Investigation and Application of Multi-Disciplinary Optimization for Automotive Body-in-White Development
A process has been created for applying multi-disciplinary optimization (MDO) during the development of an automotive body-in-white (BIW) structure. The initial phase evaluated the performance of several different optimization algorithms when applied to structural MDO problems. From this testing, two algorithms were chosen for further study, one of these being sequential metamodeling with domain reduction (SRSM) found within LS-OPT. To use the LS-OPT optimization software effectively within a production environment, adaptations were made to integrate it into an established CAE infrastructure. This involved developing a LS-OPT server and architecture for the parallel job submission and queuing required in the MDO process. This enabled LS- OPT to act as an integral part of the enterprise CAE architecture as opposed to a standalone tool. Within this integrated environment, the SRSM method has been applied to an MDO process that combines 7 load cases and takes into account crash and NVH requirements. The objective of the MDO was to minimize mass while constraints enforced the performance requirements of each load case. The thicknesses of 35 parts were considered in this MDO. The application of the SRSM MDO strategy resulted in an optimized design with a 6% weight reduction for the portion of the BIW considered. The optimized design was determined with reasonable computational resources and time considering the computational intensity of the analysis.
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Investigation and Application of Multi-Disciplinary Optimization for Automotive Body-in-White Development
A process has been created for applying multi-disciplinary optimization (MDO) during the development of an automotive body-in-white (BIW) structure. The initial phase evaluated the performance of several different optimization algorithms when applied to structural MDO problems. From this testing, two algorithms were chosen for further study, one of these being sequential metamodeling with domain reduction (SRSM) found within LS-OPT. To use the LS-OPT optimization software effectively within a production environment, adaptations were made to integrate it into an established CAE infrastructure. This involved developing a LS-OPT server and architecture for the parallel job submission and queuing required in the MDO process. This enabled LS- OPT to act as an integral part of the enterprise CAE architecture as opposed to a standalone tool. Within this integrated environment, the SRSM method has been applied to an MDO process that combines 7 load cases and takes into account crash and NVH requirements. The objective of the MDO was to minimize mass while constraints enforced the performance requirements of each load case. The thicknesses of 35 parts were considered in this MDO. The application of the SRSM MDO strategy resulted in an optimized design with a 6% weight reduction for the portion of the BIW considered. The optimized design was determined with reasonable computational resources and time considering the computational intensity of the analysis.