Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving binders

This study aims to improve laboratory aging procedures for bituminous materials to better replicate field conditions. Two binders and mixtures were subjected to various levels of humidity, temperatures, pressures, film thicknesses, and aging durations. By comparing these lab-aged samples to field-ag...

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Main Authors: Sadaf Khalighi, Lili Ma, Yasmine Mosleh, Diederik van Lent, Aikaterini Varveri
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Materials & Design
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Online Access:http://www.sciencedirect.com/science/article/pii/S0264127524008955
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author Sadaf Khalighi
Lili Ma
Yasmine Mosleh
Diederik van Lent
Aikaterini Varveri
author_facet Sadaf Khalighi
Lili Ma
Yasmine Mosleh
Diederik van Lent
Aikaterini Varveri
author_sort Sadaf Khalighi
collection DOAJ
description This study aims to improve laboratory aging procedures for bituminous materials to better replicate field conditions. Two binders and mixtures were subjected to various levels of humidity, temperatures, pressures, film thicknesses, and aging durations. By comparing these lab-aged samples to field-aged samples, the study aims to simulate real-world aging more accurately. Fourier-transform infrared (FTIR) spectroscopy and frequency sweep tests were employed to analyse these samples. Multivariate techniques—Principal Component Analysis (PCA), Multiple Linear Regression (MLR), and Support Vector Regression (SVR)—were used to explore chemical and rheological relationships, evaluate the interchangeability of aging factors, and quantify the equivalency between laboratory and field aging. The findings revealed that increased temperature, pressure, and duration lead to more oxidative products. The PCA distinguished between two binders and aging trends, highlighting the importance of both FTIR and rheological measurements. The SVR model demonstrated strong predictive performance for rheological properties, identifying critical FTIR region, 710–912 -1cm. By MLR model, optimal aging conditions to simulate nine years of field aging for porous asphalt and stone mastic asphalt were back-calculated. The Euclidean distance found laboratory conditions that closely match field-aged samples. SVR models provided predictions of simulated field aging time for various laboratory aging conditions.
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publishDate 2024-12-01
publisher Elsevier
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series Materials & Design
spelling doaj-art-38235415db3e4b51a9db676ce85458b62025-08-20T02:52:34ZengElsevierMaterials & Design0264-12752024-12-0124811352010.1016/j.matdes.2024.113520Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving bindersSadaf Khalighi0Lili Ma1Yasmine Mosleh2Diederik van Lent3Aikaterini Varveri4Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands; Corresponding author.Delft University of Technology, Stevinweg 1, 2628 CN Delft, the NetherlandsDelft University of Technology, Stevinweg 1, 2628 CN Delft, the NetherlandsNetherlands Organizations for Applied Scientific Research (TNO), Van Mourik Broekmanweg 6, 2628 XE Delft, the NetherlandsDelft University of Technology, Stevinweg 1, 2628 CN Delft, the NetherlandsThis study aims to improve laboratory aging procedures for bituminous materials to better replicate field conditions. Two binders and mixtures were subjected to various levels of humidity, temperatures, pressures, film thicknesses, and aging durations. By comparing these lab-aged samples to field-aged samples, the study aims to simulate real-world aging more accurately. Fourier-transform infrared (FTIR) spectroscopy and frequency sweep tests were employed to analyse these samples. Multivariate techniques—Principal Component Analysis (PCA), Multiple Linear Regression (MLR), and Support Vector Regression (SVR)—were used to explore chemical and rheological relationships, evaluate the interchangeability of aging factors, and quantify the equivalency between laboratory and field aging. The findings revealed that increased temperature, pressure, and duration lead to more oxidative products. The PCA distinguished between two binders and aging trends, highlighting the importance of both FTIR and rheological measurements. The SVR model demonstrated strong predictive performance for rheological properties, identifying critical FTIR region, 710–912 -1cm. By MLR model, optimal aging conditions to simulate nine years of field aging for porous asphalt and stone mastic asphalt were back-calculated. The Euclidean distance found laboratory conditions that closely match field-aged samples. SVR models provided predictions of simulated field aging time for various laboratory aging conditions.http://www.sciencedirect.com/science/article/pii/S0264127524008955Laboratory accelerated agingField agingMultivariate analysisMLRPCASVR
spellingShingle Sadaf Khalighi
Lili Ma
Yasmine Mosleh
Diederik van Lent
Aikaterini Varveri
Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving binders
Materials & Design
Laboratory accelerated aging
Field aging
Multivariate analysis
MLR
PCA
SVR
title Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving binders
title_full Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving binders
title_fullStr Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving binders
title_full_unstemmed Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving binders
title_short Multivariate chemo-rheological framework for optimizing laboratory aging protocols of paving binders
title_sort multivariate chemo rheological framework for optimizing laboratory aging protocols of paving binders
topic Laboratory accelerated aging
Field aging
Multivariate analysis
MLR
PCA
SVR
url http://www.sciencedirect.com/science/article/pii/S0264127524008955
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AT yasminemosleh multivariatechemorheologicalframeworkforoptimizinglaboratoryagingprotocolsofpavingbinders
AT diederikvanlent multivariatechemorheologicalframeworkforoptimizinglaboratoryagingprotocolsofpavingbinders
AT aikaterinivarveri multivariatechemorheologicalframeworkforoptimizinglaboratoryagingprotocolsofpavingbinders