Evaluation of differential temperature (ΔT)-based thermal segregation criteria for asphalt mixtures using full-coverage thermal profile data

Thermal segregation during asphalt mixture construction increases spatial variability in in-place density, potentially resulting in elevated air void contents and reduced pavement performance. Current quality control practices primarily rely on differential temperature (ΔT)-based criteria, which have remained largely unchanged despite advances in asphalt mixtures and paving practices. This study evaluated the applicability of current ΔT criteria using full-coverage thermal profile data from multiple asphalt mixture types in Texas. A total of 20,718 thermal profiles from 39 projects, representing approximately 588.6 miles (946.9 km) of paving, were analyzed over 150 ft (45.7 m) segments using the 98.5th–1st percentile method. Field evaluations of SP-C, DG-D, and SP-D mixtures were also conducted to examine relationships among placement temperature, profile ΔT, and laboratory-measured air void contents. Approximately 30% of profiles exhibited moderate thermal segregation, whereas 4.4% exhibited severe segregation. Elevated air void contents were observed at uniformly low placement temperatures (<250 °F [121 °C]) even when ΔT was relatively low, while some profiles with higher ΔT achieved acceptable compaction. These results indicate that ΔT primarily reflects temperature uniformity and may not adequately capture compaction risk associated with absolute placement temperature. Therefore, thermal segregation criteria should be refined to better reflect current paving practices and mixture behavior.

Authors

Institutions

Publication Details

Journal
International Journal of Pavement Engineering
Published
2026-10-07
DOI
https://doi.org/10.1080/10298436.2026.2737364
Primary Topic
Asphalt Pavement Performance Evaluation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of differential temperature (ΔT)-based thermal segregation criteria for asphalt mixtures using full-coverage thermal profile data

Jinho Kim
International Journal of Pavement Engineering
Asphalt Pavement Performance Evaluation
article

Evaluation of differential temperature (ΔT)-based thermal segregation criteria for asphalt mixtures using full-coverage thermal profile data

Jinho Kim
article en

Abstract

Thermal segregation during asphalt mixture construction increases spatial variability in in-place density, potentially resulting in elevated air void contents and reduced pavement performance. Current quality control practices primarily rely on differential temperature (ΔT)-based criteria, which have remained largely unchanged despite advances in asphalt mixtures and paving practices. This study evaluated the applicability of current ΔT criteria using full-coverage thermal profile data from multiple asphalt mixture types in Texas. A total of 20,718 thermal profiles from 39 projects, representing approximately 588.6 miles (946.9 km) of paving, were analyzed over 150 ft (45.7 m) segments using the 98.5th–1st percentile method. Field evaluations of SP-C, DG-D, and SP-D mixtures were also conducted to examine relationships among placement temperature, profile ΔT, and laboratory-measured air void contents. Approximately 30% of profiles exhibited moderate thermal segregation, whereas 4.4% exhibited severe segregation. Elevated air void contents were observed at uniformly low placement temperatures (<250 °F [121 °C]) even when ΔT was relatively low, while some profiles with higher ΔT achieved acceptable compaction. These results indicate that ΔT primarily reflects temperature uniformity and may not adequately capture compaction risk associated with absolute placement temperature. Therefore, thermal segregation criteria should be refined to better reflect current paving practices and mixture behavior.

International Journal of Pavement EngineeringVol. 27(1)
Texas Department of Transportation (US)
Openalex Percentile: Top 17%
Asphalt Pavement Performance Evaluation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.