Review on the measurement and calculation of frost characteristics

Song, Mengjie; Dang, Chaobin

doi:10.1016/j.ijheatmasstransfer.2018.03.094

Cited by 139 publications

(23 citation statements)

References 122 publications

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“…Dimensionless quantity generally refers to the ratio of several similar physical quantities or the dimensionless similarity criterion of different physical quantities. Based on the dimensional theory, the error of predicting the amount of frosting is 18.4% [ 26 ]. In the study, the original dimensionless correlation equation of frosting amount is improved by combining dimensionless parameters with neural network.…”

Section: Methodsmentioning

confidence: 99%

“…Song and Dang (2018) proposed a complex model to analyze the dynamic distribution characteristics of the thermal conductivity, density, and temperature during the frost layer growth process. He pointed out that, the thermal conductivity of the frost layer is not just a pure density function, and it also includes many other factors [ 13 ]. Zhang et al (2021) made certain amendments to the water vapor penetration process and boundary conditions in the porous medium in the frost layer.…”

Section: Introductionmentioning

confidence: 99%

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Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm

Yu¹,

Luo²,

Chu

2021

PLoS ONE

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The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source heat pump system are analyzed. Then, a new defrost technology is proposed, and dimensional theory and neural network are combined to predict the transfer performance of the new system. Finally, an adaptive network control algorithm is proposed to predict the frosting amount. This algorithm optimizes the traditional neural network algorithm control process, and it is more flexible, objective, and reliable in the selection of the hidden layer, the acquisition of the optimal function, and the selection of the corresponding learning rate. Through model performance, regression analysis, and heat transfer characteristics simulation, the effectiveness of this method is further confirmed. It is found that, the new air source heat pump defrost system can provide auxiliary heat, effectively regulating the temperature and humidity. The mean square error is 0.019827, and the heat pump can operate efficiently under frosting conditions. The defrost system is easy to operate, and facilitates manufactures designing for different regions under different conditions. This research provides reference for energy conservation, emission reduction, and sustainable economic development.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm

Yu¹,

Luo²,

Chu

2021

PLoS ONE

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“…Additionally, it is worthy of mentioning that the frosting process on a float plate and on a parallel plate heat exchangers are different from each one. The more explanations for these differences can be found in 8 .…”

Section: Introductionmentioning

confidence: 99%

An insight into the estimation of frost thermal conductivity on parallel surface channels using kernel based GPR strategy

Zhou

Naseri

2021

Sci Rep

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In heat exchange applications, frost formation on the cold surface causes a decrease in the rate of heat transfer and growth in the pressure drop. Thus, the study on the frost thermal conductivity has a significant and vital place for the engineers and researchers dealing with the heat exchangers. In the literature, there is a lack of accurate and applicable methods for determination of frost thermal conductivity. Additionally, the high cost and difficulties of experimental works clarify the importance of computational and mathematical methods. The errors in the determination of frost thermal conductivity on parallel surface channels can cause inaccuracy in estimations of frost density and thickness. The main aim of present work is suggesting Gaussian Process Regression (GPR) models based on four different kernel functions for the estimation of frost thermal conductivity in terms of time, air velocity, relative humidity, air temperature, wall temperature, and frost porosity. To achieve this purpose, a total number of 57 frost thermal conductivity values has been collected. Comparing the suggested GPR models and other available computational methods express the quality of the developed models. The best predictive tool has been selected as a GPR model, including Matern kernel function with R2 values of 0.997 and 0.994 in training and testing phases, respectively. In addition, the effectiveness of discussing variables on frost thermal conductivity has been investigated by sensitivity analysis and showed that air temperature is the most effective parameter. The present work gives engineers an insight into frost thermal conductivity and the effective parameters in its determination.The significant advantage of present work is the accurate prediction of thermal conductivity by a brief knownledge in artificial intelligence.

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“…The literature is well-served in review papers concerning the fundamentals of evaporator frosting, not only in terms of first-principles models for frost growth and densification, but mostly related to the thermophysical properties of mature frosts, such as density and thermal conductivity, and their dependence on the surface characteristics [5,6]. Rather than putting forward another critical review of the open literature, the present communication summarizes the key fundamental aspects of frost formation that the cooling engineer must be acquainted with for designing new evaporators and better defrost systems.…”

Section: Introductionmentioning

confidence: 99%

Evaporator Frosting in Refrigerating Appliances: Fundamentals and Applications

et al. 2021

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Modern refrigerators are equipped with fan-supplied evaporators often tailor-made to mitigate the impacts of frost accretion, not only in terms of frost blocking, which depletes the cooling capacity and therefore the refrigerator coefficient of performance (COP), but also to allow optimal defrosting, thereby avoiding the undesired consequences of condensate retention and additional thermal loads. Evaporator design for frosting conditions can be done either empirically through trial-and-error approaches or using simulation models suitable to predict the distribution of the frost mass along the finned coil. Albeit the former is mandatory for robustness verification prior to product approval, it has been advocated that the latter speeds up the design process and reduces the costs of the engineering undertaking. Therefore, this article is aimed at summarizing the required foundations for the design of efficient evaporators and defrosting systems with minimized performance impacts due to frosting. The thermodynamics, and the heat and mass transfer principles involved in the frost nucleation, growth, and densification phenomena are presented. The thermophysical properties of frost, such as density and thermal conductivity, are discussed, and their relationship with refrigeration operating conditions are established. A first-principles model is presented to predict the growth of the frost layer on the evaporator surface as a function of geometric and operating conditions. The relation between the microscopic properties of frost and their macroscopic effects on the evaporator thermo-hydraulic performance is established and confirmed with experimental evidence. Furthermore, different defrost strategies are compared, and the concept of optimal defrost is formulated. Finally, the results are used to analyze the efficiency of the defrost operation based on the net cooling capacity of the refrigeration system for different duty cycles and evaporator geometries.

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Review on the measurement and calculation of frost characteristics

Cited by 139 publications

References 122 publications

Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm

Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm

An insight into the estimation of frost thermal conductivity on parallel surface channels using kernel based GPR strategy

Evaporator Frosting in Refrigerating Appliances: Fundamentals and Applications

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