Search Results (50)

This study investigates the valorization of construction and demolition (C&D) waste streams and an industrial by-product for sustainable concrete production. Recycled concrete aggregates (RCA) and recycled brick aggregates (RBA), derived from C&D wastes, together with pelletized recycled fly ash aggregates (FAA) produced from thermal power plant fly ash, were used as total replacements for natural coarse aggregates. Six concrete mixtures were prepared at a constant water-to-cement ratio of 0.50 using untreated and slag slurry–treated aggregates. A slag slurry-based two-stage mixing approach (TSMA), incorporating ground granulated blast furnace slag (GGBFS), was applied as a practical and potentially scalable treatment method to enhance aggregate quality and interfacial bonding. The results show that complete replacement of natural aggregates reduced fresh concrete unit weight by up to 17%, while meeting the minimum compressive strength requirements for structural applications. Slag slurry treatment led to statistically significant improvements in mechanical properties, reduced variability, and enhanced overall reliability. In addition, widely used code-based prediction models (TS500, ACI, Eurocode-2, NZS 3101-1:2006, and CSA A23.3-04), originally developed for conventional concrete, were evaluated for their applicability in estimating key mechanical properties of recycled and by-product aggregate concretes, and alternative regression-based models were developed to improve prediction accuracy. Overall, the findings demonstrate the potential for effective utilization of C&D wastes and industrial by-products in structural concrete, contributing to resource efficiency and reduced reliance on natural aggregates. Full article

The National Park Service conducted an amphibious battlefield survey in 2023 of the Agat and Asan Beach Units of War in the Pacific National Historical Park, Guam. This exploratory project used a multidisciplinary approach to further understanding of the 1944 Battle of Guam, one of the most significant invasions of the Pacific Theater during World War II. As part of the project, the team located and documented blast features created by U.S. Navy Underwater Demolition Teams during the removal of obstacles placed on and near the landing beaches by the Japanese as deterrents. The discovery of these blast features was guided by archival research and documented through photogrammetry, bathymetry, and RTK GNSS surveys. The blast features represent intentional modification to the seafloor and were examined in archaeological and ecological contexts. This article discusses the discovery and documentation of the blast features, the long-lasting impact of World War II on the island, the value of integrating cultural and natural resource studies, and implications for maritime heritage research and management. This article concludes with considerations for future directions for archaeological and multidisciplinary research focused on seafloor modification. Full article

The construction sector consumes significant amounts of natural resources and contributes substantially to global CO₂ emissions, making it necessary to develop materials with a reduced environmental impact. In this context, the valorization of reusable industrial waste as secondary raw materials represents a strategic direction for applying circular economy principles and for decarbonizing the construction materials industry. The scientific problem addressed in this review is the urgent need to develop construction materials with a reduced environmental footprint, given that the construction sector is a major consumer of natural resources and a significant contributor to global CO₂ emissions. This challenge requires the identification and critical evaluation of sustainable solutions that support decarbonization and the transition toward a circular economy. The main findings indicate that the valorization of industrial waste offers high decarbonization potential: supplementary cementitious materials (SCMs), such as ground granulated blast furnace slag and fly ash, can reduce CO₂ emissions by approximately 20–50%, while alkali-activated binders and geopolymers achieve reductions of 40–80% compared to Portland cement. These materials also enhance durability, extending service life by 10–20% in aggressive environments, although early-age strength may decrease by 10–30%; recycled aggregates derived from construction and demolition waste (CDW) can substitute up to 100% of natural aggregates, while rubber fibers can increase impact resistance by 30–50% and reduce density by 10–20%. However, key limitations relate to waste variability, heavy metal leaching risks (requiring immobilization efficiencies > 90%), and the relatively low technological maturity of many solutions (TRL < 7), leading to the TRL–CO₂ paradox and highlighting the need for standardization and performance-based regulatory frameworks. The synthesized results indicate that the appropriate integration of industrial waste enables a significant reduction in clinker content, lowers associated CO₂ emissions, and decreases primary energy consumption while maintaining physical–mechanical properties and durability characteristics comparable to or in some cases superior to those of traditional materials, if mix design is based on clear performance criteria, stratified according to the type of waste, dosage used, curing regime, binder chemistry, and the target application. Full article

