Abstract Fiber-reinforced polymer (FRP) composites continue to provide designers with the ability to deliver innovative and intelligent solutions to overcome the ever-growing aging issues in infrastructure. Since it has been more than 50 years to the introduction of FRP materials to the construction industry, this paper presents a state-of-the-art review on historic and recent developments of FRP in strengthening and rehabilitation of civil engineering applications. This review highlights some of the classic and modern experimental, numerical, and analytical studies associated with the integration of FRPs into buildings, among other structures. The discussion presented herein aims at covering application of FRP systems in reinforced concrete structural members and also highlights the performance of FRPs (including bonding agents) under extreme conditions such as elevated temperature, saline environment, and cycles of freezing and thawing. This paper also presents a collective perspective on number of limitations, challenges and research needs associated with successful, sustainable, and durable implementation of FRPs in civil infrastructure.
Abstract This study investigated the feasibility of waste construction powder (WCP), a by-product generated from construction waste recycling plants, as a partial replacement for Portland cement through thermal activation. Mortar specimens were prepared using thermally activated WCP at 600 °C and 800 °C, replacing cement at rates of 6%, 13%, and 20%. The flowability, compressive strength, and flexural strength were evaluated. The results showed that mortar with WCP activated at 800 °C met the KS L 5201 industrial standard even at a 20% replacement ratio, achieving up to 21% and 6% increases in compressive strength and flexural strength, respectively. In addition, a machine learning (ML) model based on the light gradient boosting (LGB) algorithm was developed using 405 literature-derived data entries to predict the compressive strength of cementitious composites incorporating thermally activated WCP. The predictive performance was validated against experimental results, achieving strong correlation with the measured data (R 2 = 0.813), and yielding an RMSE of 3.044 MPa, MAE of 2.507 MPa, and SMAPE of 5.675%. More than 90% of the predictions fell within a ± 10% error margin. These findings demonstrate the practical applicability of the proposed ML model for strength prediction of WCP-based cementitious materials, as well as the technical feasibility of thermally activated WCP as cement replacement.
Systems of building construction. Including fireproof construction, concrete construction
Dry‐bolted connections in precast wall structures simplify the assembly process and offer significant advantages in terms of construction speed and cost. In fact, the reduction of the required workmanship, compared to wet connections, makes this solution highly competitive. Moreover, dry connections also bring benefits in terms of sustainability, by turning possible disassembly and reuse in different locations. The deconstruction process at the end of building service life is also facilitated, promoting recycling and, in this way, supporting the circular economy. This paper describes an experimental study conducted to evaluate the performance of bolted connections in a new composite precast wall system, focusing on three different solutions specifically developed for this purpose. Connections play a fundamental role in force transfer and energy dissipation during seismic events. To assess the structural performance of the wall solution and the reliability of these connections, cyclic loading tests under tensile force were conducted. This evaluation is particularly important for cases where seismic activity must be considered. The results, including damage and failure mode, energy dissipation capacity, strength, stiffness degradation, and ductility, are presented and discussed. It was concluded that the connections show good energy dissipation capacity, without significant damage under low loading conditions. However, they exhibited low ductility and significant concentration of compression was observed near the opening (for bolt installation) due to steel plate bending. Based on the findings of this investigation, it was possible to identify some improvements to enhance the structural behavior of the connections, such as optimizing the steel plate's dimensions (length and thickness) and minimizing the geometric clearances in the steel plates after assemblage.
The possibility of the Russian housing construction industrial base of house-building and precast concrete plants usage in factory products for low-rise buildings construction manufacture was considered. In the Russian Federation, since the 1980s, the commissioning of housing in large-scale production has sharply decreased (from 70% to 10–15% currently). Herewith the volume of apartment buildings construction has decreased over the past 3–5 years, and a further decrease to 30% for the coming years is confirmed. Meanwhile people prefer the construction of individual low-rise buildings with a small plot of 6–8 acres. The volume of such construction exceeds multi-storey one annually on 8–10 million m2. Production facilities are being released. This allows, according to the author, to use the released capacities for the individual low-rise buildings production. Pilot developments of the most in-demand area from 80 to 120–140 m2 let to create the system of fully assembled houses of factory-made house kits from prefabricated grillings to prefabricated roof slabs, including all roof elements, which installation was previously carried out on the construction site and was significant in time and cost. 100% of the prefabricated products for low-rise house construction allows transferring low-rise house construction processes to factory conditions as much as possible, increase labor productivity, better working conditions for workers and improve the construction quality.
