Predicting Performance Margins

Project Organization

Task 1: Nanoscale framework for crack initiation and growth in body-centered cubic (bcc) transition metals

The goal of this task is to develop an experimentally validated model for the earliest stages of ductile failure and initiation in bcc transition metals. The fundamentals of  plasticity among bcc transition metals are studied through both simulation and experimental endeavors at the atomistic through nanometer length scales.

Specific undertakings include:

  • Atomistic simulations to examine the formation of stable voids under stress and/or diffusive flux.
  • Dislocation dynamics and/or molecular dynamincs simulations of initial growth of complex void structures.
  • Atomic resolution imaging of void structures in model materials using TEM, diffraction contrast imaging, and atom probe.
  • In-situ TEM straining to observe void growth at the sub-microstructrual level.
  • Characterization of void size, shape, structure, and distribution at the nanoscale.

Task 2: Microscale effects of defect fields in bcc transition metals and their alloys

The goal of this task is to develop physically-based,  and experimentally validated models for damage accumulation, void coalescence, and  mechanical variability in bcc transition metals and their alloys.   Details of the dominant mechanisms occurring during plastic deformation  are studied through simulation and experiments at the mesoscale.

Specific undertakings include:

  • Derivation of model geometry libraries, informed by experimental microstructures and results  from Task 1.
  • Simulating  strain interactions and defect coalescence for multiple defects of varying  arrangements, using defect properties determined in Task 1.
  • Performing  a computational and experimental survey of mechanical response as a function of  microstructural variability.
  • Simulating  variability in deformation localization for single, nano- to micro-scale defects  embedded in microstructures
  • Micro-tension experiments to impart controlled deformations and provide  high-resolution mechanical test data for model structures.
  • Coupling experimental characterization of strain near defects using EBSD and digital image correlation  with  simulation results.

Task 3:  Connecting microstructural variability to performance margins in bcc transition metals and other structural alloys

This  task has two goals: (1) to develop a statistical connection between geometry,  microstructure, and failure in bcc transition and other structural alloys, and (2)  deliver a product to  designers and analysts for improved, statistically-sound predictivity.  Simulations and experiments within this task  are performed at continuum scales.

Specific undertakings include:

  • Development of a physically-based, stochastic constitutive models, using results from Task 2, that  include the effect of microstructural variability and defect properties on  mechanical properties of bcc transition metals and other alloys.
  • Utilization of the stochastic constitutive model to perform a phase-space analysis of the  extent and impact of microstructural variability on mechanical performance of  bcc transition metals and  alloys.
  • Development of a statistical model for uncertainty based on microstructural variability for bcc transition metals and other structural alloys.
  • Using  SEM and serial sectioning to characterize 3D microstructures of structural alloy weldments.
  • Derivation of model geometry libraries using experimental structural alloy microstructures as templates.
  • Simulation of the effects of pore distribution on strength, using a continuum scale finite  element model, for realistic, 3D, porous weld structures in a structural alloy.
  • Development of a stochastic constitutive model that includes the effect of microstructural  variability on mechanical properties of a structural metal.
  • Implementation of the stochastic constitutive model into production code (SNL-Sierra) to be used by  designers and analysts.
  • Perform formal QMU (quantification of margins and uncertainties) analysis on a structural metal weldment using the aforementioned microstructural variability model.
  • Extending  the stochastic constitutive model to additional mission-essential structural metals and alloys.

Task 4:  Connecting processing variability to performance margins in structural alloys

The goal of this task is to increase understanding and produce quantitative descriptors for the effect of materials processing on material properties and performance in structural alloys.

Specific undertakings include:

  • Leverage results from Task 3, to improve predictive models for process-driven microstructural formation inclusive of microstructural variability.
  • Development of a physically-based, experimentally derived, stochastic model for processing defects in structural alloys and their resultant effect on micro-or macroscale properties.