Improved procedure for calculating the cleared pressure acting on a finite target due to a mid-field blast
Bibliographic record
Abstract
For a structure subjected to it, a blast shockwave may be the severest load it will experience in its service life. A structure inadequately designed against blast may experience extensive damage and, in extreme cases, may collapse completely. Ensuring an adequate design depends on the accurate prediction of the blast shockwave and the loads it will impart on the structure. Blast shockwaves, however, are notoriously difficult to predict. The difficulties arise in part due to the reflected pressure and impulse developed by a blast shockwave depending on the obstacle’s response and geometry. Clearing is a result of the blast shockwave propagating around the edge of an obstacle, thus reducing the pressure build up from what would develop on an infinite surface. Thus, a clearer understanding of this phenomenon, and a simple practical method for predicting it, would improve blast load predictions and aid in blast resistant design. There are several experimental studies reported in the literature investigating this phenomenon. The studies, however, are limited to small scale blasts, and the prediction tools they propose are complicated to use. This article extends the range of available results numerically using ANSYS Autodyn, and proposes a tool to aid the blast resistant design engineer in more accurately quantifying the cleared blast loads imparted on a structure or structural element. Thus, after validating that Autodyn was suitable for investigating clearing problems, a series of two-dimensional models were built to investigate the parameters affecting clearing. The parameters investigated were the range, blast scaled distance, and distance to the edge of the target. The results of the numerical study resulted in a design aid for determining the cleared blast shockwave pressure on a finite target a given distance from the edge. The design aid proposed in this article is simple and applicable over a wide range of scaled distances.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".