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Enregistrement W7057400000

Investigating and Developing Fatigue-Healing Characterization of Asphalt Materials

2023· dissertation· en· W7057400000 sur OpenAlexfundaboutno aff

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2023
Typedissertation
Langueen
DomainePhysics and Astronomy
ThématiqueMagnetic confinement fusion research
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
Mots-clésAsphaltLimitingWork (physics)Filter (signal processing)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Canada’s aging highway network, consisting of over 1.1 million kilometres of roads, is a vital component in ensuring the safe and reliable day-to-day movement of people and goods. Flexible asphalt pavements experience deterioration due to repeated traffic and environmental loading, and as a consequence, may require costly maintenance and rehabilitation treatments to remain functional over their service life. An alternative strategy to these reactive treatments can be found in the form of self-healing asphalt pavements. \nThe innovative strategies employed in self-healing materials are rooted in natural and biological processes. In the simplest sense, as these materials become damaged, a natural healing response allows them to restore their integrity or functional properties. Bitumen and asphalt materials have a very similar intrinsic healing ability which has been recognized since it was first observed in the 1960s. Asphalt material self-healing arises from the asphalt cement and its ability to fill microcracks caused by repeated small strain amplitude loading (i.e., fatigue). Intrinsic healing is influenced by internal factors (e.g., asphalt cement chemistry, aging level, and modification type) and external factors (e.g., moisture, UV exposure, rest period duration and temperature, etc.). To overcome the limitations of intrinsic healing, several extrinsic healing technologies have been used in literature including molecular interdiffusion techniques, structures containing healing agents and secondary self-healing polymer phases. In recent studies, healing is primarily characterized using destructive accelerated fatigue and fracture-based tests with rest periods, but the lack of industry-standard tests and terminology for both asphalt cement and mixtures leads to an often-ambiguous understanding of healing itself. This lack of standardization limits the capability of researchers to effectively characterize the intrinsic healing ability, but also develop new extrinsic healing technologies. The principal goal of this thesis is then to investigate current self-healing characterization techniques and develop new testing protocols for asphalt materials. \nThe work presented in this thesis uses a multiscale approach to the healing characterization of asphalt materials in collaboration with RILEM Technical Committee CHA-278 (Crack Healing of Asphalt Materials). Based on the initial healing study of unaged and aged asphalt cement containing a chemical warm mix additive using the linear amplitude sweep healing (LASH) test, it was evident that current generation DSR-based fatigue and healing characterization techniques experience measurement artifacts caused by geometry changes/ specimen flow under loading. As a result, a comprehensive evaluation of the linear amplitude (LAS) test and different failure criteria found in literature was conducted. These failure criteria were then supplemented with the complementary parameters: the electric torque inflection point, the peak normal force, and the flow strain amplitude (FSA) as determined from the novel DSR Visual Analysis workflow. From the analysis of the LAS test, it was shown that failure criteria strain amplitudes could be categorized as either peak or post-peak behaviour; the traditional peak shear strain amplitude was concluded to be the most conservative failure criteria for all aging levels. From the FSA analysis, it was demonstrated that the shear stress-strain peak correlated with the onset of specimen flow, thus, the peak value was selected as the maximum strain amplitude for the first phase end condition for subsequent healing tests. In cooperation with the RILEM CHA-278 Task Group (TG) 2a, a second version of the LASH test protocol was proposed and evaluated based on the recommendations of the LAS visual analysis. From various works in literature, the Pure-LASH or P-LASH peak-based analysis method was derived using fracture mechanics to model the restoration ability of several binders at different aging levels using the LASH V2 protocol. Test parameters such as rest period duration and aging level were found to not be statistically significant factors, but further analysis determined that “damage” was only observed when the first loading phase end condition was the peak shear stress strain amplitude (γpeak) as flow had already irreparably change the geometry of the DSR specimen. The general conclusion of these works was that geometric changes of the DSR sample during loading produce increasingly inaccurate measurements of post-peak data in amplitude sweep tests, thus, future work should take a greater emphasis on the characterization of pre-peak behaviour. \nAs a contribution to RILEM CHA-278 TG 2b, intermediate temperature fatigue tests with rest periods were conducted on a single asphalt mix at two strain levels. From the fatigue tests, a new fatigue model called the Intrinsic-VECD or iVECD linearization model was derived from the DGCB intrinsic damage model and simplified viscoelastic continuum damage model (VECD). The iVECD model was then extended to healing tests to separate “true” fatigue damage from common bias prevalent in accelerated fatigue testing of asphalt materials. From the iVECD model, several restoration/healing and damage indices were proposed: %Heal, %Recovery, %Restoration and Permanent Damage (%PD). Results of the iVECD healing indices indicated that the majority of recovery and healing occurs within the first 4 to 6 hours of the rest period. However, it was observed that increasing the strain level produces more permanent damage for the same loading duration. Finally, non-invasive ultrasonic measurements were coupled to these destructive fatigue tests and coda wave interferometry (CWI) was used to analyze the effects of multiple scattering due to damage and healing. Two windowing selection methods were proposed (i.e., a simplistic statistical method and an adaptive analytical method). Using both window selection techniques, it was demonstrated that CWI could capture the effect of both loading/unloading and was sensitive enough to clearly distinguish between different strain levels.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,023
Tête enseignante GPT0,245
Écart entre enseignants0,222 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission2
Résumé présentoui

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