An experimentally validated numerical analysis of UHP-FRC subjected to blast loading
Bibliographic record
Abstract
This paper presents a new material constitutive model for simulating the uniaxial material behavior of ultra-high performance fiber reinforced concrete (UHP-FRC). The model accounts for the contribution of the steel fiber content to the tensile behavior. The model variables are the fracture energy, the characteristic length, and the crack bandwidth. Thus, it guarantees a mesh size independent numerical modeling of UHP-FRC. The model is developed based on the reported results of a state-of-the-art and highly accurate experimental investigation for the uniaxial behavior of UHP-FRC. This paper also adopts the concrete damage plasticity model (CDP) as a multi-axial yield surface criterion and presents the applicability of the material constitutive model and CDP for modeling UHP-FRC under unconfined non-contact blast loading. The results of the numerical models are validated against the experimental data of shock tube testing conducted by the authors at the University of Ottawa shock tube in collaboration with Ryerson University. The results revealed that the developed material constitutive model accurately represented the uniaxial behavior of UHP-FRC. The CDP model combined with the material constitutive model developed in this study can accurately model UHP-FRC structures under unconfined non-contact blast loading.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".