作者机构：
[Liu, Peng; Wu, Gang; Feng, Guoda; Liu, Zhiqiang] Changsha Univ Sci & Technol, Coll Automot & Mech Engn, Changsha 410114, Peoples R China.;[Zhao, Xiaohuan] Jinan Univ, Int Energy Coll, Energy & Elect Res Ctr, Zhuhai Campus, Zhuhai 519070, Peoples R China.;[Zhao, Xiaohuan] Jinan Univ, Sch Mech & Construct Engn, MOE Key Lab Disaster & Control Engn, Guangzhou 510632, Peoples R China.;[Zhao, Xiaohuan] Jinan Univ, Minist Educ, Sch Mech & Construct Engn, Key Lab Disaster & Control Engn, Guangzhou 510632, Peoples R China.
通讯机构：
[Zhao, XH ] J;Jinan Univ, Int Energy Coll, Energy & Elect Res Ctr, Zhuhai Campus, Zhuhai 519070, Peoples R China.
关键词：
CO oxidation;Oxygen vacancy;DFT plus U;Catalysts;Doped CeO2
摘要：
Catalyst addition can improve system after treatment efficiency of pollutants purification. In this study, the performance of (Mn, Hf) co-doped Ce-based catalysts has been investigated in oxidation to mitigate CO emission of engines. A series of Ce-Mn-Hf-Ox with different metal ratios (Ce: Mn: Hf = 8:1:1,7:2:1,7:1:2,6:1:3,6:2:2 and 6:3:1) catalysts were prepared. DFT (density functional theory) calculations were carried out to investigate the mechanism of applied surface catalytic reaction. XRD (X-ray Diffraction) analysis and SEM (Scanning Electron Microscope) revealed Mn and Hf doping increased the catalysts surface area contact with the CO gas with the catalytic performance improvement. XPS (X-ray Photoelectron Spectra), H2-TPR (Temperature-Programmed Reduction) and DFT calculations manifested the Mn and Hf doping would promote the formation of oxygen vacancy to enhance the catalytic performance for CO oxidation. The thermal stability of the catalysts increased with Hf content increasement. Ce6Mn3Hf1 had the highest catalytic activity with the favorable thermal stability according to the temperature-programmed oxidation of CO experiment. T10, T50 and T90 of CO oxidation were 156, 188 and 198 °C, which lost 4.82 % mass at 500°C and 6.18 % mass at 900 °C. Ce6Mn1Hf3Ox displayed the best thermal stability according to TG with the lowest catalytic activity.
Catalyst addition can improve system after treatment efficiency of pollutants purification. In this study, the performance of (Mn, Hf) co-doped Ce-based catalysts has been investigated in oxidation to mitigate CO emission of engines. A series of Ce-Mn-Hf-Ox with different metal ratios (Ce: Mn: Hf = 8:1:1,7:2:1,7:1:2,6:1:3,6:2:2 and 6:3:1) catalysts were prepared. DFT (density functional theory) calculations were carried out to investigate the mechanism of applied surface catalytic reaction. XRD (X-ray Diffraction) analysis and SEM (Scanning Electron Microscope) revealed Mn and Hf doping increased the catalysts surface area contact with the CO gas with the catalytic performance improvement. XPS (X-ray Photoelectron Spectra), H2-TPR (Temperature-Programmed Reduction) and DFT calculations manifested the Mn and Hf doping would promote the formation of oxygen vacancy to enhance the catalytic performance for CO oxidation. The thermal stability of the catalysts increased with Hf content increasement. Ce6Mn3Hf1 had the highest catalytic activity with the favorable thermal stability according to the temperature-programmed oxidation of CO experiment. T10, T50 and T90 of CO oxidation were 156, 188 and 198 °C, which lost 4.82 % mass at 500°C and 6.18 % mass at 900 °C. Ce6Mn1Hf3Ox displayed the best thermal stability according to TG with the lowest catalytic activity.
作者机构：
[Long, Chengyun; Long, CY] South China Univ Technol, Shien Ming Wu Sch Intelligent Engn, Guangzhou 511442, Peoples R China.;[Cai, Zizheng; Zhao, Bing; Zhou, Weichao; He, Daji] Changsha Univ Sci & Technol, Sch Civil Engn, Dept Mech, Changsha 410114, Peoples R China.
通讯机构：
[Long, CY ] S;[Zhao, B ] C;South China Univ Technol, Shien Ming Wu Sch Intelligent Engn, Guangzhou 511442, Peoples R China.;Changsha Univ Sci & Technol, Sch Civil Engn, Dept Mech, Changsha 410114, Peoples R China.
摘要：
Accurate assessment of the thermal buckling behavior of microdevices is critical for the safe and secure operation of MEMS. However, the coupling of shearing and size effects on the thermal buckling of microbeams remains elusive and needs to be clarified. Here, we propose a theoretical model for the thermal buckling of microbeams that considers both the shearing and size effects, based on the modified gradient elasticity theory combined with the Timoshenko beam model. The explicit analytical forms of the deflection, the bending angle, the shearing angle and the critical buckling temperature rise are presented. The results show that the bending angle increases with the length/thickness ratio while the shearing angle decreases. It is confirmed that the shearing effect cannot be ignored in the thermal buckling of the doubly clamped microbeams with low aspect ratio. The size effect is captured in the thermal buckling of microbeams, which shows an increase in thermoelastic strength with the size reduction. The coupling effect on thermal buckling shows a weakening of the shearing effect by the size effect as the microbeam size decreases. This work could provide a theoretical reference for the design and monitoring of microdevices operating in high temperature environments.
