Near-alpha titanium alloys are used for moderate-temperature applications in the early stages of the compressor in gas turbine engines. The quasi-static an

The consolidation of metal powders is a complex thermomechanical process, and the temperature has a significant effect on the density distribution in the compact. The consolidation process of metal powders with an average particle size of 10 μm, 25 μm, and 50 μm under hot isostatic pressure was simulated by finite element modeling. The distribution and evolution of the relative density after being hot isostatic pressing (HIP) under 1050 °C/130 MPa/4 h, 1150 °C/130 MPa/4 h, and 1250 °C/130 MPa/4 h conditions were simulated, respectively. The experimental data of HIP at 1050 °C/130 MPa/4 h were used to verify the modeling results via the geometric change in the container. The relative density difference between the simulated results and the experimental results at different positions was less than 2%. This methodology called “modeling prediction, experimental validation” can accelerate experimental discovery in an economic manner.

With the advancement in computational approaches and experimental, simulation, and modeling tools in recent decades, a trial-and-validation method is attracting more attention in the materials community. The development of powder metallurgy Ni-based superalloys is a vivid example that relies on simulation and experiments to produce desired microstructure and properties in a tightly controlled manner. In this research, we show an integrated approach to predicting the grain size of industrial forgings starting from lab-scale cylindrical compression by employing modeling and experimental validation. (a) Cylindrical compression tests to obtain accurate flow stress data and the hot working processing window; (b) double-cone tests of laboratory scale validation; (c) sub-scale forgings for further validation under production conditions; and (d) application and validation on full-scale industrial forgings. The procedure uses modeling and simulation to predict metal flow, strain, strain rate, temperature, and the resulting grain size as a function of thermo-mechanical processing conditions. The models are calibrated with experimental data until the accuracy of the modeling predictions is at an acceptable level, which is defined as the accuracy at which the results can be used to design and evaluate industrial forgings.