DOIONLINE 
DOIONLINE Publish In |
International Journal of Mechanical and Production Engineering (IJMPE)-IJMPE |
 Journal Home Volume Issue |
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Issue |
Volume-11,Issue-7 ( Jul, 2023 ) | |||||||||
Paper Title |
An Improved Methodology for Modelling and Simulation of Laser Shock Peening | |||||||||
Author Name |
Da Desai, Ffameso,S Kok | |||||||||
Affilition |
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Pages |
31-40 | |||||||||
Abstract |
The variable speed driving feature is used by vehicle air conditioning systems. It illustrates the changing nature of cooling and the driving dynamics in this regard. As a result of recent environmental sensitivity, alternative refrigerant R1234yf is one of the most frequently explored refrigerants for automotive air conditioning systems. The goal of this study is to find the best structure and model by training the data we collected with experimental data and multi-regression, ANN, and ANFIS models and comparing the predictions. The key distinction is that the data sets should be restricted by limiting the number of inputs of the collected data from 8 to 4 and obtaining results with fewer input values. In our experiment setup, different compressor speeds (n =600/800/1000/1200/1400 rpm) were used for -20/-15/-10/-5/-0-5 oC evaporator (Te) and 40 oC condenser (Tc) temperatures, respectively. In our system, we have 5oC of supercooling. A tube heat exchanger is offered for this purpose. Input data for R134a and R1234yf fluids is restricted, and it has been demonstrated that the ANFIS model can predict both R2 and %Means Error values, as well as RMSE values, with more accuracy than other techniques in all values. Keywords - ANFIS, ANN, Artificial Intelligent, R134a, R1234yf, COP | |||||||||
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