Review
Green & Sustainable Science & Technology
Yuguang Mao, Jianhui Liu, Caijun Shi
Summary: RAC has lower autogenous shrinkage compared to NAC due to the internal curing effect of RCA; however, its drying shrinkage is larger mainly because of the mortar attached to OVA. Strengthening adhered mortar or removing it can effectively reduce the drying shrinkage of RCA.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Materials Science, Ceramics
Lifeng Zhang, Shaoqin Ruan, Kuangliang Qian, Xuliang Gu, Xiaoqian Qian
Summary: The study investigated the effects of wind speeds on early-age shrinkage and tensile strength of cement paste, showing that with increasing wind speed, shrinkage and tensile strength experienced changes, and wind speeds altered the proportion of capillary water evaporation and humidity difference between the surface and interior of specimens.
JOURNAL OF THE AMERICAN CERAMIC SOCIETY
(2022)
Article
Construction & Building Technology
Liang Li, Vinh Dao, Pietro Lura
Summary: The research focused on thermal and autogenous deformations of high-performance concrete at early ages, with a new Temperature Stress Testing Machine used to generate reliable data. Results showed that higher curing temperatures significantly accelerate autogenous shrinkage development, while at 35℃ curing, the shrinkage gradually becomes the largest after the initial period. Using the newly-measured linear CTE, an attempt was made to separate thermal strain and self-desiccation shrinkage, revealing the presence of non-negligible delayed thermal strain.
CEMENT & CONCRETE COMPOSITES
(2021)
Article
Chemistry, Physical
Christoph Strangfeld, Tim Klewe
Summary: This study investigates the moisture content and degree of hydration of different mixtures using two measurement methods. The results show that the calcium carbide method is a suitable alternative to the time-consuming drying method.
Article
Construction & Building Technology
Xu Luo, Jianming Gao, Shujun Li, Yasong Zhao, Gaofeng Chen, Cheng Liu
Summary: The early age hydration and autogenous shrinkage of blended cement containing brick powder (BP) were studied using hydration heat, internal relative humidity (IRH) and 1H NMR methods. The results show that BP can promote the early nucleation and growth process of cement. The unique porous structure of BP gives it water absorption property, which plays a role in internal curing. The internal curing effect of BP reduces the rate of decrease of IRH in cement paste and effectively reduces the autogenous shrinkage of cement paste.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Construction & Building Technology
Dongbing Jiang, Xiangguo Li, Yang Lv, Changjiao Li, Ting Zhang, Chenhao He, Difei Leng, Kai Wu
Summary: This study comprehensively analyzed the early-age hydration process of high performance cement pastes using H-1 nuclear magnetic resonance relaxometry and isothermal calorimetry, revealing the relationship between free water consumption and autogenous shrinkage. Results showed good agreement in hydration degree calculation methods and indicated that cement pastes with lower water/cement ratio exhibit higher autogenous shrinkage.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Construction & Building Technology
Chuyuan Wen, Dejian Shen, Yueyao Luo, Wenting Wang, Ci Liu, Ming Li
Summary: It was found that early-age autogenous shrinkage and thermal shrinkage in concrete can lead to cracking, but the addition of polypropylene macro fiber can improve mechanical properties and mitigate autogenous shrinkage. The early-age tensile creep behavior of concrete including creep, creep coefficient, and specific creep decreased with the inclusion of polypropylene macro fiber. A modified model for predicting the early-age specific creep of concrete reinforced with polypropylene macro fiber was proposed.
