redirection at the inlet side of multi-blade centrifugal fans and, this study takes the volute of a double-inlet multi-blade centrifugal fan used in integrated stoves as the research object and proposes an optimization method for a curved volute with parameterized design of its flowpassage cross-sections. The stacking line of the curved volute is determined based on the original volute profile and the impeller outer diameter. By constructing a three-arc-shaped flow-passage cross-section profile at each circumferential position of the volute, the axially cut portion of the volute is geometrically reconstructed, and the curved volute configuration is completed along the stacking line. Numerical simulations are conducted to investigate the aerodynamic performance and noise characteristics of the optimized multi-blade centrifugal fan, and a prototype is fabricated considering manufacturing requirements for experimental validation. Under the actual operating conditions of integrated stove applications, experimental measurements are performed to verify the improvement effects of the curved volute on the aerodynamic performance and noise level of the multi-blade centrifugal fan at the working flow rate. The results show that, compared to the original fan, the curved volute fan achieves a noise reduction of 6.4dB and a power reduction of 4.6% at the same working flow rate. Based on numerical analysis of the internal flow field, the curved volute reduces the velocity gradient at the axial airflow interface, suppresses the diffusion of high turbulent kinetic energy regions near the volute outlet and tongue, and weakens the periodic interaction between the outlet airflow and the volute tongue, effectively lowering the aerodynamic noise level of the multi-blade centrifugal fan. This study provides theoretical foundations and practical insights for internal flow control and efficiency-enhancing, noisereducing designs of multi-blade centrifugal fans.关键词：multi-blade centrifugal fan;curved volute;working airflow;parametric design;aerodynamic noise30|11|0更新时间：2025-09-28
- 摘要：Abstract:To address the limited theoretical and quantitative research on steam leakage in soot blowers, this study investigates the leakage characteristics of steam soot blowers based on packing seal structures. An improved flat-plate leakage model is employed to analyze the variation patterns of steam parameters along the leakage path and the unit leakage rate under different operating conditions. The results indicate that under standard conditions, the density, pressure, and temperature of steam along the leakage path decrease by 92%, 92%, and 4%, respectively, with a significant acceleration in the decline near the outlet. Steam temperature and pressure have minimal impact on outlet density. As the blowing steam temperature increases and pressure decreases, the unit leakage rate of the soot blower exhibits a decreasing trend. Under wear conditions, when the wear coefficient is 2, the sealing ring still provides some sealing effect, with a unit leakage rate of 3.49×10-4kg·m-1·s-1.However, when the coefficient exceeds 2, the sealing ring nearly fails entirely, leaving only the packing material functional, and the unit leakage rate increases to 3.91×10-4kg·m-1·s-1.This highlights the critical importance of maintaining the sealing structure during the early stages of wear. By appropriately increasing the blowing steam temperature and reducing pressure, the unit leakage rate can be effectively reduced. This study provides a theoretical basis and practical reference for evaluating and improving the sealing performance of steam soot blowers, offering significant implications for enhancing equipment operational efficiency and safety.关键词：steam soot blower;leakage;sealing structure;wear conditions;optimization strategies20|10|0更新时间：2025-09-28
- 摘要：Abstract:To address the stress concentration issues inmolten salt storage tank walls caused by liquid level variations and temperature fluctuations during operation, structural evaluation and optimization research are conducted under thermo-mechanical coupling effects. First, a thermomechanical couplingmodel of themolten salt storage tank is established using a finite volumefinite element coupledmethod. Multi-physics simulations are employed to analyze the distribution characteristics of the temperature field, stress field, and deformation field in the tank wall under different liquid level conditions. Subsequently, key failure risk areas are identified based on simulation results. Finally, targeted optimization schemes are proposed, and their effectiveness is validated. Simulation results indicate that liquid level changes lead to significant temperature stratification in the tank, with amaximum temperature difference of 8℃ in the tank wall. Under thermo-mechanical coupling effects, the wall stress increases with rising liquid levels, peaking at 105MPa, primarily concentrated in the first and second layers of the tank wall. The dome area exhibits themost pronounced deformation due tominimal thermal expansion constraints, with amaximum deformation of 0.16m, while other regions of the tank wall require thermal deformation freedom to avoid additional stresses. By locally arranging stiffeners to optimize the structural design, the stress at critical points is reduced by 38%, effectively improving themechanical performance of the structure. This research provides theoretical support for the design optimization and safe operation ofmolten salt storage tanks.关键词：molten salt storage tank;thermo-mechanical coupling;thermal deformation;stiffener arrangement29|11|0更新时间：2025-09-28