期刊：
Journal of Alloys and Compounds,2025年:182583 ISSN：0925-8388
通讯作者：
Y.C. Lin
作者机构：
School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China;State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Changsha 410083, China;Rongcheng Huadong Metal-forming Machinery Co. LTD, Rongcheng 264300, China;[Xiao-Dong Zhan] Hunan Xiangtou Goldsky Titanium Industry Technology Co. Ltd, Changde, 410007, China;[Xiao-Ming Chen] College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
通讯机构：
[Y.C. Lin] S;School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China<&wdkj&>State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Changsha 410083, China<&wdkj&>Rongcheng Huadong Metal-forming Machinery Co. LTD, Rongcheng 264300, China
摘要：
The microstructure characteristics and deformation mechanisms of a near-beta Ti-55511 alloy during thermal deformation at 860 °C and 830 °C are investigated. The results reveal that dynamic recovery (DRV) and extended continuous dynamic recrystallization (CDRX) are the primary mechanisms driving microstructure development in β matrix. At 830 °C, when the strain rate ranges from 0.001 to 1 s -1 at tenfold intervals, the grain size decreases from 480 μm to 7.26, 5.18, 4.05, and 3.79 μm, respectively, representing a decrease of an order of magnitude compared to that observed at 860 °C. The refining mechanisms are attributed to the fencing effect of α phase. The β matrix is partitioned into individual cells by lamellar α phases. The presence of phase boundaries (PBs) and the gradually deviating Burgers orientation relationship (BOR) during thermal compression significantly restrict dislocation slip, facilitating the accumulation and interaction of dislocations. Consequently, β-subgrains and dynamically recrystallized (DRXed) grains progressively form near α lamellae. In contrast to the alloy deformed at 860 °C, the increased fraction of α-lamellae at 830 °C accelerates the development of subgrains and their rotation into DRXed grains. In addition, the dynamic globularization and dynamic phase transformation processes in α plates, along with the CDRX behavior in β matrix, result in pronounced flow softening at 830 °C. This study enhances the understanding of microstructure development and provides further insight into grain refinement in β matrix with lamellar α phases.
The microstructure characteristics and deformation mechanisms of a near-beta Ti-55511 alloy during thermal deformation at 860 °C and 830 °C are investigated. The results reveal that dynamic recovery (DRV) and extended continuous dynamic recrystallization (CDRX) are the primary mechanisms driving microstructure development in β matrix. At 830 °C, when the strain rate ranges from 0.001 to 1 s -1 at tenfold intervals, the grain size decreases from 480 μm to 7.26, 5.18, 4.05, and 3.79 μm, respectively, representing a decrease of an order of magnitude compared to that observed at 860 °C. The refining mechanisms are attributed to the fencing effect of α phase. The β matrix is partitioned into individual cells by lamellar α phases. The presence of phase boundaries (PBs) and the gradually deviating Burgers orientation relationship (BOR) during thermal compression significantly restrict dislocation slip, facilitating the accumulation and interaction of dislocations. Consequently, β-subgrains and dynamically recrystallized (DRXed) grains progressively form near α lamellae. In contrast to the alloy deformed at 860 °C, the increased fraction of α-lamellae at 830 °C accelerates the development of subgrains and their rotation into DRXed grains. In addition, the dynamic globularization and dynamic phase transformation processes in α plates, along with the CDRX behavior in β matrix, result in pronounced flow softening at 830 °C. This study enhances the understanding of microstructure development and provides further insight into grain refinement in β matrix with lamellar α phases.
作者机构：
[Dongying Dong; Kun Chen; Linjun Zeng] College of Energy and Power Engineering, Changsha University of Science & Technology, Changsha, 410114, China;[Jianing Zhang; Zhoucheng Wu] International College of Engineering, Changsha University of Science & Technology, Changsha, 410114, China;[Xu Zhang] College of Automotive and Mechanical Engineering, Changsha University of Science & Technology, Changsha, 410114, China;[Junjia Cui] State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, 410082, China
通讯机构：
[Linjun Zeng] C;College of Energy and Power Engineering, Changsha University of Science & Technology, Changsha, 410114, China
摘要：
TC4 based composites were facing an urgent need to enhance physical performance. In this work, electromagnetic powder compaction (EMPC) technology was used to prepare carbon nanotubes reinforced TC4 based (CNTs/TC4) composites. The micro morphology and properties of the sintered bodies were studied through scanning/transmission electron microscopy (SEM/TEM) and a universal material testing machine at different sintering temperatures. Results showed that there was a significant turning point at 1100 °C, with a relative density of 98.01%. The relationship between the relative length and density of sintered bodies was established through Gaussian fitting. The CNTs partially reacted with the TC4 matrix after 700 °C, generating equiaxed TiC particles. The compressive strength and strain reached the maximum values at 1300 °C and 600 °C, respectively, with values of 1884.64 MPa and 0.2336. The enhancement factors for compressive strength were only alloying and TiC particles at 1100 °C. There was not much difference in the fusion effect of particles at 1100 °C and 1300 °C. From the above analysis, it can be concluded that the CNTs/TC4 composites prepared by EMPC had relatively good comprehensive mechanical properties when sintered at 1100 °C.
TC4 based composites were facing an urgent need to enhance physical performance. In this work, electromagnetic powder compaction (EMPC) technology was used to prepare carbon nanotubes reinforced TC4 based (CNTs/TC4) composites. The micro morphology and properties of the sintered bodies were studied through scanning/transmission electron microscopy (SEM/TEM) and a universal material testing machine at different sintering temperatures. Results showed that there was a significant turning point at 1100 °C, with a relative density of 98.01%. The relationship between the relative length and density of sintered bodies was established through Gaussian fitting. The CNTs partially reacted with the TC4 matrix after 700 °C, generating equiaxed TiC particles. The compressive strength and strain reached the maximum values at 1300 °C and 600 °C, respectively, with values of 1884.64 MPa and 0.2336. The enhancement factors for compressive strength were only alloying and TiC particles at 1100 °C. There was not much difference in the fusion effect of particles at 1100 °C and 1300 °C. From the above analysis, it can be concluded that the CNTs/TC4 composites prepared by EMPC had relatively good comprehensive mechanical properties when sintered at 1100 °C.
