On the adverse influence of higher statistical moments of flow maldistribution on the performance of a heat exchanger

Chin, Wai Meng; Raghavan, Vijay R.

doi:10.1016/j.ijthermalsci.2010.10.016

Cited by 16 publications

(20 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The refrigerant side two phase pressure drop coefficient was introduced by Mishima and Hibiki [36]. Figure 5 shows the effect of the standard deviation on the D. From the graph, it is shown that higher standard deviation has a major impact on the D. This finding is similar to the result from Chin and Raghavan [37]. Nielsen et al [38] also stated that the effective thermal performance of heat exchanger decreased as the standard deviation increased.…”

Section: Pressure Drop Correlationsupporting

confidence: 55%

Analysis on the refrigerant (R32) flow maldistribution of microchannel heat exchanger under superheat and sub-cool

Chng¹,

Chin²,

Tang³

2017

Int. J. Automot. Mech. Eng.

View full text Add to dashboard Cite

The aim of this research is to study the impact of statistical moments of probability density function such as mean, standard deviation, skew of R32 flow maldistribution profile on the thermal performance of microchannel heat exchanger under superheat, and subcooling effect. A mathematical model was developed in order to analyse the influence of the statistical moments of probability density function of R32 flow maldistribution on the thermal performance of microchannel heat exchanger under superheat and sub-cooling effect. It was found that the high standard deviation and high negative skew of R32 flow maldistribution profile gave a large impact on the D of microchannel heat exchanger and can achieve up to 10%. Moreover, it was found that the heat transfer performance of microchannel heat exchanger dropped significantly when the sub-cool increases. In short, low standard deviation, high positive skew, and superheat of a flow maldistribution profile is preferred in order to minimize the performance deterioration effect. An experiment was set up to verify the mathematical model. The results from the mathematical model agreed well within 10% of the experimental data. A performance deterioration correlation related to refrigerant maldistribution under superheat and subcool was developed to provide a faster solution to design an even flow distribution heat exchanger. The proposed correlation in this research offers a quicker and simpler way to study the R32 flow maldistribution problem.

show abstract

Section: Pressure Drop Correlationsupporting

confidence: 55%

Analysis on the refrigerant (R32) flow maldistribution of microchannel heat exchanger under superheat and sub-cool

Chng¹,

Chin²,

Tang³

2017

Int. J. Automot. Mech. Eng.

View full text Add to dashboard Cite

show abstract

“…This paper documents the continuation of the work presented in an earlier paper by the authors [1] which has demonstrated the mathematical model used to describe the contribution of each of the statistical moments of the probability density function for flow maldistribution on the performance degradation of an arbitrary heat exchanger. From that work, the general relationship between the thermal degradation factor, D, which is defined in the following equation (1), and the moments have been established.…”

Section: Introductionmentioning

confidence: 52%

“…From that work, the general relationship between the thermal degradation factor, D, which is defined in the following equation (1), and the moments have been established. Only the first three moments, i.e., mean, standard deviation and skew, have significant effect, while the fourth moment, kurtosis does not have any effect.…”

Section: Introductionmentioning

confidence: 99%

The influence of the moments of probability density function for flow maldistribution on the thermal performance of a fin-tube heat exchanger

Chin¹,

Raghavan²

2011

International Journal of Thermal Sciences

Self Cite

View full text Add to dashboard Cite

“…Chin and Raghavan [28] have indicated that any effort to analyse and predict the detrimental effects due to flow maldistribution must take into consideration the effects of higher statistical moments [28]. Without consideration of those effects, it would be difficult for refrigeration system designers to optimise the performance of the heat exchanger.…”

Section: Analysis Of the Refrigerant Maldistribution Problemmentioning

confidence: 99%

A Review of Refrigerant Maldistribution

Tang¹,

Chng²,

Chin³

2014

Int. J. Automot. Mech. Eng.

View full text Add to dashboard Cite

In recent years, conservation of energy has become a challenging issue in air-conditioning applications. In order to overcome this issue, many researchers have recommended the use of a Parallel Flow Condenser and a low Global Warming Potential and Ozone Depletion Potential refrigerant, such as R32, in air conditioning systems. However, PFC faces the critical challenge of flow maldistribution in the tubes. This literature review mainly examines the refrigerant maldistribution problem which has been investigated by previous researchers. It was found that many of the researchers did not properly analyse the influence of flow maldistribution profiles on the performance degradation of heat exchangers. In order to have a comprehensive analysis of tube-side maldistribution in Parallel Flow microchannel heat exchangers, it is recommended that the influence of the higher statistical moments of the probability density function of the flow maldistribution profiles on performance degradation be quantified. Additionally, R32 maldistribution should be analysed and compared with R410A, which is the current commonly used refrigerant in air conditioning units. Moreover, in order to have a realistic simulation of the effect of refrigerant flow maldistribution profiles on performance degradation of heat exchangers, the effect of superheat and sub-cooling must be analysed.

show abstract

On the adverse influence of higher statistical moments of flow maldistribution on the performance of a heat exchanger

Cited by 16 publications

References 9 publications

Analysis on the refrigerant (R32) flow maldistribution of microchannel heat exchanger under superheat and sub-cool

Analysis on the refrigerant (R32) flow maldistribution of microchannel heat exchanger under superheat and sub-cool

The influence of the moments of probability density function for flow maldistribution on the thermal performance of a fin-tube heat exchanger

A Review of Refrigerant Maldistribution

Contact Info

Product

Resources

About