ECP ALCC Quarterly Report (Oct-Dec 2017)

Technical Report · Wed Jan 17 04:00:00 EST 2018

DOI:https://doi.org/10.2172/1513455· OSTI ID:1513455

Sprague, Michael A. ^[1]; Thomas, Stephen ^[1]; Rood, Jon ^[1]; Hu, Jonathan J. ^[2]; Melvin, Jeremy ^[3]

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1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
3. Univ. of Texas, Austin, TX (United States)

The scientific goal of ExaWind Exascale Computing Project (ECP) is to advance our fundamental understanding of the flow physics governing whole wind plant performance, including wake formation, complex terrain impacts, and turbine-turbine-interaction effects. Current methods for modeling wind plant performance fall 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. Thus, our ten-year exascale challenge is the predictive simulation of a wind plant composed of O(100) multi-MW wind turbines sited within a 100 km2 area with complex terrain, involving simulations with O(100) billion grid points. The project plan builds progressively from predictive petascale simulations of a single turbine, where the detailed blade geometry is resolved, meshes rotate and deform with blade motions, and atmospheric turbulence is realistically modeled, to a multi turbine array in complex terrain. The ALCC allocation will be used continually throughout the allocation period. In the first half of the allocation period, small (e.g., for testing Kokkos algorithms) and medium (e.g., 10K cores for highly resolved ABL simulations) sized jobs will be typical. In the second half of the allocation period, we will also have a number of large submittals for our resolved-turbine simulations. A challenge in the latter period is that small time step sizes will require long wall-clock times for statistically meaningful solutions. As such, we expect our allocation-hour burn rate to increase as we move through the allocation period.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE Office of Science (SC)
• DOE Contract Number: AC04-94AL85000; NA0003525
• OSTI ID: 1513455
• Report Number(s): SAND--2018-0425R; 659955
• Country of Publication: United States
• Language: English

Related Subjects

17 WIND ENERGY
42 ENGINEERING
97 MATHEMATICS AND COMPUTING