摘要：
The coating thickness of fuel particles is a critical parameter for ensuring the safe operation of high-temperature gas-cooled reactors. However, existing detection technologies still face limitations in measurement accuracy, efficiency, and automation. Notably, accurate thickness measurement relies on the precise identification of anomalous particles, which is hindered by several key challenges. First, incomplete particles in edge regions introduce significant interference. Second, some anomalies exhibit weak morphological features, making them difficult to detect. To address these issues, this study proposes an innovative focal attention-based large convolutional kernel network detection framework comprising three core modules. First, a Vision Transformer backbone incorporating a Large Selective Kernel Module dynamically adapts multi-scale receptive fields to enable coordinated global and local feature perception. Second, the Multi-Scale Feature Fusion Module establishes cross-layer feature interactions to enhance responses to subtle anomalies. Third, the Focal Attention Module employs a dynamic convolutional attention mechanism to strengthen the saliency representation of critical regions. Experimental results demonstrate the effectiveness of the proposed method, reducing the false detection rate and miss detection rate of anomaly detection to 1.96% and 1.9%, respectively.
摘要：
Stress-constrained topology optimization under geometrical nonlinear conditions is still an open topic as it often encounter difficulties such as mesh distortion, inaccurate stress evaluation and low computational efficiency. For this purpose, this paper develops a novel parallel-computing based topology optimization methodology for geometrically nonlinear continuum structures with stress constraints. To alleviate the mesh distortions in the low-density regions, a smooth material interpolation scheme from with different penalization for the elastic and nonlinear stiffness is proposed. Moreover, a new hybrid stress finite element formulation is included into the geometrically nonlinear topology optimization to capture a more accurate stress distribution that is less sensitive to mesh distortions. Then, to improve the computational efficiency of geometrically nonlinear and sensitivity analysis, a parallel computing framework based on the assembly free iterative solution is established. Meanwhile, an efficient sparse matrix-vector multiplication strategy, which is applicable to solve the geometrically nonlinear problems, is proposed to exploit the computing power of GPU effectively. Finally, several numerical examples are given to illustrate the efficiency and feasibility of the proposed method.
Stress-constrained topology optimization under geometrical nonlinear conditions is still an open topic as it often encounter difficulties such as mesh distortion, inaccurate stress evaluation and low computational efficiency. For this purpose, this paper develops a novel parallel-computing based topology optimization methodology for geometrically nonlinear continuum structures with stress constraints. To alleviate the mesh distortions in the low-density regions, a smooth material interpolation scheme from with different penalization for the elastic and nonlinear stiffness is proposed. Moreover, a new hybrid stress finite element formulation is included into the geometrically nonlinear topology optimization to capture a more accurate stress distribution that is less sensitive to mesh distortions. Then, to improve the computational efficiency of geometrically nonlinear and sensitivity analysis, a parallel computing framework based on the assembly free iterative solution is established. Meanwhile, an efficient sparse matrix-vector multiplication strategy, which is applicable to solve the geometrically nonlinear problems, is proposed to exploit the computing power of GPU effectively. Finally, several numerical examples are given to illustrate the efficiency and feasibility of the proposed method.
通讯机构：
[Peng, Y ] C;Cent South Univ, Sch Traff & Transportat Engn, Minist Educ, Key Lab Traff Safety Track, Changsha 410000, Peoples R China.
关键词：
Hazard perception;Powered two-wheeler (PTW);Visual Characteristics;Collision scenario;Driving behavior;Eye movement
摘要：
Understanding drivers’ hazard perception levels and visual behavior in conflict scenarios is crucial for improving traffic safety and advancing intelligent driving systems, especially given the growing complexity of traffic conditions and the rapid evolution of intelligent driving technologies. This study examines typical near-collision scenarios involving vehicles and powered two-wheelers, focusing on the effects of collision scenarios, driving states, and risk conditions on drivers’ hazard perception and visual characteristics. Using quantile regression and generalized linear mixed models, the study quantitatively assesses how these factors influence hazard perception and visual behavior, uncovering the visual response mechanisms underlying hazard perception. The results reveal that different vehicle-to-powered two-wheeler collision scenarios significantly affect drivers’ hazard perception and visual behavior. Drivers exhibited higher hazard perception levels and collision avoidance success rates in “Crossing from Right” and “Cut-in from Right” scenarios, whereas lower hazard perception abilities were observed in “Crossing from Left” and “Oncoming” scenarios. Fatigue was shown to severely impair drivers’ alertness and visual search abilities, resulting in diminished hazard perception levels. Under high-risk conditions, while drivers exhibited reduced collision avoidance success rates, their heightened attention and vigilance toward powered two-wheeler enhanced hazard perception. Besides, the study also highlights a strong correlation between visual characteristics and drivers’ hazard perception. These findings are significant for understanding the mechanisms underlying drivers’ hazard perception in intersection scenarios and may provide a scientific basis for future developments in human–machine collaborative monitoring and intelligent traffic safety strategies.
