Research And Experiment Of Thermal Performance Of Gas Cookers Based On Monte Carlo Method

The thermal performance(heat load and thermal efficiency)of household gas cookers is a key index to measure and evaluate the stable operation state of gas utensil.At present,every batch of gas utensil must conduct thermal performance test before they enter the market,and check whether they meet the requirements of the national standard.However,in the process of measurement,the true value of measurement result is difficult to determine due to the existence of measurement error,and the measurement result is uncertain.At present,most laboratories only give the measurement results for gas utensil,and the corresponding uncertainty is not given,so it is incomplete.Secondly,most laboratories still use the uncertainty propagation rate(GUM method)to evaluate the uncertainty.When the model is nonlinear,the evaluation will be very difficult and the result is not accurate.Finally,in the evaluation of uncertainty,most laboratories do not know the contribution of the input variables to the uncertainty,so it is impossible to achieve the purpose of improving the measurement accuracy by controlling the important input.The main work of this article is as follows:First,in this paper,use a method based on the Monte Carlo Method(MCM)and maximum entropy principle is proposed to evaluate the uncertainty of measurement.First,the maximum entropy model is established according to the finite measurement data and the maximum entropy model is solved.When the maximum value of entropy function is satisfied,the probability distribution function is obtained,and the probability density function of each input is closer to the actual situation.According to the Monte Carlo method,a random number of random numbers which obey the corresponding probability distribution is generated by the correlation function.Finally,the probability distribution is carried out,and the probability distribution of the output is obtained,and the uncertainty of the output is obtained by the statistical method.Compared with the GUM method,this method is simpler and wider,and the evaluation result is more stable and accurate.The uncertainty of thermal load and thermal efficiency measured by the two methods has little difference,but the probability of the MCM method is 95%,which includes the smaller interval,that is,the result is more accurate.In addition,To understand the contribution of each input variable to the uncertainty,the sensitivity analysis is carried out in this paper.The results obtainedfrom the existing local sensitivity analysis methods,such as direct derivation and parameter perturbation method,are analyzed by the nonlinear model,and the results are unstable,while the global sensitivity analysis method can find out the contribution of each input to the output of the model well,but it is due to the large amount of operation and the complex solution process.The technology requirements of inspectors are too high,which is not conducive to popularization and popularization.Therefore,a local sensitivity analysis method based on Monte Carlo method is proposed in this paper.The result accords with the result of global sensitivity analysis.For heat load,test time and natural gas low calorific value have the greatest impact on the results;for thermal efficiency,consumption and low calorific value have the greatest impact on the results.It is easy to calculate and is suitable for nonlinear model.Sensitivity analysis can be realized in the program of uncertainty evaluation,and the efficiency of calculation and analysis data is improved.At last,the results of uncertainty evaluation and sensitivity analysis are used to simplify and optimize the thermal performance model of gas tool.The model uncertainty of the simplified model is not changed,the process of calculating and analyzing data is simplified,the detection cost is reduced,and the detection efficiency is improved.