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Hardening Advanced Methods for Predicting 3D Unsteady Flows Around Wind Turbines for Industrial Use

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0013231
Agency Tracking Number: 215754
Amount: $149,923.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 02c
Solicitation Number: DE-FOA-0001164
Solicitation Year: 2015
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-02-17
Award End Date (Contract End Date): 2015-11-16
Small Business Information
34 Lexington Avenue
Ewing, NJ 08618-2302
United States
DUNS: 222248930
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Glen Whitehouse
 (609) 538-0444
Business Contact
 Eileen Burmeister
Title: Ms.
Phone: (609) 538-0444
Research Institution
 Georgia Tech Research Corp/Georgia Institute of Technology
 Marrilyn Smith
270 Ferst Street
Atlanta, GA 30332-0150
United States

 (404) 894-3065
 Nonprofit College or University

Wind power plays an increasingly important role in satisfying the power needs of the U.S., and serves to reduce dependence on fossil fuels. With increased penetration, significant maintenance costs and reductions in power generation have underscored the need to predict the unsteady loading related to turbine configuration, layout and off-design wind conditions as well as importance of accounting for inter-turbine interactions in wind farms. Contemporary turbine design tools fail to account for the unsteady fluid structure interactions that drive costly fatigue loads, and thus, the research community has started utilizing High Performance Computing (HPC) solvers to investigate these phenomena. Unfortunately, such tools often require dedicated technical experts to generate reliable predictions and are too complicated and expensive for general industrial use. This problem is exacerbated for wind turbines given the unsteady coupling between blade motion, flexibility, wake aerodynamics and the interaction with other turbines and the turbulent atmosphere. In a recently completed DOE STTR, Continuum Dynamics, Inc. (CDI) and Georgia Institute of Technology (GIT) developed an advanced method for predicting wind turbine fatigue and wind farm aeromechanics. While this effort successfully demonstrated improved analysis capabilities, the HPC-based methods still require expert users to exploit their capabilities.
The proposed effort builds upon this prior work and the experience of CDI and GIT in developing numerical methods, along with collaborators in the wind energy industry (NREL), to extend, harden and ultimately transition these numerical methods to industry. Phase I would commence addressing critical code hardening issues such asreliable MPI error handling, automated input generation and checking, and throughput optimization. One of themost significant hurdles to transitioning solvers to industry is that while many HPC-level solvers are very capable, they require complete adoption, whereby legacy software is relegated to the scrap-heap. Given significant investment in legacy software, this barrier is often insurmountable, and can be seen throughout the industry where simplified models are used for routine engineering. CDI has adopted a successful modular software strategy to address this barrier, where advanced solvers components are packaged as libraries, thus enabling industry to adopt the improved numerical methods without the loss of institutional knowledge. Through standardized interfaces, this, in effect, facilitates the development of traceable, hierarchical HPC analysis tools that no longer need expert users. In this vein, Phase I would culminate with the proof-of-concept interfacing between components of the wind turbine aeromechanics methods with NRELs industry standard wind turbine computer-aided engineering code FAST.Commercial Applications and Other Benefits: A successful STTR effort would produce a robust, validated multidisciplinary computational tool for integrated wind turbine design and analysis, along with individual solver libraries for more general application. This tool directly addresses the limitations of current HPC 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, as is evidenced by the included letter of support, additional commercialization is anticipated through application to other vorticity dominated flow filed such as rotorcraft, automotive and bluff-bodies.

* Information listed above is at the time of submission. *

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