Error Estimations and Adaptive Techniques for Nonlinearized Parametrized Equations.

Abstract

Many problems in science and engineering concern the determination of steady-state equilibrium solutions of nonlinear equations. In general, for such problems, interest centers not so much of the computation of a few specific equilibria rather than on an assessment of the response of the system to the action of various external or internal influence quantities. In other words, we are interested in the effect of changes of the values of certain parameters upon the computed equilibria. Thus, other than in the typical linear case, for nonlinear problems we usually have to consider equations of the form which depend nonlinearly not only on the state variable z but also on a parameter vector lambda. Typically, z varies in some infinite-dimensional space Z while lambda belongs to a space lambda with some finite dimension m > or = z of (1.1) for a few a priori specified parameter vectors lambda. Instead, we have to look at the solutions of (1.1) as points (z, lambda) in the product X = Z x lambda of the state and and parameter space. Under fairly general conditions, the set of all solutions (z, lambda) of (1.1) in X forms a smooth surface -- or more precisely an m-dimensional differentiable manifold -- in that space. When (1.1) represents the equilibrium equation of a mechanical system, this manifold has been called the equilibrium surface of the system.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1984
Accession Number
ADA142041

Entities

People

  • Werner Rheinboldt

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Boundary Value Problems
  • Closed Loop Systems
  • Computations
  • Coordinate Systems
  • Differential Equations
  • Engineering
  • Equations
  • Feedback
  • Mathematics
  • Mechanical Engineering
  • Navier Stokes Equations
  • New York
  • Numerical Analysis
  • Partial Differential Equations
  • Statistics
  • Theorems
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Control Systems Engineering.
  • Graph Algorithms and Convex Optimization.
  • Statistical inference.

Technology Areas

  • Space