Understanding drivers’ hazard perception levels and visual behavior in conflict scenarios is crucial for improving traffic safety and advancing intelligent driving systems, especially given the growing complexity of traffic conditions and the rapid evolution of intelligent driving technologies. This study examines typical near-collision scenarios involving vehicles and powered two-wheelers, focusing on the effects of collision scenarios, driving states, and risk conditions on drivers’ hazard perception and visual characteristics. Using quantile regression and generalized linear mixed models, the study quantitatively assesses how these factors influence hazard perception and visual behavior, uncovering the visual response mechanisms underlying hazard perception. The results reveal that different vehicle-to-powered two-wheeler collision scenarios significantly affect drivers’ hazard perception and visual behavior. Drivers exhibited higher hazard perception levels and collision avoidance success rates in “Crossing from Right” and “Cut-in from Right” scenarios, whereas lower hazard perception abilities were observed in “Crossing from Left” and “Oncoming” scenarios. Fatigue was shown to severely impair drivers’ alertness and visual search abilities, resulting in diminished hazard perception levels. Under high-risk conditions, while drivers exhibited reduced collision avoidance success rates, their heightened attention and vigilance toward powered two-wheeler enhanced hazard perception. Besides, the study also highlights a strong correlation between visual characteristics and drivers’ hazard perception. These findings are significant for understanding the mechanisms underlying drivers’ hazard perception in intersection scenarios and may provide a scientific basis for future developments in human–machine collaborative monitoring and intelligent traffic safety strategies.
摘要：
Proper spacing of rebar mesh is essential for structural integrity and safety, but measuring the spacing performance in three-dimensional (3D) space can be complicated. Existing spacing verification either relies on well-annotated data or encounters challenges when dealing with obscured point clouds. To address these challenges, we propose a novel approach using a projection clustering algorithm. Initially, we project the 3D point cloud onto a frontal view and perform density peak clustering in two directions, enabling accurate recognition of vertical and horizontal boundaries. Then, we iteratively select the centerline of each rebar based on clustering center points, maximizing internal points. Evaluation using the Dimension Quality Assessment System showed that our method achieves 94.5% accuracy in estimating rebar spacing. Compared with classical methods, our approach significantly improves spacing measurement.
作者机构：
[Yijian Duan; Liwen Meng; Yanmei Meng; Yuan Liang; Jiachun Wu] College of Mechanical Engineering, Guangxi University, Naning, Guangxi, China;[Jihong Zhu] Department of Precision Instrument, Tsinghua University, Beijing, China;[Jinlai Zhang] College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan, China
摘要：
Adversarial patches represent a critical form of physical adversarial attacks, posing significant risks to the security of neural network-based object detection systems. Previous research on adversarial patches has predominantly focused on pedestrian detection, facial recognition, and vehicle detection, with limited attention to the detection of positive and negative obstacles on unstructured roads. Moreover, prior studies typically optimize perturbation information while fixing parameters such as the patch’s position and rotation angle, or manipulate parameters such as position and rotation angle while fixing the perturbation information to generate adversarial patches. In this context, we propose a PRP multi-adversarial patch attack method based on a simulated annealing improved differential evolution algorithm (SADE-PRP), designed to deceive unstructured positive and negative obstacle detection systems. Firstly, We propose a PRP-guided multi-adversarial patch framework for visible light-based positive-negative obstacle detection systems. This framework simultaneously considers three features of the adversarial patch: position, rotation angle and perturbation pixels, as opposed to manually setting these parameters like most previous works. Secondly, we employ more robust based simulated annealing improved differential evolution algorithm (SADE), which effectively improved the robustness, achieving higher attack success rates in black-box attack scenarios. Finally, we constructed a dataset of positive-negative obstacles on unstructured roads. Then, we conducted extensive experiments in both digital and physical environments to demonstrate the superiority of the proposed method.
摘要：
Advanced heating is essential for mitigating temporary losses in battery capacity and peak power at low temperatures, thereby enhancing utilization efficiency and reducing safety risks. Expanding upon our prior research, this paper proposes a safety-reinforced mutual pulse heating (MPH) strategy based on microscopic-state estimation, in which multiplexing converter-based drivers are reused as on-board heating topologies. An adaptive super-twisting sliding mode observer is utilized to capture battery solid-liquid phase Li + concentration, electrode and electrolyte potentials, and side-reaction overpotentials. Then, a microscopic-state constraints-based MPH current prediction method is formulated to delineate the safe operational area of battery micro-states. The MPH current amplitude is updated by an online negative feedback-based optimization controller, while the heating duty ratio is still adjusted using fuzzy feedback mechanisms. Experimental validation of the proposed method is conducted across five critical metrics: heating duration, temperature-rise rate, safety risk, temperature uniformity, and degradation. The method demonstrated its efficacy by elevating the battery temperature from -20 °C to 0 °C within 178.3 s, while keeping the microscopic states within safe thresholds, with a peak temperature gradient of <2 °C. During 800 heating cycles, battery integrity remains intact as evidenced by stable capacity, coulomb efficiency, internal resistance, and differential voltage curves.
Advanced heating is essential for mitigating temporary losses in battery capacity and peak power at low temperatures, thereby enhancing utilization efficiency and reducing safety risks. Expanding upon our prior research, this paper proposes a safety-reinforced mutual pulse heating (MPH) strategy based on microscopic-state estimation, in which multiplexing converter-based drivers are reused as on-board heating topologies. An adaptive super-twisting sliding mode observer is utilized to capture battery solid-liquid phase Li + concentration, electrode and electrolyte potentials, and side-reaction overpotentials. Then, a microscopic-state constraints-based MPH current prediction method is formulated to delineate the safe operational area of battery micro-states. The MPH current amplitude is updated by an online negative feedback-based optimization controller, while the heating duty ratio is still adjusted using fuzzy feedback mechanisms. Experimental validation of the proposed method is conducted across five critical metrics: heating duration, temperature-rise rate, safety risk, temperature uniformity, and degradation. The method demonstrated its efficacy by elevating the battery temperature from -20 °C to 0 °C within 178.3 s, while keeping the microscopic states within safe thresholds, with a peak temperature gradient of <2 °C. During 800 heating cycles, battery integrity remains intact as evidenced by stable capacity, coulomb efficiency, internal resistance, and differential voltage curves.