JOURNAL OF SUSTAINABLE CEMENT-BASED MATERIALS
(2023)
Article
Construction & Building Technology
Victor Revilla-Cuesta, Luis Evangelista, Jorge de Brito, Marta Skaf, Vanesa Ortega-Lopez
Summary: This study analyzed the effectiveness of MgO as a shrinkage-reducing agent in recycled aggregate high-performance concrete (HPC). The results showed that MgO could partially offset the autogenous shrinkage of HPC and reduce total shrinkage. However, the effectiveness of MgO was reduced with increasing amounts of recycled aggregate.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Crystallography
Xiaohui Yan, Yaogang Tian, Xin Lu, Jing Jiang, Lin Qi, Mengyuan Zhang
Summary: The study found that the replacement percentage of recycled sand is positively related to both drying and autogenous shrinkages of mortar. Increasing water to cement ratio leads to an increase in drying shrinkage but decrease in autogenous shrinkage. Adding fly ash inhibits shrinkages, while adding granulated blast-furnace slag reduces drying shrinkage but increases autogenous shrinkage.
Article
Construction & Building Technology
Bayram Tutkun, Ege Su Barlay, Caglar Yalcinkaya, Halit Yazici
Summary: This study investigates the effect of internal curing on the shrinkage strains of ultra-high-performance concrete under drying conditions. The results show that internal curing can effectively mitigate both autogenous and drying shrinkage strains, but excessive usage of internal curing materials and larger particle sizes may lead to increased cracking.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Materials Science, Ceramics
Weihao Zheng, Juan He, Yueping Tong, Junhong He, Xuefeng Song, Guochen Sang
Summary: The influence of reactive MgO on shrinkage properties of AAS cement was studied. It was found that reactive MgO increases autogenous shrinkage but has different effects on drying shrinkage depending on the type of activator. This is due to its influence on pore structure and hydration products.
CERAMICS INTERNATIONAL
(2022)
Article
Chemistry, Multidisciplinary
Byoungsun Park, Young Cheol Choi
Summary: The study found that carbon nanotubes accelerated the early hydration of cement pastes, and the compressive strength was highest when the CNT content was 0.1%. As the CNT content increased, the internal relative humidity decreased and autogenous shrinkage showed a decreasing tendency.
APPLIED SCIENCES-BASEL
(2021)
Article
Polymer Science
Jung Heum Yeon
Summary: The study demonstrates that internal curing through SAP effectively mitigates early-age residual stress build-up from autogenous shrinkage. However, the addition of SAP, regardless of type and content, does not significantly improve the shrinkage cracking resistance of mortar directly exposed to drying conditions.
Article
Construction & Building Technology
Victor Revilla-Cuesta, Luis Evangelista, Jorge de Brito, Vanesa Ortega-Lopez, Juan M. Manso
Summary: This study examined the impact of recycled aggregate content and maturity on the properties of high-performance concrete. The research found that increasing the recycled aggregate content and using early-age recycled aggregates with lower strength and stiffness worsened the mechanical behavior of concrete, while the hydration level of matured recycled aggregates affected the shrinkage performance of the concrete.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Construction & Building Technology
Dejian Shen, Ci Liu, Yueyao Luo, Haoze Shao, Xiaoyu Zhou, Songlin Bai
Summary: Ultra-high-performance concrete (UHPC) has superior performance but high early-age cracking potential due to autogenous shrinkage. Adding polypropylene fibers can enhance the tensile strength and reduce the cracking potential of UHPC under restrained conditions.
CEMENT & CONCRETE COMPOSITES
(2023)
Article
Environmental Sciences
Hamdy A. Abdel-Gawwad, Salah Kassem, Aref Abadel, Hussam Alghamdi, Moncef L. Nehdi, Hamad Shoukry
Summary: Geopolymer bricks were synthesized from lead glass sludge and alumina flakes filling waste. The use of thermally treated lead glass sludge improved the mechanical properties of the bricks and reduced the environmental impact.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Arash Mohammadi Fallah, Ehsan Ghafourian, Ladan Shahzamani Sichani, Hossein Ghafourian, Behdad Arandian, Moncef L. Nehdi
Summary: Proper analysis of building energy performance requires selecting appropriate models for complicated calculations. Machine learning has emerged as a promising solution for this problem. This study proposes a novel integrative machine learning model for predicting two energy parameters of residential buildings with superior accuracy.
