Journal of Building Material Science

Effect of Steel Wool Fibre Addition on Self-Healing Capability and Marshall Characteristics of Rehabilitated Asphalt Concrete Wearing Course (AC–WC)

2025-12-22T16:50:54+08:00

This study investigates the effect of steel wool fibre addition on the self-healing capability and Marshall performance of Asphalt Concrete Wearing Course (AC–WC). The concept of induction-activated self-healing is introduced to prolong pavement service life by restoring mechanical integrity after microcracking. Four fibre dosages (0%, 1%, 1.5%, and 2%) were evaluated through Marshall testing and controlled induction-healing cycles. The Marshall results revealed a decreasing stability trend with increasing fibre content, from 1870 kg at 0 % to 1717 kg, 1367 kg, and 1038 kg at 1%, 1.5%, and 2%, respectively. Flow increased to 4.3 mm at 1.5% before slightly decreasing at 2%, while VIM rose significantly from 3.82% to 13.85% with increasing fibre dosage. The Marshall Quotient declined from 558 kg/mm at 0% to 276 kg/mm at 2%, indicating reduced stiffness at high fibre contents. Healing performance, assessed via three-point bending before and after induction, showed the highest recovery at 1–1.5% fibre content, confirming the role of conductive fibres in enabling localized binder regeneration. These findings demonstrate that a 1% fibre dosage offers a practical balance between structural stability and healing capability. The results support the potential use of conductive-fibre-modified asphalt as a cost-effective smart pavement strategy in tropical regions while highlighting the need for further field validation and standardization before large-scale implementation.

Studies on Calcium Sulfoaluminate-Belite (CSAB) Cement Using Industrial Wastes

2025-04-03T10:36:28+08:00

Researchers and engineers have been looking at novel approaches to develop cementitious materials with decreased environmental impact without sacrificing performance and durability in response to these difficulties. Calcium Sulfoaluminate-Belite cement (CSAB) is a value-added binder that has gained popularity for its unique qualities and benefits. The CSAB cement system is regarded as an innovative and promising sustainable construction material that helps to mitigate the environmental consequences of regular Portland cement. CSAB cement has been developed as a more sustainable alternative to Portland cement because of its lower energy consumption and CO₂ emissions. The presented study examines the modern research to develop newly produced cement known as CSAB cement. Also, ongoing research activities at the author institute to synthesize CSAB binders using different kinds of low-graded industrial waste materials such as low-grade limestone and phosphogypsum has been presented, which makes it innovative. Physico-mechanical parameters such as setting time and compressive strength were compared in various investigations. CSAB cement quick setting periods and early strength development allow for a greater amount of work to be accomplished within the project timeline. In the various investigations the compressive strength data revealed impressive results ranging from 39.0 to 45.10 MPa, demonstrating the material robust structural capabilities. The mineralogical composition of CSAB cement primarily consists of ye'elimite (C₄A₃S), belite (C₂S), ferrite (C₄AF), and anhydrite (CS), contributes to both the rapid setting characteristics and the development of substantial compressive strength. It has been observed that CSAB cement manufacturing can provide up to 30% reduction in carbon footprint as its manufacturing process requires lower kiln temperatures which results in lower energy consumption and associated emissions from fuel combustion.

Investigating Thermal Performance of Building Materials for Improved Comfort and Energy Efficiency

2025-12-22T10:18:14+08:00

This research investigates the mixed proportions of cement, sand, water, superplasticizer, and waste materials, like recycled concrete, recycled rubber, recycled wood, tea-leaf residue, and recycled plastic, with their replacement levels clearly reported for reliability. Eight mixes were manufactured and tested at the Kuwait Institute for Scientific Research (KISR). The samples were then cured for 28 days, and compressive strength and thermal conductivity were measured. The control mix (Mix 1) showed a thermal conductivity of 0.788 W/m·K, while the wood and plastic mix (Mix 7) showed the lowest value of 0.266 W/m·K, which is equivalent to good insulation performance. Thermal conductivity (k) and thermal resistance (R) were reported together to provide a complementary insulation assessment for 50 mm (R = 0.05/k). Relative to the control (k = 0.788 W/m·K, R = 0.063 m²·K/W), Mix 7 (wood + plastic) achieved the best insulation (k = 0.266 W/m·K, R = 0.188 m²·K/W), representing a 66.27% reduction in k and a 196.45% increase in R. Mix 2 also showed strong insulation gains (k = 0.316 W/m·K, R = 0.158 m²·K/W, −59.95% k, +149.67% R), whereas strength results indicate these highly insulating mixes are most suitable for non-load-bearing applications. Compressive strength varied significantly across mixes, ranging from 0.38 MPa in wood-plastic composites to 19.30 MPa in the control, highlighting the trade-off between strength and insulation. The outcomes of this research are the demonstration of the capacity of the recycled and organic additive options to create energy-efficient, eco-friendly building materials fit for Kuwait's hot climate.

