Influence of Hydrogreen Bioasphalt on Viscoelastic Properties of Reclaimed Asphalt Mixtures
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.
Bibliographic record
Abstract
The incorporation of reclaimed asphalt pavement (RAP) into asphalt mixtures exposes some challenges from the design perspective because of the aged asphalt binder in RAP. Steps are being taken to offset the addition of stiff materials, often with the use of rejuvenating additives. This paper summarizes the laboratory evaluation of one of the available bio-rejuvenating agents called BituTech RAP. High RAP content mixtures used in Manitoba, Canada, were evaluated to study the impact of BituTech RAP on the viscoelastic properties of asphalt mixtures to overcome any possible moisture damage or thermal cracking problems that might arise in such a wet–freeze environment. The laboratory experiment consisted of the production and test of mixtures that contained 15% and 50% RAP, with and without BituTech RAP. The 2S2P1D analogical model was used to generate the complex modulus (E*) of the various evaluated mixtures and to assess the influence of BituTech RAP on the storage and loss moduli. The addition of BituTech RAP improved the moisture resistance of the mixtures that contained RAP, as observed after three freeze–thaw cycles. The addition of BituTech RAP restored the thermal cracking properties of the mixtures revealed by the thermal stress restrained specimen test. The use of BituTech RAP could result in cost savings without the need to use a softer binder, as long as the high-temperature properties of the mixtures were not jeopardized.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it