Blast response of ultra-high performance concrete beams with high-strength steel and varying detailing levels under far-field blast loads
Why this work is in the frame
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Bibliographic record
Abstract
This paper studies the influence of high-strength steel (HSS) and detailing level on the blast response of ultra-high-performance concrete (UHPC) beams. The variables in the tests included the steel grade (HSS vs. ordinary steel), fiber content (1–3 %), detailing level (blast, intermediate and ordinary) and tension steel ratio (ρ = 1.0–2.4 %). UHPC beams with both ordinary and HSS bars were subjected to shock-tube blast testing, followed by residual static testing to assess post-blast capacity. Key findings indicate that incorporating HSS bars significantly improved blast performance by reducing damage and displacements compared to ordinary steel. Increasing the HSS ratio from 1.0 % to 1.5 % further enhanced blast resistance, prevented bar fracture, and preserved significant residual capacity, leading to more ductile failure. The inclusion of steel fibers enabled relaxed detailing (such as increasing tie spacing to s = d/2 or eliminating stirrups altogether), while still achieving comparable performance to beams with stringent blast detailing. This comparable performance highlights the potential of steel fibers to simplify construction. However, since the beams ultimately failed due to bar fracture, the mechanisms driving bar rupture must be carefully considered when designing the detailing in UHPC beams. Finite-element modelling using LS-DYNA’s Winfrith concrete model for UHPC and the Linear Plasticity for high-strength steel accurately predicted blast responses, including displacements, reaction loads, and damage modes. Overall, the study demonstrates that combining UHPC with optimized fiber content and HSS reinforcement provides a novel solution that enhances blast resilience while permitting for practical and constructible detailing approaches.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it