Measurement of Dynamic Modulus and Master Curve Modeling of Hot Mix Asphalt from Senegal (West Africa)
Bibliographic record
Abstract
The main purpose of this paper is to model the master curve of dynamic modulus |E*| for Hot Mix Asphalt mix designed with aggregate from Senegal named basalt of Diack and quartzite of Bakel. The prediction model used is the Witczak model, used in the Mechanistic-Empirical Pavement Design Guide. A study has been conducted in the Laboratory of Pavements and Bituminous Materials. Six different HMA (BBSG 0/14 mm) were subjected to complex modulus test by tension-compression according to the European or Canadian procedure using the same range of temperatures and frequencies. For each mixture studied the uniqueness of modulus curves in the Cole-Cole or in Black diagrams have shown that the asphalt mixes are thermorheologically simple materials and the Canadian test process is suitable for determining the HMA complex modulus mix designed with the aggregates from Senegal. This implies their tender with the principle of time-temperature equivalence. The test results were used to model the master curves of HMA studied. A correlation with the results of dynamic modulus measured have shown an accuracy of R2 = 0,99 and p = 0,00 in STATISTICA software, which allows to conclude that the sigmoidal model has good modeling of the dynamic modulus.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".