Published October 10, 2025
| Version v1
Dataset
Open
Dataset for Dynamic Modulus Prediction: GRA-MLR Compared with Sigmoidal Modelling for Asphalt Mixtures with Reclaimed Asphalt within Weave-UNISONO 2021 project NCN project No 2021/03/Y/ST8/00079, and GACR project GA22-04047K
Authors/Creators
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1.
Czech Technical University in Prague
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2.
University of Udine
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3.
Warsaw University of Technology
Description
Summary:
A total of 62 asphalt concrete (AC) mixtures were investigated. They involved three grading types (AC 11, AC 16, AC 22), four bitumen types (50/70, 70/100, 160/220, PMB), and four reclaimed asphalt contents (20%, 30%, 40%, 50%).
Two testing methods were used: the 4-point bending test on prismatic specimens (4PB–PR) at 10Hz and temperature 0°C, 10°C, 20°C and 20°C, and the indirect tension test on cylindrical specimens (IT-CY) at 0°C, 15°C and 27°C.
The dataset includes:
Outcomes of the experimental carried out on AC 11, AC 16, AC 22 mixtures:
01 bitumen_Infrastructures.csv
02 basic properties HMA.csv
03 stiffness modulus IT-CY.csv
04 dynamic modulus.csv
Notes (English)
This research was conceptualized and developed as part of activities related to project GA22-04047K, funded by The Czech Scientific Foundation (GACR), and project No. 2021/03/Y/ST8/00079, funded by the Polish National Science Centre (NCN) under the Weave-UNISONO 2021. The dataset was used for analyses for the journal paper titled "Evaluating Factors Influencing Dynamic Modulus Prediction: GRA-MLR Compared with Sigmoidal Modelling for Asphalt Mixtures with Reclaimed Asphalt", which is available on https://doi.org/10.3390/infrastructures10100269
Files
01 bitumen_Infrastructures.csv
Additional details
Identifiers
Funding
- Czech Science Foundation
- GACR GA22-04047K
- National Science Centre
- (NCN) Weave-UNISONO 2021 2021/03/Y/ST8/00079