A5068515422- Combustion and Detonation Processes
- Probabilistic and Robust Engineering Design
- Fire dynamics and safety research
- Advanced Multi-Objective Optimization Algorithms
- Combustion and flame dynamics
- Optimal Experimental Design Methods
- Risk and Safety Analysis
- Structural Health Monitoring Techniques
- Fatigue and fracture mechanics
- Energetic Materials and Combustion
- Reliability and Maintenance Optimization
- Mechanical Behavior of Composites
- Epoxy Resin Curing Processes
- Advanced Computational Techniques and Applications
- Lipid metabolism and biosynthesis
- Gas Sensing Nanomaterials and Sensors
- Advanced Battery Technologies Research
- ZnO doping and properties
- Electrocatalysts for Energy Conversion
- Advanced Algorithms and Applications
- Railway Engineering and Dynamics
- Industrial Technology and Control Systems
- Smart Grid and Power Systems
- Advanced Decision-Making Techniques
- Advanced Data Storage Technologies
Southwest Jiaotong University
2001-2025
Luliang University
2025
Nanjing Normal University
2025
Xiamen University
2024
Institute of Botany
2022-2024
Dalian University of Technology
2020-2023
Chinese Academy of Sciences
2022
Inner Mongolia University of Technology
2022
Chongqing University
2018-2021
National Quality Inspection and Testing Center for Surveying and Mapping Products
2021
A high-speed train dynamics system involves numerous uncertainty parameters, and there are multiple evaluation indices for its dynamic performance. In this paper, we conduct high-dimensional multi-output global sensitivity analysis the performance of trains by comprehensively considering these parameters indices. Firstly, simulation model is established six evaluating safety comfort obtained under operating conditions. Subsequently, characteristics analysis, propose a method based on...
Strategies combining active learning Kriging (ALK) model and Monte Carlo simulation (MCS) method can accurately estimate the failure probability of a performance function with minimal number training points. That is because points are close to limit state surface size approximation region be minimized. However, estimation rare event very low remains an issue, purely building ALK time-demanding. This paper intended address this issue by researching fusion kernel-density-estimation (KDE)-based...
Summary Reliability analysis with both aleatory and epistemic uncertainties is investigated in this paper. The are described random variables, tackled evidence theory. To estimate the bounds of failure probability, several methods have been proposed. However, existing suffer dimensionality challenge variables. get rid challenge, a so‐called random‐set based Monte Carlo simulation (RS‐MCS) method derived from theory sets offered. Nevertheless, RS‐MCS also computational expensive. So an active...
Abstract A novel method which combines the active learning Kriging (ALK) model with important sampling is proposed in this paper. The main aim of to solve problems very small failure probability and multiple regions. surrogate limit state surface (LSS) strikes a balance between mean variance proposed. In each iteration, samples LSS are generated, optimal training points chosen, updated refined. After several iterations, will converge true LSS. To obtain all local global most probable (MPPs)...