A Rapid Prediction Method Based on Response Surface Surface Correlation of Heat Transfer Pressure Drop
A prediction method and a related technology, applied in the field of heat and mass transfer, can solve problems such as shortening the product development cycle and reducing the cost of experiments, and achieve the effects of saving test costs, reducing test costs, and shortening the development cycle
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Embodiment 1
[0035] In this embodiment, a regression model containing multiple factors and weak coupling is established, and the heat transfer pressure drop prediction formula of the nonlinear regression model is obtained through the response surface. The experimental data of the heat exchange pressure drop can be obtained by experiment or simulation. This example cites the experimental data of correlation estimation in the existing literature to prove that the response surface method has the ability to deal with such multi-factor and weakly coupled regression models, and can predict the same A form of relation with the same or similar source relation. The flat tube louver fin of Chang (Chang Y J, Wang C C.Ageneralized heat transfer correlation for louver fin geometry[J].International Journal of heat and mass transfer,1997,40(3):533-544.) The j-factor correlation is used as the data source, and the deviation between the correlation and the experimental data is 15%, and the correlation is i...
Embodiment 2
[0063] In this example, the nonlinear regression model fitting based on the response surface is carried out for the heat transfer pressure drop prediction formula which is common in heat transfer engineering and the power exponent includes strong coupling between factors. The experimental data of the heat exchange pressure drop can be obtained through experiments or simulations. This example cites the existing literature correlation estimation test data to prove that the response surface method has the ability to deal with such complex nonlinear regression models and can predict homologous Relational forms that are the same or similar. Wang (Thome J R.Engineering data book III[J].Wolverine Tube Inc,2004.) was selected as the data source for the j-factor correlation of the circular tube slit-shaped fin heat transfer, and the deviation between the correlation and the experimental data was 10%. Its relational form is as formula (2-1);
[0064]
[0065] In the formula,
[006...
Embodiment 3
[0089] In order to verify that the correlations containing coupling items in the form of power exponents can be completely obtained through the response surface nonlinear regression model, this example establishes a simple power exponent model with three factors interacting to describe the pressure drop characteristics of the heat exchange structure, as Formula (3-1);
[0090] f=5.04A f1 B f2 C f3
[0091] In the formula,
[0092] f1=-0.6+0.13ln B-0.03ln C-0.009ln A (3-1)
[0093] f2=-0.01+0.009ln C-0.2ln B
[0094] f3=1.8+1.2ln C-0.04ln B
[0095] (1) In the first step, sort out the parameter changes among the three factors A, B, and C, and set the range of changes as shown in Table 3-1. Based on the test point design criteria of response surface analysis, the three-level BBD (Box-Behnken Design) was selected for the design of the response surface test scheme, and a total of 17 tests were arranged. The parameter combinations and the experimental design points formed a...
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