Many countries, including Poland, are currently testing the construction of multi-family houses using a prefabricated system of glued laminated timber (CLT). Poland has a great potential for the application of wood technologies in the housing sector. The purpose of the article is to analyse the real advantages of this technology, as well as the difficulties and threats. It is important to determine the boundary conditions for the location of this type of construction, such as the legal system in force in each country, especially with regard to the fire protection of buildings, the availability of local wood resources, as well as the transport distance between the place of extraction of the raw wood material, the place of production of the CLT panels, the prefabrication of the elements and the final location of the construction site. A separate problem to be considered is overcoming the mental barrier in a society that is accustomed to the durability of a house as a concrete or brick structure, and that associates wood with impermanence. Other bottlenecks to development are the high price of imported panels, the low level of CLT production in Poland and the social acceptance of wooden structures as a long-term, stable and safe housing solution.
Abstract One-way shear strength evaluation is one of the essential and complex aspects in the design of prestressed concrete (PSC) members. Current design standards adopt different empirical or semi-empirical approaches to predict the one-way shear strength of PSC members. This study evaluated the applicability of the KDS 14 draft design method, which is based on compression zone failure theory, for predicting the shear strength of slender PSC beams. The evaluation utilized the ACI-DAfStb database, comprising 331 one-way shear tests on PSC beams with and without shear reinforcement. The strength prediction of the KDS 14 draft model was compared against those of existing design codes and design-oriented models. Results indicated that the KDS 14 draft model demonstrated promising performance in predicting the shear strength of a large dataset of PSC beams, both with and without stirrups. For PSC beams without stirrups, the KDS 14 draft model exhibited better accuracy with less scatteredness compared to the ACI 318-19 and CSA A23.3:24 models, while maintaining design conservatism. For PSC beams with stirrups, the KDS 14 draft model showed predictive performance comparable to the CSA A23.3:24 model. In addition, the KDS model exhibits similar scatteredness compared to the mechanics-based model proposed Marí et al. but while providing more conservative predictions. Furthermore, parametric study and design example were conducted to understand the influence of key design parameters and the applicability of the KDS 14 draft model for PSC beams. Overall, the predictions by the KDS 14 draft model closely aligned with trends observed in experimental results across most scenarios.
Systems of building construction. Including fireproof construction, concrete construction
Abstract Fabric-reinforced cementitious matrix (FRCM) technology has emerged as a promising solution for the reinforcement of existing buildings, particularly in seismically active regions. This paper presents a comprehensive review of experimental research methods focusing on the seismic performance of masonry-infilled reinforced concrete (RC) frames retrofitted with FRCM. Drawing on a wealth of literature from various regions, this review synthesizes advancements in FRCM technology, experimental techniques, and theoretical frameworks. Key aspects explored include material properties testing, bond behaviour between fabric and matrix, and the seismic behaviour of masonry-infilled RC frames. Additionally, the significance of in-plane and out-of-plane behaviours is discussed, highlighting the importance of comprehensive testing methodologies. This paper also examines advancements in experimental equipment, such as shake tables, underscoring their pivotal role in simulating realistic seismic conditions. Overall, this review provides a systematic foundation for further research on the efficacy and potential of FRCM technology in structural reinforcement, contributing to the ongoing discourse in seismic engineering and retrofitting strategies.
