2016
DOI: 10.1016/j.applthermaleng.2016.03.077
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Minimization of loss in small scale axial air turbine using CFD modeling and evolutionary algorithm optimization

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Cited by 29 publications
(12 citation statements)
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References 26 publications
(22 reference statements)
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“…The ratio of the flow loss to the ideal energy in the static and dynamic cascades was called the energy loss coefficient, which is an index to measure the flow loss in cascades. 22,23 It can be expressed as follows:…”
Section: Experimental Methodsmentioning
confidence: 99%
“…The ratio of the flow loss to the ideal energy in the static and dynamic cascades was called the energy loss coefficient, which is an index to measure the flow loss in cascades. 22,23 It can be expressed as follows:…”
Section: Experimental Methodsmentioning
confidence: 99%
“…Many studies have been published on the both the characterizations and the methods of calculation for different types through various correlations as previously shown in section 3. In turbines, losses can be divided to those which takes place in the stator and those happens in the rotor part, more details can be found in [12,[52][53][54][55]. In the current study the loss coefficients in terms of pressure losses, as one significant indicator of losses, for each of three configurations and at different working circumstances will be evaluated and discussed next.…”
Section: Loss Coefficientmentioning
confidence: 99%
“…With the aim of decreasing losses of small scale axial turbine by using the multi-objective function, Bahr Ennil et al [12] uses and improved some loss correlations. They concluded that the Kacker & Okapuu loss model is able to predict effectively the closest losses to those from the CFD in the SSAT.…”
Section: -Introductionmentioning
confidence: 99%
“…The turbine showed maximum power output of 3.5 kWe at 70,000 RPM with efficiency of 76% while maximum system efficiency was about 45% when operating with air at ambient temperatures without external sources of heat. Ennil et al [10] proposed a methodology for minimization of losses in small-scale air-driven axial turbine suitable for CAES systems. The proposed method was based on fully automated CFD simulation coupled with Multi-objective genetic algorithm (MOGA) technique.…”
Section: Categorymentioning
confidence: 99%