Rutting prediction of asphalt pavement with semi-rigid base: Numerical modeling on laboratory to accelerated pavement testing-Reference-Cited by-同舟云学术

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Rutting prediction of asphalt pavement with semi-rigid base: Numerical modeling on laboratory to accelerated pavement testing

Published:2023-04 Issue: Volume:375 Page:130903
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Liu Zhen,Gu Xingyu^ORCID,Ren Hua

Funder

Scientific Research Foundation of the Graduate School of Southeast University

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference44 articles.

1. GPR-based detection of internal cracks in asphalt pavement: A combination method of DeepAugment data and object detection;Liu;Measurement,2022

2. Research on Rutting Deformation Monitoring Method Based on Intelligent Aggregate;Tan;IEEE Trans. Intell. Transp. Syst.,2022

3. Predicting rutting performance of asphalt mixture from binder properties and mixture design variables;Yan;Road Mater Pavement,2022

4. Evaluation of High-Temperature Performance Indexes of Anti-rutting Asphalt Mixture;Zhang;J. Test. Eval.,2021

5. Establishment and verification of prediction models of creep instability points of asphalt mixtures at high temperatures;Gu;Constr. Build. Mater.,2018

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1. Novel base predictive model of resilient modulus of compacted subgrade soils by using interpretable approaches with graphical user interface;Materials Today Communications;2024-08

2. Investigation of rutting performance of asphalt mixture and pavements based on mesostructured finite element simulation;International Journal of Pavement Engineering;2024-07-04

3. Finite Element Analysis of Geogrid-Incorporated Flexible Pavement with Soft Subgrade;Applied Sciences;2024-07-03

4. Study on the correlation between spatial variability of asphalt mixture material parameters and fracture performance;Case Studies in Construction Materials;2024-07

5. AI-based recognition for road distressed from GPR measurement using artificial neural networks;International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024);2024-06-13

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