Neural networks analysis of free laminar convection heat transfer in a partitioned enclosure

Mahmoud, M. A.; Ben-Nakhi, Abdullatif

doi:10.1016/j.cnsns.2005.12.008

Cited by 54 publications

(21 citation statements)

References 19 publications

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“…As indicated by Mahmoud and Ben-Nakhi [24] that soft computing codes have been employed in heat and mass flow processes mainly to predict some lumped performance parameters rather than predicting thermal and flow variables throughout a domain. They have been successfully applied in many scientific researches and engineering practices [25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 98%

Estimation of thermal and flow fields due to natural convection using support vector machines (SVM) in a porous cavity with discrete heat sources

Varol

Öztop

Avcı

2008

International Communications in Heat and Mass Transfer

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Section: Introductionmentioning

confidence: 98%

Estimation of thermal and flow fields due to natural convection using support vector machines (SVM) in a porous cavity with discrete heat sources

Varol

Öztop

Avcı

2008

International Communications in Heat and Mass Transfer

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“…AdaptiveNetwork-Based Fuzzy Inference System (ANFIS) has been used by [19] to control convergence in a CFD simulation. [20] have used neural networks for free convection in a partitioned enclosure. In their study, they made predictions considering complete thermal and flow variables.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-based estimation of mixed convection heat transfer in a square cavity in the presence of an adiabatic inclined fin

Selimefendigil

Öztop

2012

International Communications in Heat and Mass Transfer

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“…Juntaek et al [18] were used the soft computing technique (ANFIS) to control the convergence of the finite volume computational fluid dynamics algorithm. While, Mahmoud and Ben-Nakhi [19] were utilized three types of neural network for predicting the thermal and flow variables inside a partitioned enclosure. The results showed an excellent prediction of neural network results with the corresponding CFD results.…”

Section: Fuzzy Logic Techniquementioning

confidence: 99%

Numerical Analysis of Transport Phenomenon inside a Pulse Tube Refrigerator Coupled with Fuzzy Logic Controller

Rout¹,

Hussein²,

Sahoo³

et al. 2013

ujme

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This research article illustrates a numerical study of single stage coaxial as well as inline Inertance-Type Pulse Tube Refrigerator (ITPTR). In this present work a computational fluid dynamic (CFD) approach has been adopted for numerical simulation purpose. The detail analysis of cool down behaviour, heat transfer at the cold end and the pressure variation inside the whole system has been carried out by using the most powerful computational fluid dynamic software package FLUENT. A number of cases have been solved by changing the porosity of the regenerator from 0.5 to 0.9 while the rest of the considered parameter are remains unchanged. The operating frequency for all the studied cases is (34 Hz) while the other system dimensions and the boundary conditions are considered unchanged for all cases. The results show that the porosity value of (0.6) produces a better cooling effect on the cold end of the pulse tube refrigerator. The variation of the pressure inside the pulse tube refrigerator during the process are also analysed. In this work an attempt has been made to make a thermally non-equilibrium model applied numerically to the porous region by considering two different energy equations to the solid matrix and for the fluid inside the porous medium and the results are compared with the thermally equilibrium model. In fact , to get an optimum parameter experimentally is a very tedious for iterance pulse tube refrigerator job , so that the CFD approach gives a better solution which is the main purpose of the present work. In the next part the fuzzy logic approach is applied to optimize the different component parameters that affect the cooling performance of the ITPTR. The investigation is performed with different design parameters such as the length and diameter of pulse tube and regenerator given as an input to the fuzzy controller while the output from the controller is the cold end temperature. The predicted optimum results have been verified by performing the confirmation tests.

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Neural networks analysis of free laminar convection heat transfer in a partitioned enclosure

Cited by 54 publications

References 19 publications

Estimation of thermal and flow fields due to natural convection using support vector machines (SVM) in a porous cavity with discrete heat sources

Estimation of thermal and flow fields due to natural convection using support vector machines (SVM) in a porous cavity with discrete heat sources

Fuzzy-based estimation of mixed convection heat transfer in a square cavity in the presence of an adiabatic inclined fin

Numerical Analysis of Transport Phenomenon inside a Pulse Tube Refrigerator Coupled with Fuzzy Logic Controller

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