From Materials to Missions Assess-Predict-Optimize: A Computational Approach to Adaptive Design
Abstract
We develop an Assess-Predict-Optimize (APO) strategy for the adaptive design of optimal missions for critical components and systems. We first Assess the system - through non-destructive inverse procedures for evaluating the system characteristics of interest: this yields the many possible realizations of the system. We then Predict future behavior of the system - through various modeling and computational procedures: this translates the uncertainties in system characterization into ranges of performance. Finally, we Optimize the system mission - through mathematical programming methods: this provides the best possible configuration and deployment schedule relative to the design objectives and now-identified (but uncertain) system characteristics. The essential mathematical ingredients of our approach are twofold. First, we employ Reduced-Basis Output Bound Methods: dimension reduction - the rational construction of highly efficient ("real-time" response) system-specific approximation spaces that reflect the low-dimensional parametric manifold on which a component "evolves" during design and operation; and a posteriori error estimation - relaxation of the classical error-residual equality that provide inexpensive bounds for the prediction error. Second, we employ Mathematical Programming Methods: techniques which incorporate our reduced-basis output bounds for efficient minimization of objective functions with strict adherence to constraints even in the presence of uncertainty.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2001
- Accession Number
- ADA418927
Entities
People
- Anthony T. Patera
Organizations
- Massachusetts Institute of Technology