2022
DOI: 10.1016/j.enganabound.2022.09.016
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Evaluating the parameters affecting the direct and indirect evaporative cooling systems

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Cited by 32 publications
(7 citation statements)
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“…Three different Bayesian surrogate models including the gaussian process (GP), random forest (RF), and gradient boosting regression trees (GBRT) were employed to fine-tune the hyper-parameters. The details about these hyper-parameters tuning procedures can be found in prior works [ 35 , 36 ]. These surrogate models were evaluated for three different cases.…”
Section: Methodsmentioning
confidence: 99%
“…Three different Bayesian surrogate models including the gaussian process (GP), random forest (RF), and gradient boosting regression trees (GBRT) were employed to fine-tune the hyper-parameters. The details about these hyper-parameters tuning procedures can be found in prior works [ 35 , 36 ]. These surrogate models were evaluated for three different cases.…”
Section: Methodsmentioning
confidence: 99%
“…The tuebulence model k-ε is adopted to simulate the hydrodynamic characteristics of the undulatory fin, and its transport equation is as follows (Hussain et al 2022;Alqahtani et al 2023):…”
Section: Turbulence Modelmentioning
confidence: 99%
“…Moreover, these systems are able to cool down the product air without increasing its specific humidity, thus guaranteeing adequate thermohygrometric conditions in the refrigerated environment [3]. For these reasons, IEC systems seem to be ideal for many different applications, such as residential buildings, agricultural storage and livestock air-conditioning, greenhouses, and pharmaceutics [4].…”
Section: Introductionmentioning
confidence: 99%