Record link: 
http://hdl.handle.net/20.500.12708/230057
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Title: 
Inverse-designed neural networks for rheological prediction of asphalt binders using SARA properties
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Citation: 
Khadijeh, M., Stüwe, S., Mirwald, J., Hofko, B., Eberhardsteiner, L., & Varveri, A. (2026). Inverse-designed neural networks for rheological prediction of asphalt binders using SARA properties. International Journal of Pavement Engineering, 27(1). https://doi.org/10.1080/10298436.2026.2711076
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Publisher DOI: 
10.1080/10298436.2026.2711076
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Publication Type: 
Article - Original Research Article
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Language: 
English
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Authors: 
Khadijeh, Mahmoud 
Stüwe, Sophie 
Mirwald, Johannes 
Hofko, Bernhard 
Eberhardsteiner, Lukas 
Varveri, Aikaterini 
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Organisational Unit: 
E230-03 - Forschungsbereich Straßenwesen 
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Journal: 
International Journal of Pavement Engineering 
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ISSN: 
1029-8436
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Date (published): 
2026
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Publisher: 
TAYLOR & FRANCIS LTD
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Keywords: 
SARA fractation; asphalt binder; inverse neural network; machine learning; cycle consistent
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Project title: 
CD-Labor für Chemo-Mechanische Analyse von bituminösen Stoffen: Chemo-M46 (Christian Doppler Forschungsgesells) 
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Research Areas: 
Materials Characterization: 50%
Computational Materials Science: 25%
Non-metallic Materials: 25%
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Science Branch: 
5070 - Humangeographie, Regionale Geographie, Raumplanung: 20%
2011 - Bauingenieurwesen: 30%
2013 - Verkehrswesen: 50%
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