Assessment of the effect of residual stresses on the mechanical behavior of steel lattice transmission towers
Bibliographic record
Abstract
Abstract: Power transmission lines predominantly involve lattice towers, which are typically composed of steel angle members connected together by means of bolted joints. An effective design of such structures requires the consideration of a range of complex phenomena likely to affect either the carrying capacity or the failure mode. In practice, simple numerical models are combined with standard design equations to consider these effects. A few advanced numerical models reported in the literature deal with eccentricities, stiffness of the connections, and joint slippage. However, the impact of residual stresses on the global behavior of lattice towers is not addressed in prior works. In this work, the influence of residual stresses is studied numerically using the finite element software Code_Aster. The proposed model employs multi-fibre beam elements to model the elastoplastic angle members, and discrete elements to represent the bolted connections. Both the connection eccentricity and the rotational stiffness of connections are modeled. The associated problem is solved in an incremental way, so as to deal with geometric and material nonlinearities, and the results are compared with experimental tests. Considering residual stresses in advanced models is an important step for the numerical evaluation of the failure of lattice towers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".