Dissolution of delta phase in Ni-based superalloy during linear friction welding: integrated multiphysics computational process modelling

Abstract

Linear friction welding (LFW) is an increasingly popular solid-state joining method for challenging applications such as integrated blade disk of aero-engines. However, the influence of friction-generated heat on the material microstructural evolution, material deformation and resultant mechanical performance of the manufactured components is not well understood. A novel integrated multiphysics computational modelling is presented for predicting the component-scale microstructural evolution of IN718 alloy during LFW. A modified time-temperature equivalence formulation was implemented for predicting the evolution of the δ phase, which was coupled with thermomechanical modelling of the LFW process. There is reasonably good agreement between the computational modelling results of this paper and the experimental results from the literature in terms of δ phase volume fraction and weld temperature. The integrated multiphysics computational modelling predicts the influence of process parameters on thermomechanical and microstructural processes of IN718 LFW. By systematically analysing the influence of 10 different LFW process parameter configurations, the friction pressure was identified as the most influential process parameter determining the extent of δ phase dissolution and weld temperature during LFW.

Computational modelling of dynamic recrystallisation of Ni-based superalloy during linear friction welding

“…3 Results and discussion [11,20,35]. Thermomechanical model verification in relation to weld temperature, axial shortening, and flash shape has been previously presented by the authors in [33,34]. Thus, this study focuses primarily on the analysis of the microstructural modelling results.…”

“…The thermomechanical model for LFW of IN718 was implemented by using dynamic temperature-displacement analysis in the Abaqus/Explicit solver, which is suitable for resolving contact problems as well as overcoming excessive element distortion by dynamic remeshing [55]. Similar thermomechanical modelling was previously presented by the authors, in which comprehensive presentations of the thermal and mechanical sub-models of IN718 during LFW can be found in [33,34]. The thermal sub-model and mechanical sub-model are fully coupled.…”

“…Heat transfer coefficient was specified as a fixed value of 100 Wm −2 K −1 [20,35,42]. The thermal properties and boundary conditions presented in this paper are the same as those presented by the authors in a past paper [34].…”

“…Geng et al applied Eqs. 10-13 within the temperature range (1213-1453 K), which is higher than the γ' and δ equilibrium solvus temperatures of 1172 K and 1283 K [30,34]. In this study, the critical temperature for onset of DRX is assumed to be 1213 K. The material constants in relation to DRX of γ grains of IN718 alloy were sourced from Geng et al [11,30].…”

“…LFW process optimisation can be achieved by experimentally varying three important welding parameters of such as friction pressure, oscillating frequency, and oscillating amplitude. Multiple researchers have reported the influence of different LFW parameter configurations on such as weld temperature, heating rate, and resultant microstructure and mechanical properties of IN718 weld [20,[33][34][35]. Ma et al [18] found that DRX and dynamic recovery (DRV) could be enhanced by increasing the friction pressure and oscillating amplitude of LFW.…”