High-Fidelity Modeling, Verification, and Validation

Primary Objective

Use high-performance, massively parallel computers to understand and accurately model fundamental physics on appropriate temporal and spatial scales to predict complex, rapidly changing inflow to the wind plant, complex flow within the plant, and individual turbine and wind plant responses (as a whole) to the flows, as well as provide credible assessment of computational accuracy within a verification and validation (V&V) paradigm.

Model development and experimental validation account for the largest segment of the portfolio investment, reflecting both modeling problem scope and expense of experimental measurements. The high-fidelity modeling (HFM) effort develops modular elements, or a modular framework, that users can build into a full model. For example, no single model will span from turbine blade boundary layers to the atmospheric boundary layer in one massive compilation. Instead, each element will be fully validated before being considered for the HFM toolkit. In addition, every model development and experimental validation combination is conducted in a joint and fully integrated V&V process. The verification (evaluation of correct implementation of the assumptions into the software) and validation (evaluation of the model’s ability to reproduce the physical process) structure unites the computational and experimental efforts to assure they achieve results as intended.

Focus Area Goals

  • Assess applicability and limitations of the current modeling approaches and tools used in analyzing wind turbine and wind plant performance
  • Inventory existing observational databases, construct V&V framework, and identify deficiencies for high-performance computational model validation
  • Develop an open simulation environment for high-performance computing (HPC) model development
  • Develop the next generation of HPC-based computational tools
  • Plan and execute research-grade measurements within a formal V&V framework to acquire benchmark validation databases
  • Assess existing wind plant siting and operating paradigms using new HPC modeling capabilities to determine performance enhancement potential
  • Propose innovative technology and operational paradigms to optimize new installation cost and performance