Welded T-joint connections of square thin-walled tubes under a multi-axial state of stress
Bibliographic record
Abstract
T-joint connections are used extensively in industry as parts of machine components and structures. The T-joint connection is typically constructed through the welding of its tubular members, with significant stress and strain concentrations occurring at the toe of the weld under loadings. In this paper, a welded T-joint connection of square hollow-section (SHS) tubes subjected to a multi-axial state of stress is examined both numerically and experimentally. The hot spot strains and stresses in the connection are determined through a detailed finite element (FE) analysis of the joint. The weld geometry is accurately modelled using FE. To model the weld, several full-scale welded T-joints were cut at the connection to obtain the size and depth of penetration of the weld. For the experimental study, a test rig with a hydraulic actuator capable of applying both static and cyclic loadings is designed and used. Strain gauges are installed at several locations on the joint to validate the FE model. The verified FE model is then used to study the through-the-thickness stress distributions of the tubes. It is shown that the membrane stresses which occur at the mid-surface of the tubes remain similar regardless of the weld geometry. The weld geometry only affects the bending stresses. It is also shown that the stress concentrations are highly localized at the vicinity of the weld toe. At a distance of about half of the weld thickness from the weld toe, the effect of the weld geometry on the bending stresses becomes insignificant as well. To reduce the stress concentrations at the T-joint, plate reinforcements are used in a number of different arrangements and dimensions to increase the load-carrying capacity of the connection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".