In-Situ Multiphysics Characterization of Mechanical Behavior of Materials at Different Strain rates

Abstract

High strain rate deformation is very important for numerous military and civilian applications. Various impact events, blast, and explosions are typical military examples where high rate deformation occurs. For civilian applications, numerous forming and machining operations of metals induce large strains at a high rate on materials. In any case, the material behavior, strength, ductility, shear localizations, and energy absorption are strongly influenced by the deformation rate. Because of this, engineers and scientists have tried to build good understanding of material performance in such dynamic events with varying success. The success has been good with ‘simple’ materials where the structure of the material does not change too much, but as modern materials are becoming more complex there is a strong need for more complex characterization techniques and more powerful tools to analyze and quantify the experimental observations. Because of this we propose development of methodology that allow simultaneous measurements of full field deformation and temperature, HE-XRD, and mechanical performance of the material in a wide range of strain rates. We argue that the lack of exact information and details of the high strain rate microplasticity and ductile fracture are a tight bottleneck for the development of both better materials, but also accurate numerical models. We also propose that the results of the new multimodal experiments are used in data driven modelling approaches to attain material constitutive descriptions based on artificial intelligence (AI) that can be used in, for example, Finite Element (FE) codes. A promising next step is the combination of multimodal experimental procedures with data driven modelling approaches to enhance predictive capabilities of complex processes occurring during dynamic loading. From the military perspective, this project will provide useful information about the material behavior, but more importantly, the methodology developed in this work will open doors for many new investigations. In the future, the ballistic performance, ductile failure, shear localization and strain rate dependent plasticity of various military materials can be studied using the same methodology developed in this work. The accurate prediction of the plasticity and failure would significantly improve the design of armors and eventually safety of military personnel, as well as improve the design and material selection criteria for forming operations including high rate deformation.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 22, 2024
Source ID
FA86552317058

Entities

People

  • Mikko Hokka

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force

Tags

Fields of Study

  • Engineering

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Mechanical Engineering/Mechanics of Materials.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy