MétaCan
Menu
Back to cohort
Record W2903136365 · doi:10.1080/14680629.2018.1552620

Effects of extreme climatic conditions on pavement response

2018· article· en· W2903136365 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

VenueRoad Materials and Pavement Design · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMoistureEnvironmental scienceGeotechnical engineeringLimitingWater contentTensile strainUltimate tensile strengthGeologyMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Conventionally it has been presumed that heavy traffic loading is the main driver that causes pavements to reach its limiting performance criteria such as fatigue and permanent deformation, and as a result, pavement designs have primarily only incorporated traffic loading. However, close monitoring of pavements has revealed that in fact, traffic loading alone may not create the conditions that lead to sudden failure of pavements. One aspect that is often not directly included in pavement design is the climatic factors, specifically temperature and moisture variations of the pavement soil. The occurrence of climatic extremes is becoming ever so frequent and there is a pressing need to better understand the effects of these extreme climatic conditions on pavement performance. This study presents the findings of an investigation into the effects of moisture and environmental conditions on the mechanical behaviour of granular pavements. The study was conducted with the aim of determining how seasonal effects from hot and wet climatic conditions impact on the sudden failure of pavements. Data was collected from state-of-the-art instrumentation on two field pavement sites located in Sunshine Coast, Australia. The sites were monitored over three years, and variations in daily temperature, moisture and strain values were analysed. Cyclic strain variations were observed in a cemented pavement basecourse layer where large fatigue tensile strains were present when moisture increased and temperature decreased. The results indicate that as moisture rises and temperature falls, critical fatigue strain increase above the fatigue endurance limit. This occurs when moisture was at or above optimum moisture content and surface layer temperature was between 38°C and 31°C. The data indicated that the change in pore pressure as a result of moisture and temperature variations within the granular basecourse soil were causing the strains in the pavement. Heavy traffic volume only had a minor effect on basecourse strain although the combined effect of soil moisture, temperature and heavy traffic loading was a cause for large fatigue strains in the pavement.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.496

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 head0.018
GPT teacher head0.222
Teacher spread0.203 · 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