Asphalt Mix Compaction Modeling
Sector: Power Transmission • Location: Washington, United States of America (USA)
Source: Federal Highway Administration (FHWA)
Phase I Technology Review, Model Selection. This project will identify mathematical models that could be applied to the compaction of hot-mix asphalt (HMA) and modify them to be suitable for modeling HMA compaction. Phase II will include: input determination, verification/calibration, sensitivity analysis/development of guidelines, and final report. This phase will identify parameters to be determ
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | completed |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | Phase I Technology Review, Model Selection. This project will identify mathematical models that could be applied to the compaction of hot-mix asphalt (HMA) and modify them to be suitable for modeling HMA compaction. Phase II will include: input determination, verification/calibration, sensitivity analysis/development of guidelines, and final report. This phase will identify parameters to be determined or estimated for the model selected in Phase I and perform a sensitivity study on the parameters. The intended outcomes of the project are to theoretically relate laboratory and field compaction; understand the important parameters in obtaining density without sacrificing performance; and improve the construction process to obtain the optimum in-place density. Researchers are collaborating with United States Department of Energy Argonne National Laboratory to utilize its Transportation Research and Analysis Computing Center (TRACC) cluster for computational capabilities. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
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