The large deformation of soft rock within tunnels not only induces cracking in the initial supports and distortion of steel arches but also compromises the structural integrity of the secondary lining. In this study, we first examined the cracking characteristics of the secondary lining on both sides of the Baoligang Tunnel situated in a strong tectonic zone. A total of 257 cracks were identified, with 118 located on the left side of the tunnel and 139 on the right side. The triaxial compression test revealed that the failure characteristics of carbonaceous slate are mainly caused by shear slip failure due to the presence of weak bedding planes. Subsequently, a tailored blasting charge structure was designed to demolish the reinforced concrete secondary lining. This design incorporated a dense arrangement of blasting holes and interval charging techniques applied to the arch shoulders and sidewalls of the blasting zone, effectively fracturing the secondary lining in the left tunnel of the Baoligang Tunnel. Finally, an analysis was conducted based on vibration signals recorded during the dismantling process from three representative sections. The recorded vibration velocities from Case 1 indicate that the explosive charge has a relatively minor impact on the lining of the right tunnel. The peak particle velocity (PPV) recorded from the damaged lining closest to the blast center on the left side is 31.48 cm/s, exceeding the allowable vibration standard. Thereafter, the Hilbert–Huang Transform (HHT) was employed to identify the dominant frequency of the recorded vibration signals, which was determined to be 64 Hz. In Case 2, the PPVs at all monitoring points are below the vibration control standard for traffic tunnels. In Case 3, the PPVs suggest that the vibration has a minimal effect on the newly installed initial support. Full article

Waste concrete powder (WCP), characterized by low reactivity and limited utilization potential, is rapidly accumulating due to the increasing volume of demolition and recycling activities, creating significant environmental and resource challenges. Meanwhile, the shortage of natural fine aggregate (NFA) has become increasingly severe. To address these issues, this study develops a sustainable approach that utilizes WCP as the main raw material, together with fly ash (FA), ground granulated blast-furnace slag (GGBFS), ordinary Portland cement (OPC), and sulphoaluminate cement (SAC), to produce a WCP-based artificial fine aggregate (WAFA) through a cold-bonding process. The physical, mechanical, and microstructural properties of WAFA were systematically analyzed, and its concrete performance was evaluated by replacing NFA at 100% volume. The results show that WAFA exhibits a regular spherical morphology and, after grading adjustment, meets the Zone II sand requirements of GB/T 14684-2022. Increasing the cement content from 2% to 10% raises the 28-day single-particle compressive strength (SPCS) from 12.98 MPa to 23.08 MPa (a 77.8% increase), while enhancing WCP reactivity improves SPCS from 16.17 MPa to 22.80 MPa (a 29.1% increase). Higher cement content and WCP reactivity also promote the formation of C–S–H gel and ettringite (AFt), resulting in higher bulk density, reduced water absorption, and a denser microstructure. In concrete applications, WAFA substantially improves workability, with slump values exceeding those of NFA and recycled fine aggregate (RFA) concretes. Although WAFA concrete exhibits slightly lower compressive and splitting tensile strengths compared with NFA concrete, optimized mix design allows the achievement of target strength grades from C30 to C50, with the C50-W10-50 mixture showing the most favorable mechanical performance. In summary, WAFA shows potential for contributing to the high-value utilization of construction waste and the reduction in natural sand consumption. Full article

This study examines magnesium potassium phosphate cements (MKPCs) modified with industrial wastes for extrusion-based 3D concrete printing, evaluating the rheological properties (workability, setting time), mechanical performance and printability of formulations incorporating secondary materials: Mg dross waste (up to 20 wt.%, replacing MgO), calcined sewage sludge (up to 10 wt.%, replacing KH₂PO₄), alternative fillers such as glass from municipal solid waste glass and from construction and demolition waste and ground blast furnace slag, benchmarked against volcanic ash. The baseline MKPC exhibited initial/final setting times of 34/109 min, good workability and compressive strengths of 29 MPa (1 day)/28 MPa (28 days). Optimal low-waste mixes (e.g., using municipal glass or 20 wt.% Mg dross) shortened the initial setting to 19–25 min (decreasing 24–42%), reduced the slump by 9–18% yet remained printable at laboratory-scale and achieved 1-day strengths >23 MPa/28-day >31 MPa (comparable or superior). Glass from municipal waste proved most promising, due to superior workability, lighter aesthetics and strength gains, supporting circular economy goals while substantially reducing material costs; higher waste levels compromised fluidity and buildability. Mineralogical analyses confirmed K-struvite formation alongside residual periclase, validating these formulations for upscaling sustainable 3D printing. Full article

