White Papers
Flexible Approximation Model Approach for Bi-Level Integrated System Synthesis
Hongman Kim, Scott Ragon, Grant Soremekun, Brett Malone, and Jaroslaw Sobieszczanski-Sobieski
Abstract
Bi-Level Integrated System Synthesis (BLISS) is an approach that allows design problems to be naturally decomposed into a set of subsystem optimizations and a single system optimization. In the BLISS approach, approximate mathematical models are used to transfer information from the subsystem optimizations to the system optimization. Accurate approximation models are therefore critical to the success of the BLISS procedure. In this paper, new capabilities that are being developed to generate accurate approximation models for BLISS procedure are described. The benefits of using flexible approximation models such as Kriging are demonstrated in terms of convergence characteristics and computational cost. An approach of dealing with cases where subsystem optimization cannot find a feasible design is introduced by using the new flexible approximation models for the violated local constraints.
Introduction
Approximation models have become an essential element in many multidisciplinary design optimization (MDO) techniques. For example, polynomial models known as response surface (RS) models have been widely used1,2. Approximation models replace expensive simulation codes in the optimization process to reduce total computational cost. By performing the simulation a priori, the simulation model may be separated from the optimizer or other coupled simulation codes so that the tool integration efforts can be reduced.
Bi-Level Integrated System Synthesis (BLISS)3 is an approach that allows design problems to be naturally decomposed into a set of subsystem optimizations and a single system optimization. The BLISS approach overcomes the difficulties of optimizing complex systems such as aircraft or automobiles where multidisciplinary interactions are prominent. BLISS performs a set of subsystem optimizations to create approximation models of the optimal subsystem, which are then used in the system optimization. The approximation model approach of BLISS effectively separates coupled subsystems and plays an important role in transferring information from subsystem level to system level. Therefore the success of the BLISS process depends on generating accurate approximation models.
Download The Complete Paper
(A one-time registration will be requested)
