Bidirectionally Coupled FE-CFD Simulation Study on MQL Machining Process of Ti-6Al-4V Alloy

In the context of sustainable manufacturing practices, minimum quantity lubrication (MQL) has been extensively employed in machining operations involving hard-to-cut materials. While substantial experimental and numerical investigations on MQL-assisted machining have been conducted, existing simulation approaches remain inadequate for modeling the dynamic flow field variations inherent to MQL processes, significantly compromising the predictive reliability of current models. This study introduced an innovative bidirectional iterative coupling framework integrating finite element (FE) analysis and computational fluid dynamics (CFD) to enhance simulation accuracy. Since fluid flow characteristics critically influence tribological and thermal management at the tool–workpiece interface during machining, CFD simulations were initially performed to evaluate how MQL parameters govern fluid flow behavior. Subsequently, an integrated FE-CFD modeling approach was developed to simulate Ti-6Al-4V alloy turning under MQL conditions with varying feed rates. The novel methodology involved transferring thermal flux data from FE simulations to CFD’s heat source domain, followed by incorporating CFD-derived convective heat transfer coefficients back into FE computations. This repetitive feedback process continued until the thermal exchange parameters reached convergence. Validation experiments demonstrated that the proposed method achieved improved alignment between the simulated and experimental results for both cutting temperature profiles and principal force components across different feed conditions, confirming the enhanced predictive capability of this coupled simulation strategy.