Construction Technologies and Architecture Vol. 23

Abstract: The escalating global demand for energy efficient infrastructure has intensified interest in Phase Change Materials (PCMs) for thermal regulation in buildings. PCMs, owing to their high latent heat storage capacity, can significantly reduce operational energy demands when integrated into construction materials. However, for structural applications, the mechanical integrity of concrete remains paramount, requiring careful evaluation of how PCM incorporation affects its strength characteristics over time. In concrete technology, the introduction of secondary functional materials often alters the internal microstructure, influencing both load bearing capacity and durability. For PCMs, this balance between thermal enhancement and mechanical performance remains a pertinent research frontier in sustainable construction. However, in recent past, focus of the research in construction sector has not brought this aspect to the limelight for practical integration of these materials into concrete especially in Pakistan. Therefore, this study has attempted to instroduce this technology in construction sector of Pakistan by investigating the influence of two distinct microencapsulation shell materials, Melamine Formaldehyde (MF) and Polyurethane (PU), on the compressive strength of PCM modified concrete. Fine aggregates were partially substituted with microencapsulated n-octadecane paraffin PCMs by mass to observe performance trends. Experimental results demonstrated a consistent and progressive reduction in compressive strength with increasing PCM content, with MFPCM mixtures exhibiting comparatively lower strength loss than PUPCM mixtures throughout the curing period. The observed deviations ranged from 7.73% at the lowest replacement level to a maximum of 24% at the highest level, emphasizing the decisive role of shell material stiffness and composition in preserving structural performance while enabling thermal benefits. Through these results, this research has paved a way for construction sector in Pakistan to incorporate the PCM technology in concrete by conducting more research on PCM properties.

Abstract: Pakistan’s construction industry is facing increasing pressure to adopt sustainable practices due to rapid urbanization, rising CO₂ emissions, and resource depletion. Rice husk ash (RHA) and fly ash (FA)—agricultural and industrial by-products—present significant potential as supplementary cementitious materials (SCMs) for sustainable concrete. This paper reviews global research on the physical, chemical, and microstructural properties of RHA and FA, emphasizing their combined use in enhancing strength, durability, and resistance to environmental degradation. To align with the theme of Nano-Driven Material Innovation, the study highlights the importance of particle size distribution analysis, SEM/TEM imaging, and other nano-scale characterizations for understanding pozzolanic reactivity and microstructural improvements. The work also explores the potential integration of these materials into Pakistan’s construction industry, considering local availability, cost implications, and environmental benefits. By replacing a portion of Portland cement with these waste materials, Pakistan can reduce its carbon footprint, mitigate waste disposal issues, and promote a circular economy in construction. The paper concludes with a proposed framework for pilot-scale implementation and further experimental validation tailored to Pakistan’s conditions. In the long term, such research can support the establishment of dedicated organizations or firms in Pakistan that pioneer sustainable construction practices, translating academic innovation into real-world application.

Abstract: This study investigates the mechanical and durability properties of Self-Compacting Concrete (SCC) incorporating bentonite clay and marble dust as partial cement replacements. Bentonite clay, a natural pozzolanic material sourced from Jehengirah (Swabi district), was evaluated for its physical properties, including specific gravity, setting time, and soundness. Results indicate that bentonite has a lower specific gravity and shorter initial setting time compared to Ordinary Portland Cement (OPC), though the final setting time remains similar. A total of nine SCC mix designs were prepared, replacing cement with up to 20% marble dust and 20% bentonite clay by weight. The study focuses on assessing compressive strength, split tensile strength, and durability characteristics compared to conventional SCC. Findings reveal that exceeding 20% cement replacement with pozzolanic materials leads to a notable reduction in compressive strength. However, while the modulus of rupture at 28 days is lower than conventional concrete, the flexural strength relative to compressive strength shows improvement.

Abstract: Use of Waste materials and pozzolanic materials in concrete offer a solution to solve environmental problems arising due to the production of cement and discarded rubber tyres worldwide. The use of crumb rubber in concrete decreases the formation of cracks which helps to withstand greater tensile loads. Several Studies have been conducted to use pozzolanic materials in concrete, like Fly ash, Silica Fumes and GGBS. Very limited research has been done on the use of naturally occurring clay, which is rich in silicain, which provide pozzolanic properties in bentonite. The present study is conducted to evaluate the properties of concrete by partially replacing sand by 5%, 10% and 15% crumb rubber, and bentonite is used to replace cement by 10%, 20% and 30%. Several tests, slump test, compressive tests, were performed at 28 days to evaluate the properties of concrete. The test results showed that the strength decreases with the increase in crumb rubber percentage. This effect was minimized by the use of bentonite which filled the voids generated by rubber particles up to 10% use of bentonite replacement level, and beyond that the strength decreases due to poor bond formation between particles due to increased replacement of cement.