- 摘要：Abstract:To address the question of whether hydrogen addition chemically promotes or inhibits soot formation, a two-dimensional numerical simulation is conducted to systematically investigate pure ethylene, nitrogen-added, and hydrogen-doped co-flow diffusion flames. The effects of adding 30% hydrogen/nitrogen by volume on flame temperature, soot volume fraction, particle growth, nucleation, precursor evolution, and oxidation processes are analyzed. The variations in key characteristic parameters are obtained, and the mechanism of the chemical promotion effect of low-proportion hydrogen addition on soot formation is elucidated. The simulation results show that compared to nitrogen-diluted flames, the addition of 30% hydrogen slightly promotes soot formation, with the peak soot volume fraction increasing from 4.37×10-6to 4.52×10-6, while the influence of hydrogen-induced temperature field changes on soot formation is minor. The chemical promotion effect of hydrogen addition is primarily achieved by accelerating the formation of polycyclic aromatic hydrocarbons (PAHs) and particle nucleation rates, thereby enhancing particle mass growth through PAHs deposition rather than dehydrogenation-acetylene reactions. Although hydrogen addition promotes particle oxidation by simultaneously increasing OH and O2oxidation rates, its chemical promotion of particle growth outweighs the oxidation enhancement. This study provides theoretical insights for controlling soot particles in hydrogen-doped combustion.关键词：hydrogen/nitrogen;ethylene;co-flow diffusion flame;soot;chemical promotion30|7|0更新时间：2025-09-28
- 摘要：Abstract:To investigate the stability andmass transfer performance of the three-phase interface in the cathode catalytic layer of proton exchangemembrane fuel cells (PEMFCs) using nonpreciousmetal Fe-N-C catalysts, a series of Fe-N-C catalysts are synthesized via pyrolysis at temperatures ranging from 800—1200 ℃, using zeolitic imidazolate framework (ZIF-8) as a precursor with the introduction of graphene oxide. The optimal catalyst for oxygen reduction reaction activity is selected through electrochemical testing andmorphological characterization, and its representative active site, Fe3N, is analyzed. Molecular dynamics simulations are employed to explore themass transfer processes within the three-phase interface of the cathode catalytic layer containing Fe3N, as well as the wettability of the active site surface, which determine the structural stability, and its adhesion to the ionomer. The results show that the Fe-N-C-1000 catalyst obtained at 1000℃ exhibits the best catalytic activity, with a limiting current density of 5.18mA/cm2, a half-wave potential of 0.86V, and a 4-electron reaction pathway. Fe-N-C-1000 inherits the dodecahedral structure of ZIF-8 and contains a large number ofmesopores with an average pore size of approximately 3.9nm, with Fe3N as the representative active site. At 298K and 358K, the Fe3N active site surface demonstrates excellent hydrophilicity, and its adhesion to Nafion ionomer is stronger than that of Pt, regardless of whether the surface is flat or nanoparticlestructured. Within the three-phase interface containing Fe3N, the diffusion coefficients of H3O+and O2are significantly higher than those in the Pt/C three-phase interface. Additionally, Fe3N nanoparticles exhibit stronger adsorption capabilities for H3O+and O2.This study provides valuable insights for the screening andmolecular-scale performance evaluation of Fe-N-C catalyst active sites.关键词：proton exchange membrane fuel cells;Fe-N-C catalyst;oxygen reduction reaction;molecular dynamics simulation;three-phase interface;adhesivity;diffusion coefficient24|6|0更新时间：2025-09-28
- 摘要：Abstract:To evaluate the resolution capability and applicability of different turbulence models in analyzing the transient evolution characteristics of cloud cavitation in nozzles, this study employs numerical simulations combined with a cavitation multiphase flow model to compare the performance of the shear stress transport (SST) k-ωReynolds-averaged Navier-Stokes (RANS) model, large eddy simulation (LES), delayed detached-eddy simulation (DDES), and very large eddy simulation (VLES).The results show that the SSTk-ωmodel offers high computational efficiency but fails to accurately capture transient behaviors such as cloud cavitation shedding and collapse due to its time-averaged treatment. In contrast, the LES model precisely resolves small-scale vortex structures and transient pressure fluctuations, reproducing the full-cycle evolution of cloud cavitation, with simulation results closely matching visual experimental data. However, its computational cost exceeds that of the SSTk-ωmodel by more than four times. DDES, due to the employment of RANS in near-wall and low-vorticity regions, exhibits limited accuracy in predicting shedding processes, re-entrant jets and high-frequency pressure responses. VLES, based on a scale-adaptive dynamic hybridRANS-LESapproach, significantly reduces computational costs, approximately 30% less than LES, while maintaining high resolution of shedding details. Furthermore, Fourier transform analysis based on pressure fluctuations reveals that VLES predicts the dominant shedding frequency of cloud cavitation with less than 5% deviation from experimental data, validating its accuracy and efficiency in cloud cavitation modeling and demonstrating its potential for engineering applications.关键词：turbulence model;nozzle;cloud cavitation;shedding;resolving capability22|8|0更新时间：2025-09-28
