Quantifying Uncertainties in Parameterizations of Strength Models of Rolled Homogeneous Armor: Part 3, Python-Based Workflow

Abstract

This report describes a workflow, based on the Python language and the Bayesian software tools PyStan and PyMC3, that has been used to obtain information on strength model parameters in rolled homogeneous armor that can be used in uncertainty propagation analyses. This workflow is supplemented with an illustration of how an approximate interval predictor model can be implemented using the Python software package SciPy. It is hoped that this workflow may serve as a source of example code for other CCDC Army Research Laboratory researchers who wish to obtain results that facilitate uncertainty quantification.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2019
Accession Number
AD1082376

Entities

People

  • J. J. Ramsey

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Bayesian Networks
  • Computer Programming
  • Computer Programs
  • Crystal Structure
  • Data Analysis
  • Databases
  • Information Science
  • Language
  • Military Research
  • Monte Carlo Method
  • Probability
  • Programming Languages
  • Rolled Homogeneous Armor
  • Specific Heat
  • Statistics
  • Three Dimensional
  • Two Dimensional

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Metallurgy

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference