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Record W610724523 · doi:10.33593/iccp.v10i1.382

Composite Pavement Systems – A Sustainable Approach for Long-Lasting Concrete Pavements

2025· article· en· W610724523 on OpenAlexaboutno aff
Shreenath Rao, M I Darter

Bibliographic record

VenueProceedings of the International Conference on Concrete Pavements · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
FundersFederal Highway AdministrationUniversity of MinnesotaMinnesota Department of TransportationUniversity of PittsburghU.S. Department of Transportation
KeywordsComposite numberGeotechnical engineeringCivil engineeringForensic engineeringEngineeringGeologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

This paper summarizes work performed under the Strategic Highway Research Program project R21 on developing MEPDG-compatible mechanistic-empirical design procedures, test methods, and construction guidelines and specifications, for two-lift PCC/PCC composite pavements and HMA/PCC composite pavements. Composite pavements consisting of high quality top layer(s) have been proven in Europe and in the United States to provide long lives with excellent surface characteristics and rapid renewal when needed. The lower PCC layer is a sustainable JPC or CRC pavement that utilizes recycled and lower cost locally available materials, thus reducing the need to haul aggregates over long distances. As part of this research, three full-scale instrumented test sections on the MnROAD mainline roadway (I-94, west of Minneapolis) were constructed in Spring 2010. The sections include one HMA/JPC and two two-lift PCC sections subject to real highway traffic. Accelerated Pavement Tests (APT) using the Heavy Vehicle Simulator (HVS) were used at the University of California Pavement Research Center (UCPRC) at Davis to evaluate various HMA/PCC test sections. These test sections were constructed in Fall 2009. The research also includes evaluation of in-service composite pavement across the U.S., Canada, and Europe. The results from these experiments were used to develop performance models and procedures for designing HMA/PCC and PCC/PCC composite pavements.

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 score0.605
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.023
GPT teacher head0.257
Teacher spread0.234 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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