Systems of building construction. Including fireproof construction, concrete construction
Abstract The objective of this study is to propose a framework to evaluate the mechanical properties of hardened cement paste, such as stiffness and tensile strength, using Bayesian updating. To supplement time-consuming experiments conducted for the evaluation of material properties, virtual experiments conducted using simulations have been found to be effective and promising. However, even with the help of simulations, accurate and reliable evaluation of the mechanical properties of cement paste is challenging. Owing to the heterogeneous and complex nature of the microstructure of cement paste, considerable time and effort are required to reduce the uncertainties in its responses. The need for a large number of samples from the frequentist approach induces uncertainties and precludes accurate probabilistic assessments. Therefore, this study proposes a framework for a Bayesian approach to assess the mechanical properties of hardened cement pastes using a reduced number of data sets. Mechanical properties evaluated from actual microstructures obtained using micro-computed tomography were adopted as priors, and properties from reconstructed microstructures using generative artificial intelligence were selected as the observed data set. The conjugate prior distribution was then updated using the observed data set, resulting in a posterior distribution. From the updated statistical measures (mean and standard deviation) of the stiffness and tensile strength, it was found that the mechanical properties of cement paste could be estimated with reduced uncertainty using the Bayesian framework.
Systems of building construction. Including fireproof construction, concrete construction
Lifting on construction sites, as a frequent operation, works still with safety risks, especially for modular integrated construction (MiC) lifting due to its large weight and size, probably leading to accidents, causing damage to the modules, or more critically, posing safety hazards to on-site workers. Aiming to reduce the safety risks in lifting scenarios, we design an automated safe lifting monitoring algorithm pipeline based on learning-based methods, and deploy it on construction sites. This work is potentially to increase the safety and efficiency of MiC lifting process via automation technologies. A dataset is created consisting of 1007 image-point cloud pairs (37 MiC liftings). Advanced object detection models are trained for automated two-dimensional (2D) detection of MiCs and humans. Fusing the 2D detection results with the point cloud information allows accurate determination of the three-dimensional (3D) positions of MiCs and humans. The system is designed to automatically trigger alarms that notify individuals in the MiC lifting danger zone, while providing the crane operator with real-time lifting information and early warnings. The monitoring process minimizes the human intervention and no or less signal men are required on real sites assisted by our system. A quantitative analysis is conducted to evaluate the effectiveness of the algorithmic pipeline. The pipeline shows promising results in MiC and human perception with the mean distance error of 1.5640 m and 0.7824 m respectively. Furthermore, the developed system successfully executes safety risk monitoring and alarm functionalities during the MiC lifting process with limited manual work on real construction sites.
The full-scale military invasion of Ukraine by the Russian Federation in February 2022 caused widespread damage to civilian infrastructure, including large-panel residential buildings constructed primarily in the late Soviet period. These structures are prevalent in urban districts like Saltivka, a densely populated area of Kharkiv located near the state border. Due to their modular design and proximity to frontline hostilities, many of these buildings experienced either partial or complete destruction, particularly affecting floor slabs.This study investigates the restoration of floor systems in damaged large-panel buildings and proposes a practical, innovative reinforcement method based on tubular concrete (concrete-filled steel tubes) enhanced with a specialized infill composition. The solution involves constructing a steel subframe integrated with a modified concrete core that includes steel fiber and mineral additives to improve mechanical performance. Structural analysis and experimental tests demonstrated that this configuration significantly improves the stiffness and strength characteristics of floor elements while allowing for a reduction in slab thickness. Compared to traditional solutions, the proposed system offers up to 50 % less deformation than empty steel sections and about 30 % better performance than standard concrete-filled tubes.From a construction standpoint, the design allows for efficient assembly within existing buildings, maintaining room height and minimizing the impact on architectural ergonomics. Additional central beams redistribute loads more effectively, transforming the floor into a system supported along its entire perimeter, which reduces bending moments and enhances load-bearing capacity.This method addresses critical challenges in post-war reconstruction by providing a costeffective, scalable approach to residential rehabilitation. Its compatibility with prefabricated panel housing makes it particularly valuable in regions where restoring living space quickly and safely is essential. The findings confirm that tubular concrete elements with optimized infill materials can serve as a reliable alternative to traditional slab replacement techniques in the context of modern structural retrofitting.
