U.S. Department of Energy Reference Model Program RM1 [electronic resource] : Experimental Results

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Tác giả:

Ngôn ngữ: eng

Ký hiệu phân loại: 333.914 *Water for generation of energy

Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2014

Mô tả vật lý: Size: 22 p. : , digital, PDF file.

Bộ sưu tập: Metadata

ID: 258676

 The Reference Model Project (RMP), sponsored by the U.S. Department of Energy?s (DOE) Wind and Water Power Technologies Program within the Office of Energy Efficiency & Renewable Energy (EERE), aims at expediting industry growth and efficiency by providing non-proprietary Reference Models (RM) of MHK technology designs as study objects for open-source research and development (Neary et al. 2014a,b). As part of this program, MHK turbine models were tested in a large open channel facility at the University of Minnesota?s St. Anthony Falls Laboratory (UMN-SAFL). Reference Model 1 (RM2) is a 1:40 geometric scale dual-rotor axial flow horizontal axis device with counter-rotating rotors, each with a rotor diameter d<
 sub>
 T<
 /sub>
  = 0.5m. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADVs) aligned with each rotor and the midpoint for RM1. Flow conditions for each case were controlled such that depth, h = 1m, and volumetric flow rate, Q<
 sub>
 w<
 /sub>
  = 2.425m3s<
 sup>
 -1<
 /sup>
 , resulting in a hub height velocity of approximately U<
 sub>
 hub<
 /sub>
  = 1.05ms<
 sup>
 -1<
 /sup>
  and blade chord length Reynolds numbers of R<
 sub>
 ec<
 /sub>
  ? 3.0x105. Vertical velocity profiles collected in the wake of each device from 1 to 10 rotor diameters are used to estimate the velocity recovery and turbulent characteristics in the wake, as well as the interaction of the counter-rotating rotor wakes. The development of this high resolution laboratory investigation provides a robust dataset that enables assessing turbulence performance models and their ability to accurately predict device performance metrics, including computational fluid dynamics (CFD) models that can be used to predict turbulent inflow environments, reproduce wake velocity deficit, recovery and higher order turbulent statistics, as well as device performance metrics.
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