Fatigue Characterization of WMA and Modeling Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Fatigue Characterization of WMA and Modeling Using Artificial Neural Networks

Published:2022-03 Issue:3 Volume:34 Page:
ISSN:0899-1561
Container-title:Journal of Materials in Civil Engineering
language:en
Short-container-title:J. Mater. Civ. Eng.

Author:

Abd Duraid M.¹^ORCID,Al-Khalid Hussain²

Affiliation:

1. Lecturer, Dept. of Civil Engineering, College of Engineering, Univ. of Anbar, Ramadi, Iraq (corresponding author). ORCID: .

2. Retired; formerly, Professor, Dept. of Civil Engineering, School of Engineering, Univ. of Liverpool, The Quadrangle, Liverpool L69 3GQ, UK.

Publisher

American Society of Civil Engineers (ASCE)

Subject

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

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29MT.1943-5533.0004100

Reference35 articles.

1. Fatigue performance characterization of warm-modified bituminous binders

2. Adhesion properties of warm-modified bituminous binders (WMBBs) determined using pull-off tests and atomic force microscopy

3. An investigation into the impact of warm mix asphalt additives on asphalt mixture phases through a nano-mechanical approach

4. Novel Methodology to Investigate and Obtain a Complete Blend between RAP and Virgin Materials

5. Neural Networks in Civil Engineering: 1989–2000

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1. Effect of carbonation of soil-slag mixtures on the resilient behaviour and structural response of an asphalt pavement;Road Materials and Pavement Design;2024-01-17

2. Effect of Acid and Thermo-Mechanical Attacks on Compressive Strength of Geopolymer Mortar with Different Eco-Friendly Materials;Sustainability;2023-09-30

3. Characterization of rutting resistance of warm-modified asphalt mixtures tested in a dynamic shear rheometer;Journal of the Mechanical Behavior of Materials;2023-01-01

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