Team 5: Multi-objective design of a fuel tank

Monday, June 18, 2012 - 10:40am - 11:00am
Laura Lurati (The Boeing Company)
Algorithms for design optimization are increasingly able to handle complex problem formulations. We will consider the design of a fuel tank consisting of four different disciplinary sub-system components- structures, aerodynamics, cost, and systems. This is a multi-disciplinary, design problem with multiple competing objectives. We will examine several formulations and how to best match the problem formulation with the choice of optimizer.
As the complexity of the problem grows, so does the amount of data generated during an optimization. This adds on the challenge of interpreting the data. We will investigate different methods for representing the data. Visualization methods will be considered in two groups- those suited to developing a greater understanding of the problem (for team members) and those suited to presenting results (for customers).

This project is intended to give a flavor of what an industrial mathematician does throughout the lifecycle of a given project. This project has 3 steps:
  1. Model the various components representing each discipline (some components will be provided) and link them together into a system.

  2. Implement solution to multi-objective optimization problem, including choosing which problem formulation to use and which optimization libraries to use.

  3. Explore various methods of visualizing data to best communicate differences between designs.

Prerequisites: All team members must have some computing skills (Matlab, Java, Python, or C++). Some familiarity (or interest) in design optimization is desired.

Schuman, T., De Weck, O., Sobieski, J. (2005) Integrated System-Level Optimization for Concurrent Engineering with Parametric Subsystem Modeling AIAA 2005-2199.

De Weck, O. (2004), Multidisciplinary System Design Optimization (MSDO): Decomposition and Coupling, Module 6 Notes, MIT OpenCourseWare 16.888 / ESD.77, Massachusetts Institute of Technology.

Cramer, E. J., J. E. Dennis, Jr., P. D. Frank, R. M. Lewis, G. R. Shubin (1994), Problem formulation for multidisciplinary optimization, SIAM Journal of Optimization 4 (4): 754-776.