Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Kurumsal BaşvuruSign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Language

Kurumsal Başvuru

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Contact

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Development Super Fibre Warm Mix Asphalt for Desert Environments: Mechanical Performance and Implications for Non-Destructive Evaluation

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2025

Development Super Fibre Warm Mix Asphalt for Desert Environments: Mechanical Performance and Implications for Non-Destructive Evaluation

0 Datasets

0 Files

en
2025
Vol 30 (10)
Vol. 30
DOI: 10.58286/31707

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Mohammed Al-osta
Mohammed Al-osta

King Fahd University Of Petroleum & Minerals

Verified
Suleiman Abdulrahman
Mohammed Al-osta
Hamad Al-Abdul Wahhab
+4 more

Abstract

This study investigates the mechanical performance of Super Fibre Warm Mix Asphalt (WMA) using Non-Destructive Testing (NDT) based on Resilient Modulus (MR). Four fibre types: commercial Dellanite Fibre (DF), waste Cellulose Fibre (CF), Wool Fibre (WF), and Jute Fibre (JF) were added at 0.3% by weight to Evotherm-modified bitumen, mixed at 130°C, and compacted at 115°C. MR testing was conducted at 25°C and 40°C to evaluate fatigue and rutting behaviour, respectively. At 25°C, DF and CF exhibited the highest MR values of 3830 MPa and 3774 MPa, indicating superior fatigue resistance. At 40°C, CF had the highest MR (1698 MPa), followed by DF (1647 MPa), showing better rutting resistance. JF consistently showed the lowest performance, with MR values of 1444 MPa (25°C) and 679 MPa (40°C). Statistical analysis confirmed significant differences among fibres (p < 0.001). The findings demonstrate that DF and CF substantially enhance WMA stiffness and temperature resilience.

How to cite this publication

Suleiman Abdulrahman, Mohammed Al-osta, Hamad Al-Abdul Wahhab, Waqas Rafiq, Ali Mohammed Babalghaith, Abdulhadi A. Al‐Juhani, Abdulwarith Ibrahim Bibi Farouk (2025). Development Super Fibre Warm Mix Asphalt for Desert Environments: Mechanical Performance and Implications for Non-Destructive Evaluation. , 30(10), DOI: https://doi.org/10.58286/31707.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2025

Authors

7

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.58286/31707

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access