computational engineering

Simulation Aids Rapid Development

With the advent of large-scale computers, computational approaches have become indispensable for characterizing, predicting and simulating physical events and engineering systems. Industrial competitiveness demands reduction in design cycle time which, in turn, relies heavily on numerical simulations to reduce the number of tests of physical prototypes. From the point of view of scientific investigations, one of the great strengths of computer simulations over physical experiments is the ability to study a complete range of physical and temporal scales. That is, one can study in detail physical phenomena that last only a picosecond, or one can move back in time and identify the evolution of interesting physical events.
The Mechanical Engineering Department features many faculty working at the forefront of simulation techniques from several groups.  Faculty from the  Flow Physics & Computational Engineering Group have lead for decades in the simulation of complex transport processes, starting with turbulent fluid mechanics and now ranging from fuel cell chemistry and biomedical devices to high speed aircraft.  Faculty from FPCE play a central role in the continuing presence of large externally funded computational centers in the Department (e.g., the Center for Turbulence Research and the PSAAP). 
Faculty from the Mechanics and Computation Group are at the forefront of computational methods, with a particular focus on techniques required for the design of nanoscale devices and nanostructured materials.  Applications range from the motion and transport of molecules and tissue to the atomic-scale physics of material behavior.  Much research is focussed on the special challenge of multi-scale simulations, which are essential for engineering systems containing nanoscale components.

Research Focus

We are focusing our energies on number of areas in computational engineering:

• computational geometry and virtual design;
• multi-scale phenomena including bridging of atomistic to continuum models;
• biomedical applications, including predictive surgery;
• computational study of cells, tissues, bones and other biological systems;
• chemical reactions and multi-phase flows;
• atomistic physics of material behavior and failure;
• climate modeling;
• energy systems including fuel cells and efficient engines.

Success in these areas leverages our core competencies in computer science such as parallel computing, numerical analysis, model selection and adaptivity.

Leadership in Computational Mathematics and Parallel Computing

Some of these areas have traditionally been in the domain of other departments such as Computer Science, but experience has shown that the best numerical tools are developed by those interested in specific applications. Furthermore, Stanford's ME Department has an excellent track record and international reputation for making contributions in both research and educational components of computational mathematics and parallel computing.