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Record W2287706372 · doi:10.4271/2006-01-3587

Comparative Testing for Aftermarket (Secondary Item) Truck Brake Components by the US Army and Industry Partners

2006· article· en· W2287706372 on OpenAlexaff
Leo P. Miller, Carlos Agudelo

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2006
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsEngineering Link (Canada)
FundersU.S. Department of Defense
KeywordsTruckAutomotive engineeringBrakeAutomotive industryAeronauticsEngineeringManufacturing engineeringComputer scienceAerospace engineering

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Military and commercial fleets share many challenges, most of which are driven by Federal laws, regulations, and policies.</div> <div class="htmlview paragraph">The US military has one of the largest and most varied wheeled vehicle fleets in the world with a broad range of vehicle weights and types, most over 10,000 lbs GVW. These vehicle brake systems include disc and drum, using mechanical, hydraulic, and air actuation systems.</div> <div class="htmlview paragraph">The US military buys vehicle systems only, not the individual components or subsystems other than for spare parts (a.k.a. Secondary Items). In addition, brake shoes are bought as assembled units only and not as separate brake blocks or lining.</div> <div class="htmlview paragraph">The objective of the Government project presented in this paper was to provide a decision-making tool so that the responsible engineering authority could make a reasoned decision on the acceptability of alternative spare parts and sources through a Government-approved standardized off-vehicle testing process. Subject paper presents the background, different test plans, test procedures, and the main workflow for 1) potential offerors interested in pursuing a brake component (secondary item) supply contract with the US Military, 2) comparative testing for non-standard vehicle configurations (overloaded), and 3) research and development (R&D) of alternative systems.</div> <div class="htmlview paragraph">The output of the Government's effort was the development of the “ATPD 2354” specification and its pre-planned replacement, a DODISS-approved Federal Test Standard (FTS) in MIL-STD-962 format.</div>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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 designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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