Application of Computational Intelligence and Knowledge-Based System in Predicting Flow Stress of AISI 4340

Prediction of flow stress of any engineering material is vital for modeling its plastic deformation process and for having estimate of force and power requirements in various manufacturing processes. The paper focuses on the application of two most important tools of artificial intelligence: computational intelligence and knowledge-based system, in predicting flow stress of a common high-strength low-alloy steel type, AISI 4340. The estimation process is based on different settings of material's microstructure (quantified by hardness), applied temperature, strain, and strain rate. The simulation results of both tools show a great deal of agreement with the experimental data. The prediction results are also compared with the estimations made by a commonly used empirical model.