摘要：
Many materials in practical engineering exhibit completely different mechanical properties under tension and compression, such as reinforced concrete materials and fiber-reinforced polymers, etc. However, the existing structural design methods usually assume that the mechanical responses of material structures under tensile and compressive loads are the same (i.e. Symmetrical tension and compression characteristics). Considering that the loads are deterministic, the obtained design results may not meet the service requirements and could potentially cause catastrophic damage. This paper proposes a topology optimization method for the strut-and-tie composite structure model under uncertain load conditions. First, a composite structural model is constructed using three-phase materials with different tensile and compressive properties. Then, the design domain is discretized using the hybrid stress element, and a criterion for determining the state of the element in tension and compression is developed. Furthermore, the bivariate dimension reduction method and Gaussian integration method are employed to quantify and propagate load uncertainty. Moreover, an additional method for determining the state of the element in tension and compression under multiple load conditions is developed. Finally, the sensitivity of the objective function concerning the design variables is derived for both single and multiple load cases. Several examples are used to verify the effectiveness of this method, and the influence of optimization parameters such as different load uncertainty levels and the ratio of the elastic moduli of the tensile material and the compressive material on the design results is studied in detail.
Many materials in practical engineering exhibit completely different mechanical properties under tension and compression, such as reinforced concrete materials and fiber-reinforced polymers, etc. However, the existing structural design methods usually assume that the mechanical responses of material structures under tensile and compressive loads are the same (i.e. Symmetrical tension and compression characteristics). Considering that the loads are deterministic, the obtained design results may not meet the service requirements and could potentially cause catastrophic damage. This paper proposes a topology optimization method for the strut-and-tie composite structure model under uncertain load conditions. First, a composite structural model is constructed using three-phase materials with different tensile and compressive properties. Then, the design domain is discretized using the hybrid stress element, and a criterion for determining the state of the element in tension and compression is developed. Furthermore, the bivariate dimension reduction method and Gaussian integration method are employed to quantify and propagate load uncertainty. Moreover, an additional method for determining the state of the element in tension and compression under multiple load conditions is developed. Finally, the sensitivity of the objective function concerning the design variables is derived for both single and multiple load cases. Several examples are used to verify the effectiveness of this method, and the influence of optimization parameters such as different load uncertainty levels and the ratio of the elastic moduli of the tensile material and the compressive material on the design results is studied in detail.
摘要：
In this article, the hyperelastic material of resilient wheels of subway vehicles is taken as the research object, a method system of identifying and calibrating the constitutive parameters of hyperelastic model based on joint experiment-simulation-deep learning is proposed. The theoretical analytical expression of the true stress-strain on stretch of the hyperelastic model Yeoh model under uniaxial loading condition is deduced, the accurate stress-strain curve data are captured by performing the compression experiment of cylindrical specimen of rubber component of urban rail transit system resilient wheel, and the initial values of parameters of the Yeoh hyperelastic model are fitted by the experimental data. The true stress-strain response samples of compression specimens under different Yeoh model parameter conditions were obtained by finite element numerical simulation. The Yeoh model's optimal parameters are obtained by training the data using a deep learning technique under the specified compression test stress-strain circumstances. Finite element numerical simulation is utilized to confirm the parameters' accuracy. The radial stiffness test of the resilient wheel rubber component was carried out, and the examination of the resilient wheel rubber component's stiffness analysis using the model parameters that were optimized. The study's findings indicate that the methodological system of identifying and calibrating the hyperelastic model constitutive parameters of the hyperelastic model proposed in this paper by combined experiment-simulation-deep learning has high prediction accuracy for the hyperelastic constitutive model parameters.
In this article, the hyperelastic material of resilient wheels of subway vehicles is taken as the research object, a method system of identifying and calibrating the constitutive parameters of hyperelastic model based on joint experiment-simulation-deep learning is proposed. The theoretical analytical expression of the true stress-strain on stretch of the hyperelastic model Yeoh model under uniaxial loading condition is deduced, the accurate stress-strain curve data are captured by performing the compression experiment of cylindrical specimen of rubber component of urban rail transit system resilient wheel, and the initial values of parameters of the Yeoh hyperelastic model are fitted by the experimental data. The true stress-strain response samples of compression specimens under different Yeoh model parameter conditions were obtained by finite element numerical simulation. The Yeoh model's optimal parameters are obtained by training the data using a deep learning technique under the specified compression test stress-strain circumstances. Finite element numerical simulation is utilized to confirm the parameters' accuracy. The radial stiffness test of the resilient wheel rubber component was carried out, and the examination of the resilient wheel rubber component's stiffness analysis using the model parameters that were optimized. The study's findings indicate that the methodological system of identifying and calibrating the hyperelastic model constitutive parameters of the hyperelastic model proposed in this paper by combined experiment-simulation-deep learning has high prediction accuracy for the hyperelastic constitutive model parameters.
