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The virtual optimisation of tooling equipment is nowadays one of the common challenges in mechanical serial production. Even some numerical Eulerian approaches (grid-based) exist for modelling solid materials under dynamic loading, most of them are not very successful. Especially the solids undergoing large deformation and the subsequent material separation and propagating cracks demonstrate the limitations: variables become discontinuous across the crack surface, and the computational domain loses its continuum nature. Grid-based methods are not naturally equipped to deal with such situations due to the mesh distortion, mesh entanglement and requirement of mesh refinement. Very promising alternatives to the Eulerian methods are meshfree Lagrangian methods. Among them, smoothed particle hydrodynamics (SPH) is entirely meshfree and naturally equipped to handle large material deformation. In SPH the computational domain is discretised by a set of particles.

Large material distortion, plastic deformation and forging make the numerical modelling of metal forming a difficult task. Grid-based methods such as the Finite Element Method (FEM) are incapable of simulating this process as these schemes suffer from mesh distortion and mesh entanglement. The mesh-based numerical frameworks with discontinuous enrichment can model finite deformation problems with limited success. Moreover, the presence of flaws, multiple crack surfaces and their interaction make the simulation even more numerically and computationally intensive. In this regard, Lagrangian particle-based meshfree methods are more relevant. There exist several mesh-free methods and among these Smoothed Particle Hydrodynamics (SPH) is a truly meshfree method. In SPH the computational domain is discretised by a set of particles. A given particle interacts only with its neighbouring particles through a kernel function with a constant radius.

Rotary Bell Atomizers are well established in the automotive industry for top coating applications. This type of atomizer allows to create a uniform coating and is characterized by high productivity. Meanwhile, the effectiveness of the process depends on many complex factors. For instance, the transfer efficiency of the paint material, which is the percentage of the paint reaching the structure surface, ranges from 60-95% depending on the application conditions. Any increase in the transfer efficiency can not only reduce energy and material costs, but also reduce the emission of harmful non-deposited paint particles and the effort to handle them. The use of accurate numerical methods in this process helps to optimize the application process, reduce the number of expensive field experiments, and shortens the development cycle of new vehicles, which ensures predictability of production costs.

Baking ovens in the automotive paint shop are crucial to ensuring quality of paint curing and hence meet the corrosion protection targets in manufacturing process. Ovens are also among the most energy consuming processes in the entire paint shop. With the onset of Electric Vehicle revolution, original equipment manufacturers focus heavily on light weighting resulting in significant design changes to the body in white (BIW). This presents a challenge of achieving accurate curing in the existing ovens designed for the current and past generations of vehicles Using Computational fluid dynamics (CFD), this research intends to present a solution by minimizing the need for prototyping for design changes. Lattice Boltzmann Method (LBM) based thermal simulations are used to predict the curing behaviour on the BIW surface. The LBM based conjugated heat transfer simulations consider turbulence using a Large-Eddy Simulation (LES) approach and Boussinesq approximation.