Parametric Investigation on the Performance of RC Slabs Subjected to Accidental Impact Loadings
Bibliographic record
Abstract
Due to the loading intensities generated as a result of vehicular impacts, heavy drop weights, collision of ships and aircraft, debris impact loading form as a result of Tsunami and flood and impact forces generated due to the missiles, bullets and explosive loadings etc. may cause a reinforced concrete slab to withstand forces for a very short duration of time but having magnitudes and intensities much higher than the static loading rates.Several studies have already been carried out which focuses on investigating the response of slabs to accidental impacts having initial contact velocities of up to 1000m/s.The focus of these studies mainly aims in predicting the threshold value for the thickness of the reinforced concrete slabs under high-velocity projectiles impacts to restrict the level of penetration required in the nuclear and military structures.However, for the case of reinforced concrete slabs as a part of civil and non-protective structures, the loading intensities produced due to accidental and abnormal impact activities are mainly caused due to velocities of up to 10 m/s.Therefore, this investigation aims in studying the response of the reinforced concrete slabs subjected to low-velocity impact loading.Following a critical review of already published experimental studies and the empirical equations used in industry to predict the response of such slabs, a detailed parametric investigation on the response of the reinforced concrete slabs under low-velocity impacts has been carried out using a non-linear explicit dynamic technique using finite element software ABAQUS.The parametric investigation focuses on studying the influence of the velocity and thickness of the slab on the behaviour of the reinforced concrete slabs subjected to low-velocity impact loads.It was found that these parameters significantly influence the behaviour of the reinforced concrete slabs which are not explicitly considered in the empirical equations used by the industry, which in turn, as a result, does not always provide safe predictions for the case of the low-velocity impact loadings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".