This study presents an analytical comparison of alternative foundation solutions for a frame-type agricultural building, with a specific focus on the efficiency of deep soil mixing technology employing soil–cement piles. The research evaluates three foundation types: reinforced bored concrete piles, bored injection piles, and soil–cement piles produced using in-situ mixing technology. A comprehensive techno-economic comparison was conducted based on the reduced cost coefficient method to determine the most cost-effective solution. The findings demonstrate that soil–cement piles provide the most economical option among the three examined alternatives. This type of pile foundation showed the lowest value of reduced costs, making it the most financially viable solution for the construction of agricultural structures. Additionally, significant savings in material consumption – particularly concrete and reinforcement steel – were identified, contributing further to the cost-effectiveness of the proposed solution. The practical benefits of using soil–cement foundations extend beyond direct cost savings. These elements are especially suitable for agricultural applications, including buildings for livestock farming, greenhouses, grain depots, food processing facilities, and auxiliary structures. One of the major logistical advantages of deep soil mixing technology is its adaptability to remote rural areas, where infrastructure is limited. The use of local soils mixed with cementitious binders directly on-site minimizes the transportation of bulk materials, reducing both environmental impact and logistical expenses. Mobile soil-mixing equipment enables flexible and rapid deployment, enhancing project execution efficiency in field conditions. Furthermore, the technology eliminates the need for extensive material storage or large construction staging areas, making it particularly advantageous for projects located far from urban centers. The research confirms the technical and economic viability of soil–cement piles constructed via deep soil mixing technology as a rational and sustainable foundation solution for agricultural buildings, particularly in remote or infrastructure-limited settings. The outcomes of this study may serve as a foundation for further research on optimizing the structural performance and cost-efficiency of soil–cement systems in agricultural settings. Moreover, the findings could assist engineers and project planners in selecting sustainable and locally adaptable solutions for rural construction challenges.
Against the backdrop of rapid advancements in smart construction and digital twin technologies, traditional building material selection and construction decision-making processes face challenges of inefficiency, lack of systematicity, and imprecision due to excessive reliance on manual expertise. To address this issue, this paper proposes a novel decision-making framework based on "agentic AI" (AI with multiagent capabilities), aiming to achieve automated optimization and process design for high-performance polymer composites in smart construction. The core of this framework is a multiagent system. A conductor agent based on a large language model (LLM) parses complex project requirements and coordinates multiple specialized agents to execute tasks, including data retrieval, performance prediction, multiobjective optimization, and interpretable reporting. The performance prediction module innovatively employs an "LLM-XGBoost" hybrid cascading architecture. It leverages the LLM's reasoning capabilities to intelligently tune XGBoost model hyperparameters, enabling high-precision quantitative predictions of material properties, cost-effectiveness, and construction efficiency. To ensure transparency and credibility in the decision-making process, the system integrates an explainability (XAI) module based on Shapley Additivity Propensity (SHAP) analysis, enabling quantitative assessment of each input parameter's contribution to the final recommended solution. Case studies on two typical scenarios — "anti-corrosion coatings for cross-sea bridges" and "self-healing concrete for high-rise residential buildings" — validate that this framework can accurately recommend optimal material solutions such as "0.7% graphene-modified epoxy resin" and "microcapsule-based self-healing polymer concrete." It predicts potential savings of 60–80% in full-lifecycle maintenance costs and reductions of 25–35% in the carbon footprint. This research not only provides a data-driven, explainable, end-to-end intelligent decision-making tool for engineering management but also demonstrates the immense potential of agent-based AI in driving digital transformation and sustainable development within the construction industry. This study offers crucial theoretical and technical support for accelerating the adoption and widespread use of novel green building materials.
