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Record W3088898681 · doi:10.21608/jesaun.2007.114560

COMPARATIVE STUDY FOR ESTIMATION OF DYNAMIC STRESS AND STRAIN LEVELS INDUCED BY BLASTING VIBRATIONS

2007· article· en· W3088898681 on OpenAlexaboutno aff
Elseman I. Abdel-Rasoul

Bibliographic record

VenueJES. Journal of Engineering Sciences/JES. Journal of engineering sciences · 2007
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsRock blastingDynamic stressStructural engineeringVibrationStrain (injury)Stress (linguistics)EngineeringGeotechnical engineeringDynamic loadingAcousticsPhysicsMedicine

Abstract

fetched live from OpenAlex

This study investigates the truthfulness of the claims of damage of the buildings in the City of the 15th of May due to blasting vibrations. A comparative study has been carried out for three case studies: Golden Sunlight surface mine in Montana, Canada; Bani Khalid quarry, Samalout, Minia, and the limestone quarry of the National Cement Company in relation to the city of the 15th of May, Helwan, Egypt. As a result of the study, the magnitudes of the dynamic Young’s modulus, strains, and stresses have been found compatible for Golden Sunlight mine and Bani Khalild case studies. On the other hand, the case of the city of the 15th of May has showed very high magnitudes for both dynamic Young’s modulus and stresses. Hence, re-calculation and re-evaluation have been carried out following the procedures of Golden Sunlight mine and Bani Khalid cases. The obtained new magnitudes of Young’s modulus and stresses are found compatible with Golden Sunlight and Bani Khalid. Accordingly, the conclusions of the previous study on the City of the 15th of May that damages of the buildings in the City are due to blasting vibrations are not acceptable. Re-investigation of the damage in the buildings of the city has to be carried out to find other causes of the damage. These causes may be geological, environmental or even design causes.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.304
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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