Advanced Methods for Predicting 3D Unsteady Flows Around Wind Turbines
Wind power has an important role in satisfying the power needs of the United States. Since wind power is a clean renewable source of energy, it also serves an important role in reducing dependence on fossil fuels, in particular foreign oil supplies, as well as reducing greenhouse gas and carbon emissions. Unfortunately, significant maintenance costs, recently highlighted by a series of blade failures, can be a direct result of unsteady blade loading and wake interactions related to configuration, installation layout and off-design wind conditions. Much research has been performed to understand the aerodynamic loading on isolated wind turbines, but little has been done to understand and mitigate the fluid-structure-interactions (FSI) between wind turbines, atmospheric turbulence, and local terrain that contribute to structural fatigue and characteristic noise. This effort will develop an advanced methodology for accurately capturing the nonlinear FSI of the blade, long period wakes, and unsteady effects influencing wind turbine fatigue and noise-inducing FSI. This methodology will be capable of quantifying many of these phenomena so that modifications can be made to address these issues early in the design process of turbines and wind farms. In addition, as inflow models of the atmospheric boundary layer (ABL) under development through other funding mechanisms (by experts in that field) become available, they can be coupled with this methodology, via coupling mechanisms proposed in this effort. Thus a successful effort will pave the way for the development of quieter, more efficient wind turbines and wind farms with enhanced longevity and reduced maintenance costs. The proposed 9 month (36 week) effort seeks to build upon the mutually supporting experience of the team of Continuum Dynamics, Inc (CDI) and Georgia Institute of Technology (GIT) in wind turbine analysis, unsteady fluid dynamics, FSI, and noise prediction. It leverages prior and ongoing research rotorcraft aerodynamics and wake prediction to directly address the issue of wind turbine FSI. To address the inherent numerical diffusion of vorticity in RANS methods, this effort will apply CDIs VorTran-M to long age wakes, and capture near-body wakes via RANS coupling. For this effort, NASAs FUN3D massively parallel, unstructured grid RANS analysis, capable of hybrid RANS-LES turbulence modeling, will be used as the demonstration CFD solver. The FUN3D methodology is also capable of modeling the FSI of turbine blades through coupling with computational structural dynamics (CSD) methods, such as DYMORE and RCAS. Proposed follow-on work includes the integration of the FUN3D/VorTran-M tool with an acoustic propagation tool for accurate noise prediction, and evaluation on several configurations. This tool, consisting of a fully-coupled near-body CFD-CSD methodology, VorTran-M module and acoustic propagation model, will be able to address both near- and far-field interactional aerodynamics problems unique to wind turbines, in particular multiple rotor-tower and rotor-wake interactions, unlike current RANS-based simulation tools, that lead to structural vibration, fatigue and interactional acoustics. Commercial Applications and Other Benefits: A successful SBIR effort would produce a validated multidisciplinary computational tool for integrated wind turbine design and analysis that builds upon CDIs VorTran-M wake module and NASAs FUN3D CFD system. This tool directly addresses the limitations of current CFD techniques for predicting FSI problems such as unsteady turbine blade loading and situational interactions. Based upon a modest market entry, combined sales, and associated service work, could generate ~$3M in sales over several years, with major cost savings attributed to improved prediction of FSI to customers and lower maintenance costs for end users. Moreover, this tool will be adept at predicting other vorticity dominated flow filed such as rotorcraft, automotive and bluff-bodies.
Small Business Information at Submission:
Research Institution Information:
Continuum Dynamics, Inc.
34 Lexington Avenue Ewing, NJ -
Number of Employees:
George Institute of Technology
School of Aerospace Engineering 0150
270 Ferst Drive
Atlanta, GA 30332-0150