The focus of the current research is the multi-criteria task of decision-making support for the effective management of ready-mix concrete production and its delivery to construction sites, taking all possible risk factors into account. The development of a simulation model for the network of production facilities and the distribution chain of ready-made concrete mixtures is a key element of the project to create a digital twin in the production and logistics of a concrete plant. The relevance of this study is supported by the fact that post-war restoration of the destroyed housing stock, reconstruction of damaged infrastructure and industrial buildings, and the resumption of work at all construction sites in the country will lead to a sharp increase in the demand for concrete, which will obviously exceed the existing production capacity. Therefore, one of the top priorities for Ukrainian concrete plants today should be the implementation of a strategy and relevant development projects aimed at increasing productivity without losing quality. This research aims to create a simulation model of the production and delivery of ready-mixed concrete in a network of manufacturing plants and construction sites, as part of a project to create a digital double for making effective risk management decisions in real-time for the early detection of suboptimal activity in the production of high-quality concrete mix and its effective logistics. Thus, the objectives of the study are as follows: to analyze the problems and features of creating digital duplicates in the production and logistics of concrete plants; to develop a simulation model of analyzing production processes and logistics of ready-mixed concrete mixtures; to provide an illustrated example of modeling production and logistics processes in a network of concrete factories and construction sites; to conduct optimization experiments to determine the modes of system operation. After all necessary work had been done, the following results have been obtained. A simulation model of the analyzing production processes and logistics of ready-mixed concrete mixtures has been developed, with the help of which it is possible to solve several tasks, including the evaluation of the rationality and efficiency in the organization of production and delivery of ready-mixed concrete, the identification of bottlenecks in production and logistics processes, forecasting of indicators activities of concrete plants, taking into account changes in production conditions, and forming data for decision-making on reducing plant and customer downtime, among others. Conclusions. The academic novelty of the study is related to the solution of the actual problem related to the preparation and planning of logistical actions for the delivery of ready-mixed concrete in the network of plants and construction sites bycreating a complex of optimization and simulation models, that contributes to the effectiveness of decision-making on risk management for the early detection of suboptimal activities in the production of commercial concrete mixtures and logistics. The effectiveness of the proposed approach is illustrated by an example of concrete delivery in a network of concrete factories in the Kharkiv region.
Sergey M. Dymov , Maxim V. Vishchekin, Aleksandr M. Aleksandrov
et al.
The article discusses the most popular rescue systems (harnesses) used in a set with rope descent fire devices. The ranking of rescue systems by operational characteristics is carried out. The need to develop a national standard for rescue systems is identified.
Systems of building construction. Including fireproof construction, concrete construction
The article considers the specific fire hazards of rolling stock and equipment in double track underground tunnels. Examples of major fires in underground tunnels in different countries have shown that the most complicated and catastrophic fires are associated with rolling stock in the tunnel. It is noted that fires in double track tunnels are characterised by the spread of fire hazards in one volume of the tunnel and can lead to the simultaneous stoppage of two electric trains. For the modelling of the fire evolution and its hazard factors, as well as for the development of evacuation measures in double track tunnels, it is recommended to consider the following design accidents: rolling stock fire and tunnel fire.
Systems of building construction. Including fireproof construction, concrete construction
The advancement of concrete 3D printing (C3DP) technology has revolutionized the construction industry, offering unique opportunities for innovation and efficiency. At the heart of this process lies a comprehensive digital chain that integrates various stages, from initial design to post-processing. This article provides an overview of this digital chain, explaining each crucial step. The chain begins with design, utilizing Design for Additive Manufacturing (DFAM) concept and parametric modeling to create optimized structures. Path generation follows, determining the precise toolpath for extruding concrete layers. Simulations, both numerical and analytical, ensure the design's integrity and feasibility. Several articles have addressed parametric modeling, process and numerical simulation, and the post-processing phase. However, none has proposed an updated methodology for the workflow. This study aims to propose a robust digital chain for C3DP technology, using one platform (3Dexperience) and seamless data transfer between applications. These steps provide insights into the structural performance of printed components, enabling necessary adjustments and optimizations. In essence, the digital chain coordinates a seamless workflow that transforms digital designs into concrete structures, unlocking the full potential of C3DP and paving the way for innovative and efficient construction.