A team of Sandia experts in aerospace engineering, scientific computing, and mathematics collaborated with researchers at Stanford University to study wind-energy design problems, using computational fluid dynamics (CFD) simulations and uncertainty analyses. The project developed new mathematical uncertainty quantification techniques and applied them, in combination with high-fidelity CFD modeling, to probabilistic wind-turbine design problems. Quantifying uncertainty for this project required analyzing hundreds of simulation scenarios/ three-dimensional high-fidelity computational runs to evaluate fluid dynamic flow past a wind turbine rotor using unstructured sliding meshes. This project contributed to developing the Nalu simulation code, a low-Mach-number CFD solver, scalable to problem sizes on the order of billions of elements
running on hundreds of thousands of cores. The research team reviewed different computational models and discovered that using high-fidelity (CFD) and low-fidelity engineering models in combination to simulate the phenomena provides more reliable results at lower cost. The analysis from this project provides the wind turbine industry with a new paradigm for design, relying more on high-fidelity simulation and less on simple empirical models. As the industry increasingly adopts high-fidelity modeling approaches, new design approaches will lead to greater certainty in wind-turbine performance and design load predictions, resulting in much more cost-effective wind turbines.
Contact: Matthew Barone | firstname.lastname@example.org