Physically-based, real-time visualization and constraint analysis in multidisciplinary design optimization

Abstract

As computational tools becomes a valuable part of the engineering process, multidisciplinary design optimization (MDO) has become a popular approach for the design of complex engineering systems. MDO has had considerable impact by improving the performance, lowering the lifecycle cost and shortening product design time for complex systems; however, lack of knowledge on the design process is often expressed by the engineering community. This thesis addresses this issue by proposing a novel approach that brings visualization into the MDO framework and delivers a physically-based real-time constraint analysis and visualization. A framework and methodology are presented for effective, intuitive visualization of design optimization data. The visualization is effected on a Computer-Aided-Design (CAD)-based, physical representation of the system being designed. The use of a parametric CAD model allow real-time regeneration by using the Computational Analysis PRogramming Interface (CAPRI). CAPRI is used to link a general optimization framework to the CAD model. An example is presented for multidisciplinary design optimization of an aircraft. The new methodology is used to visualize the path of the optimizer through the design space. Visualizing the optimization process is also of interest for optimization health monitoring. By detecting flaws in the optimization definition, useless computations and time can be saved. Visualization of the optimization process enables the designer to rapidly gain physical understanding of the design tradeoffs made by the optimizer. The visualization framework is also used to investigate constraint behavior. Active constraints are displayed on the CAD model and the participation of design variables in a given constraint is represented in a physically intuitive manner. This novel visualization approach serves to dramatically increase the amount of learning that can be gained from design optimization tools and also proves useful as a diagnostic tool for identifying formulation errors.