Combinations of high-fidelity and reduced-order computational models can radically reduce the cost and time required to produce innovative designs for aerospace and related systems. Research focuses on multidisciplinary and multiscale computational frameworks and algorithms and their integration in the design process.

Millions of people each day benefit from the research that has been conducted in the control and navigation labs at Stanford. As the uses of GPS multiply and as we reach places never before reached, the range of research in this area continues to expand.

Stanford students and professors are working on breakthrough satellite designs, safer means of propulsions, and the control of robots at interplanetary distances, as they develop a wide variety of technologies for deployment in orbit and on other planets.

Embedding an advanced network of intelligent sensors and actuators within an airframe provides an infrastructure for data processing and diagnostics. It gives an aircraft a central nervous system capable of quickly detecting emerging structural problems. Mitigating solutions can then avoid failures and loss of lives, while decreasing operational costs.

As air traffic continues to increase over the coming decades, innovative ideas will be needed to achieve radical improvements in the performance of the air transportation system while minimizing the impact on the environment. Research and teaching in this area seek to produce technologies and basic understanding to enable sustainable growth.