摘要：
In order to explore the failure behaviors of lithium-ion batteries (LIBs) during thermal runaway (TR) under various oven temperatures, this study conducts comprehensive oven box abuse tests to investigate the impact of oven temperature on the characteristics of multidimensional signals during battery failure processes. The temporal relationships among expansion force, voltage, and temperature are revealed across four distinct stages of the thermal abuse process. The results indicate that within the oven temperature range of 150 °C to 250 °C, the LIBs invariably undergo venting, with the venting force ranging from 4000 N to 6422 N. Furthermore, the voltage of the batteries remains relatively stable at approximately 3.33 V before venting. An Internal short circuit and TR events occur once the oven temperature exceeds 180 °C, and the corresponding TR trigger temperatures are approximately 232 °C. Moreover, the abnormal force can be utilized as the earliest warning indicator prior to venting, and the lead time for expansion force warning signals decreases with increasing oven temperature in batteries undergoing TR. This study investigates multidimensional signals to effectively identify battery failures, deepening the understanding of the TR behaviors of batteries under different oven temperatures, and providing valuable insights for early warning and safety design of battery systems.
In order to explore the failure behaviors of lithium-ion batteries (LIBs) during thermal runaway (TR) under various oven temperatures, this study conducts comprehensive oven box abuse tests to investigate the impact of oven temperature on the characteristics of multidimensional signals during battery failure processes. The temporal relationships among expansion force, voltage, and temperature are revealed across four distinct stages of the thermal abuse process. The results indicate that within the oven temperature range of 150 °C to 250 °C, the LIBs invariably undergo venting, with the venting force ranging from 4000 N to 6422 N. Furthermore, the voltage of the batteries remains relatively stable at approximately 3.33 V before venting. An Internal short circuit and TR events occur once the oven temperature exceeds 180 °C, and the corresponding TR trigger temperatures are approximately 232 °C. Moreover, the abnormal force can be utilized as the earliest warning indicator prior to venting, and the lead time for expansion force warning signals decreases with increasing oven temperature in batteries undergoing TR. This study investigates multidimensional signals to effectively identify battery failures, deepening the understanding of the TR behaviors of batteries under different oven temperatures, and providing valuable insights for early warning and safety design of battery systems.
摘要：
Leaky Rayleigh waves are sensitive to surface defects and beneficial for automated detection due to their non-contact characteristics. However, the amplitude of the leaky Rayleigh waves is low due to the attenuation of waveform conversion and acoustic waves propagation, which limits the imaging quality for long-distance detection. This study introduces a novel method combining leaky Rayleigh waves detection with virtual source total focusing method. The virtual source (VS) technology enhances the emission energy of leaky Rayleigh waves. Then, the total focusing method (TFM) is applied to acquire high-accuracy images of defects. To reduce noise and artifacts, a weighting function based on the coherence factor (CF) is developed to weight the TFM superimposed signals, thereby achieving high-quality image reconstruction. Experimental results show that compared with the conventional TFM method, the proposed method can effectively improve the amplitude of imaging signals while reducing system noise and imaging artifacts. The lateral accuracy of defects is improved, with the average lateral error of defect size being 0.178 mm. The signal-to-noise ratio (SNR) of ultrasound images is increased by 27.59 dB, and the array performance index (API) of ultrasound images is decreased by 33.78 %. The proposed method provides a new and effective approach for quantitatively assessing the surface defects of metal components using leaky Rayleigh waves.
Leaky Rayleigh waves are sensitive to surface defects and beneficial for automated detection due to their non-contact characteristics. However, the amplitude of the leaky Rayleigh waves is low due to the attenuation of waveform conversion and acoustic waves propagation, which limits the imaging quality for long-distance detection. This study introduces a novel method combining leaky Rayleigh waves detection with virtual source total focusing method. The virtual source (VS) technology enhances the emission energy of leaky Rayleigh waves. Then, the total focusing method (TFM) is applied to acquire high-accuracy images of defects. To reduce noise and artifacts, a weighting function based on the coherence factor (CF) is developed to weight the TFM superimposed signals, thereby achieving high-quality image reconstruction. Experimental results show that compared with the conventional TFM method, the proposed method can effectively improve the amplitude of imaging signals while reducing system noise and imaging artifacts. The lateral accuracy of defects is improved, with the average lateral error of defect size being 0.178 mm. The signal-to-noise ratio (SNR) of ultrasound images is increased by 27.59 dB, and the array performance index (API) of ultrasound images is decreased by 33.78 %. The proposed method provides a new and effective approach for quantitatively assessing the surface defects of metal components using leaky Rayleigh waves.
期刊：
Chemical Engineering Journal,2025年:166492 ISSN：1385-8947
通讯作者：
Shuntong Hu
作者机构：
[Yi Yuan; Panyao Long; Juan Huang; Yiwei Chen; Xiaobo Li; Zhi Song; Shuntong Hu] Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha 410013, China;Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Anesthesiology, The Third Xiangya Hospital, Central South University, Changsha 410013, China;Clinical Research Center, The Third Xiangya Hospital, Central South University, Changsha 410013, China;College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
通讯机构：
[Shuntong Hu] D;Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha 410013, China
摘要：
The aim of this study was to investigate the molecular basis and therapeutic potential of SOX17 activation using a CRISPRa-based gene editing system in treating intracranial aneurysm (IA), supported by targeted delivery through nanomicrospheres. An IA model in mice was established through basal cistern elastase injection and angiotensin II-induced hypertension. RNA sequencing of intracranial arteries identified 77 DEGs significantly enriched in vascular remodeling pathways, particularly Wnt and Hippo signaling. Computational analyses (LASSO and random forest) identified SOX17 as a central regulator. CRISPRa constructs targeting SOX17 were loaded into CH-NF nanomicrospheres and delivered to lesion sites. Doppler ultrasound and microCT monitored aneurysm formation and dilation. In vitro assays measured endothelial cell proliferation, migration, and apoptosis. SOX17 was markedly downregulated in IA tissue. Its CRISPRa-mediated activation led to reduced endothelial proliferation, migration, and neovascularization. Flow cytometry revealed decreased apoptosis in oxidative stress conditions. In vivo imaging confirmed successful localization of CH-NF to brain regions. Vascular dilation was notably inhibited in treated mice. Targeted activation of SOX17 using CRISPRa and CH-NF delivery demonstrates therapeutic efficacy in suppressing endothelial dysfunction and aneurysm progression, offering a mechanistically grounded strategy for IA treatment.
