Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.4
3.1
Journals
Buildings
Special Issues
Development and Structural Applications of Green High-Performance Fiber-Reinforced Concrete
share announcement

Development and Structural Applications of Green High-Performance Fiber-Reinforced Concrete

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1296

Special Issue Editors

Dr. Qiao Liao

E-Mail Website
Guest Editor
College of Architecture & Environment, Sichuan University, Chengdu 610065, China
Interests: engineering cementitious composites; lightweight concrete; fiber reinforced polymer; structural engineering; finite element analysis
Dr. Pengfei Men

E-Mail Website
Guest Editor
School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Interests: ultra-high-performance concrete; high-performance steel-concrete composite structures; high-strength steel structures; flexural and shear behaviour
Special Issues, Collections and Topics in MDPI journals
Dr. Wenxiang Cao

E-Mail Website
Guest Editor
School of Infrastructure Engineering, Nanchang University, Nanchang 330031, China
Interests: low-carbon cement; heavy metal treatment; resource utilization of solid waste; advanced functional materials

Special Issue Information

Dear Colleagues,

Green high-performance fiber-reinforced concrete (G-HPFRC) has great potential for application in infrastructure construction and repair, attributed to its high ductility and excellent durability. G-HPFRC has become the preferred material for large-span bridges, high-rise buildings and key tunnel linings. Accordingly, this Special Issue invites research papers focused on the development and structural applications of G-HPFRC. This Special Issue, titled Development and Structural Applications of Green High-Performance Fiber-Reinforced Concrete, will provide new knowledge for G-HPFRC. Original research, theoretical and experimental studies, case studies, and comprehensive review papers are invited for possible publication. Relevant topics to this Special Issue include, but are not limited to, the following subjects:

  • Engineered cementitious composite (ECC);
  • Ultra-high performance concrete (UHPC);
  • Concrete durability and mechanical properties;
  • Performance of concrete structures;
  • Concrete 3D printing technology.

Dr. Qiao Liao
Dr. Pengfei Men
Dr. Wenxiang Cao
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 250 words) can be sent to the Editorial Office for assessment.

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. Buildings 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

  • engineered cementitious composite
  • ultra-high performance concrete
  • durability property
  • mechanical behavior
  • structural performance
  • concrete 3D printing

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

20 pages, 9486 KB  
Article
Enhancing Ultra-High-Performance Concrete with High-Titanium Slag Sand: A Sustainable Approach to Low Carbon Emissions
by Bixiong Li, Chengcheng Yan, Lianghui Li, Wenfeng Liu, Yanke Zhang and Sumin Guan
Buildings 2026, 16(10), 1865; https://doi.org/10.3390/buildings16101865 - 8 May 2026
Viewed by 232
Abstract
This study aims to explore the feasibility of utilizing high-titanium slag sand (HTSS) as a sustainable alternative to quartz sand in ultra-high-performance concrete (UHPC). The results indicated that incorporating HTSS accelerated cement hydration, enhancing 7-d and 28-d compressive strengths by up to 42.1% [...] Read more.
This study aims to explore the feasibility of utilizing high-titanium slag sand (HTSS) as a sustainable alternative to quartz sand in ultra-high-performance concrete (UHPC). The results indicated that incorporating HTSS accelerated cement hydration, enhancing 7-d and 28-d compressive strengths by up to 42.1% and 33.1%, respectively. Notably, at a 100% replacement ratio, the mixture exhibits distinct strain-hardening behavior with uniaxial tensile strength exceeding 6 MPa. Concurrently, autogenous shrinkage is reduced by 32% at 5 h and 68% at 7 d, while CO2 emissions and energy consumption are lowered by 53 kg/m3 and 826 kJ/m3, respectively. Despite its rough and porous morphology, HTSS only marginally affects rheological properties. These findings provide theoretical insights into the development of low-carbon, low-shrinkage UHPC through the strategic valorization of industrial solid waste. Full article
(This article belongs to the Special Issue Development and Structural Applications of Green High-Performance Fiber-Reinforced Concrete)
►▼ Show Figures