Operational Resilience Strategies for Geopolymer Concrete Production under Raw Material Supply Variability

2025-12-30T10:24:50+08:00

The advent of low-carbon construction has made geopolymer concrete (GPC) a sustainable material for construction. However, the supply uncertainty of the raw materials needed for GPC production makes this a challenge. This research aims to develop and design an integrated digital twin-reinforcement learning framework for optimizing geopolymer concrete production processes. The problem statement concerns the uncertainty involved when producing geopolymer concrete. This paper focuses on building a digital twin structure for optimizing the geopolymer concrete process. The authors also designed a reinforcement learning framework for optimizing the geopolymer concrete production process. The objective is achieved since the digital twin is a computer representation of a production environment. The computer simulation will utilize reinforcement learning. This will ensure that the production is done at a lower cost. Additionally, the digital twin can predict the supply uncertainty. The computer simulation will determine the supply uncertainty level. Performance was evaluated for three supply conditions: stable, with a moderate and severe level of variability, based on a set of indicators: throughput, downtime, energy consumption, CO₂ emission, and quality variability. In all cases, it has been shown that the Digital Twin–Reinforcement Learning (DT–RL) approach results in a considerable improvement of production resilience and sustainability performance by as much as 22% relative to downtime performance, as well as saving 13% of energy and a decrease of CO₂ emission by as much as 15% relative to static planning. Additionally, a strongly negative correlation between resilience and quality variability of manufactured products was shown to exist. This research shows that applying digital intelligence to green material production leads to an improvement in efficiency and green performance.

Compressive Strength–Water Absorption Behaviour of Concrete with Coal Bottom Ash as Sand Replacement across Water–Cement Ratios

2026-01-19T11:43:49+08:00

Coal bottom ash (CBA) is produced in large quantities by coal-fired power plants. It offers a viable opportunity for sustainable utilisation as a partial replacement, especially for fine aggregate in concrete. However, its porous morphology and surface characteristics complicate controlling water demand and optimising concrete performance. In this research, the synergistic effects of water–cement (WC) ratio (0.40, 0.45, and 0.50) with CBA contents (0%, 10%, and 20% from mass of sand) on compressive strength and water absorption of concrete at 28 and 56 curing ages. Increasing the WC ratio and CBA content generally reduced compressive strength and increased water absorption, whereas extended curing improved strength while lowering absorption. Target performance was achieved with up to 20% CBA when the WC ratio was maintained within 0.40–0.45, defining a practical mix-design window. A strong inverse correlation was observed between compressive strength and water absorption at WC = 0.40–0.45 (R² ≈ 0.92–0.95), whereas the relationship weakened at WC = 0.50 (R² ≈ 0.82–0.83) due to increased pore connectivity and variability associated with excess mixing water. The reliability of these correlations was further confirmed through statistical error analysis, with low RMSE, RAE, and RRMSE values, particularly at WC = 0.45, indicating high predictive accuracy and minimal deviation between measured and predicted strengths. In contrast, higher error metrics at WC = 0.50 reflect reduced model robustness. These findings establish design boundaries that can be adopted in practice to valorise CBA while safeguarding performance, thereby informing greener specifications and guiding future standards for the use of industrial by-products in concrete.

Supply Chain Digital Twins for Modular Timber Construction: Monitoring Durability and Circular Reuse

2025-12-31T10:22:08+08:00

The shift towards sustainable and circular building systems has placed modular timber systems in the limelight as an alternative with lower carbon footprints. Nevertheless, the durability of the used material and the efficiency of the reuse cycle are factors that are now significantly impacted by digitalization. In the investigation described in this article, the influence of overall Supply Chain Digital Twin maturity and overall Supply Chain Responsiveness on Timber Durability and the overall Reuse Potential of Timber in the emerging modular timber buildings in Jordan was investigated. In the research design adopted for the quantitative approach, using Python software for the analysis of the results of the survey conducted using the questionnaire administered to 131 respondents in the industry. The results showed that DTM had a remarkably positive effect on TD (β = 0.43, p < 0.001) and CRP (β = 0.57, p < 0.001), accounting for 35% and 49% variance, respectively. SCR partially mediated the relation between DTM and CRP (indirect effect = 0.07, p = 0.002), suggesting that the agility of the supply chain magnifies the effectiveness of DTM. Monte Carlo analyses validated the robustness of the findings, with DTM and SCR cumulatively accounting for more than 75% variance in the sensitivity of reuse performance. This study concludes that upgrading digital maturity and responsiveness is a strategy for achieving long-lasting modular timber construction on a circular basis. This study provides novel empirical insights into the relation of digital transformation to the aims of a circular economy.