The aim of this study was to investigate the molecular basis and therapeutic potential of SOX17 activation using a CRISPRa-based gene editing system in treating intracranial aneurysm (IA), supported by targeted delivery through nanomicrospheres. An IA model in mice was established through basal cistern elastase injection and angiotensin II-induced hypertension. RNA sequencing of intracranial arteries identified 77 DEGs significantly enriched in vascular remodeling pathways, particularly Wnt and Hippo signaling. Computational analyses (LASSO and random forest) identified SOX17 as a central regulator. CRISPRa constructs targeting SOX17 were loaded into CH-NF nanomicrospheres and delivered to lesion sites. Doppler ultrasound and microCT monitored aneurysm formation and dilation. In vitro assays measured endothelial cell proliferation, migration, and apoptosis. SOX17 was markedly downregulated in IA tissue. Its CRISPRa-mediated activation led to reduced endothelial proliferation, migration, and neovascularization. Flow cytometry revealed decreased apoptosis in oxidative stress conditions. In vivo imaging confirmed successful localization of CH-NF to brain regions. Vascular dilation was notably inhibited in treated mice. Targeted activation of SOX17 using CRISPRa and CH-NF delivery demonstrates therapeutic efficacy in suppressing endothelial dysfunction and aneurysm progression, offering a mechanistically grounded strategy for IA treatment.
摘要：
This study systematically characterized the microstructure, phase transformation, and mechanical properties of Ti65 titanium alloy T-joints welded using dual-beam laser with Ti65 welding wire as filler. The welded joint exhibits distinct zones: the base material retains a fine duplex α-phase microstructure; the heat-affected zone (HAZ) shows grain coarsening and phase transformation; and the fusion zone (FZ) forms needle-like α′ martensite due to rapid cooling-induced β-phase transformation. Elemental analysis confirms uniform alloy distribution with no segregation. X-ray diffraction (XRD) reveals that the fusion zone comprises predominantly α′ martensite (76.79%) with a minor β phase. Electron backscatter diffraction (EBSD) demonstrates grain refinement and a high proportion of high-angle grain boundaries in the fusion zone, enhancing strength and crack resistance. Tensile testing indicates high strength (723–779 MPa) but limited ductility (1.3–1.5% elongation). Hardness decreases gradually from the fusion zone to the skin zone, with fine-grain strengthening significantly increasing fusion zone hardness. These findings demonstrate that dual-beam laser welding with Ti65 filler wire effectively refines microstructure and enhances mechanical properties, addressing critical challenges in welding high-performance titanium alloys.
This study systematically characterized the microstructure, phase transformation, and mechanical properties of Ti65 titanium alloy T-joints welded using dual-beam laser with Ti65 welding wire as filler. The welded joint exhibits distinct zones: the base material retains a fine duplex α-phase microstructure; the heat-affected zone (HAZ) shows grain coarsening and phase transformation; and the fusion zone (FZ) forms needle-like α′ martensite due to rapid cooling-induced β-phase transformation. Elemental analysis confirms uniform alloy distribution with no segregation. X-ray diffraction (XRD) reveals that the fusion zone comprises predominantly α′ martensite (76.79%) with a minor β phase. Electron backscatter diffraction (EBSD) demonstrates grain refinement and a high proportion of high-angle grain boundaries in the fusion zone, enhancing strength and crack resistance. Tensile testing indicates high strength (723–779 MPa) but limited ductility (1.3–1.5% elongation). Hardness decreases gradually from the fusion zone to the skin zone, with fine-grain strengthening significantly increasing fusion zone hardness. These findings demonstrate that dual-beam laser welding with Ti65 filler wire effectively refines microstructure and enhances mechanical properties, addressing critical challenges in welding high-performance titanium alloys.
通讯机构：
[Peng, X ; Jia, WQ ] Z;Zhejiang Univ Technol, Coll Mech Engn, Hangzhou, Peoples R China.;Zhejiang Lab, Hangzhou, Peoples R China.
关键词：
composite;deep learning;finite element method;local stress;representative volume element
摘要：
Predicting the full-field stress distribution has important significance in analyzing mechanical characteristics of composite materials. Numerical calculations of stress field distribution using finite element analysis (FEA) can call for significant computational effort for microscale geometries. To address this challenge, this paper demonstrates a deep learning (DL) framework for predicting local stress distributions in fiber-reinforced composites with diverse fiber volume fractions. An adaptive generation algorithm of representative volume element (RVE) microstructures is developed for constructing stochastic RVE with diverse fiber volume fractions, and the corresponding von Mises stress distribution is calculated using the FEA method. The U-Net framework is developed, whose weights are trained based on the samples with fiber volume fractions of 30%, 40%, and 50%. Then the weights of the DL model are updated based on additional little samples with random fiber volume fractions between 30% and 50%. The structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) are used for qualifying the accuracy of predicted stress field distributions. The predicted results for a series of microscale geometries show that the mean SSIM values for stress field prediction for diverse fiber volume fractions are up to 98.04%, which can illustrate that the proposed DL model can predict the stress field distribution with diverse fiber volume fractions successfully.
