Computational Applications for Energy Research
NREL's computational applications integrate applied mathematics techniques with high-performance computing to analyze, simulate, and derive insights and advance complex energy research.
Computational simulations of energy technologies enable rapid prototyping, design and process optimization, physical insights and discoveries, and reliability engineering. These capabilities translate to rapid development and reliable deployment of more efficient and more affordable renewable energy technologies.
Computational scientists are domain scientists using computers as their primary method of investigating scientific, engineering, and analysis problems. NREL experts in this space focus their research on:
- Techniques for efficient numerical solution of equations describing the evolution of physical processes—crucial for understanding energy technologies (e.g., fluid flow, chemical reactions, molecular dynamics, technoeconomic systems) often using high-performance computing (HPC) systems
- Data-driven methods for developing high-speed and low-cost alternatives to direct numerical solutions
- Application-oriented questions that can be solved using these models and simulations. Such questions include the design, optimization, and efficient operation of energy technologies.
Biofuels
NREL's computational research in biofuels delivers tools for the simulation of the full life cycle, including initial processing, chemical conversion, and end use.
BDEM: Discrete-Element Simulator for High-Solids Granular Flows (GitHub)
A discrete element method-based simulation tool for modeling high-solids granular
flows that include polydispersity, heat transfer, moving boundaries, and chemistry.
The solver provides facilities for simulating spherical/nonspherical particles with
modified contact and friction models in complex dynamic geometries defined using level-sets
or triangulated files.
Biomass Feedstock Conversion Interface Handling Computational Models
Simulating the handling and flowability of organic biomass feedstock in coupled feed
systems
Mesoflow: Mesoscale Modeling Tool for Biomass Pyrolysis and Catalytic Upgrading
AMReX-based code for catalytic upgrading and pyrolysis
Virtual Engineering of Biofuels Software
Pipeline of simulation capabilities—including simulation of pretreatment, enzymatic
hydrolysis, fermentation processes—for the conversion of biomass into second-generation
biofuels
Mesoflow: Mesoscale Modeling Tool for Biomass Pyrolysis and Catalytic Upgrading
AMReX-based code for catalytic upgrading and pyrolysis
Adaptive Computing
Framework for performing multi-fidelity modeling—including in support of catalytic
upgrading
Sustainable Aviation Fuels End Use
High-fidelity simulations of biofuels used in aircraft engines to affect performance,
fuel economy, and reliability
Energy Storage
Computer simulations can quickly and affordably evaluate a new battery's lifecycle performance.
Discrete-event-based simulations of the degradation of Li-ion cells
Decarbonization and Sustainability
Large-scale simulations of industrial sector processes aimed at reducing emissions
Technologies for extracting fresh water from higher salinity sources are an urgent need in regions with diminishing fresh-water resources.
Exagoop (GitHub)
An open-source material point method solver that efficiently simulates the dynamics
of highly deformable continuum phases
NMACFoam Software for Ultra-High-Pressure Reverse Osmosis Membrane and Module Design
and Optimization
Ultra high-pressure reverse osmosis process for water purification
Adaptive Computing
Framework for performing multi-fidelity modeling including machine-learning-based
electrical controllers that learn on the fly from simulations of the electrical demands
of communities of buildings
Event-driven simulations of vehicle traffic and mobility systems can help evaluate strategies to relieve congestion and reduce emissions from vehicles. See SPADES: Scalable Parallel Discrete Events Solvers.
Sustainable Combustion and Carbon Capture
NREL’s research in sustainable combustion is enabled by our open-source Pele Software Suite PeleC, a compressible turbulent reacting flow solver.
High-fidelity simulations of biofuels used in aircraft engines to affect performance, fuel economy, and reliability
Solar Power
or simulations of halide perovskites to help discover better manufacturing techniques
Simulates wind loading and stability in solar-tracking PV systems
Wind Power
NREL's computational research in wind energy includes simulations of the atmosphere to inform optimal wind farm sites, simulations of wind turbine wakes to inform ideal arrangement of turbines, and simulations of wind turbine blades to inform structural and aerodynamic design to maximize power production and reliability.
A prerequisite for accurate simulations of wind farms, atmospheric boundary layer modeling can predict how much wind is available—which informs locations for new wind farms.
In offshore wind applications, atmospheric modeling is complicated by the presence of buoyancy effects and ocean-air interactions.
Exawind Software Suite
AmrWind AMReX-based solver for atmospheric flows, equipped with buoyancy modeling
and an efficient hierarchical mesh topology for boundary layer simulations
Energy Research and Forecasting Model
AMReX-based mesoscale atmospheric wind code accounting for compressibility effects,
terrain modeling, and atmosphere-ocean interactions
Wind-farm-scale simulations predict evolution of wind turbine wakes and how they affect the power production of the farm.
During design, farm-scale simulations can inform optimal siting of turbines to maximize power production. During operation, farm-scale simulations can inform how to rotate turbines and adjust blade angles to maximize power production and mitigate effect of wake on other turbines.
ExaWind Software Suite
AmrWind AMReX-based solver for atmospheric flows with turbine (actuator line and disk)
models
Wind turbines in farm-scale simulations are often represented by actuator or wake models that do not have moving parts and introduce uncertainty into the calculations. In blade-resolved simulations, higher fidelity simulations are achieved by directly simulating the moving geometry of the wind turbine. This is not only more accurate but also provides insights into the effect of the turbine blade design on the power production and structural loads on the blade. It also enables fluid-structure interaction simulations, which can capture unsteady vibrations of blades, an important mode for structural failure.
Nalu-wind
Fully unstructured, Trilinos-based solver for blade-resolved wind problems, simulating
flows over complex, moving bodies. Part of the Exawind software suite (a composite
solver that uses the AMR-Wind solver for atmospheric boundary layers), Nalu-Wind solves
for the flow near wind turbines.
Wind Turbine Stall Modeling
Improved modeling of separated flows and airfoil stall
G2Aero Software: Aerodynamic Shape Parametrization Using Separable Shape Tensors
Data-driven framework uses a matrix manifold to parametrize a manifold of airfoil
shapes
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