Affiliation:
1. Department of Aerospace and Mechanical Engineering,
University of Notre Dame, Notre Dame, IN 46556-5637
Abstract
In this research two comparative studies are conducted in application to the concurrent design optimization method of Simulta neous ANalysis and Design (SAND) In one study three different forms of equality constraints referred to as compatibility constraints in the SAND procedure are compared with respect to their impact on algorithm efficiency. Results indicate that the form of the compatibility con straints can have a significant impact on performance in the SAND based procedure. In a second study a Generalized Reduced Gradient (GRG) optimizer and a Sequential Quadratic Programming (SQP) optimizer are compared with respect to their efficacy as the internal opti mizer within the SAND based optimization procedure. Comparative studies indicate that the SQP method is preferred over the GRG method in application of SAND based design. The comparative studies were conducted in application to two Multidisciplinary Design Optimization (MDO) test problems. The method of SAND was originally developed as an optimization strategy for structural design problems. Recent studies have focussed on applying the principles of SAND to multidisciplinary design environments In this research we focus on the concurrency that can be achieved in multidisciplinary design environments using SAND. In a multidisciplinary design environment the SAND approach facilitates each of the seven principles of concurrent engineering as described in Prasad, 1996. The SAND based method provides for: parallel work groups, parallel product decomposition, concurrent resource scheduling, concurrent processing, minimal interfaces, transparent communi cation and quick processing. Application studies confirm that a significant savings in the number of analyses required for design optimiza tion are observed when using the SAND approach of concurrent design. SAND based design delivers on the promise of concurrent engi neering, namely to develop optimal designs, working concurrently, while reducing design cycle time.
Subject
Computer Science Applications,General Engineering,Modelling and Simulation
Cited by
8 articles.
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