摘要：
Metal matrix composite (MMC) coatings with good metallurgical bonding were fabricated using laser cladding, focusing on the effect of SiC ceramic contents on the tribological properties and oxidation resistance of nickel matrix composite coatings. The results demonstrated that the microhardness of MMC coatings increased by a factor of 2.28–3.16 and 1.20–1.38, respectively, over the substrate and metal coating under the synergistic action of multiple strengthening effects. As SiC content increases, the wear resistance of coatings shows a trend of first enhancement and then decrease, but both are better than the SiC-free coating and substrate. Where the MMC coating with 15 wt% SiC addition showed the best tribological performance at room and high temperatures, the wear rate was reduced by 71.54 %/ 49.28 % (RT) and 58.8 %/38.17 % (HT) compared to the metal coating and the substrate, respectively, which was mainly attributed to its highest microhardness and densest microstructure. After prolonged oxidation at elevated-temperature, the uniformity and densification of the oxide film on the coating surface increased with increasing SiC content, and the oxidation resistance was linearly strengthened. The synergistic effect of uniformly distributed stable oxide Cr 2 O 3 and self-repairing SiO 2 led to a remarkable improvement in the oxidation resistance of MMC coatings.
Metal matrix composite (MMC) coatings with good metallurgical bonding were fabricated using laser cladding, focusing on the effect of SiC ceramic contents on the tribological properties and oxidation resistance of nickel matrix composite coatings. The results demonstrated that the microhardness of MMC coatings increased by a factor of 2.28–3.16 and 1.20–1.38, respectively, over the substrate and metal coating under the synergistic action of multiple strengthening effects. As SiC content increases, the wear resistance of coatings shows a trend of first enhancement and then decrease, but both are better than the SiC-free coating and substrate. Where the MMC coating with 15 wt% SiC addition showed the best tribological performance at room and high temperatures, the wear rate was reduced by 71.54 %/ 49.28 % (RT) and 58.8 %/38.17 % (HT) compared to the metal coating and the substrate, respectively, which was mainly attributed to its highest microhardness and densest microstructure. After prolonged oxidation at elevated-temperature, the uniformity and densification of the oxide film on the coating surface increased with increasing SiC content, and the oxidation resistance was linearly strengthened. The synergistic effect of uniformly distributed stable oxide Cr 2 O 3 and self-repairing SiO 2 led to a remarkable improvement in the oxidation resistance of MMC coatings.
摘要：
Additive manufacturing of hard TiC-based cermets typically employs a high-energy beam as the energy source but suffers from high residual stress and microcracks. Herein, we propose an economical additive-manufacturing process for TiC-based cermets using powder extrusion printing (PEP) combined with pressureless sintering, which overcomes inadequacies such as extensive residual stress and microcracks. Complex cermet parts with high densities are successfully fabricated, thereby experimentally demonstrating the feasibility of this method. The as-produced TiC 60 (Ni 88 Fe 12 ) 40 composites exhibit a typical core-rim structure, which plays an important role in improving the interfacial bonding ability. The sintering temperature has a significant impact on the microstructure and mechanical properties. The flexural strength and microhardness increase first and then decrease at temperatures ranging from 1390 to 1430 °C. Optimum mechanical properties are achieved at 1410 °C with flexural strength and microhardness of 1013 ± 17 MPa and 965 ± 18 HV 0.2 , respectively. The additive-manufactured cermets exhibit superior abrasive resistance and the main abrasive mechanism is adhesive wear accompanied by oxidative wear. The good wear resistance is attributed to the high hardness of the TiC phase and the lubricating effect of the abrasive debris.
Additive manufacturing of hard TiC-based cermets typically employs a high-energy beam as the energy source but suffers from high residual stress and microcracks. Herein, we propose an economical additive-manufacturing process for TiC-based cermets using powder extrusion printing (PEP) combined with pressureless sintering, which overcomes inadequacies such as extensive residual stress and microcracks. Complex cermet parts with high densities are successfully fabricated, thereby experimentally demonstrating the feasibility of this method. The as-produced TiC 60 (Ni 88 Fe 12 ) 40 composites exhibit a typical core-rim structure, which plays an important role in improving the interfacial bonding ability. The sintering temperature has a significant impact on the microstructure and mechanical properties. The flexural strength and microhardness increase first and then decrease at temperatures ranging from 1390 to 1430 °C. Optimum mechanical properties are achieved at 1410 °C with flexural strength and microhardness of 1013 ± 17 MPa and 965 ± 18 HV 0.2 , respectively. The additive-manufactured cermets exhibit superior abrasive resistance and the main abrasive mechanism is adhesive wear accompanied by oxidative wear. The good wear resistance is attributed to the high hardness of the TiC phase and the lubricating effect of the abrasive debris.
摘要：
To support regulations related to cyclists dismounting and pushing across motor vehicle lanes, this study first extracted posture parameters for riding/pushing through physical experiments, then simplified the posture parameters and extracted typical postures with distinguishability. Finally, simulated experiments were designed to compare the differences in human injury between riding and pushing in collision accidents. The physical experiment found that the bicycle controller's (individuals who ride or push bicycles) forward leaning angle of the back (referred to as the 'back angle') when riding can be estimated by the ratio of saddle height to bicycle handlebar height, but the back angle when pushing is not affected by other parameters. Eight typical postures containing only lower limb posture parameters were then identified, and statistical analysis showed significant differences in over 80% of parameters among the postures. Through simulated experiments, the rider's tolerable saddle height was identified. Even at this saddle height, the injury in riding state was still significantly higher than that in the pushing state, indicating that pushing the bicycle across the motor vehicle lane can reduce the injury to the bicycle controller. The research results not only support relevant regulations, but also provide typical postures for the bicycle controller in vehicle-bicycle collision experiments in the future, and have certain theoretical and practical value.
