NREL's computational science experts use advanced high-performance computing (HPC) capabilities to gain new insights and drive innovations in energy efficiency and renewable energy technologies.
Computational science at NREL uses HPC to propel technology innovation as a research tool by which scientists and engineers find new ways to tackle our nation's energy challenges—challenges that cannot be addressed through traditional experimentation alone. NREL's state-of-the-art computational modeling and predictive simulation capabilities reduce the risks and uncertainty that are often barriers to industry adopting new and innovative technologies, thereby accelerating the transformation of our nation's energy system.
Enabling High-Impact Research
NREL's computational science capabilities enable high-impact research. Some recent examples include:
Modeling the transport of species through plant cell walls for bioenergy applications
Performing large-scale analysis of the U.S. residential building stock for potential energy-efficiency projects
Running computational fluid dynamics and finite element analyses to help design, build, and field-test an engineering prototype of a laser-based geothermal well completion tool, and applying high-fidelity simulations to wave energy converters
Employing density functional theory to investigate cation degradation pathways in alkaline-membrane fuel cells and predict the thermodynamic and kinetic behaviors of perovskite and spinel materials of interest for solar thermochemical water splitting
Investigating third-generation advanced high-strength steels for automotive applications
Investigating wind power plant optimization at both the wind turbine and plant system level
Combinatorial screening of materials, efficiency gains in organic photovoltaic materials.
NREL focuses its computational science capabilities in the following areas.