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Emerging Approaches for Performance Assessment and Prediction of Cement-Based Materials

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Construction and Building Materials".

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 3483

Special Issue Editors


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Guest Editor
Department of Civil, Geological, and Environmental Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA
Interests: sustainable construction materials and technologies; alternative binders; supplementary cementitious materials; CO2 sequestration systems; smart infrastructure materials and systems; nanotechnology; responsive/adaptive polymer automation in construction; additive and robotic construction; multi-sensory inspection; big data; cloud computing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Computer and Electrical Engineering, California State University, Bakersfield, CA, USA
Interests: sensors; big data; smart materials; advanced monitoring technologies

Special Issue Information

Dear Colleagues,

This Special Issue brings together a collection of research papers that delve into emerging approaches for assessing performance of cement-based composites. The selected contributions present innovative techniques, experimental studies, and numerical modeling approaches that shed light on the intricate nature of these materials and their response under various loading conditions.

The Issue covers a broad spectrum of topics, including:

  1. Novel imaging techniques: These contributions explore state-of-the-art imaging methods to provide detailed insights into the microstructure of cement-based composites at different length scales.
  2. Smart sensing systems: These contributions emphasize the development and application of smart sensors, wireless sensor networks, and data analysis techniques for real-time monitoring of structural behavior of cement-based composites.
  3. Multi-scale modeling: These contributions present computational modeling approaches to simulate and predict the behavior of cement-based composites.
  4. Data-driven approaches: These contributions showcases the use of data-driven methodologies, machine learning techniques, and big data analysis to enhance the characterization and assessment of cement-based materials.

The collection of papers in this Special Issue serves as a valuable resource for researchers, engineers, and practitioners involved in the design, construction, and maintenance of cement-based structures, providing insights that can contribute to the development of more durable, sustainable, and high-performance cement-based composites.

Dr. Nima Farzadnia
Dr. Amin Malek
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mechanical performance evaluation
  • durability assessment
  • imaging techniques
  • smart sensing systems and Big Data
  • multi-scale modeling.

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Published Papers (2 papers)

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Editorial

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2 pages, 147 KiB  
Editorial
Special Issue: Emerging Approaches for the Performance Assessment and Prediction of Cement-Based Materials
by Nima Farzadnia and Amin Malek
Materials 2023, 16(21), 6974; https://doi.org/10.3390/ma16216974 - 31 Oct 2023
Viewed by 773
Abstract
The current Special Issue, entitled “Emerging Approaches for Performance Assessment and Prediction of Cement-Based Materials”, aims to showcase cutting-edge research into the technologies, smart sensing systems, and tools for assessing and predicting the performance of cement-based materials [...] Full article

Research

Jump to: Editorial

24 pages, 5254 KiB  
Article
Performance Prediction of Hybrid Bamboo-Reinforced Concrete Beams Using Gene Expression Programming for Sustainable Construction
by Hafiz Ahmed Waqas, Alireza Bahrami, Mehran Sahil, Adil Poshad Khan, Ali Ejaz, Taimoor Shafique, Zain Tariq, Sajeel Ahmad and Yasin Onuralp Özkılıç
Materials 2023, 16(20), 6788; https://doi.org/10.3390/ma16206788 - 20 Oct 2023
Cited by 6 | Viewed by 2112
Abstract
The building and construction industry’s demand for steel reinforcement bars has increased with the rapid growth and development in the world. However, steel production contributes to harmful waste and emissions that cause environmental pollution and climate change-related problems. In light of sustainable construction [...] Read more.
The building and construction industry’s demand for steel reinforcement bars has increased with the rapid growth and development in the world. However, steel production contributes to harmful waste and emissions that cause environmental pollution and climate change-related problems. In light of sustainable construction practices, bamboo, a readily accessible and eco-friendly building material, is suggested as a viable replacement for steel rebars. Its cost-effectiveness, environmental sustainability, and considerable tensile strength make it a promising option. In this research, hybrid beams underwent analysis through the use of thoroughly validated finite element models (FEMs), wherein the replacement of steel rebars with bamboo was explored as an alternative reinforcement material. The standard-size beams were subjected to three-point loading using FEMs to study parameters such as the load–deflection response, energy absorption, maximum capacity, and failure patterns. Then, gene expression programming was integrated to aid in developing a more straightforward equation for predicting the flexural strength of bamboo-reinforced concrete beams. The results of this study support the conclusion that the replacement of a portion of flexural steel with bamboo in reinforced concrete beams does not have a detrimental impact on the overall load-bearing capacity and energy absorption of the structure. Furthermore, it may offer a cost-effective and feasible alternative. Full article
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