@inproceedings{b3adf86062844e47858e5b3ec3c84c39,
title = "A Data-Driven Multidisciplinary Heterogeneous Distributed Computing Framework Considering Time Consumption Disparity",
abstract = "While multidisciplinary design optimization (MDO) exhibits theoretical efficacy for complex system design, its practical implementation encounters fundamental challenges due to computationally intensive multidisciplinary analyses. To enhance computational effectiveness and optimization results, this paper presents a multidisciplinary heterogeneous distributed computing framework (MHDCF) that considers the time consumption disparities among different disciplinary evaluations. The framework employs various computational nodes to decouple the multidisciplinary evaluation process into surrogate modeling and distributed disciplinary simulations. Besides, the framework replenishes and allocates samples to different nodes based on time consumption disparity to maximize the utilization of the framework. By applying MHDCF to the MDO of a blended-wing-body underwater glider (BWBUG), the framework{\textquoteright}s effectiveness and the necessity for managing time consumption disparities are validated through comparative experiments.",
keywords = "BWBUG, Data-driven, Distributed computation, Multidisciplinary design optimization, Time consumption disparity",
author = "Yichen Jiang and Jinglu Li and Wenxin Wang and Huachao Dong",
note = "Publisher Copyright: {\textcopyright} The Chinese Mechanical Engineering Society 2026.; International Conference on Mechanical Design, ICMD 2025 ; Conference date: 09-05-2025 Through 11-05-2025",
year = "2026",
doi = "10.1007/978-981-95-7342-4\_42",
language = "英语",
isbn = "9789819573417",
series = "Mechanisms and Machine Science",
publisher = "Springer Science and Business Media B.V.",
pages = "631--642",
editor = "Jianrong Tan and Zhenyu Liu and Weifei Hu",
booktitle = "Advances in Mechanical Design - Proceedings of the 2025 International Conference on Mechanical Design ICMD 2025",
}