2018
DOI: 10.1016/j.applthermaleng.2018.07.073
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Experimental and numerical investigations of thermal characteristics of heat exchangers in oscillatory flow

Abstract: This is a repository copy of Experimental and numerical investigations of thermal characteristics of heat exchangers in oscillatory flow.

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Cited by 30 publications
(18 citation statements)
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“…Briefly, the experimental results fit well with the predictions of even better three-dimensional CFD models [74], From this, it is presumed to teach that the CFD model is a reliable method for examining the effects of a number of design changes on the elements' performance, representing a cost-effective route for design optimization [73]. CFDs have become an effective tool in several heat exchangers; it is almost sure to be less expensive than experimental characterization studies [18].…”
Section: Cfd Modeling and Analysis Of The Phenomenonmentioning
confidence: 76%
“…Briefly, the experimental results fit well with the predictions of even better three-dimensional CFD models [74], From this, it is presumed to teach that the CFD model is a reliable method for examining the effects of a number of design changes on the elements' performance, representing a cost-effective route for design optimization [73]. CFDs have become an effective tool in several heat exchangers; it is almost sure to be less expensive than experimental characterization studies [18].…”
Section: Cfd Modeling and Analysis Of The Phenomenonmentioning
confidence: 76%
“…Experiments involving standing wave devices with two identical HXs and no stack in between were conducted by Kamsanam et al [10] and Ilori et al [11] to investigate the thermal performance of HXs of the parallel-plate type and parallel tube type. The derived correlation laws were expressed in terms of Nusselt numbers.…”
Section: Of 10mentioning
confidence: 99%
“…Therefore, a lot of attention has been devoted so far in the literature to the PDE-based modeling of these thermal devices, which are often described by hyperbolic equations resulting from the balance laws of continuum physics. The development of the PDE-based phenomenological modeling methods progressed in two parallel directions, with the use of either analytical [1][2][3][4][5][6][7][8] or numerical [9][10][11][12][13][14][15] approaches. The other approach consists of using data-based techniques, also known as black-box modeling or process identification [16][17][18], or even in using artificial neural networks [19][20][21].…”
Section: Introductionmentioning
confidence: 99%