Theoretical and experimental verification for determining pool boiling heat transfer coefficient using fuzzy logic
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ORIGINAL
Theoretical and experimental verification for determining pool boiling heat transfer coefficient using fuzzy logic Tamer M. Mansour1
· Reda A. Khalaf-Allah2
Received: 5 August 2019 / Accepted: 11 July 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Finding pool boiling heat transfer coefficient of refrigerant is considered one of the great challenges which affects the refrigeration system in terms of design and power consumed. Yet most of the calculation is done based on empirical equations. The major defect with those equations is that they rely on certain operating range for the pressure and heat flux. Outside that range the correctness of the equation will be weak. A fuzzy logic model to predict the heat transfer coefficient of the pool boiling process is exposed in this research. The model is utilized to find the heat transfer coefficient for refrigerant R-134a at different operating conditions. The operating pressure, the applied heat flux and the surface roughness of brass heating plate are changed to exam the ability of the model to find the heat transfer coefficient correctly. Mamdani method is used to model the fuzzy system. An experimental confirmation is done to authenticate the proposed fuzzy model. The obtained fuzzy logic results have a deviation of ± 2% at low heat flux and maximum deviation is ±6% at high heat flux. In addition, the attained results from both fuzzy logic and experimental work are compared with previous work and found to have the same qualitative behave and near quantitative with previous results of other researchers worked in the same range. Keywords Experimental verification · Fuzzy logic · Heat transfer coefficient · Pool boiling
Nomenclature V Applied voltage (V) I Applied current (A) q Heat flux (W/m2 ) A Surface Area (m2 ) h Heat transfer coefficient (W m−2 K−1 ) m Mass flow rate (kg s−1 ) Saturation pressure (MPa) Ps Arithmetic mean deviation of the surface profile. Ra (μ m) Ten point height of irregularities ( ISO, JIS Rz standard) (μ m) Rp Maximum surface profile peak height (μ m) k Thermal conductivity (W m−1 K−1 ) Tamer M. Mansour
[email protected] 1
Faculty of Engineering, Suez Canal University, Ismailia, Egypt
2
Faculty of Technology and Education, Suez University, Suez, Egypt
N Bubble density Surface Temperature (K) Ts Inner radius (m) ri ro Outer radius (m) ∗ Normalized heat flux q D Diameter (m) Normalized heat transfer coefficient h∗ Cp Specific heat (J kg−1 K−1 ) Critical pressure (MPa) Pc P∗ Normalized pressure L Length (m) r Bubble diameter (μm) Nano particle diameter (nm) dp M Molecular weight of refrigerant (kg kmol−1 ) Tsat Saturation Temperature (K)) Greek letter Difference Abbreviations H.T.C. Heat transfer coefficient C.H.F. Critical heat flux vol. Volume
Heat Mass Transfer
1 Introduction Most power and refrigeration systems depend on liquid to vapor phase change phenomenon. This change is accomplished by a boiling process. The design of flooded evaporators requires more accurate data about the heat tr
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