Leveraging Multi-Fidelity Modeling for Computational Shock Response Prediction

Abstract

The Navy invests significant time and effort into shock testing because understanding failure modesfrom explosive events is a critic,al facet of asset performance. However, the current state-of-the-practicefor shock testing is rather destructive and costly, making,it an impractical long-term solution.The Navy has recently begun to pivot to digital twins as virtual representations of its assets,for tracking service life, maintenance, and repairs. The ability to perform shock testing in the virtual environment on these digita,l surrogates would constitute a transformational improvement as compared to the current practice. However, this can only be accompli,shed with detailed modeling of the physics of failure for shock loads, which often leads to numerical simulations with incredibly ex,pensive, if not prohibitive, computational costs.This program aims to leverage multi-fidelity modeling methods as a means for reliev,ing thecomputational burden of shock response prediction without sacrificing accuracy. Multi-fidelity approachesutilize low-fidelity, models of a given system that can be run with minimal computational costs, albeit with reduced accuracy, and then intelligently com,bine those results with a few select results from a much more computationally expensive high-fidelity model. This practice has been,used extensively in aerospace for unsteady, turbulent flow simulations, but this program seeks to brings those methods and ideas ove,r to computational shock response prediction. A wide-ranging literature review of the current state-of-the-art in multi-fidelity mod,eling will be prepared, along with strategies for low-fidelity models of shock response and discrepancy correction factors. In addit,ion, this program has an option to develop a proof-of-concept model to more deeply explore the proposed multi-fidelity methods and s,trategies.APPROVED FOR PUBLIC RELEASE

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 13, 2022
Source ID
N000142212508

Entities

People

  • Patrick T Brewick

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Notre Dame

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Systems Analysis and Design

Technology Areas

  • Space