Development of a Conservative Model Validation Approach for Reliable Analysis

Abstract

Simulation models are approximations of real-world physical systems. Therefore, simulation model validation is necessary for the simulation-based design process to provide reliable products. However, due to the cost of product testing, experimental data in the context of model validation is limited for a given design. When the experimental data is limited, a true output PDF cannot be correctly obtained. Therefore, reliable target output PDF needs to be used to update the simulation model. In this paper, a new model validation approach is proposed to obtain a conservative estimation of the target output PDF for validation of the simulation model in reliability analysis. The proposed method considers the uncertainty induced by insufficient experimental data in estimation of predicted output PDFs by using Bayesian analysis. Then, a target output PDF and a probability of failure are selected from these predicted output PDFs at a user-specified conservativeness level for validation. For validation, the calibration parameter and model bias are optimized to minimize a validation measure of the simulation output PDF and the conservative target output PDF subject to the conservative probability of failure. For the optimization, accurate sensitivity of the validation measure is obtained using the complex variable method (CVM) for sensitivity analysis. As the target output PDF satisfies the user-specified conservativeness level, the validated simulation model provides a conservative representation of the experimental data. A simply supported beam is used to carry out the convergence study and demonstrate that the proposed method establishes a conservatively reliable simulation model.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2015
Accession Number
ADA623514

Entities

People

  • David A. Lamb
  • David J. Gorsich
  • Hyunkyoo Cho
  • K K Choi
  • Min-yeong Moon
  • Nicholas Gaul

Organizations

  • United States Army Tank Automotive Research, Development and Engineering Center

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Bayesian Networks
  • Calibration
  • Complex Variables
  • Computational Science
  • Computer Simulations
  • Convergence
  • Data Sets
  • Engineering
  • Experimental Data
  • Measurement
  • Optimization
  • Probability
  • Random Variables
  • Reliability
  • Simulations
  • Validation

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference