Large-Scale Welding Process Simulation by GPU Parallelized Computing

The computational design of industrially relevant welded structures is extremely time consuming due to coupled physics and high nonlinearity. Previously, most welding distortion and residual stress simulations have been limited to small coupons and reduced order (from three-dimensional [3D] to two-dimensional [2D]), or inherent strain approximations were used for large structures. In this current study, an explicit finite element code based on a graphics processing unit was utilized to perform 3D transient thermomechanical simulation of structural components during welding. Laser brazing of aluminum alloy panels as representative of automotive manufacturing scenarios was simulated to predict out-of-plane distortion under different clamping conditions. The predicted deformation pattern and magnitude were validated by laser scanning data of physical assemblies. In addition, the code was used to investigate residual stresses developed during multipass arc welding of a nuclear industry pressurizer surge nozzle and subsequent welding repair where a 3D simulation was necessary. Taking the experimental data as reference, the 3D model predicted better residual stress distribution than a typical 2D asymmetrical model. Stress evolution in welding repair was also presented and discussed in this study. The efficient numerical model made it feasible to use integrated computational welding engineering to simulate welding processes for large-scale structures.

A Geometry-Based Welding Distortion Prediction Tool

The prediction of welding distortion requires expertise in computer simulation programs, a clear definition of the nonlinear material properties, and mesh settings together with the nonlinear solution settings of a coupled thermal–structural analysis. The purpose of this paper is to present the validation of an automatic simulation tool implemented in Ansys using Python scripting. This tool allows users to automate the preparation of the simulation model with a reduced number of inputs. The goal was, based on some assumptions, to provide an automated simulation setup that enables users to predict accurate distortion during the welding manufacturing process. Any geometry prepared in a CAD software can be used as the input, which gave us much geometrical flexibility in the shapes and sizes to be modeled. A thermomechanical loosely coupled analysis approach together with element birth and death technology was used to predict the distortions. The automation of the setup enables both simulation and manufacturing engineers to perform welding-induced distortion prediction. The results showed that the method proposed predicts distortion with 80–98% accuracy.

Welding distortion generated uncertainties in the vibrational behavior of a ladder-like structure

Recent developments in acoustic simulation methods allowed engineers to assess the vibroacoustic behavior of various type of structures within a virtual environment, thus allowing the replacement of prototype-based development with simulations. However, there are some factors, that cannot be considered in simulations in advance. In the present study, the effect of the distortions generated due to welding on a ladder-like structure equipped with flat plates was investigated. The measured acceleration frequency response functions were compared to finite element simulation results. The measured responses differed significantly from the simulation, even in the low frequency range, where the global modes were not expected to be altered or vanished. Investigation of the simulated results revealed that the additional modes were related to the vibration of the plates, which were assumed to be flat, instead of considering the warping caused by the welding process. After measuring the approximate deformation of the plates, an updated simulation model was made, introducing an approximate curvature in them. The results obtained with the updated simulation model performed much better in the low frequency range as well as in the third octave-averaged frequency bands up 1200 Hz. The sensitivity of the warping was also systematically evaluated.

Influence of Clamping for Out-of-Plane Welding Distortion Mitigation During Thin Steel Plates Welding

Thin steel plates is usually employed for lightweight application, while welding distortion in particular welding induced buckling, will significantly influence dimensional accuracy of thin-walled structure. As elementary investigation of out-of-plane welding distortion mitigation, butt and fillet welded joints with thin plates were experimentally conducted with considering clamping influence. Effective thermal elastic plastic FE computation was proposed to examine mechanical response caused by welding, and large deformation theory was applied to represent welding induced buckling. Good agreement between measured data and computed results can be observed. Furthermore, FE computation without clamping was also carried out to clarify the difference of plastic strains and residual stress comparing with experimental case. Influence of clamping on out-of-plane welding distortion mitigation was eventually proposed for mechanism understanding.

Multi-Pass Welding Distortion Analysis Using Layered Shell Elements Based on Inherent Strain

In this article, a layered shell element-based, elastic finite element method for predicting welding distortion in multi-pass welding is developed. The welding distortion generated in each pass can be predicted by employing layer-by-layer equivalent plastic strains as thermal expansion coefficients and using the heat-affected zone (HAZ) width as the mesh size. The final distortion can be expressed as the sum of the distortions for each pass. This study focuses on extraction of the equivalent plastic strain and HAZ width through 3D thermal elastic plastic analysis (TEPA) for each pass. The input variables extracted from each pass can be converted and added to simulate the final distortion of the multi-pass welding. A 10 mm thick, multi-pass butt-welded joint, subjected to three passes, is simulated via the proposed method. The predicted welding distortion is compared with the 3D TEPA results and the measured experimental data. The outcome indicates that good agreement can be obtained.

Geometry and Distortion Prediction of Multiple Layers for Wire Arc Additive Manufacturing with Artificial Neural Networks

Wire arc additive manufacturing (WAAM) is a direct energy deposition (DED) process with high deposition rates, but deformation and distortion can occur due to the high energy input and resulting strains. Despite great efforts, the prediction of distortion and resulting geometry in additive manufacturing processes using WAAM remains challenging. In this work, an artificial neural network (ANN) is established to predict welding distortion and geometric accuracy for multilayer WAAM structures. For demonstration purposes, the ANN creation process is presented on a smaller scale for multilayer beads on plate welds on a thin substrate sheet. Multiple concepts for the creation of ANNs and the handling of outliers are developed, implemented, and compared. Good results have been achieved by applying an enhanced ANN using deformation and geometry from the previously deposited layer. With further adaptions to this method, a prediction of additive welded structures, geometries, and shapes in defined segments is conceivable, which would enable a multitude of applications for ANNs in the WAAM-Process, especially for applications closer to industrial use cases. It would be feasible to use them as preparatory measures for multi-segmented structures as well as an application during the welding process to continuously adapt parameters for a higher resulting component quality.