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Record W4402426536

Fatigue and restoration of bituminous mixtures during cyclic loading and rest

2023· dissertation· en· W4402426536 on OpenAlexaboutno aff
Frank Ndanusa Williams

Bibliographic record

Venuetheses.fr (ABES) · 2023
Typedissertation
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsRest (music)AsphaltMaterials scienceEnvironmental scienceComposite materialMedicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

This PhD research is within the framework of the work of RILEM (The International Union of Laboratories and Experts in Construction Materials, Systems and Structures) Technical Committee (TC) 278-CHA: Crack-Healing of Asphalt Pavement Materials. The objectives of this study entail firstly, the analysis of DSR test data to evaluate damage and recovery of bituminous binders with data obtained from Politecnico di Torino, Italy and University of Waterloo, Canada. Secondly, the development of ENTPE (Ecole Nationale des Travaux Publics de l’Etat) laboratory test procedure to analyze and evaluate damage and recovery of bituminous mixtures. The Université Gustave Eiffel (France) provided the required bitumen and bituminous mixtures. The study focused on performing repetitive loading and rest tests on binders and mixtures in order characterize damage and recovery of material properties. To successfully undertake this task, different test protocols and analysis methods were carried out on binders and mixtures, with the primary goal to differentiate restoration and reversible phenomena. All the rheological measurements carried by the two laboratories (Politecnico di Torino, Italy and University of Waterloo, Canada) were performed by means of a DSR from Anton Paar Inc. (Physica MCR 301 and MCR 102 respectively), using an 8-mm parallel plates geometry with a 2-mm gap. The tests performed in this experimental campaign were carried out in strain-control mode. The test involved using the linear amplitude sweep (LAS) test under various loading and rest period durations to effectively determined the recovery behaviour of binder. Therefore, different recovery protocols based on the LAS test were carried out to evaluate the recovery behaviour of the binders. From the result on the binder, Different phenomena occurring during loading and rest were either reversible and not reversible. Therefore, the test protocol does not allow identifying and estimating different phenomena.A test protocol developed at ENTPE was further improved and carried out on bituminous mixtures. The test procedure is composed of two parts in strain-controlled tension/compression mode on cylindrical samples. In the first part, short complex modulus tests (200 cycles at 10 Hz) at temperatures ranging from 8°C to 14°C and strain amplitudes ranging from 50 to 110µm/m are used to examine the dependency of the mechanical characteristics on strain amplitude and temperature. The aim of the CMT is basically to characterize the linear viscoelastic (LVE) behaviour of the studied bituminous mixtures at undamaged condition. In the second part, five partial fatigue tests (at 10°C) are carried out (each consisting of 100,000 cycles at a 100µm/m strain amplitude and frequency 10 Hz). Each fatigue lag is followed by a 48-hour rest period which consist of short complex modulus tests (100 cycles at 10 Hz) done at predetermined intervals to track the recovery of mechanical parameters. All the two parts of the tests carried out on the mixtures tested. From the results from mixtures, restoration and unrecovered variations of LVE properties during rest after fatigue loading were successfully isolated, with over 80% of the observed variation of 3D mechanical properties (E* and ѵ*) during cyclic loading is recovered after 48 hours of rest.

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 categoriesMeta-epidemiology (narrow)
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 score0.421
Threshold uncertainty score1.000

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 head0.026
GPT teacher head0.276
Teacher spread0.250 · 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
Published2023
Admission routes1
Has abstractyes

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