Accelerated Laboratory Evaluation of Joint Sealants Under Cyclic Loads
Bibliographic record
Abstract
The sealing of joints and cracks in pavement structures has been in practice since the early 1900s. The optimized selection of joint sealant products can extend pavement service life and reduce annual maintenance and rehabilitation needs particularly in regions with experience extreme climatic conditions. Early sealant materials were not subjected to standardized testing procedures and many failed as a result. Recently, several test procedures have been investigated and a few have been accepted into approved standards, such as the American Society for Testing and Materials (ASTM). The variability of the sealants and the empirical nature of the tests have not been effective in predicting sealant behavior in the field. Also, since ASTM laboratory test procedures require long and sophisticated tests that many highway or transportation agencies are unable to perform, therefore relying on past performance or previous field trials. This potentially leaves many of the newer and better performing sealants off the approved list of many agencies because of the lengthy and expensive process of field acceptance. The purpose of this research was to investigate and rank the performance of eight hot pour joint and crack sealant materials for applicability for use in Manitoba through a performance based lab testing approach. The project involves laboratory testing of sealant materials to verify fundamental properties and performance simulation under cyclic loading. The results of the laboratory tests indicated that Type I sealants exhibited higher initial load values and also experienced adhesion failure at both the 0C and 30 C test temperatures. The Type IV sealants generally exhibited lower resistance to load and three of the eight sealants did not show signs of failure at any of the three test temperatures. Low modulus sealants are typically able to withstand larger extension. The accelerated testing compared sealants subjected to displacements similar to traffic and temperature loadings in the field. In general, and based on the limited number of sealant products tested, Type I sealants performed poorly when compared to Type IV sealants. The results show that the fatigue test can be used as a performance based testing for successfully evaluating sealant performance in the lab. However the results of this study are preliminary and are based on a limited number of samples. The lab ranking must be correlated and verified with field performance data that used the eight sealants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".