Estimating flow control with genetic programming

Fluid mechanics is a field of science that studies the balance of fluids (static fluids) and characteristics of moving fluids, and thus the name. One of the primary problems in fluid dynamics is the calculation of the pressure gradient of a fluid that flows through a pipe. Navier Strokes equations are used for this. Correct parameters that are chosen according to pressure gradient calculations affect the time of manufacturing and cost.Genetic programming is a technique based on Darwin?s theory of evolution that lets computers find a solution automatically. Genetic programming can also be described as an evolutionary algorithm that provides for the perfection of possible primitive solutions derived from the basics of the problem at hand.Learning and verification data sets have been arranged using real pressure gradient data based on specific materials and environments. Various experiments have been conducted for various genetic processor values for the pressure gradient estimation problem, and a pressure gradient estimation model with a 70% success has been devised. The results obtained show that the genetic programming approach produces successful models. Matlab CFD simulation has been prepared to confirm the success of the models and the results from the genetic programming model have been compared to the simulation results and actual data. As a result of comparison, genetic programming has proved to produce values that are close to actual values and since it is prone to development, will yield better results with some improvements.The devising of models based on various materials and environments using genetic programming will greatly contribute to the pressure gradient problems and the costs. The genetic programming software prepared for modeling can be easily adapted to reverse problems for which the answer is known, but the problem isn?t.