A Plane Equivalent Micro-truss Element for Reinforced Concrete Structures
Bibliographic record
Abstract
Plane or solid elements are the most commonly used elements for finite element analysis (FEA), especially for predicting the behaviour of reinforced concrete structures in engineering practices.However, there are some limitations in the continuum model built with plane or solid elements.Traditional FEA with the continuum model is not only time consuming due to numerous degrees of freedom but also difficult to predict crack propagation.Properly replacing the continuum model with micro-truss elements in the analysis could be cost effective, especially for automatically generating the strut-and-tie model (STM), which is an ideal tool for analysis and design of the distributed region (D region).In this paper, a micro-truss element consisting of four nodes, using horizontal, vertical and diagonal members only hinged at both ends of the element is proposed to replace the plane elements.The equivalence formulas between the micro-truss element and the plane element are derived.The result was validated by comparing the solution of three cases modelled by Abaqus standard element.Moreover, the feasibility of combining with other types of element was studied by modelling a simply supported beam with reinforcements.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".