ZAP: a knowledge-based FEA modeling method for highly coupled variable topology multi-body problems

Some of the most significant challenges in automated CAD–FEA integration are information and model transformations between CAD and FEA tools. These are especially labor-intensive and time-consuming in a newly characterized class of problems termed highly coupled variable topology multi-body (HCVTMB) problems. This paper addresses these challenges with a knowledge-based FEA modeling method called ZAP that consists of three stepping-stone information models and the mapping processes between these models. The information and knowledge of a typical FEA modeling process are explicitly captured in semantically rich information models to achieve benefits including knowledge sharing, system extension, and model modification. ZAP mapping processes automatically transform abstract analytical concepts into tool-specific commands and functions that accomplish HCVTMB model generation and solution management. This method enhances flexibility and reusability in FEA modeling and enables CAD–FEA integration at the knowledge level. To demonstrate the efficacy of ZAP, we overview a sample HCVTMB problem—an electronic chip package plastic ball grid array (PBGA) thermal analysis case study. Experience indicates that ZAP increases knowledge capture and decreases modeling time from days/hours to hours/minutes compared to conventional methods, thus providing a key enabler toward design optimization.