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.