Special Session XIV

Reliability Analysis and Design Optimization with Meta-models
基于元模型的可靠性分析与设计优化

The increasing complexity of engineering systems and the demand for enhanced reliability have necessitated the development of advanced methods for reliability analysis and design optimization. Traditional approaches often involve substantial computational costs due to extensive simulations or experiments. Meta-models, or surrogate models, have become essential tools to address these challenges by providing efficient approximations of complex systems. These models facilitate reliable analysis and optimization with reduced computational resources. Additionally, accurate prediction of the remaining useful life (RUL) of components and systems has become crucial for effective maintenance and operational planning. Integrating meta-models with RUL prediction enhances the capability to anticipate system failures and optimize design and maintenance strategies.

The goal of this special session is to bring together researchers and practitioners from various disciplines to discuss recent advances in the use of meta-models for reliability analysis (such as RUL prediction) and design optimization. The session aims to explore innovative methodologies, applications, and case studies that highlight the effectiveness of meta-models in enhancing reliability, optimizing design under uncertainty, and predicting the remaining useful life of engineering systems. By fostering discussions and knowledge exchange, the session seeks to advance the state-of-the-art in this area and identify future research directions to further improve the reliability and performance of engineering systems. Topics include but are not limited to:

1) Development of Meta-Models for Reliability Analysis: Techniques for constructing and validating accurate meta-models in reliability analysis.
2) Meta-Models for Remaining Useful Life Prediction: Techniques for predicting the remaining useful life of components and systems using meta-models.
3) Meta-Models in Sustainable and Resilient Design: Application of meta-models in optimizing sustainability and resilience in engineering designs.
4) Real-Time Reliability Analysis and Optimization: Development of online meta-models and their integration with digital twins for real-time analysis.
5) Advanced Meta-Modeling Techniques: Exploration of innovative surrogate modeling approaches, including machine learning and hybrid methods.
6) Machine Learning-Driven Meta-Models: Integration of AI and machine learning for developing adaptive and automated meta-models.
7) Collaborative and Distributed Meta-Modeling: Cloud-based and crowdsourced approaches for collaborative meta-model development and application.

Chairs: Yongxiang Li, Shanghai Jiao Tong University, China (E-mail: yongxiangli@sjtu.edu.cn)
Linhan Ouyang, Nanjing University of Aeronautics and Astronautics, China (E-mail: ouyang@nuaa.edu.cn)
Jianguo Wu, Peking University, China (E-mail: j.wu@pku.edu.cn)

 Submission Portal

If you are interested in the special session, please submit your paper or abstract here
https://www.zmeeting.org/submission/srse2025 and choose special session 14.

For any questions, please mail the organizers or conference secretary srse@sciei.org.