Article
Green & Sustainable Science & Technology
Samira Rastbod, Farnaz Rahimi, Yara Dehghan, Saeed Kamranfar, Omrane Benjeddou, Moncef L. Nehdi
Summary: Recent developments in indirect predictive methods have led to promising solutions in energy consumption modeling. This study proposes and evaluates a new integrated methodology for estimating the annual thermal energy demand (D-AN), which is an indicator of building heating and cooling loads. The multilayer perceptron (MLP) neural network is trained using the symbiotic organism search (SOS) algorithm, known for its strength as a metaheuristic algorithm. Benchmark algorithms such as political optimizer (PO), harmony search algorithm (HSA), and backtracking search algorithm (BSA) are also used and compared. The results demonstrate that utilizing building properties within an artificial intelligence framework provides a suitable prediction for the D-AN indicator, and the suggested MLP-SOS model achieves accurate learning and reproduction of the nonlinear D-AN pattern with nearly 1% error and 99% correlation, outperforming other models like MLP-PO, MLP-HSA, and MLP-BSA. The discovered solution is expressed in an explicit mathematical format for practical applications in the future.
Article
Chemistry, Physical
Iman Faridmehr, Mohammad Ali Sahraei, Moncef L. Nehdi, Kiyanets A. Valerievich
Summary: One-part geopolymer concrete/mortar is a pre-mixed material that can be activated by water, reducing complexity and improving consistency in the mixing process. The study examined the effects of different materials and curing conditions on the compressive strength of one-part geopolymer paste. An ANN model was developed to estimate compressive strength and optimize the alkaline activator dosage. The results showed that increasing Na2O content and slag dosage improved compressive strength, with 6% Na2O being the optimum dosage.
Article
Chemistry, Physical
Aref A. Abadel, Hussam Alghamdi, Yousef R. Alharbi, Mohammed Alamri, Mohammad Khawaji, Mohammed A. M. Abdulaziz, Moncef L. Nehdi
Summary: This study investigated the production process of eco-efficient alkali-activated slag-based samples using recycled construction cementitious materials (RCCM) and red mud (RM). The findings showed that when a high quantity of dehydrated cement powder (DCP) and red mud were used, the strength and durability of the specimens improved significantly. It was concluded that DCP and RM could be potential sustainable binder substitutes, allowing waste valorization and reducing negative environmental impact.
Article
Chemistry, Physical
Mohammad Reza Akbarzadeh, Hossein Ghafourian, Arsalan Anvari, Ramin Pourhanasa, Moncef L. Nehdi
Summary: This study develops a novel integrative method for efficient prediction of concrete compressive strength (CCS) by tuning an artificial neural network (ANN) with electromagnetic field optimization (EFO). The results show that the ANN-EFO is a highly efficient hybrid model for the early prediction of CCS.
Article
Green & Sustainable Science & Technology
Xuesong Zhang, Farag M. A. Altalbawy, Tahani A. S. Gasmalla, Ali Hussein Demin Al-Khafaji, Amin Iraji, Rahmad B. Y. Syah, Moncef L. Nehdi
Summary: This research compared various machine learning models to forecast the uniaxial compressive strength (UCS) of rocks. The support vector machine with radial basis function outperformed all other methods and achieved high accuracy (R-2 = 0.99, PI = 1.92). The models showed excellent accuracy (R-2 > 90%) in estimating UCS, with a small average difference of +0.28% compared to the measured values.
Article
Green & Sustainable Science & Technology
Safeer Abbas, Farwa Jabeen, Adeel Faisal, Moncef L. Nehdi, Syed Minhaj Saleem Kazmi, Sajjad Mubin, Sbahat Shaukat, Muhammad Junaid Munir
Summary: The alkali-silica reaction (ASR) is a major cause of premature concrete degradation. This study investigated the effects of cement alkali content, exposure solution concentration, temperature, and test duration on mortar bar expansion. Various factors and their interactions were analyzed using a factorial experimental design. The study revealed the contribution of different exposure conditions to ASR expansion, highlighting the importance of selecting suitable aggregate sources for sustainable construction.
