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Bibliographic Data
Control Number
314465
Date and Time of Latest Transaction
20150706094104.AM
General Information
150706s |||||||||b ||00|||
Cataloging Source
STII-DOST
Local Call Number
ScienceDirect
Main Entry - Personal Name
Pence, Deborah
Heymann, Douglas
Narayanan, Vinod
Title Statement
Optimization of fractal-like branching microchannel heat sinks for single-phase flows by Douglas Heymann, Deborah Pence and Vinod Narayanan
Physical Description
pages 1383-1393 computer file; text; 1,318kb
Summary, Etc.
Fractal-like branching flow networks in disk-shaped heat sinks are numerically optimized to minimize pressure drop and flow power. Optimization was performed using a direct numerical search, gradient-based optimization, and genetic algorithm. A previously validated one-dimensional pressure drop and heat transfer model, with water as the working fluid, is employed as the objective function. Geometric constraints based on fabrication limitations are considered, and the optimization methodology is compared with results from a direct numerical search and a genetic algorithm. The geometric parameters that define an optimal flow network include the length scale ratio, width scale ratio, and terminal channel width. Along with disk radius, these parameters influence the number of branch levels and number of channels attached to the inlet plenum. The geometric characteristics of the optimized flow networks are studied as a function of disk radius, applied heat flux, and maximum allowable wall temperature. A maximum inlet plenum radius, minimum interior channel spacing, and ranges of terminal channel widths and periphery channel spacing are specified geometric constraints. In general, all geometric constraints and the heat flux have a significant influence on the design of an optimal flow network. Results from a purely geometrically derived network design are shown to perform within 15% of the direct search and gradient-based optimized configurations
Subject Added Entry - Topical Term
Engineering
Genetic algorithm
Heat sink
Optimization methodology
Location
DOST STII ScienceDirect NONPRINTS NP 14-16658 1 14-16658 Online/Download 2012-01-24
Physical Location
Department of Science and Technology
Science and Technology Information Institute
ScienceDirect
Digital Copy
Not Available
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