Interaction prediction optimization in multidisciplinary design environment
Debiao Meng, Hua Zhang, Hong‐Zhong Huang, Xiaoling Zhang, Huanwei Xu
Abstract
Debiao Meng, Hua Zhang, Hong‐Zhong Huang, Xiaoling Zhang, Huanwei Xu
Abstract
The increasing complexity of engineering systems has sparked rising interests in multidisciplinary design optimization (MDO). However, the main challenges in MDO are its computational expense and complexity structure. Therefore, to address these challenges, this paper focuses on a new MDO method, interaction prediction optimization approach, which is a design architecture applied in the multidisciplinary environment. In this approach, a complex system is decomposed hierarchically along disciplinary boundaries into a number of subsystems, which are taken multidisciplinary agreement into account by a system-level coordination process. A mathematical problem and an engineering design problem are presented to highlight the potential application of the new method in multidisciplinary design optimization.
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The increasing complexity of engineering systems has sparked rising interests in multidisciplinary design optimization (MDO). However, the main challenges in MDO are its computational expense and complexity structure. Therefore, to address these challenges, this paper focuses on a new MDO method, interaction prediction optimization approach, which is a design architecture applied in the multidisciplinary environment. In this approach, a complex system is decomposed hierarchically along disciplinary boundaries into a number of subsystems, which are taken multidisciplinary agreement into account by a system-level coordination process. A mathematical problem and an engineering design problem are presented to highlight the potential application of the new method in multidisciplinary design optimization.
Key concepts: Multidisciplinary approach, Multidisciplinary design optimization, Computer science, Engineering design process, Engineering optimization, Systems engineering, Process (computing), Management science