The construction sector faces the dual challenge of reducing energy consumption and mitigating the environmental burden of construction and demolition waste (CDW). Geopolymers offer a low-carbon alternative to Portland cement, yet their performance depends strongly on precursor composition. This study presents an extensive investigation of precursor chemistry, mechanical performance and phase composition, focusing on the partial substitution of ground granulated blast furnace slag (GGBFS) with mechanically activated CDW powder (15% and 30% by weight) alongside fly ash (FA). The oxide composition, amorphous content and particle size distribution were analyzed, using XRF, XRD and laser diffraction to evaluate the reactivity. Mortar samples were subsequently synthesized and tested for compressive and flexural strength, ultrasonic pulse velocity, density and porosity. The results demonstrate that while mechanically activated CDW incorporation decreases early strength compared with GGBFS-rich systems, compressive strengths above 45 MPa were attained at 28 days, with continuous improvement to >69 MPa for aged composites. The relationship between precursor chemistry, precursor sizes and mechanical performance highlights the feasibility of CDW valorization in geopolymer binders, contributing to energy efficiency, circular economy strategies and sustainable construction materials. Full article

Alkali-activated materials (AAMs) or geopolymers have been considered for many years as a sustainable substitution for the traditional ordinary Portland cement (OPC) binder. However, their production needs energy consumption and creates carbon emissions. Since construction and demolition waste (CDW) can become precursors for manufacturing alkali-activated materials, their use as substitutes for traditional AAM (such as metakaolin, blast furnace slag, and fly ash) can solve both the problem of their disposal and the problem of sustainability. Furthermore, CDW can also be used as aggregate replacement, avoiding the exploitation of natural river sand and gravel. A new circular economy could be created based on CDW recycling, creating a new eco-friendly building practice. Unfortunately, this process is quite difficult owing to several variables that should be taken into consideration, such as the possibility of separating and sorting the CDW, the great variability of CDW composition, the cost of the mechanical and thermal treatment, the different parameters that compose an alkali-activated mix-design, and public opinion still being skeptical about the use of recycled materials in the construction sector. This review tries to describe all these aspects, summarizing the results of the most interesting studies performed on this subject. Today, thanks to a comprehensive protocol, the use of building information modeling (BIM) software and machine learning models, a large-scale reuse of CDW in the building industry appears more feasible. Full article

Recycled aggregate sourced from construction and demolition waste presents a viable means of reducing the environmental impact associated with concrete production. However, previous research has shown that concrete incorporating recycled aggregate typically exhibits reduced strength and increased susceptibility to deterioration. In this work, eight concrete mixes were prepared using both virgin and locally sourced recycled coarse aggregate from the United Arab Emirates, with selected mixes incorporating various combinations of supplementary cementitious materials (SCMs) (ground granulated blast-furnace slag (GGBS) and silica fume). The mixes were tested over a period of 180 days to evaluate key mechanical properties, durability, and embodied carbon. It was found that partial replacement of Portland cement with GGBS and silica fume had no marked beneficial effect on the strength and water absorption of recycled aggregate concrete when compared to mixes containing virgin aggregate. However, improvements in resistance to chloride ingress and reductions in drying shrinkage were observed. Notably, the incorporation of SCMs resulted in a significant reduction in embodied carbon, with reductions in excess of 40% when compared with conventional Portland cement concrete. Full article

