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Record W2111434352 · doi:10.1520/gtj20140233

Dynamic Modulus Measurements of Bound Cement-Treated Base Materials

2015· article· en· W2111434352 on OpenAlexaff
Korakod Nusit, Peerapong Jitsangiam, Jayantha Kodikara, Ha H. Bui, Gordon L. M. Leung

Bibliographic record

VenueGeotechnical Testing Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsGeotechnical engineeringCementDynamic modulusBase (topology)ModulusMaterials scienceGeologyComposite materialForensic engineeringEngineeringDynamic mechanical analysisMathematics

Abstract

fetched live from OpenAlex

Abstract One of the most common methods used in road-pavement construction is the stabilizing of the conventional pavement base course layer. This is achieved by adding cement or lime to gain better material performance. However, obtaining modulus input parameters from a cement-stabilized base course layer for pavement-response analysis under real traffic conditions has proven difficult in that, to date, only ambiguous results have been produced. Using the flexural modulus or elastic modulus in the response analysis has certain limitations in embracing real pavement behavior under traffic and temperature conditions. Accordingly, a more reliable modulus input parameter for pavement analysis under traffic (cyclic) loads is required to obtain more precise and reliable outputs. Moreover, there is, at present, no test protocol to determine a suitable modulus for a cement-stabilized base material under the cyclic loading regime. This study aims to examine the real dynamic responses of cement-stabilized base course materials with a view to adapting the asphalt mixture performance tester (AMPT), a specifically designed dynamic modulus test machine used on asphalt concrete material. The AMPT dynamic modulus test has as an advantage in that loading and temperature regimes based on real pavement conditions can be rationally simulated and directly applied to the test samples. As such, the dynamic moduli of a cement-stabilized base course material can be obtained under different temperature and loading rates. Moreover, the effects of the dynamic strain range, cement content, and curing duration on the dynamic responses of a cement-stabilized base course material may also be examined. Cement-stabilized base course materials of 4 %, 5 %, and 6 % cement contents (by mass) were used as the study materials. The findings of this study indicate that curing durations and cement contents significantly influence the dynamic modulus values of cement-stabilized base course materials. However, the dynamic modulus is insignificantly affected by the changes in temperature and loading rates within a specific range of testing conditions in this study. The test results also reveal that cement-stabilized base course materials under examination behave in the manner of an elastic material when subjected to an axial compressive deformation of 45–105 μstrains. This is because of the dynamic modulus having no impact upon changes in the dynamic strain ranges or on the magnitudes of cyclic loads. Moreover, the dynamic moduli from this study were found to be much higher than the elastic moduli suggested by previous studies. However, the flexural moduli, which are derived from standard flexural tests, demonstrated close values to those of the dynamic moduli obtained in this study. In the study, the dynamic modulus of cement-stabilized base course materials, derived from the dynamic modulus using AMPT, could more reasonably embrace the dynamic responses of a material under traffic-loading conditions. This leads to a somewhat more reliable modulus input for the cement-stabilized base course materials used in a rational pavement design and analysis method.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.114
GPT teacher head0.295
Teacher spread0.181 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations7
Published2015
Admission routes1
Has abstractyes

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