Hosseini, Sayyed AliNguyen, Nam2023-04-252023-04-252023-04-01https://hdl.handle.net/10155/1616This thesis studies the machining of additively manufactured (AM) titanium Ti-6Al-4V and presents a model to determine Johnson Cook (J-C) constitutive parameters from complex machining processes through numerical modeling and experimental validation. The J-C parameters are important in describing the characteristics and behaviors of materials during high-strain rate high-temperature machining processes. These parameters are traditionally determined through time-consuming and costly split-Hopkinson pressure bar tests. The proposed model uses a combination of experimentally measured cutting forces and optimization methods including genetic algorithm and particle swarm optimization to find the suitable J-C parameters. Force simulation and experiments were conducted to validate the proposed model and the results showed its effectiveness in estimating the J-C parameters directly from milling tests as an oblique cutting operation. Chip morphology has also been investigated to determine the mechanics of chip formation and its relationship to the properties of the AM titanium.enMillingAdditive manufacturingJohnson-Cook modelOxley modelGenetic algorithmThesis