Abstract: With a growing global focus on sustainability, the construction industry is steadily replacing conventional materials with environmentally friendly alternatives. Plant-based fibers, particularly cellulose fibers, are increasingly considered as reinforcement in cement-based materials due to their favorable mechanical properties and renewable origin. Cement-based materials, despite their strength, are prone to porosity and moisture absorption, which compromise long-term durability. To address these challenges while promoting sustainable material use, this study investigates the effects of micro and nanoscale cellulose fibers extracted from sugarcane bagasse on the performance of cement-based materials. Cellulose fibers were obtained through a chemo-mechanical process and surface-modified to achieve hydrophilic and hydrophobic properties. The produced fibers were characterized using SEM and XRD, confirming predominantly amorphous structures and smooth, rod-like morphologies Mortar samples with hydrophobic cellulose microfibers (0.5% and 1%) and cement paste samples with hydrophilic cellulose nanofibers (0.1, 0.25, 0.5 and 1%) were prepared and tested for fresh and hardened properties. Results demonstrated that hydrophobic cellulose microfibers improved mortar workability by up to 13.6% and reduced water absorption by 31.5%, while also enhancing compressive strength (4.7% increase) and density (3.8% increase) at 0.5% dosage. However, higher fiber content (1%) led to entrapped air voids, reducing strength and density. In cement paste, hydrophilic cellulose nanofibers exhibited dual behavior: small dosages had negligible effect, 0.5% significantly improved density (4.9% increase) and compressive strength (38–40 MPa at 7–14 days), while higher dosages caused strength reduction and increased absorption due to fiber agglomeration. Overall, 0.5% fiber incorporation at both scales provided the optimal balance of strength, durability, and workability.

Abstract: This study evaluates the effect of acid attack on the behavior of concrete containing bentonite and fly ash. The concrete mixes contain varying dosages of bentonite mixed with a constant ratio of 10% fly ash. The concrete mixes include A0, A1, A2, A3, A4, and A5, which contain 0%, 10%, 20%, 30%, 40%, and 50% bentonite, respectively. Experimental results reveal that the addition of 10% fly ash along with 10% bentonite can show significant resistance toward acid attack. The concrete mix A1, containing 10% fly ash and 10% bentonite, loses only 1.1% of its mass as compared to the controlled mix of concrete, which shows a significant loss of its mass up to 8.4%. Microstructural analysis of concrete specimens reveals significant changes in hydration products using scanning electron microscopy (SEM). The addition of 10% bentonite along with fly ash creates a denser microstructure due to the formation of calcium silicate hydrate gel and refines the internal pores of the concrete, which provides a significant resistance towards acid attack. In addition, higher dosages of bentonite lead to a porous and loose microstructure, which becomes susceptible to microcracking and spalling.

Abstract: Textile-Reinforced Mortar (TRM) is increasingly used for strengthening reinforced concrete structures, yet the selection of an appropriate finite element modeling strategy remains ambiguous. While simplified smeared models are often employed for their computational efficiency, their accuracy for complex multi-layer TRM applications is not well-established. This study presents a critical evaluation of three distinct modeling approaches in ATENA3D—discrete fiber modeling with perfect bond, a smeared reinforcement model, and discrete modeling with a bond-slip interface—for simulating the flexural behavior of full-scale RC beams strengthened with TRM. Validated against experimental data, the results reveal a stark divergence in predictive capability. The smeared approach severely underestimated the capacity of beams with four TRM plies by up to 48%, demonstrating its fundamental inadequacy for modeling layered composites. In contrast, both discrete modeling approaches accurately captured the structural response, with deviations below 21% for all multi-ply scenarios. It is concluded that discrete modeling is essential for the reliable simulation of multi-ply TRM systems, whereas smeared models are only acceptable for preliminary single-ply analysis. This work provides crucial guidance for researchers and practitioners, steering the numerical analysis of TRM-strengthened members toward more reliable and defensible modeling practices.

Abstract: Physics-based neural networks and data-driven models for health monitoring of structures, remaining useful life, and prognostics have expanded over the past decade. This includes applications like computer vision and interpreting natural phenomena. Challenges mainly arise from limitations in applicability, such as the incomplete representation of complex industrial phenomena and data availability. The framework typically begins with damage detection, followed by classification and assessment to determine prognosis. Developing simulators for this process involves complex nonlinear parameters obtained from design space exploration of modular data, coupled with finite element models to predict damage and support decisions for preventive maintenance. This review provides a comprehensive overview of current advancements, challenges, potential solutions, and future research needs in the integration of deep learning with physics-informed neural networks for prognostics and structural health management.

Abstract: In harsh and aggressive environments, steel reinforcement corrodes, leading to a loss of rebar strength and spalling of concrete due to internal stresses caused by the swelling of corrosion products. Therefore, in order to increase the lifespan of a structure, noncorrosive reinforcement is recommended, which includes Glass Fibre Reinforcing Polymer (GFRP) bars. These bars also offer several other advantages over steel, which include higher tensile strength, low weight and cost-effectiveness. These bars exhibit a distinct bond with concrete due to linearly elastic behaviour and different surface deformation patterns. Several empirical equations have been established to analytically predict the bond strength of these bars. This study finds out that even though these empirical models provide useful insights, they may have limitations in predicting bond strength with significant accuracy; therefore, it is imperative to come up with more rigorous data-driven prediction models. This study presents the application of an eXtreme Gradient Boosting (XGBoost)-based machine learning model which predicts the bond strength with significant accuracy, exhibiting a 0.876 coefficient of determination and a 2.319 root mean square error on the full set of data, which concludes improved predictive capability compared to traditional empirical equations.