Stanford University Department of Aeronautics & Astronautics Aerospace Computing Laboratory

Patrick LeGresley

E-mail: plegresl@stanfordalumni.org

Background

Doctor of Philosophy
Department of Aeronautics and Astronautics, Stanford University (1999-2005)

Master of Science
Department of Aeronautics and Astronautics, Stanford University (1998-1999)

Bachelor of Science
Department of Aerospace Engineering, University of Kansas (1994-1998)

Research Interests

Reduced Order Modeling

My research focuses on the development of reduced order models for use in design and optimization. To be computationally feasible the order of some systems, such as an aeroelastic system with millions of degrees of freedom, may need to be reduced. I am currently investigating the use of Proper Orthogonal Decomposition (POD) as a means to construct linear based models, with the ultimate goal of applying these models to Aerodynamic Shape Optimization (ASO) and Multidisciplinary Design Optimization (MDO) problems.

The preliminary work in this area has focused on applying these modeling techniques to the 2-D inviscid flow over an airfoil. For example, consider a model based on flow solutions, or 'snapshots', of an airfoil at different Mach numbers:

Mach 0.30 Mach 0.40

Mach 0.50 Mach 0.60

Mach 0.70


In this case we have solutions at Mach numbers of 0.30, 0.40, 0.50, 0.60, and 0.70. The first three are entirely subsonic while the flow at Mach 0.60 has a small shock and the flow at Mach 0.70 has a significant shock.

If we now use this data to reconstruct the flow at a new Mach number, such as 0.67, using traditional POD the results are essentially useless:

POD, Mach 0.67


However, by combining a full order and POD solver we can decompose the spatial domain of the problem and represent the majority of the problem with POD while still solving the full order equations in a small subset of the domain. Here is an example of this method applied to the Mach 0.67 case previously shown, with a factor of five reduction in degrees of freedom from the original problem:

POD with DD, Mach 0.67


We are currently investigating the application of these types of order reduction methods to multidisciplinary design, primarily as a means to reduce the bandwidth of the coupling between multiple disciplines such as aerodynamcis and structures.

Aircraft Design

Here is a link to an AIAA student design project I was involved with:

Stanford Cardinal Design Project

Useful Links

Python- An interpreted, interactive, object-oriented programming language
Scripting Techniques for Scientific Computing
Numerical Python- Multidimensional arrays for Python
PyMat- Python to Matlab interface
Python VTK Pipeline Browser- Browse and modify objects in VTK pipeline
F2PY- Fortran to Python interface generator
Pyfort- Fortran to Python interface generator
pyMPI- Python implementation of MPI
HappyDoc- Extract documentation from Python source code
Style Guide- Guidelines for Python code
Intel® Compilers

Entertaining Links

Piled Higher and Deeper- Life as a grad student

Publications

2005

  PDF   LeGresley, P. A.,"Application of Proper Orthogonal Decomposition (POD) to Design Decomposition Methods," Ph.D. Dissertation, Stanford University, October 2005.

2004

  PDF  LeGresley, P. and Alonso, J.J., "Improving the Performance of Design Decomposition Methods with POD",10th AIAA/ISSMO Multidisciplany Analysis and Optimization Conference, AIAA Paper 2004-4465, Albany, New York, August 30 - September 1, 2004.

  PDF  Alonso, J.J., LeGresley, P., Van der Weide, E., and Martins, J., "pyMDO: A Framework for High-Fidelity Multi-Disciplinary Optimization",10th AIAA/ISSMO Multidisciplany Analysis and Optimization Conference, AIAA Paper 2004-4480, Albany, New York, August 30 - September 1, 2004.

2003

  PDF  LeGresley, P.A., and Alonso, J. J., "Dynamic Domain Decomposition and Error Correction for Reduced Order Models," 41st AIAA Aerospace Sciences Meeting & Exhibit, AIAA Paper 2003-0250, Reno, NV, January 6-9, 2003.

2001

  PDF   LeGresley, P.A., and Alonso, J. J., "Investigation of Non-Linear Projection for POD Based Reduced Order Models for Aerodynamics," 39th AIAA Aerospace Sciences Meeting & Exhibit, AIAA Paper 2001-0926, Reno, NV, January 8-11, 2001.

2000

  PDF   LeGresley, P.A., et. al., "1998/1999 AIAA Foundation Graduate Team Aircraft Design Competition: Super STOL Carrier On-board Delivery Aircraft," World Aviation Congress & Exhibition, AIAA/SAE Paper 2000-01-5535, San Diego, CA, October 10-12, 2000.

  PDF   LeGresley, P.A, and Alonso, J.J., "Airfoil Design Optimization Using Reduced Order Models Based on Proper Orthogonal Decomposition," Fluids 2000 Conference and Exhibit, AIAA Paper 2000-2545, Denver, CO, June 19-22, 2000.

1999

  PDF   LeGresley, P.A., et. al., "The Cardinal, A Graduate Team Aircraft Design," 1999 AIAA Graduate Team Aircraft Proposal, June 1, 1999.

Presentations

2005

  PDF   LeGresley, P.A., "Application of Proper Orthogonal Decomposition (POD) to Design Decomposition Methods," Stanford University, Dissertation Defense, August, 25, 2005.

2004

  PDF  LeGresley, P. and Alonso, J.J., "Improving the Performance of Design Decomposition Methods with POD",10th AIAA/ISSMO Multidisciplany Analysis and Optimization Conference, AIAA Paper 2004-4465, Albany, New York, August 30 - September 1, 2004.

2003

  PDF   LeGresley, P.A., and Alonso, J. J., "Dynamic Domain Decomposition and Error Correction for Reduced Order Models," 41st AIAA Aerospace Sciences Meeting & Exhibit, AIAA Paper 2003-0250, Reno, NV, January 6-9, 2003.

2001

  PDF   LeGresley, P.A., and Alonso, J. J., "Investigation of Non-Linear Projection for POD Based Reduced Order Models for Aerodynamics," Stanford University, Department of Aeronautics and Astronautics, Industrial Affiliates Meeting, April 25, 2000.

  PDF   LeGresley, P.A., and Alonso, J. J., "Investigation of Non-Linear Projection for POD Based Reduced Order Models for Aerodynamics," 39th AIAA Aerospace Sciences Meeting & Exhibit, AIAA Paper 2001-0926, Reno, NV, January 8-11, 2001.

2000

  PDF   LeGresley, P.A., et. al., "1998/1999 AIAA Foundation Graduate Team Aircraft Design Competition: Super STOL Carrier On-board Delivery Aircraft," World Aviation Congress & Exhibition, AIAA/SAE Paper 2000-01-5535, San Diego, CA, October 10-12, 2000.

  PDF   LeGresley, P.A, and Alonso, J.J., "Airfoil Design Optimization Using Reduced Order Models Based on Proper Orthogonal Decomposition," Fluids 2000 Conference and Exhibit, AIAA Paper 2000-2545, Denver, CO, June 19-22, 2000.

  PDF   LeGresley, P.A, and Alonso, J.J., "Airfoil Design Optimization Using Reduced Order Models Based on Proper Orthogonal Decomposition (POD)," Stanford University, Department of Aeronautics and Astronautics, Industrial Affiliates Meeting, April 26, 2000.


Last Modified: Tue Oct 11 15:53:11 PDT 2005

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