Controlled demolition is a critical engineering practice that enables the safe and efficient dismantling of structures while minimizing risks to the surrounding environment. This study presents, for the first time, a detailed, structured framework for understanding the fundamental principles of controlled demolition by outlining key procedures, methodologies, and directions for future research. Through original, carefully designed charts and full-scale numerical simulations, including two 23-story building scenarios with different delay and blasting sequences, this paper provides real-life insights into the effects of floor-to-floor versus axis-by-axis delays on structural collapse behavior, debris spread, and toppling control. Beyond traditional techniques, this study explores how emerging technologies, such as real-time structural monitoring via object tracking, LiDAR scanning, and Unmanned Aerial Vehicle (UAV)-based inspections, can be further advanced through the integration of artificial intelligence (AI). The potential Deep learning (DL) and Machine learning (ML)-based applications of tools like Convolutional Neural Network (CNN)-based digital twins, YOLO object detection, and XGBoost classifiers are highlighted as promising avenues for future research. These technologies could support real-time decision-making, automation, and risk assessment in demolition scenarios. Furthermore, vision-language models such as SAM and Grounding DINO are discussed as enabling technologies for real-time risk assessment, anomaly detection, and adaptive control. By sharing insights from full-scale observations and proposing a forward-looking analytical framework, this work lays a foundation for intelligent and resilient demolition practices. Full article

This article presents a unique study on the demolition process of a high-rise reinforced concrete building simulated using a methodology based on the Applied Element Method (AEM). Prior to the parametric analyses, the progressive collapse-based solid model was visually validated against real-world controlled demolition footage captured by both Unmanned Aerial Vehicles (UAVs) and fixed cameras, showing close agreement in building motion and debris dispersion patterns. In contrast to the Finite Element Method (FEM) model, the simulation is not blast-induced; it is instead developed on a column removal approach, which is widely adopted in progressive collapse assessments. Discussions related to the FEM model are provided as well. The parametric analysis is conducted in two stages. First, a constant removal sequence (removal of 4, 3, and 2 floors, respectively, in the first, second, and third axes) is applied to both 20- and 15-storey buildings under three time delays: 100 ms, 300 ms, and 500 ms. Based on these results, a 300 ms delay is identified as a suitable compromise for controlling debris dispersion, and this value is adopted for the subsequent analyses. In the second stage, three distinct removal sequences are examined on the 20-storey structure using the fixed 300 ms delay: Scenario 1 (4–3–2), Scenario 2 (12–8–6), and Scenario 3 (16–12–6). Among these, Scenario 3 yields the most compact horizontal debris spread. The findings indicate a strong correlation between the actual demolition behavior and the proposed model, demonstrating its capability to realistically capture complex structural failure mechanisms and provide practical guidance for optimizing controlled demolition strategies. Full article

In urban construction, the efficient demolition of concrete structures imposes high-precision requirements on blasting technology. The mesoscopic evolution mechanism of concrete blasting damage is the key to optimizing blasting parameters. In this study, a numerical model of concrete blasting is established using Particle Flow Code (PFC). By comparing it with an experimental model containing a blast hole and a horizontal single fissure, the rationality and reliability of the model in simulating blasting damage evolution are verified. On this basis, four groups of control variable schemes are designed (concrete particle size distribution, aggregate content, prefabricated fissure inclination angle, and fissure length) to systematically explore the effects of mesoscopic structures and macroscopic defects on blasting damage. The results show that larger concrete particles make it easier for damage cracks to avoid large particles, forming sparse and irregular crack networks. A higher aggregate content enhances the “obstruction-guidance” effect of aggregate distribution on damage. When the aggregate content is 40%, the vertical damage expansion is the most prominent, reaching up to 3.05 cm. Fissure inclination angle affects the damage direction by guiding the propagation path of stress waves. Fissures inclined at 30°~60° serve as preferential damage channels, while 90° vertical fissures make vertical damage more significant. An increased fissure length expands the damage range, and the damage degree is the highest for a 40 mm long fissure, being 1.29 times that of a 30 mm fissure. The research results reveal the mesoscopic evolution laws of concrete blasting damage, providing a theoretical basis for the optimization of engineering blasting parameters and safety control. Full article

