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Impacts

Read about the impacts of NREL's innovations in computational science.

Visualization at NREL: Toward Exascale Wind Simulation

2018

Challenge

A key challenge to wide-scale deployment of wind energy in the utility grid without subsidies is predicting and minimizing plant-level energy losses—which are currently estimated to be 20% in relatively flat areas, and much higher in regions of complex terrain. Current HPC simulation tools and methods for modeling wind plant performance fall far short due to insufficient model fidelity and inadequate treatment of key phenomena, combined with a lack of computational power necessary to address the wide range of relevant length scales associated with wind plants.

Achievement

In the Exascale Predictive Wind Plant Flow Physics Modeling project, also referred to as ExaWind, NREL is leading the development of an exascale modeling and simulation capability (coupled fluid and structural mechanics) to understand the fundamental multiphysics, multiscale flow phenomena in large wind plants, including complex terrain. NREL and partners have created a new blade-resolved model of a large modern wind turbine, enabling scientists and engineers to begin understanding the complex flow physics in multi-turbine wind farms that will take advantage of future exascale modeling and simulation capability.

Impact

ExaWind will result in advancements in the development of a next-generation wind farm simulation capability and the understanding of how the capability can answer important science questions challenging the wind energy community. It will also ensure new wind farm simulation code scales well on today’s petascale systems and is well positioned to utilize first-generation U.S. exascale systems.

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Building The World's Largest Experimental Materials Database

2018

Challenge

In working on new thin-film materials for energy applications, scientists synthesize many samples of data, but only a fraction of what they learn along the way is ever published.

Achievement

NREL data scientists and architects consolidated these data—more than 140,000 sample entries—into one extensive experimental materials database, organizing a decade’s worth of research into the largest such database in the world.

Impact

This database can significantly accelerate research related to or involving thin-film materials, providing tremendous opportunity for data-driven research and knowledge discovery. Collaborations with commercial partners (e.g., Citrine, Apple, and Google) and other research organizations (e.g., NIST, SLAC, Argonne, and Colorado School of Mines) promise to continue to expand the breadth and depth of this key materials data resource.

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