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Record W2161385308 · doi:10.4271/2014-01-2523

On Similarities and Differences of Measurements on Inertia Dynamometer and Scale Testing Tribometer for Friction Coefficient Evaluation

2014· article· en· W2161385308 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSAE International Journal of Materials and Manufacturing · 2014
Typearticle
Languageen
FieldEngineering
TopicBrake Systems and Friction Analysis
Canadian institutionsEngineering Link (Canada)
Fundersnot available
KeywordsTribometerDynamometerInertiaScale (ratio)Coefficient of frictionFriction coefficientMaterials scienceEngineeringMechanical engineeringComposite materialPhysicsClassical mechanicsGeographyCartography

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Inertia dynamometers are commonly used to determine the friction coefficient of brake assemblies. Dynamometers are a well-established platform, allow testing under controlled conditions, exhibit a good correlation to many situations encountered in real driving, and are comparatively economical and less time-consuming than full vehicle test. On the other side of the spectrum is the use of scaled tribometer. These test systems make possible a test without the entire brake corner. This separation allows the investigation of the frictional-contact only (frictional boundary layer) speedily and independently of a given brake system or vehicle configuration. As the two test systems (inertia dynamometers and tribometers) may have different users with possibly different tasks, the question remains regarding how comparable the two systems are. These issues provide incentives to better define the fields of investigations, correlation, and applicability for the two systems.</div><div class="htmlview paragraph">In order to provide further insights and learning on this topic, this paper focuses on the measurement of the friction coefficient and the wear behavior using inertia dynamometer and scaled pin-on-disc tribometer testing. Thus, friction coefficient levels and sensitivity are investigated on both systems when using a tribometer based test sequence (test with constant speed) as well as using a standard inertia dynamometer test procedure (with dynamic braking with in-stop deceleration). Different types of lining-materials (e.g. low-met or OES, and NAO or RE) are tested and compared.</div><div class="htmlview paragraph">One major difference between the two systems is the energy input and thus the different temperature regimes. Therefore the influence of the initial temperature is a critical item the paper focuses on.</div><div class="htmlview paragraph">Lastly, the paper presents potential areas for integration with the objective of improving the overall correlation between the two methods and the ability to use a scale tribometer to predict full inertia dynamometer results for friction and wear evaluations during the product life-cycle.</div></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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.250
Teacher spread0.212 · 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