Recent advances in modeling and simulation technology have made it feasible to generate large datasets of design alternatives and their attributes in a relatively short amount of time. However, tools to understand and explore these datasets are limited. To this end, the Applied Research Laboratory at Penn State University has been developing a tool, entitled the ARL Trade Space Visualizer (ATSV) to support multi-dimensional trade space exploration. The ARL, in conjunction with the Lockheed Martin Corporation, has extended the tool to tackle several real world design challenges. In response to the needs of the engineering teams at Lockheed Martin, several key enhancements to the ATSV have been designed and implemented. These enhancements include contour plotting in two dimensions; isosurface generation in three dimensions; multiple independent brushing controls; and k-means cluster analysis. This paper will describe the full capabilities of the tool, as well as give an example of the types of design optimization performed by Lockheed Martin. The paper will focus on using the advanced visualization techniques to discover relationships within the dataset that would otherwise prove difficult to extract using traditional analysis techniques.

Due to increased competition within the aerospace industry, simply meeting t he minimum project requirements for a new design will no longer ensure a project win. In order to achieve mission success, emphasis must be placed on producing an optimum final product through an efficient, lean process. To achieve an optimum final product , Multi Disciplinary Design (MDD), Multi Disciplinary Analysis (MDA), and Multi Disciplinary Optimization (MDO) must be utilized from project inception. Traditionally, MDD, MDA, and MDO have been time intensive activities, whose limited implementation in the prototyping design process has added little benefit. If significant gains are to be made by employing MDD, MDA, and MDO in a prototyping environment, the time associated with their implementation must be reduced such that a sufficient number of trades can be performed to realize these gains. In order to remain an industry leader in an increasing competitive aerospace marketplace the