The drilling and blasting method is commonly employed for the rapid demolition of outdated buildings by destroying key structural components and inducing progressive collapse. The residual bearing capacity of these components is governed by the deformation morphology of the longitudinal reinforcement, characterized by bending deflection and exposed height. This study develops and validates a finite element (FE) model of a reinforced concrete (RC) column subjected to demolition blasting. By varying concrete compressive strength, the yield strength of longitudinal reinforcement, the longitudinal reinforcement ratio, and the shear reinforcement ratio, 45 FE models are established to simulate the post-blast morphology of longitudinal reinforcement. Two databases are created: one containing 45 original simulation cases, and an augmented version with 225 cases generated through data augmentation. To predict bending deflection and the exposed height of longitudinal reinforcement, artificial neural network (ANN) and random forest (RF) models are optimized using the hunter–prey optimization (HPO) algorithm. Results show that the HPO-optimized RF model trained on the augmented database achieves the best performance, with MSE, MAE, and R² values of 0.004, 0.041, and 0.931 on the training set, and 0.007, 0.057, and 0.865 on the testing set, respectively. Sensitivity analysis reveals that the yield strength of longitudinal reinforcement has the most significant impact, while the shear reinforcement ratio has the least influence on both output variables. The partial dependence plot (PDP) analysis indicates that the ratio of shear reinforcement has the most significant impact on the deformation of longitudinal reinforcement. Full article

Occupational health monitoring in demolition environments requires precise detection of blast-dust-induced pulmonary pathologies. However, it is often hindered by challenges such as contaminated imaging biomarkers, limited access to medical resources in mining areas, and opaque AI-based diagnostic models. This study presents a novel computational framework that combines industrial-grade robustness with clinical interpretability for the diagnosis of pulmonary nodules. We propose a hybrid framework that integrates morphological purification techniques (multi-step filling and convex hull operations) with multi-dimensional features fusion (radiomics + lightweight deep features). To enhance computational efficiency and interpretability, we design a soft voting ensemble classifier, eliminating the need for complex deep learning architectures. On the LIDC-IDRI dataset, our model achieved an AUC of 0.99 and an accuracy of 0.97 using standard clinical-grade hardware, outperforming state-of-the-art (SOTA) methods while requiring fewer computational resources. Ablation studies, feature weight maps, and normalized mutual information heatmaps confirm the robustness and interpretability of the model, while uncertainty quantification metrics such as the Brier score and Expected Calibration Error (ECE) better validate the model’s clinical applicability and prediction stability. This approach effectively achieves resource-accuracy co-optimization, maintaining low computational costs, and is highly suitable for resource-constrained clinical environments. The modular design of our framework also facilitates extensions to other medical imaging domains without the need for high-end infrastructure. Full article

With the acceleration of urban renewal, directional blasting has become a common method for building demolition. Analyzing the time–frequency characteristics of blast-induced seismic waves allows for the assessment of risks to surrounding structures. However, the signals monitored are frequently tainted with noise, which undermines the precision of time–frequency analysis. To counteract the dangers posed by blast vibrations, effective signal denoising is crucial for accurate evaluation and safety management. To tackle this challenge, a dual denoising model is proposed. This model consists of two stages. Firstly, it applies endpoint processing (EP) to the signal, followed by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to suppress low-frequency clutter. High-frequency noise is then handled by controlling the multi-scale permutation entropy (MPE) of the intrinsic mode functions (IMF) obtained from EP-CEEMDAN. The EP-CEEMDAN-MPE framework achieves the first stage of denoising while mitigating the influence of endpoint effects on the denoising performance. The second stage of denoising involves combining the IMF obtained from EP-CEEMDAN-MPE to generate multiple denoising models. An objective function is established considering both the smoothness of the denoising models and the standard deviation of the error between the denoised signal and the measured signal. The denoising model corresponding to the optimal solution of the objective function is identified as the dual denoising model for blasting seismic wave signals. To validate the denoising effectiveness of the denoising model, simulated blasting vibration signals with a given signal-to-noise ratio (SNR) are constructed. Finally, the model is applied to real engineering blasting seismic wave signals for denoising. The results demonstrate that the model successfully reduces noise interference in the signals, highlighting its practical significance for the prevention and control of blasting seismic wave hazards. Full article