The article describes the method developed by the authors and tested on the example of the AI-25 engine. The study was focused on determining the probability distribution of the output parameters of a gas turbine engine mathematical model. The distribution was obtained considering the uncertainty of the initial data. The paper describes the identified problems and possible ways to solve them. In particular, it was found that it is not possible to study the influence of more than 7..8 input parameters on the probability distribution of output parameters with the current level of development of computer technology even using simple mathematical models. For this reason, a method has been developed to obtain reliable results while reducing the number of considered input data based on sensitivity analysis.
The paper also proposed a way of comparing stochastic experimental and computational data with each other using a bivariate distribution. This method allows a precise characterisation of the calculation error using 4 numerical values. The experience obtained in the work has shown that taking into account the uncertainty of the initial data dramatically changes the process of interpreting the results.
It should be noted that the obtained results are universal and can be used with other mathematical models in various industries although they were developed on the example of the mathematical model of a gas turbine engine.