Finite element modeling of the heat source during welding of 415 steel joints (13%CR-4% NI) with the robotic FCAW
Bibliographic record
Abstract
Residual stress is one of the most known problems through welding process in industry, as it caused the durability of welded part to reduce. Finite element analysis can predict the thermal distribution induced by welding process along the part, thereby calculating the residual stress. Several approaches have been developed to simulate the temperature variation and the residual stresses during welding. \n \nDespite all the efforts carried out by scholars to predict the temperature field within the welding processes, the lack of accuracy still remains an issue in the neighbouring of the heataffected zone. This study was intended to precisely calculate the thermal field within and in the vicinity of the heat affected zone through multi-pass welding using finite element analysis. A developed thermal finite element code at IREQ (Institut de recherche d'Hydro-Québec) was employed to calculate the thermal field within the multi-pass welding process. The program was modified to consider thermal properties of martensitic stainless steel 415 as the base material in order to offer a more reliable simulation of the heat transfer. Then, the capability of the program to predict the temperature distribution was evaluated at given nodes in the plate during multi-pass welding through comparison with the experimentally collected data. Goldak’s moving heat source was applied in the program to consider the induced thermal energy to the part by the welding process into the simulation. Furthermore, the element birth and death method were employed to model the deposition of the filler metal. In order to link the experimental and the numerical results, 20 thermocouples were installed in the plate, and thereby the temperature variation was monitored during welding process. \n \nThe map of micro hardness and microstructure of cross-sections were analyzed to compare with the predicted configuration of the heat-affected zone in the simulation. At last in this study, the micro-hardness of small specimens were compared upon experimentally reproduction of the analytically simulated thermal history on the specimen, to the microhardness of the node of the welded part model corresponding to this thermal history. \n \nThe comparison of the calculated and the experimentally measured thermal profile through the thermocouples demonstrate that the model can fairly predict the temperature profile during the heating and the cooling processes for the multi-pass welding process. The calculated average error was less than 10°C within the three pass welding, which is negligible compared to welding temperature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".