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Disturbance Compensation and Decoupling Optimal Backstepping Control Strategy for Hypersonic Vehicle
摘要：Abstract:To address the uncertainties associated with hypersonic vehicles, a novel composite control strategy that integrates optimal control, backstepping control, and an extreme learning machine (ELM) disturbance observer is proposed. To reduce the complexity of the controller design, the longitudinal model is decoupled into a velocity subsystem and an altitude subsystem. For the velocity subsystem, a linearized model is constructed through error state transformation, and an optimal feedback control law is designed based on a quadratic performance index. The altitude subsystem adopts a backstepping control framework, where optimal quadratic regulation theory is introduced in the first virtual control step to enhance dynamic tracking performance. Multi-source disturbances are treated as composite additive disturbances and estimated using an ELM neural network, with the estimated values incorporated into the control law for disturbance compensation to improve system robustness. The semi-global uniform ultimate boundedness of the closed-loop system is proven via Lyapunov stability theory. Simulation results demonstrate that, compared to traditional backstepping control, the proposed method reduces response times by 99.61% for velocity and 4.60% for altitude, while improving tracking accuracy for velocity and altitude by 99.91% and 85.64%, respectively. When compared to an extended state observer (ESO)-based control scheme, the ELM disturbance observer exhibits significant advantages in velocity and altitude tracking accuracy, achieving improvements of 83.3% and 71.3%, respectively. Furthermore, it outperforms fixed-time disturbance observers with an 88.76% increase in velocity tracking accuracy and a 36.14% improvement in altitude tracking accuracy. These results validate the superiority of the proposed method in terms of dynamic response performance and disturbance rejection capability.关键词：hypersonic vehicle;extreme learning machine;neural network;backstepping control;optimal control25|8|0更新时间：2025-09-28 - 摘要：Abstract:To meet the urgent demand of next-generation electronic tuning devices for high dielectric tunability, superior temperature stability, and strong breakdown performance, barium strontium titanate (BST) is selected as the matrix and co-doped with La and Mn to form (Ba0.675Sr0.325) 1-xLaxTi1-xMnxO3, where the La and Mn contents are 0.25%, 0.5%, 0.75%, and 1.0%, aiming to achieve both high dielectric tunability and low dielectric loss. By employing the two-step sintering method and optimizing sintering parameters, ceramic samples with more uniform grain size distribution and denser microstructure are obtained. Experimental results show that compared with the conventional solid-phase sintering method, BST ceramics prepared via the two-step sintering method exhibit smaller and more uniform grain sizes as well as higher density. In terms of dielectric tuning performance, when the La and Mn contents are both 0.5%, the BST ceramics prepared by the two-step sintering method demonstrate a dielectric tunability of 72.7%, a dielectric loss of 0.0011, and a calculated figure of merit (FOM) reaching a maximum of 661, nearly 40% higher than the 473 achieved by the solid-phase sintering method. The relative standard deviation of dielectric tunability in the temperature range of-10 ℃ to 60 ℃ is 0.29, approximately 20% lower than that of the solid-phase sintering method. Additionally, the breakdown field strength increases from 118.06kV/cm to 140.19kV/cm, an improvement of 18.7%.The experimental results indicate that the two-step sintering method synergistically enhances both the FOM and breakdown field strength of BST ceramics, meeting the new requirements of temperature stability for next-generation electronic tuning devices and further advancing the potential of BST materials in the electronic tuning device field.关键词：barium strontium titanate ceramics;two-step sintering method;figure of merit;breakdown strength;temperature stability18|7|0更新时间：2025-09-28
- 摘要：Abstract:To address the performance degradation of heat-resistant steel caused by hydrogen embrittlement in high-temperature and high-pressure hydrogen environments, this study proposes an atomically stabilized doped Cr2O3composite anti-hydrogen embrittlement coating and elucidates the mechanism underlying its enhanced hydrogen embrittlement resistance and hydrogen barrier effect using first-principles calculations. First, a Cr2O3bulk structure is constructed and a Cr atom is then substituted with Al, Mn, Ni, Ti, Y, or Si atoms. Subsequently, the effects of different atomic dopants on the adsorption energy of H atoms at the surface and subsurface, the electronic properties of H atom adsorption on the surface, and the diffusion behavior of H atoms on the hydrogen barrier performance of Cr2O3films are investigated. Simulation results demonstrate that doping with Al, Ti, and Si atoms increases the adsorption energy of H atoms, making surface adsorption more difficult. The electronegativity of Al, Mn, Ti, and Y dopants is lower than that of Cr, weakening the adsorption energy of H atoms at the surface A-site. Additionally, doping with Al, Mn, Ti, and Si atoms increases the diffusion energy barrier for H atoms migrating from the surface to the subsurface, thereby hindering hydrogen penetration. This study reveals the mechanism by which dopant atoms enhance the hydrogen embrittlement resistance of Cr2O3coatings and proposes an atomic doping strategy to improve hydrogen barrier performance.关键词：first principles;hydrogen barrier;composite coating;atomic doping;hydrogen embrittlement resistance13|7|0更新时间：2025-09-28
