Improving the Safety of Transportation of Dangerous Goods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The transportation of dangerous goods (DG) represents an important portion of the overall freight transport worldwide. Ground transport (excluding pipelines) moves approximately 21% to 31% of the total tonnage of DG in Canada. Accidents involving DG might occur at any time at any location along transport routes or within storage areas, and not only do they have an effect on people and the environment, but also they can have a great effect on the national economy. This paper presents the details of an experimental investigation studying the blast attenuation capability of suppressive shield panels (SSPs). Suppressive shield technology can be used for the storage, processing, and transport of explosive materials and can also be applied to protecting attractive targets and infrastructure deemed vulnerable to explosive attacks. Various configurations of commercially available steel angles were assembled as SSPs and evaluated for their ability to attenuate blast pressure from detonating Pentolite charges. Results obtained from the tests with 0.5-kg charges indicated that the SSPs attenuate the blast pressure to values in the range of 43% to 60%. The results of this research can be extended to include the design and construction of SSPs for transportation of DG by sea as well. Effectively, this can include the strengthening of current standard containers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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