Mingming Tong

A combined enthalpy / front tracking method for modelling melting and solidification in laser welding

The authors present an integrated meso-scale 2D numerical model for the simulation of laser spot welding of a Fe-Cr-Ni steel. The melting of the parent materials due to the applied heating power is an important phenomenon, leading to the formation of the weld pool and the subsequent conditions from which solidification proceeds. This model deals with the dynamic formation of the weld pool whereby melting may be occurring at a given location while solidification has already commenced elsewhere throughout the weld pool. Considering both melting and possible simultaneous solidification in this manner ensures a more accurate simulation of temperature distribution. A source based enthalpy method is employed throughout the calculation domain in order to integrate the melting model with the UCD front tracking model for alloy solidification. Melting is tracked via interpolation of the liquidus isotherm, while solidification is treated via both the tracking of the advancing columnar dendritic front, and the nucleation and growth of equiaxed dendrites using a volume-averaging formulation. Heterogeneous nucleation is assumed to take place on TiN grain refiner particles at a grain refiner density of 1000 particles per mm2. A mechanical blocking criterion is used to define dendrite coherency, and the columnar-to-equiaxed transition within the weld pool is predicted.

An integrated meso-scale numerical model of melting and solidification in laser welding

The authors present an integrated numerical model for the simulation of laser spot welding of an aluminium alloy at meso-scale in 2D. This model deals with the melting of the parent materials which form the weld pool and the subsequent solidification of the liquid metal in the pool, during the welding process. The melting of the parent materials due to the applied heating power is an important phenomenon, which determines the conditions at the onset of solidification, such as the geometry of the weld pool and the distribution of the temperature field. An enthalpy method is employed to predict the melting during the heating phase of welding. A Gaussian distribution is used to model the heat input from the laser. Once the laser beam is switched off and the melting halts, solidification commences. The UCD front tracking model [1,2] for alloy solidification is applied to predict the advancement of the columnar dendritic front, and a volume-averaging formulation is used to simulate nucleation and growth of equiaxed dendrites. A mechanical blocking criterion is used to define dendrite coherency, and the columnar-to-equiaxed transition within the weld pool is predicted.

Smoothed particle hydrodynamics modelling of the fluid flow and heat transfer in the weld pool during laser spot welding

Smoothed particle hydrodynamics is employed, for the first time, to develop a numerical model for the melting and fluid flow during laser welding process. In this meshlessLagrangian method the gas-melt two phase flow, heat transfer, surface tension, and melting of solid parent material are considered. This model was used to study the evolution of temperature field and fluid flow in the case study of laser spot welding in 2D. The simulation results show a strong influence of the melting process on the flow of liquid metal and a clear influence of the Marangoni flow on the heat transfer is also found.

A Multi-Scale Approach to Simulate Solidification Structure Evolution and Solute Segregation in a Weld Pool

During welding, work-pieces are melted to form a weld pool and are joined upon solidification. The quality of the welded product is largely determined by the solidified microstructure and solute distribution. In recent years phase-field (PF) models have been developed to simulate solidification structure evolution and microsegregation. However many input data for the PF simulations are difficult to measure, including at the nanoscale the solid-liquid interfacial energy and its anisotropy, and at the macroscale the solidification conditions. In this study, an integrated scheme is proposed to resolve the above challenges by linking nanoscale molecular dynamics modelling (MD) and mesoscale front tracking (FT) modelling to the PF modelling. The approach is demonstrated in a case study in which the solidified structures and solute distributions are simulated in the weld pool for Fe-0.3wt. %C steel.

Computational prediction of the refinement of oxide agglomerates in a physical conditioning process for molten aluminium alloy

This research is financially supported by the EC FP7 project “High Shear Processing of Recycled Aluminium Scrap for Manufacturing High Performance Aluminium Alloys” (Grant No. 603577).

An integrated framework for multi-scale multi-physics numerical modelling of interface evolution in welding

The project Modelling of Interface evolution in advanced Welding (MIntWeld) is a 4-year international research project funded by the European Commission under their FP7 programme. Its main target is to develop a numerical toolbox which can be used to predict the evolution of interfaces during welding. There are various interfaces involving multiple phenomena and different spatial scales, which can be simulated using corresponding numerical modelling methods respectively. The modelling methods include quantum dynamics, molecular dynamics, phase field, phase field crystal, computational fluid dynamics, phase transformation and heat transfer, thermodynamics, continuum mechanics and life and defects prediction. Although each modelling method is based on different physical theories and involves different scales, they are not isolated. Therefore, this project aims to design a common framework which couples each model with the upstream and/or downstream model at the relevant neighbouring length scales. The data exchange framework which underpins the coupling of the models is described, and typical examples addressing the solution to the challenges faced, such as those of data interpolation between one discretisation of the computational domain and another, are discussed. Initial successes from the model-linking efforts of the authors are also presented.

The Scale-Up of High Shear Processing for the Purification of Recycled Molten Scrap Aluminium Alloy: Key Features of Fluid Flow

In order to remove impurities in scrap aluminum alloys, hence increasing their value, a laboratory-scale high shear processing (HSP) unit for mixing the molten alloy was developed, which makes it possible to remove iron-based contaminants using physical conditioning, at relatively low cost. In order to make this technology applicable in the industrial environment, we are now investigating the scale-up of HSP by using computer simulation. The computational research quantitatively predicts a variety of key features of fluid flow, which determine the feasibility of the scale-up. These include the mass flow rate through the mixing head, the effective agitation of the melt in the bulk crucible, and the shear rate that can be achieved. Based on the configuration of HSP that we review in this paper, we predict that it is feasible to achieve a factor of four scale-up in the volume of liquid alloy treated.