- 摘要：Abstract:To address the issue of lithium targetmelting caused by rapid temperature rise under high-power beam irradiation in accelerator neutron sources, a beam spot homogenization scheme combining “beam expansion+scanning”is proposed. First, the software MATLAB is used to simulate the distribution of particles and temperature field on the target under different scanningmodes. Then, the software FLUENT is employed to analyze the impact of different initial beam spot widths on the lithium target's temperature field. Finally, the variations in the lithium target's temperature field under different scanning frequencies are investigated. The simulation results indicate that the “beam expansion+scanning”homogenizationmethod effectively reduces the peak surface temperature of the target during proton bombardment. The sawtooth wavemode achieves themost uniform particle distribution on the target, compared to sine and triangular wavemodes, reducing the peak surface temperature by 8% and 2%, respectively. Smaller initial beam spot widths and higher scanning frequencies both contribute to lowering the peak surface temperature of the lithium target under high-power beam irradiation. The optimal scanning strategy involves using a sawtooth wavemode with a scanning frequency of 300Hz and an initial rectangular beam spot width of 30mm. This study provides valuable insights for the design of lithium targets in accelerator neutron sources.关键词：accelerator neutron source;lithium target;temperature field;beam spot;scanning mode30|6|0更新时间：2025-09-28
- 摘要：Abstract:To address the issue of insufficient adaptability of existing methods in remaining useful life (RUL) prediction for multi-degradation feature equipment, where static correlation models or potential assumptions about time-varying correlation forms lead to poor performance under complex operating conditions, a time-varying Copula-based RUL prediction method is proposed. First, nonlinear Wiener processes are employed to establish models for individual degradation features, while time-varying Copula functions are introduced to capture dynamic correlations among multiple degradation models. Second, parameter identification for both the nonlinear Wiener processes and the time-varying Copula functions is achieved via Bayesian Markov chain Monte Carlo Metropolis-Hastings and maximum likelihood estimation. Finally, the optimal time-varying Copula form is selected using the Akaike information criterion, and the joint distribution of predicted RUL is derived by integrating marginal distributions. Verification is performed using numerical simulation data and actual data from a blast furnace wall. Experimental results indicate that the proposed method reduces the mean square error of RUL predictions by 8.62% compared to independent modeling of three degradation characteristics, 5.57% over static Copula function, and 17.85% against dynamic Bayesian network methods. The proposed method can accurately characterizes the impact of time-varying degradation correlations of multiple degenerative features on RUL prediction, offering a more effective solution for predicting the remaining useful life of multi-degradation feature equipment.关键词：remaining useful life;degradation processes;time-varying correlation;time-varying Copula function59|11|0更新时间：2025-09-28
- 摘要：Abstract:To address the limitations of traditional recommendation methods that rely on sparse user-item interaction data—which struggle to deeply mine the semantic logic behind user preferences and their dynamic temporal evolution—as well as the constraints of directly applying large language models (LLMs) in recommendation systems due to their lack of structured interaction modeling and temporal sensitivity, a large language model-augmented time-aware recommendation (LLATR) algorithm is proposed. This algorithm aims to integrate semantic comprehension capabilities with temporal modeling of user interests to enhance recommendation accuracy and system personalization. The method designs a collaborative feature extraction network and a time feature modeling network, and combines the semantic scoring vectors generated by LLMs. Through a contrastive learning mechanism, it achieves unified modeling of multimodal information, thereby constructing a dynamically adaptive recommendation framework. Experiments are conducted on two datasets: MovieLens-100K andKaggle-Movie. The results demonstrate that LLATR improves root mean square error (RMSE) and mean absolute error (MAE) by 2%—5%compared to existing mainstream models. Further analysis reveals that LLMs can supplement deep semantic information beyond collaborative features, enhance the recommendation system's adaptability to cold-start users, sparse data, and complex behavioral contexts, and effectively model the nonlinear evolution trends of user interests over time.关键词：large language modeling;recommender systems;rating prediction;time-attention recommender59|12|0更新时间：2025-09-28
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