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Multifidelity Uncertainty Quantification with Applications in Wind Turbine Aerodynamics

Conference ·
DOI:https://doi.org/10.2514/6.2019-0542· OSTI ID:1547242
 [1];  [1];  [2];  [2]
  1. University of Colorado
  2. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
+ Show Author Affiliations

The propagation of input uncertainty through engineering models allows designers to better understand the range of possible outcomes resulting from design decisions. This could lead to greater trust between modelers and stakeholders in the wind energy industry. In this study, we apply multilevel-multifidelity Monte Carlo sampling to flow over an airfoil, assuming uncertainty in the inflow conditions, and characterize the associated computational savings compared to standard Monte Carlo approaches. The truth model is provided by an airfoil simulation with a very fine computational time step, and auxiliary lower-level models are provided by simulations with coarser time steps. Reynolds-averaged Navier Stokes and detached eddy simulations are used to obtain two different model fidelities. The primary quantity of interest for this analysis is the lift force, which is examined for a range of angles of attack. We launch an initial set of 'trial' samples to determine the optimal allocation of model evaluations, and these trial evaluations are used to inform a larger sampling effort. Using the multilevel-multifidelity approach, we achieve roughly an order of magnitude variance reduction in expected lift as compared to the standard Monte Carlo approach with an equivalent computational cost.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1547242
Report Number(s):
NREL/CP-5000-74498
Resource Relation:
Conference: Presented at the AIAA SciTech 2019 Forum, 7-11 January 2019, San Diego, California
Country of Publication:
United States
Language:
English

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17 WIND ENERGY
wind energy
airfoils
uncertainty
aerodynamics
modeling