Residual Stress Pattern Prediction in Spray Transfer Multipass Welding by Means of Numerical Simulation

One of the main problems of gas metal arc welding (GMAW) process is the generation of residual stresses (RS), which has a direct impact on the mechanical performance of welded components. Nevertheless, RS pattern prediction is complex and requires the simulation of the welding process. Consequently, most of the currently used dimensioning approaches do not consider RS, leading to design oversized structures. This fact is especially relevant in big structures since it generates high material, manufacturing and product transportation costs. Nowadays, there are different numerical methods to predict the RS generated in GMAW process, being Goldak’s method one of the most widely used model. However, the use of these methods during the design process is limited, as they require experimentally defining many parameters. Alternatively, in this chapter, a new methodology to define the heat source energy based on the spray welding physics is exposed. The experimental validation of the methodology conducted for a multipass butt weld case shows good agreement in both the temperature pattern (9.16% deviation) and the RS pattern (42 MPa deviation). Finally, the proposed methodology is extended to analyse the influence of the thickness and the number of passes in the RS pattern of thick T-joint welds

Procedure to predict residual stress pattern in spray transfer multipass welding

Gas metal arc welding (GMAW) is one of the most used joining method in the industry. However, one of the main problems of this process is the generation of residual stresses which have direct impact on the fatigue life of welded components. Nevertheless, residual stress pattern prediction is complex and requires the simulation of the welding process. Currently, there are different numerical methods to predict the residual stresses generated in GMAW process, being Goldak’s method one of the most widely used model. However, the main limitation of these methods is that they require defining many parameters experimentally and, consequently, this method is not valid during design process. Alternatively, in this work, it is developed a procedure where the heat source is defined based on the welding physics for spray transfer welding. The developed procedure has been validated for a spray transfer multipass butt weld case. Results have shown good correspondence with an average deviation of 9.16 % in thermal field and 42 MPa in the final residual stress field. Thus, the developed procedure has been validated as a cost-effective alternative method to estimate residual stress pattern in spray transfer multipass welding. Furthermore, the developed method does not require any welding experimental characterization once the efficiency of the used welding machine is defined. The proposed method can be used as a valid tool to optimize the welding process in order to minimize the residual stress field and, consequently, improve the fatigue life

NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark

In this position paper, we argue that the classical evaluation on Natural Language Processing (NLP) tasks using annotated benchmarks is in trouble. The worst kind of data contamination happens when a Large Language Model (LLM) is trained on the test split of a benchmark, and then evaluated in the same benchmark. The extent of the problem is unknown, as it is not straightforward to measure. Contamination causes an overestimation of the performance of a contaminated model in a target benchmark and associated task with respect to their non-contaminated counterparts. The consequences can be very harmful, with wrong scientific conclusions being published while other correct ones are discarded. This position paper defines different levels of data contamination and argues for a community effort, including the development of automatic and semi-automatic measures to detect when data from a benchmark was exposed to a model, and suggestions for flagging papers with conclusions that are compromised by data contamination.Comment: Accepted at EMNLP2024-Finding

A numerical analysis of multiaxial fatigue in a butt weld specimen considering residual stresses

Residual Stress (RS) pattern changes considerably depending on the width of the plates and the welding parameters, having effect on the fatigue strength. Most of the standards do not consider them and in some works, yield stress is taken as residual stressvalue. It results in a very conservative estimation of fatigue life. Authors developed recently a numerical model to predict more properly the value of RS pattern depending on the plate thickness. In a welded joint, considering the RS and alternating axial loads, the evolution of the stresses is multiaxial, becoming necessary its study. Therefore, the aim of this work is to analyse different fatigue indicator parameters (Smith-Watson-Topper, Fatemi-Socie, and Critical Plane implementation of the Basquin equation) in order to predict the fatigue behaviour of butt-weld components. For that purpose, the numerical model to predict the RS pattern in welded joint developed by this research group is used

Bateriaren Zahartzeaz Kontziente den Energiaren Kudeaketako Estrategiaren Sentsibilitate-Analisia

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Intelligent and Adaptive Fleet Energy Management Strategy for Hybrid Electric Buses

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Adaptive Energy Management Strategy for a Hybrid Shunter Locomotive

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Development of a self-adaptive cycle ageing model for Li-ion batteries using Machine Learning methods

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Energy Management Improvement Based on Fleet Learning for Hybrid Electric Buses

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