Numerical CFD-FEM model for machining titanium Ti-6Al-4V with nano minimum quantity lubrication: A step towards digital twin

被引:12
作者
Nouzil, Ibrahim [1 ]
Eltaggaz, Abdelkrem [1 ]
Deiab, Ibrahim [1 ]
Pervaiz, Salman [1 ,2 ]
机构
[1] Univ Guelph, Sch Engn, Adv Mfg Lab AML, Guelph, ON, Canada
[2] Rochester Inst Technol Dubai, Dept Mech & Ind Engn, Dubai, U Arab Emirates
基金
加拿大自然科学与工程研究理事会;
关键词
Nano Minimum Quantity Lubrication; Minimum Quantity Lubrication; MQL; NMQL; Machining; FEM; CFD; Ti-6Al-4V; Orthogonal Machining; CUTTING FLUIDS; VEGETABLE-OIL; HEAT-TRANSFER; SIMULATION;
D O I
10.1016/j.jmatprotec.2023.117867
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Nano minimum quantity lubrication is an enhanced minimum quantity lubrication (MQL) method that utilizes nanoparticle additives to boost its thermal and lubricating capacity. Although experimental investigations of nano minimum quantity lubrication (NMQL) have been successful, literature on numerical modeling of NMQL is lacking. Further, 3D computational fluid dynamic (CFD) modeling of nanofluid spray cooling in machining is rare in literature. This study aims to develop a 3D CFD model to capture the nanofluid spray characteristics and then couple the solution to a 2D finite element machining (FEM) simulation. Additionally, a novel static temperature calibration method is developed to estimate the interface cutting temperature. First, a 3D CFD model calculates the thermal characteristics of the NMQL spray and derives the temperature dependent average heat convection coefficient values. In the second stage, the FEM model applies the derived heat transfer coefficient by imposing a boundary film on the machined surface and cutting tool. Orthogonal machining experiments conducted for cutting speeds of 120 m/min and 90 m/min at 0.1 mm/rev feed rate are used to validate the developed numerical model. For the given cutting conditions, the current model predicts the cutting temperature and cutting force with an average error of 11.44 % and 11.39 %, respectively. The low error in cutting force and temperature results highlight the model as reliable and lays the foundation for a digital twin for NMQL machining. Future works must aim to capture the rolling action of the nanoparticles at the tool-chip interface, which would enhance the simulation accuracy.
引用
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页数:11
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