Computational Phase-Field Modeler
Posted on: June 27, 2019
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An opportunity exists for a PhD - level computational scientist to
develop and utilize computational models and data analysis tools to
support NETL's solid oxide fuel cell (SOFC) research. For this
position, all models are being developed using a phase field
Research efforts focus primarily on the following tasks:
- Development, refinement, and calibration of models that
accurately represent relevant physical and chemical processes
(including multiphase flow, electrochemistry, heat transport,
chemical reactions and porous media transport phenomena) that
determine overall performance within a fuel cell.
- Development, refinement, and calibration of degradation models
that accurately represent any relevant physical, chemical, and
electrochemical processes that modify the overall performance of a
fuel cell during operation under relevant operating conditions. For
this position, particular interest is given to particle coarsening
and the formation of secondary phases at solid-solid and gas-solid
- Combination of the performance and degradation models into a
single framework to allow for large-scale parametric studies to
minimize long-term performance degradation for a given SOFC system
by adjusting the composition, structure, and/or operating
conditions of the cell.
- Collaboration with experimentalists to define the experiments
necessary for proper calibration and validation of the developed
models and to provide optimized fuel cell compositions and
structures that can be tested experimentally.
- The candidate will have a relevant PhD degree and 2 years prior
relevant experience; will possess significant experience in
identified computer programming (C++, FORTRAN, MATLAB, Python) and
will have experience in programming simulation jobs within a
high-performance computing environment (e.g. parallel processing
and programming in a message passing interface (MPI)
- The candidate should possess excellent communication skills and
have experience collaborating with experimentalists to request
experimental data most useful to model development and to guide
experimental conditions to gain a better understanding of the
underlying physics and chemistry determining overall cell
Additionally, the candidate will have a strong background in the
- Numerical modeling, including ordinary differential equations
and partial differential equations, and the use of stiff equation
solvers with both implicit and explicit modeling schemes for
partial differential equations.
- Phase field models for microstructure evolution modeling,
including coupling multiple fields and multiple diffusion
mechanisms in the diffusive-interface framework.
- Modeling electrochemical systems on the micron-to-millimeter
scale, including interpreting and coding electrochemical and
chemical reactions, modeling fluid dynamics and mass/charge
transport in porous materials, and scale bridging to pass
simulation data effectively across multiple length scales.
- Familiarity with submitting jobs and managing simulations and
data within a supercomputing facility using Slurm, including
parallelization of tasks when possible.
- Atomistic scale simulation, such as density functional theory,
molecular dynamics and kinetic Monte Carlo, to calculate
theoretical energetic and kinetic parameters for phase field model
- Machine learning techniques such as neural networks and
Gaussian processes, as well as Monte Carlo simulation for Bayesian
calibrations, used in the development of reduced order models for
scale-bridging efforts and high throughput computational
- Generating synthetic 3D microstructures with specific
microstructural parameters using the software DREAM.3D.
- Utilizing software such as Tecplot and Paraview for
visualization and analysis of 3D data.
- With respect to solid oxide fuel cells, the preferred candidate
should have a deep understanding of factors impacting long-term
fuel cell performance, such as performance limitations in cell
components and common degradation phenomena in SOFCs.
The preferred candidate will have more than two years postdoctoral
experience and have experience in modeling of solid oxide fuel
cells in a collaborative work environment such as the National
Energy Technology Laboratory.
Keywords: Leidos, Aloha , Computational Phase-Field Modeler, Other , Albany, Oregon
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