Article
Construction & Building Technology
Hossein Ghafourian, Seyed Sepehr Ershadi, Daria K. Voronkova, Sayeh Omidvari, Leila Badrizadeh, Moncef L. Nehdi
Summary: In recent years, research has been focused on designing buildings with higher energy efficiency and lower emissions while considering multiple objectives. This study aims to develop a new technique to solve this challenging multiple-objective optimization problem.
Article
Engineering, Environmental
Sepideh Nasrollahpour, Daryoush Yousefi Kebria, Moncef L. Nehdi, Amin Tanhadoust, Mohammad Ghavami
Summary: This study aimed to synthesize organoclay as an efficient alternative for removing BTEX and phenol from brackish water. The cetyltrimethylammonium bromide (CTAB) was utilized due to its high hydrophobicity and adsorption capabilities. The effects of contact time, DNAPL and LNAPL concentrations, and organoclay CECs were investigated. An adsorption capacity of 4.7-9.2 g/g was achieved, and a Bayesian neural network (BNN) model accurately predicted the adsorption capacity. The optimized CEC values were found to be around 150%-200%.
JOURNAL OF HAZARDOUS TOXIC AND RADIOACTIVE WASTE
(2023)
Article
Engineering, Civil
Jesika Rahman, A. H. M. Muntasir Billah, Palisa Arafin, Kamrul Islam, Moncef L. Nehdi
Summary: The study aims to develop a simple and efficient model for predicting the compressive strength of gusset plates. Machine learning techniques were used to select the CatBoost and XGBoost models, which outperformed existing methods with accuracy rates of 95% and 96%, respectively. These interpretable ML models provide a higher level of accuracy and performance compared to traditional methods.
ENGINEERING STRUCTURES
(2024)
Article
Engineering, Civil
Chunyi Xu, Moncef L. Nehdi, Kaile Wang, Afshin Marani, Lei Zhang
Summary: Replacing steel bars with glass fiber geogrids (GFG) can reduce the thickness of mortar joints and improve the seismic performance of autoclaved aerated concrete (AAC) masonry walls. Increasing the GFG configuration rate enhances the ultimate load-bearing capacity and ultimate displacements of wall specimens, approaching that of steel bar reinforced specimens. Finite element simulations show that the seismic performance of GFG-reinforced AAC masonry walls improves with increased vertical compressive stresses.
Article
Construction & Building Technology
Shenyu Wang, Xiaowei Gu, Jianping Liu, Zhenguo Zhu, Hongyu Wang, Xiaowei Ge, Xiaochuan Xu, Moncef L. Nehdi
Summary: This study investigates the effect of fly ash (FA) on the properties of MK cement and the interaction between MK and FA on microstructure and hydration products. The results show that adding an appropriate amount of FA improves the flowability and setting time of the cement-MK system, resulting in a more uniform structure and higher compressive strength.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Construction & Building Technology
Safeer Abbas, Rashid Hameed, Moncef Nehdi, Mudasir Afzal, Sbahat Shaukat
Summary: This study investigates the impact of different finishing rolling temperatures and chemical compositions of scrap steel on the mechanical properties of steel rebars. The findings suggest that increasing the finishing rolling temperature leads to an increase in average grain size, resulting in a decrease in ultimate tensile strength, yield strength, and hardness. On the other hand, increasing the carbon content enhances the hardness, ultimate tensile strength, and yield strength, but reduces the elongation and modulus of toughness of the rebars.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2023)
Article
Construction & Building Technology
Liu Jie, Parisa Sahraeian, Kseniya I. Zykova, Majid Mirahmadi, Moncef L. Nehdi
Summary: This study used three metaheuristic algorithms to optimize an artificial neural network model for accurately predicting the friction capacity of driven piles. The results indicate that these algorithms can provide efficient computational intelligence alternatives for the reliable design of driven piles.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2023)
