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Record W3145023195

CRASH PERFORMANCE OF ENERGY-ABSORBING GUIDE RAIL TERMINALS

2012· article· en· W3145023195 on OpenAlexaboutno aff
Ryan W. Esligar, Eric Hildebrand

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCrashCollisionOffset (computer science)IntrusionQuarter (Canadian coin)EngineeringComputer scienceForensic engineeringTransport engineeringComputer securityGeologyGeography
DOInot available

Abstract

fetched live from OpenAlex

Energy-absorbing guide rail terminals (EAGRTs) are a form of end treatment designed to absorb energy during a collision and prevent intrusion into the impacting vehicle. After several years of use in New Brunswick there is evidence to suggest these systems may not always perform as desired. This study was conducted to evaluate the real-world performance of EAGRT systems in collisions throughout the Province. A retrospective review of 103 collisions that occurred prior to the study was supplemented with an in-depth analysis and reconstruction of 18 collisions that occurred during the study period. The study involved two EAGRT systems; the ET-Plus and the SKT-350. In most cases the EAGRT absorbed a significant amount of energy (an average of 315 KJ per crash); however, several observations were made. It was determined that not all EAGRT systems are being installed in accordance with the manufacturer's guidelines. Intrusion of system components into the vehicle was documented in two collisions. It was also observed that many of the collision configurations were outside the boundaries defined by both the NCHRP Report 350 and MASH. The major recommendations focused on installation and maintenance issues. The study also revealed areas in need of further research. These areas include the feasibility of using systems that maximize lateral offset to reduce snowplow damage, and whether an impact offset greater than one quarter would be more critical than an impact with only a quarter offset, which is currently used in the NCHRP Report 350 (and MASH) Test 3-30. For the covering abstract of this conference see ITRD record number 201211RT334E.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2012
Admission routes1
Has abstractyes

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