Figure 1

30 pages, 4101 KB  
Article
Influence of Data Structure on Prediction Error in Machine Learning-Based Concrete Compressive Strength Models
by Yelan Mo, Bixiong Li, Chengcheng Yan and Xiangxin Hu
Buildings 2026, 16(8), 1537; https://doi.org/10.3390/buildings16081537 - 14 Apr 2026
Viewed by 293
Abstract
Machine learning has been widely used for concrete compressive strength prediction, yet previous studies have focused mainly on algorithm comparison and isolated feature-processing strategies. The coupled influence of dataset characteristics on prediction error has received less systematic attention. This study investigates concrete strength [...] Read more.
Machine learning has been widely used for concrete compressive strength prediction, yet previous studies have focused mainly on algorithm comparison and isolated feature-processing strategies. The coupled influence of dataset characteristics on prediction error has received less systematic attention. This study investigates concrete strength prediction from a data structure perspective by examining three structural variables, namely, sample size, feature size, and compressive strength range. A unified experimental framework was constructed using 15 concrete datasets. Correlation, partial correlation, information entropy, and relief were employed to reorganize feature subsets, and the resulting error trends were evaluated using artificial neural network (ANN), support vector regression (SVR), and random forest (RF) models. The results show that prediction error generally decreases first and then becomes stable as feature size increases, although the location of the low-error region depends on the dataset and the filtering method. Larger sample size is associated with improved prediction stability, whereas wider strength range tends to increase prediction difficulty. Based on these observations, an empirical relationship was established to describe the joint effect of sample size, feature size, and strength range on prediction error. The findings indicate that the attainable error level in concrete strength prediction is controlled not only by model form but also by dataset organization and feature configuration. Within the present framework, the study provides a practical basis for designing feature systems and interpreting model performance across datasets with different structural characteristics. Full article
(This article belongs to the Special Issue Development and Structural Applications of Green High-Performance Fiber-Reinforced Concrete)
►▼ Show Figures

Figure 1

20 pages, 16046 KB  
Article
Study on the Debris Flow Vulnerability of Mountainous Stilted Frame Structures Based on Progressive Collapse Analysis
by Guo Li, Wenhui Zeng, Maomin Wang, Liping Li, Zehan Xuan, Kaipeng Zhao, Lu Gao, Yang Tang, Zhongguo Chen and Bixiong Li
Buildings 2026, 16(7), 1373; https://doi.org/10.3390/buildings16071373 - 30 Mar 2026
Viewed by 412
Abstract
To address the progressive collapse of mountainous stilted RC frames induced by debris flows, this study establishes a three-dimensional refined solid model using ABAQUS. The alternate path method (element removal method) is employed to simulate the failure of ground-floor columns under impact, revealing [...] Read more.
To address the progressive collapse of mountainous stilted RC frames induced by debris flows, this study establishes a three-dimensional refined solid model using ABAQUS. The alternate path method (element removal method) is employed to simulate the failure of ground-floor columns under impact, revealing the underlying damage evolution mechanism. The results indicate that the loss of an edge column compromises structural stability significantly more than that of a corner column. Sequential multi-column failure leads to a nonlinear accumulation of damage; specifically, the simultaneous failure of a ‘corner column and its adjacent edge column’ completely severs the outer load-transfer paths, triggering a drastic inward load redistribution. Furthermore, under extreme scenarios, the maximum structural displacement and nodal stress surge to 66.67 mm and 40 MPa, respectively, while the axial force of the core central column jumps by nearly 150% (reaching 2.67 × 106 N). The crushing of internal central columns due to overloading is identified as the critical mechanism triggering global collapse. Based on these findings, design recommendations are proposed, emphasizing the reinforcement of upstream edge columns and the construction of a ‘component-joint-global’ hierarchical defense system. Full article
(This article belongs to the Special Issue Development and Structural Applications of Green High-Performance Fiber-Reinforced Concrete)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop