International Conference on Civil Engineering Innovative Development in Engineering Advances (ICC IDEA - 2025), Volume 4

Effective workforce management is vital for organizational success, yet inefficient resource allocation often leads to operational bottlenecks, increased costs, and reduced service quality. Traditional workforce planning models struggle with workload variability and skill-based task assignments. This study introduces a Strategic and Systematic workforce pooling methodology to optimize resource utilization by aligning workforce deployment with demand fluctuations and competency requirements. The approach comprises three core components: workforce demand analysis (task classification, skill assessment, workload forecasting), dynamic task orchestration (structured push-and-pull model) and capacity enhancement (cross-functional up-skilling, role adaptability, career growth). A real-world enterprise dataset was analyzed using the proposed model. Workforce clusters were formed through correlation-driven segmentation, for grouping the workforce with similar skill sets and mapping them to operational needs. A multi-model Time-Series Forecasting (TSF) framework, comprising basic models like Simple Moving Average, trend-based models like Holt-Winters, and statistical models like ARIMA, was used to evaluate and select the most suitable predictive model for each team based on the Mean Absolute Error (MAE) metric, achieving an average MAE of ~4% across high-variance demand categories. The implementation led to a 7–10% improvement in workforce utilization over a 6-month period. The resulting methodology offers a data-driven framework for optimizing workforce planning, enhancing agility, and enabling strategic decision-making. While expert judgment remains essential, the model serves as an AI-assisted decision-support system, providing predictive insights that streamline workforce restructuring and proactive talent deployment.

The growing energy demands worldwide have underscored the importance of optimizing energy consumption, particularly in buildings, which account for nearly 40% of global energy use. In India, the rapid pace of urbanization has further emphasized the need for sustainable energy practices in the building sector. Addressing this challenge involves reducing energy consumption without compromising on operational efficiency. Energy optimization strategies focus on enhancing energy performance through design improvements, efficient systems, and renewable integrations. The aim of this study is to identify and propose effective strategies for optimizing energy consumption in Indian buildings, enhancing efficiency while maintaining occupant comfort. By analysing existing practices, case studies, and sustainability rating systems, the research seeks to bridge gaps and provide actionable solutions tailored to India's unique context. This will contribute to increased adoption of sustainable energy management practices in the building sector. The objectives include - a bibliometric analysis of energy optimization literature and a comparative study of case studies showing implementations, as well as an assessment of sustainability rating systems like “Leadership in Energy and Environmental Design (LEED)”, “Green Rating and Integrated Habitat Assessment (GRIHA)”. This is done to identify gaps and areas for improvement. Engaging energy professionals through questionnaires will provide additional insights into the effectiveness of current practices and opportunities for innovation. The applications of this research extend to improving building energy performance within the constraints existing on-site. The study concludes by emphasizing the critical role of evidence-based approaches in achieving long-term energy sustainability in India.

Lime mortar, a sustainable substance, was utilised in historical architecture and offered thermal comfort to occupants owing to its insulating characteristics. Cement mortar has supplanted conventional lime mortar in modern construction due to its superior compressive strength, workability, rapid setting time, reduced shrinkage, and enhanced water resistance. This study aims to improve the thermo-physical qualities of lime mortar to render it a feasible choice for modern construction. To alter the characteristics of the lime mortar, stearic acid (at 10%, 15%, and 20% by weight) and alccofine (at 15% by weight) were incorporated into the lime mortar to determine the optimal combination that improves the thermo-physical properties. Microstructural analyses of the modified mortar were conducted utilising X-ray powder diffraction (XRD), FTIR spectroscopy, and SEM-EDS. Thermal conductivity and Differential Scanning Calorimetry (DSC) analyses were performed to elucidate the thermal properties and behaviour of the mortar. Evaluating the modified mortar's physical properties involved conducting compression and flexural strength tests. The optimised SA concentration (10–15%) guarantees hydrophobicity while minimally affecting structural integrity, rendering it an effective solution for passive temperature control and a decrease in thermal conductivity from 0.68 W/m. K to 0.22 W/m. K substantiates the enhanced insulation qualities, rendering it an appropriate option for energy-efficient structures. This research demonstrates that calcium carbonate can serve as a protective barrier for stearic acid due to successful encapsulation.

Developing countries like India are witnessing a sharp rise in cooling energy demand due to rapid urbanization, changing climate patterns, population growth, and improved living standards. Among the various strategies proposed to address this growing demand, the integration of phase change materials (PCMs) into buildings for enhanced energy efficiency has gained significant global attention [1–3]. In this study, capric acid, a saturated fatty acid, was encapsulated within a multilayer shell. The PCM shell is comprised of an intermediate layer of nano-reinforced calcium alginate with multi-walled carbon nanotubes (MWCNTs) to facilitate faster heat transfer across shell material. The outermost shell layer is composed of fly ash and water-based polyurethane to prevent moisture ingress and to provide protection against mortar mixing stresses and PCM leakage. Differential scanning calorimetry (DSC) was used to evaluate the latent thermal properties of capric acid. Thermogravimetric analysis (TGA) was conducted to assess the thermal stability of the PCM. The microstructure of the bead system was investigated using optical microscopy (OM) and scanning electron microscopy (SEM). Microscopic analysis demonstrates that the PCM is stored in the core as capsules, separated by very thin calcium alginate sheets. The investigation also exhibits the uniform dispersion of well-sonicated MWCNTs in the intermediate layer of calcium alginate. The outermost layer presents a rough and irregular surface morphology, which is likely to enhance the interlocking with the cement mortar matrix. Moisture absorption through the multilayer shell of the PCM bead system was also evaluated. Additionally, gravimetric analysis was utilised to examine the PCM loading in the multilayer encapsulated PCM bead system. The selected PCM has significant latent heat capacity, which can significantly improve the building's energy performance when incorporated into its envelope.

This study investigates the mechanical strength, durability, and microstructural properties of organic lime plasters applied to brickwork walls, emphasizing their performance in both fresh and hardened states. Two mix ratios, 1:2 and 1:3 (lime to sand), were evaluated. Experimental methods included compressive and flexural strength testing, X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy with energy-dispersive X-ray analysis (SEM-EDX), porosity measurements, acid resistance tests, and water absorption analysis. The 1:2 mix ratio exhibited a compressive strength of 4.01 N/mm2 at 84 days, indicating enhanced mechanical performance compared to the 1:3 mix. Results demonstrated that organic lime mortars improved bonding characteristics and durability, making them a viable, sustainable alternative to conventional plasters. Understanding the interaction between organic lime plasters and brick substrates is essential for optimizing performance in eco-friendly masonry applications.

The construction industry is a major contributor to environmental degradation due to its extensive consumption of natural resources and generation of waste. In response to these challenges, this study investigates the incorporation of recycled polyvinyl chloride (PVC) and construction debris as sustainable alternatives in concrete mix design. Recycled PVC was processed into granular form, while construction debris was cleaned and crushed to suitable sizes for use in concrete at varying proportions. The research evaluated key performance indicators such as compressive strength, tensile strength, modulus of elasticity, water absorption, and resistance to chemical degradation. To enhance bonding between the recycled components and the cement matrix, admixtures and surface treatments were applied. The results indicate that the use of recycled PVC and debris is feasible for non-structural and selected structural applications when the mix design is properly optimized. Although some reductions in mechanical performance were observed, these were compensated through the use of supplementary cementitious materials and adjustments in mix composition. Furthermore, the environmental assessment revealed notable reductions in carbon emissions and raw material extraction, supporting the goals of sustainable construction. This study highlights the potential of recycled PVC and construction debris in promoting circular economy practices and lays a foundation for future research aimed at improving the performance and applicability of waste-based concrete in sustainable building projects.

The construction industry is under growing pressure to adopt sustainable practices that minimize environmental impact and promote resource efficiency. This study investigates the development of lightweight aluminium foam blocks incorporating agricultural and industrial byproducts, such as sawdust, sugarcane waste, aluminium scrap, aluminium powder, and fly ash. Hydrated lime and cement are utilized as binders, complemented by M-sand, to enhance the durability and structural integrity of the blocks. Key material properties were evaluated in preliminary tests. Aluminium scrap forms the primary matrix, while sawdust and sugarcane waste act as fibrous fillers, contributing to lightweight properties and thermal insulation. The cellular structure of the blocks enhances thermal and acoustic insulation by trapping air, making them ideal for applications such as partition walls, noise barriers, and fire-resistant construction. The results confirm that aluminium foam blocks achieve a compressive strength of 5.2 MPa, making them structurally comparable to AAC blocks (4.5 MPa) while remaining lightweight (800 kg/m3 vs. 600 kg/m3 for AAC). Fire resistance tests at 800 ℃ confirmed non-flammability with minimal weight loss (2.5%). Microstructural studies, including XRD, SEM, and EDS, revealed well-distributed pores and stable crystalline phases, ensuring improved insulation and mechanical performance. Rapid Chloride Permeability Tests (RCPT) demonstrated superior resistance to chloride penetration, enhancing durability in humid environments. The use of agricultural and industrial waste promotes sustainability and lowers production costs. These findings demonstrate that lightweight aluminium foam blocks offer a viable, eco-friendly alternative to conventional construction materials, paving the way for sustainable, energy-efficient building solutions.

Cooling tiles are gaining popularity in India because of the hot and humid climate; this innovative tile design aids in sustaining the thermal comfort of buildings. These tiles were created to limit the amount of heat absorbed by a structure from direct sunlight, thereby reducing cooling energy costs and contributing to climate change mitigation at both local and global scales. This study investigates novel chemical compositions for conventional cooling tiles in order to improve their cooling capability and impact strength. The effectiveness of cool roof pigments is determined by different pigments that use aluminium oxide as a binder being examined for their qualities. This study focused on capacity for mechanical strength and characteristics of microstructural behaviors of the concrete mix of grade M25. Along with aluminum, copper is also added to provide a cooling effect. In addition to copper powder and alumina, tiles with the proposed higher strength and durability impact could use a wide range of alumina-rich materials. To study the mix ratio for preliminary test analysis for mechanical properties.

Biomimicry is an approach to innovation that draws inspiration from the designs and processes found in nature. It involves observing how organisms and ecosystems solve problems and applying those insights to develop sustainable technologies and solutions for human challenges. Marine organisms stabilize lateral wave currents and coastlines. The column is efficient and resistant to lateral instability because to the bioinspired column from the marine ecology. The present study investigates the two Bio-inspired columns that can be inspired by Dolphin profile and Navigational signal. The 2D modelling of the Bio-Inspired column i.e., Dolphin Inspired Column (DIC) and Navigational Inspired Column (NIC) is drafted using Auto CAD 2025. The 3D modelling was developed and analysed under fixed support conditions at the bottom and applying axial load at the top by using Abaqus v 6.14. From the result, the deflection DIC and NIC was found to be 4.37 mm and 3.60 mm. Also, the stiffness value of DIC and NIC was 111.11 kN/m and 91.53 kN/m respectively. It was observed that the DIC and NIC performed better when compared to conventional column in which Dolphin profile inspired column is regarded as the best model.

Research of an empirical tests on the use of burned clayey brick refuse as coarse aggregate in the production of concrete are presented throughout this article. The use of native gravel in Basrah, Iraq, in concrete projects as a coarse aggregate has been expanded alarmingly as a result of the faster score of development in structural concrete projects for buildings, houses, and residential complexes. Additionally, as the brick industry has grown, a lot of products have been generated, mostly waste materials that have an adverse effect on the environment, whereas crushed melted brick will be used in concrete as a replacement with gravel for the sustainability purposes. In order to fulfill the objective, many tests of properties (slump, density and compressive strength) were conducted to use melted brick by-product(waste) of clay production as coarse aggregate in concrete performance, also visual examination after concrete were observed to check homogeneity of mix, to enable study the impact of use of crushed melted brick instead of gravel, constant slump 150 mm was maintained for all mixes, reference concrete (normal concrete with natural rushed gravel) compressive strength was constant 48 MPa, the replacement ratios of crushed clayey melted brick was the primary concern. Which were 0, 50 and 100%. The mixing proportions and W/C ratio were constant 0.40 to be able for evaluation and comparison of different mixes. The findings show that, at ages of 7 and 28 days, the mixtures which include molten crushed brick aggregate, exhibit strength losses of roughly (12–17) % and (17–21) %, respectively, when compared to regular concrete. This is dependent on the percentage of brick molten aggregate replacement with gravel numerous 50 up to 100%. Furthermore, the melted crushed brick material is possible utilized as concrete’s coarse aggregate in with considerable medium density about 2100 kg/m3.

Historical structure rehabilitation, including repair and maintenance, is an increasing trend. Replacing the damaged material with a modified material that has suitable properties is a particular technique. The adoption of an affordable, environmentally beneficial, and sustainable natural polymer admixture is suggested in this study. Terminalia chebula is the polymer extract that is added to the lime mortar. The main objective of this research is to examine how the mechanical and fresh state characteristics of lime mortar alter when a natural admixture is added. Modified lime was used in the study to investigate fresh state properties such as consistency, workability, and setting time. After 28 days, tests of the mechanical characteristics, including compressive and flexural strength, were conducted. The characteristics of lime mortar were found to be more significantly influenced by the admixture. When compared to traditional mortar, the inclusion of natural admixture had favourable results in terms of mechanical qualities and fresh state.

Nowadays, conventional clay bricks are being replaced with building blocks such as Compressed stabilized earth brick, hollow blocks, autoclaved aerated Concrete blocks fly ash brick, etc. However, the application of compressed stabilized earth and fly ash bricks has increased within the past few years. To determine the seismic performance of these masonry blocks in filled frames, their compressive strength and elastic modulus must be assessed. The elastic qualities of compressed stabilized earth brick masonry prisms and fly ash brick have been assessed in this work. Brick masonry prism samples within 3 and 4 layers had been cast in cement sand mortar at 1:3, 1:4, and 1:6 ratios. These specimens underwent testing for modulus of elasticity and compressive strength. Masonry prism strength of compressed stabilized earth brick is significantly higher than that of fly ash brick, according to an analysis of compressive strength test results. According to the research, compressed stabilized earth bricks also have higher modulus of elasticity than regular brick masonry.

Ultra-High-Performance Concrete (UHPC) is a high-strength, durable material characterized by a dense microstructure and optimized mix design, providing superior resistance to environmental and mechanical stresses. This study explores the development of a UHPC mix by substituting quartz sand with manufactured sand (M-sand) and coal bottom ash (CBA) in equal proportion, aiming to improve sustainability without compromising mechanical properties. The mix comprises cement, silica fume, steel fibers, and high-range water-reducing admixture (HRWRA), with CBA and M-sand replacements at 10%, 20%, 30%, and 40% by weight. Experimental results indicate that the mix with 20% replacement of CBA and M-sand achieves the maximum compressive strength of 136.76 MPa and tensile strength of 15.9 MPa, demonstrating significant enhancements in mechanical performance. Furthermore, rapid chloride penetration and sorptivity tests confirm the exceptional impermeability of the mix, ensuring its durability against chloride ion ingress. The findings suggest that partial replacement of quartz sand with M-sand and CBA improves UHPC’s strength while contributing to its long-term durability and performance in demanding structural applications, offering an ideal solution for high-performance, sustainable construction.

Mud blocks are widely accessible, reasonably priced, and environmentally beneficial building materials. Many rural populations in Ethiopia use locally available dirt, straw, and water in unknown amounts to hand-pack mud onto wooden frames to build walls. Because of their poor strength and endurance, walls built using this old approach frequently deteriorate under wind and rain. This research addresses these challenges by enhancing the compressive strength of mud blocks made from locally available earthenware clay soil through the addition of cement, lime, and cereal straw ash. Experimental results showed that adding 10% cement increased compressive strength from 1.73 MPa (for clay and sand only) to 2.98 MPa an improvement of over 72%. Similarly, 10% lime and cereal straw ash improved strength to 2.09 MPa and 2.32 MPa, respectively. When cereal straw fiber was added to the mix, it further boosted compressive strength, with the best result of 2.66 MPa achieved using 8% cement and cereal straw fiber. These findings demonstrate that optimized mixtures significantly enhance load-bearing capacity and durability. This study provides a scientific basis for producing durable, sustainable mud blocks and encourages the construction industry to adopt cost-effective, locally sourced materials. Ultimately, this approach offers a pathway to modernize traditional housing, reduce dependency on wood and concrete, lower constructions costs, and promote resilient rural homes.

This study investigated the impact of the control specimen size and geometry on the thermal performance of geopolymer and Ordinary Portland Cement (OPC) concrete under high temperatures. With the increasing demand for sustainable construction materials, geopolymer concrete has emerged as a promising alternative. However, their behavior under extreme thermal conditions remains a crucial area of exploration. This study adopted a systematic approach to evaluate the influence of variations in the control specimen size and geometry on the thermal response of both geopolymer and OPC concrete. This study involved the casting and testing of control specimens, including cubes, cylinders, and prisms in M30-grade concrete. Compression tests revealed the highest strengths of 37.2 N/mm2 for 100 × 100 mm cubes, 33.12 N/mm2 for 150 × 300 mm cylinders, and 34.08 N/mm2 for 150 × 150 × 300 mm prisms. These analyses aim to reveal the intricate interactions between the size, geometry, and material composition. These findings offer valuable insights into optimizing the design and performance of geopolymer concrete, especially in comparison to traditional OPC concrete, when exposed to high temperatures. Subsequent temperature studies of these critical specimens revealed varying effects. A comparison of OPC and GPC specimens at different temperatures demonstrated significant differences. For instance, at 200 °C, OPC cubes exhibited a strength of 39.2 N/mm2 compared to GPC’s 45.65 N/mm2, with a percentage difference of 1.15 times. Similar trends were observed for cylinders and prisms at different temperatures. This study advances a more comprehensive understanding of the thermal behavior of alternative construction materials, laying the foundation for improved structural resilience and sustainability in extreme conditions.

Geopolymer concrete (GPC) represents a transformative advancement in sustainable construction materials, demonstrating comparable mechanical performance to conventional Ordinary Portland Cement (OPC) while reducing CO₂ emissions by 60–80%. Through systematic analysis of 120+ studies, this review establishes that alkaline activation of industrial byproducts (fly ash, metakaolin, alccofine) yields compressive strengths of 15–98 MPa, split tensile strengths of 3–13 MPa, and flexural strengths of 4–14 MPa, with performance primarily governed by SiO₂/Al₂O₃ molar ratios (2.5 to 4.5) and Na₂O content (6 to10%). However, material variability induces ±15% strength deviations in standardized mixes, highlighting significant quality control challenges. The commercial adoption of geopolymer concrete faces three primary challenges: standardized preparation methods for NaOH activator solutions (3–16 M) remain undefined, structural validation for high-strength applications (>50 MPa) is inadequate, and comprehensive long-term performance data is lacking. The review prioritizes research on binder proportion system and standardized testing protocols for ambient-to-thermal (upto 90 ℃) curing regimes to advance GPC implementation. These findings provide a technical framework for transitioning GPC from laboratory innovation to industrial implementation, addressing key knowledge gaps in standardization and scalability for sustainable infrastructure development.

Tannery wastewater, rich in organic matter, chromium, and salts, presents significant treatment challenges. This study evaluates the effectiveness of Floating Treatment Wetlands (FTWs) as an eco-friendly and low-cost alternative to conventional treatment methods. Three plant species Zizania aquatica, Rosa indica, and Canna indica were tested individually and in combination over varying hydraulic retention times (HRTs) to assess pollutant removal efficiency. The FTW systems demonstrated up to 78% COD, 82% BOD, 69% total nitrogen, 74% total phosphorus, and 91% chromium removal, with Zizania aquatica and Canna indica outperforming Rosa indica in chromium uptake. The combination series exhibited synergistic effects, particularly in nutrient removal. This study highlights the potential of terrestrial plants in FTW systems for treating high-strength industrial effluents, providing a scalable solution for tannery wastewater remediation in developing regions.

Flooding poses a substantial risk to infrastructure and communities, especially in at-risk areas such as Sambalpur district in Odisha. This research focuses on reducing flood risk via the structural design of four main interventions: an earthen embankment, a gravity dam, a cantilever retaining wall, and a counterfort retaining wall. From the identified high-risk areas on a flood susceptibility map, every structure was designed taking into account local hydrological factors, geotechnical characteristics, and safety standards. Structural analysis was performed using STAAD.Pro and PLAXIS LE, with designs validated against sliding, overturning, and bearing capacity failures as per applicable IS codes. The results indicate the vital importance of properly designed flood-resistant structures in improving regional resilience and safeguarding crucial infrastructure.

The building industry has slowly started to adapt to eco-friendly changes by focusing on resource management, improving the environment, and meeting the increasing expectations for ecofriendly infrastructure. The aim is to design and assess the performance of structural concrete made with fly ash lightweight aggregate. To achieve this, a mix of M35 grade concrete was designed and developed, incorporating supplementary materials such as sugarcane bagasse ash, following IS 10262:2019 standards. A lightweight aggregate sintagg was created during the sintering process of fly ash and expanded clays. This particular material was a special variety of high-strength lightweight aggregate which was useful in the making of concrete. The structural characteristics of LWAC, including its split tensile and compressive strengths, were assessed in laboratory tests. To obtain the required strength, the study also aims to ascertain the ideal percentage of lightweight aggregate (LWA) substitution with normal aggregate. Additionally, the study assessed the environmental impacts of using LWA, and microstructural analysis was performed to examine its behavior under various temperatures ranging from 100 ℃ to 300 ℃. This research investigated the advantages of LWA in relation to dead load reduction and enhanced sustainability. The findings of this paper indicated that LWAC could play a key role in promoting sustainable construction.

The increasing global energy demand and rising environmental concerns have necessitated the development of sustainable and eco-friendly materials. Phase Change Materials (PCMs), which stores and releases latent heat during phase transitions, have emerged as efficient solutions for thermal energy management. These materials play a critical role in enhancing energy efficiency, sustainability, and temperature regulation across various applications. Among innovative approaches, sea shell powder has gained attention as a promising and environmentally friendly PCM due to its natural abundance, sustainability, and unique thermal properties. Seashells, is primarily composed of calcium carbonate (CaCO3), in the crystalline forms of aragonite or calcite, are aqua-waste and by-products of marine energy storage materials. The intrinsic properties of sea shell powder, such as high thermal conductivity, thermal stability, and recyclability, make it a viable alternative to traditional PCMs. The research evaluates its thermal properties, heat storage, and environmental benefits, highlighting its applicability in construction, energy systems, and temperature regulation technologies. The findings underscore seashell powder’s cost-effectiveness and eco-friendliness, positioning it as a valuable resource for advancing energy-efficient technologies. In conclusion, sea shell powder represents a sustainable and innovative approach to PCM development. By transforming waste material into a resource for thermal energy management, it contributes to a greener and more sustainable future. Further research and development are essential to fully harness its potential in diverse applications.

Foam concrete (FC) is widely recognized for its lightweight nature and thermal insulation capabilities, but its use is limited in terms of durability and water penetration. The study investigates the performance enhancement of FC using coarse aggregate (CA) and silica fume (SF), to enhance its durability. The durability properties such as Water absorption, volume of permeable voids (VPV), sorptivity, thermal conductivity, and resistance to chemical assaults (sulfuric acid, sodium sulfate, and sodium chloride) were all tested at 28, 56, and 90-day curing intervals. The results showed that adding CA and SF greatly reduced water absorption, sorptivity, and VPV by 67%, 21.73%, and 36.5%, respectively, while dramatically increasing acid, sulfate, and chloride resistance by 18.66%, 28.88%, and 56%. The optimized mix (3F2C50A10S) had the lowest strength loss and the best thermal conductivity, indicating a denser microstructure, as confirmed by SEM examination. These enhancements illustrate the ability of CA and SF to produce foam concrete that meets both structural and environmental performance standards.

Natural zeolites, crystalline aluminosilicates found in volcanic and sedimentary deposits, are widely used in water purification, gas separation, catalysis and soil amendment. Their high cation exchange capacity and selective adsorption properties make them valuable, but impurities, variability, and limited tunability hinder their widespread industrial use. Researchers are exploring biomass-derived zeolites as a sustainable alternative to address these challenges. Utilizing agricultural and industrial waste aligns with circular economy principles by converting waste into valuable materials. Agricultural residues, forestry waste, and industrial by-products can serve as substitutes for conventional raw materials like kaolin and aluminosilicates. Standard synthesis methods include hydrothermal, alkali fusion, and solvothermal techniques, using activators like NaOH and KOH to facilitate crystallization. Synthesized zeolites offer economic and environmental benefits by reducing waste, lowering costs, and minimizing reliance on non-renewable resources, while demonstrating strong potential in catalysis, adsorption, and wastewater treatment. However, challenges remain in optimizing synthesis efficiency, scalability, and purity. Future research should focus on refining process parameters, enhancing yield, and exploring novel sources to improve performance. Sustainable zeolites represent a transformative approach for merging waste management with industrial applications to create a greener, more resource-efficient future.

Sugarcane bagasse ash (SCBA), by-product of sugar industry, rich in silica and pozzolanic properties, has emerged as a sustainable alternative to partially replace cement in construction materials. This study investigates the mechanical, bonding, and durability properties of 1:4 cement-to-sand ratio mortars incorporating sugarcane bagasse ash (SCBA). The various mortar mixes were prepared incorporating SCBA, fly ash, and a combination of both. The compressive strength of the mortar cubes were tested. Microstructural properties were studied using X-ray diffraction (XRD) analysis to identify phase compositions and hydration products, providing insights into the material's behavior. The bond strength of the brick masonry developed by the various mortar mixes have been tested with brick triplets to determine the shear bond strength of the brick masonry. The tests were conducted at14, 28 and 56 days of curing to investigate the effect of curing age. Mixes 15SCBA, 20FA, 7.5SCBA + 7.5FA, significantly improved the compressive strength of the mortar. The findings highlight the incorporation of SCBA promotes a sustainable alternative to conventional cement-based materials.

This study explores the mechanical properties of high-strength concrete incorporating Metakaolin (MK) as a partial substitution of cement under exposure to elevated temperatures. Metakaolin, a highly reactive pozzolanic material, is known to improves the durability and strength characteristics of concrete. In this experimental investigation, concrete mixtures were prepared with varying levels of metakaolin replacement (0%, 2%, 4% and 6% by weight of cement) and subjected to 500 ℃ and 700 ℃ for a specified duration. The main purpose of this study was to assess the impact of these elevated temperatures on key mechanical characteristics. The results provide insights into the performance of metakaolin-enhanced HSC under high-temperature conditions, offering valuable information for optimizing concrete mix designs in applications where thermal resistance is critical. This study adds to the increasing material of research on the application of additional cementitious substances to improve the mechanical and thermal properties of high-strength concrete.

Concrete, a widely used construction material, faces challenges in tensile strength and crack resistance, which impact its structural performance and durability. This study investigates the integration of hybrid fibers such as glass fibers (GF) and polypropylene fibers (PF) alongside acrylic polymer in M25-grade concrete to enhance its mechanical and durability properties. The research evaluates the effects of varying polymer content (0%–5% by weight of cement) while maintaining constant fiber proportions (1% GF and 0.25% PF by volume) on workability, Mechanical Properties, and long-term durability characteristics. Experimental results indicate that incorporating acrylic polymer significantly improves concrete's workability, transitioning from zero slump in fiber-reinforced concrete without polymer to increased slump values with higher polymer dosages. Optimal polymer content (4%) enhances compressive strength by 22.86%, split tensile strength by 38.07%, and flexural strength by 64.76% compared to conventional concrete. However, exceeding 4% polymer leads to diminished mechanical performance, highlighting the importance of dosage optimization. Durability tests, including pH analysis, carbonation depth, and water absorption, confirm improved resistance to environmental factors. Elevated pH levels (up to 11.74) ensure an alkaline environment conducive to reducing reinforcement corrosion. The reduced carbonation depth and water absorption percentages further emphasize the role of polymers in enhancing concrete's longevity. This study demonstrates that hybrid fiber-reinforced concrete modified with acrylic polymer is a viable solution for high-performance structural applications, offering improved mechanical properties and durability. These findings contribute to the development of advanced concrete composites for infrastructure subjected to heavy loads and harsh environmental conditions, paving the way for sustainable and durable construction practices.

In the present-day highly competitive and environmentally conscious market, traditional construction methods are no longer viable. At the same time, people are becoming increasingly concerned about the depletion of natural resources, which is contributing to the growing demand for urbanization. The agricultural products that are used in building offer a substantial number of renewable resources. The utilization of natural fiber, such as the hemp fiber (HF) that is accessible for commercial usage, contributes to the success of the prototype. Hemp is a plant that is easily accessible, has production methods that are both flexible and sustainable, and has a good influence on carbon sequestration. The physio-mechanical qualities of HF are superb, including high tensile strength and great insulating capacity, among other advantageous characteristics.The nonuniformity that is intrinsic to natural materials and the inadequacies that are imposed in the use of HF for composites, such as increased permeability and slow setting, are the factors that are preventing a wider acceptance of this material. The comparison between the conventional concrete with the HFC mentioned as S1, S2, S3, and S4 with various percentage of fibre added in the concrete specimens. There is a peak result shown in the S3 specimen than the all-other specimens compared in this study. This shows the bonding and better crack propagation mechanisms in the concrete matrix. The results show that there is a peak strength in additional of 3% of hemp fibre which proves that the flexibility of the concrete specimen is improved than the conventional concrete.

The objective of this study is to produce M40 and M60 grade geopolymer concrete (GPC) by using industrial by-products, specifically fly ash (FA) and ground granulated blast furnace slag (GGBS), by reducing the concentration of the alkali activator solution (AAS). Mix design for M40 and M60 grade GPC was tailored in terms of their mechanical performance parameters. The findings indicated that the 28-day compressive strength (CS) of FA and GGBS based GPC ranges between 47.48 and 68.26 MPa, at a 60:40 FA:GGBS proportion, when concentration of the AAS is kept at 3.5 M and the AAS to powder (AAS/P) proportion is kept at 0.6 for M40 grade GP concrete; on the contrary, in the case of M60 grade GP concrete, within the same 60:40 FA:GGBS proportion, the concentration of the AAS increases to 5 M, with liquid to powder (L/P) proportion being 0.47. The microstructural behavior of the modified mixes was studied using scanning electron microscopy (SEM-EDAX), and these were associated with the mechanical characteristics observed. This research supported that addition of GGBS appreciably enhanced the gel formation by accelerating reactivity in alkalis and filling pores, thus leading to improved strength properties, as inferred from SEM observations.

Investigated in this experimental project is the possible main binder material in the manufacturing of geopolymer mortar: an industrial waste rich in silica, sugarcane bagasse ash (SBA). This initiative aims to reduce waste in the building industry by offering an environmentally suitable replacement for Portland cement, therefore lowering carbon emissions. Sodium silicate (Na2SiO3) and sodium hydroxide (NaOH) in an alkaline activator solution produced SBA's geopolymer mortar. By varying the molarity of the alkaline solution and mix ratios, one improved geopolymerization. Including tiny particles generated a suitable mortar mix adequate for both structural and non-structural applications. The purpose of the experiment was to use extensive characterisation under scanning electron microscopy (SEM) to assess SBA's microstructure and chemical content. Various geopolymer mortar mixes were prepared using combinations of FA, SBA, and Ground Granulated Blast Furnace Slag (GGBS), and tested for compressive strength at 7, 14, and 28 days. The results show that SBA significantly enhances the reactivity of the geopolymer system due to its high silica content. Among all tested mixes, the blend containing 70% FA, 20% SBA, and 10% GGBS exhibited the highest compressive strength at 28 days, outperforming both OPC and other geopolymer mixes. The findings confirm the potential of incorporating agricultural (SBA) and industrial (FA and GGBS) waste materials to produce high-performance, eco-friendly binders for sustainable construction applications.

The increasing accumulation of plastic waste has led to environmental concerns, prompting researchers to explore sustainable methods for its utilization in construction materials. This study investigates the impact of PET plastic waste replacement on the water absorption and compressive strength of cement and soil bricks. PET plastic was incorporated at replacement levels of 5%, 10%, 15%, and 20% in cement bricks, and at 5% and 10% in soil bricks. The results indicate that water absorption in cement bricks increases with higher PET content, reaching 10.95% at 20% replacement due to increased void formation. In contrast, soil bricks exhibit a reduction in water absorption, dropping from 13.73% at 5% PET to 11.09% at 10%, as plastic particles fill the pores. Compressive strength testing revealed that cement bricks achieve a peak strength of 7.68 MPa at 5% PET replacement, followed by a decline with further plastic addition. Soil bricks, however, showed a consistent decrease in strength, from 3.41 MPa at 5% PET to 2.34 MPa at 10% the strength. Therefore, the results satisfy the minimum compressive strength requirement specified in IS 1077:1992 for common burnt clay bricks. The findings also suggest that PET incorporation can enhance cement brick strength at lower replacement levels while reducing water absorption in soil bricks. This study highlights the potential for PET waste utilization in sustainable construction, with careful optimization required to balance strength and durability.

The mechanical properties and structural features of the M25 grade concrete under changing E-waste content is thoroughly investigated in this work. We investigate the possibilities of using this e-waste material to raise the structural performance and strength of the concrete. Mechanical qualities of the e-waste substituted concrete have been investigated using several tests including compressive strength, tensile strength, and flexional strength. Concrete including 50% e-waste-replaced concrete is more mechanically better than reference control concrete after 28 days of cure. E-waste was used in place of a lot of the concrete, which somewhat degraded mechanical performance. Additionally conducted was a microstructural study to ascertain the e-waste distribution and interaction inside the concrete matrix. Aiming to validate the experimental results, scanning electron microscopy (SEM) and X-ray diffraction (XRD) were employed to evaluate the effect of e-waste on the microstructural properties. The results offer important knowledge on their purpose of improving the performance of M25-grade concrete by proving the way the integration of e-waste alters the microstructure and the mechanical characteristics.

Each year, billions of fired-clay bricks are produced globally, leading to significant environmental concerns due to the energy-intensive manufacturing process. This study explores a sustainable alternative by focusing on the development and performance evaluation of Cement-Stabilized Mud Blocks (CSMB) reinforced with coconut coir and jute fiber. These natural and biodegradable fibers enhance the mechanical properties of CSMBs, making them a viable substitute for conventional burnt clay bricks in construction. Although fired clay bricks are widely used, their production requires high energy input and results in harmful emissions. CSMBs, on the other hand, are more economical and environmentally friendly, though their mechanical performance typically needs improvement. This research investigates whether increasing the proportion of coconut coir and jute fiber can further improve the structural integrity and durability of CSMBs while maintaining sustainable production methods. Blocks were produced with varying ratios of cement and fiber content and tested for compressive strength, water absorption, and efflorescence. Results showed that the optimized mix (CSMB-CC75-JF75) achieved a 147.1% increase in compressive strength and a 22% reduction in water absorption compared to the lowest-performing mix (CSMB-CC15-JF15). These enhancements demonstrate the strong potential of optimized fiber-reinforced CSMBs in sustainable construction. The findings support the use of locally available agricultural fibers to create cost-effective, structurally sound, and environmentally responsible building materials, offering a practical solution to reduce the environmental impact of brick manufacturing.

This study aims to enhance environmental sustainability in the construction sector by examining the mechanical and durability characteristics of polymer-treated recycled aggregate concrete (RAC). The incorporation of recycled concrete aggregates (RCA) in the manufacturing of RAC presents a viable strategy for mitigating environmental effects and advancing sustainable construction methodologies. The quality differences between natural aggregate (NA) and recycled concrete aggregate (RCA) are addressed by applying varying amounts of hydrophobic polymer to the aggregate in order to enhance the performance of RAC. The research methodically assesses the mechanical and durability characteristics of concrete by integrating treated recycled concrete aggregate at different substitution rates (25%, 50%, 75%, and 100%) as coarse aggregate. The results demonstrate that a 25% replacement with treated RCA improves compressive strength by 2.91% compared to conventional concrete (CC), while also enhancing durability by 3.21 to 9.28% for water absorption and acid resistance by 0.55 to 4.51% relative to concrete produced with untreated RCA. However, the application of polymer treatment may increase material costs and pose long-term durability uncertainties under varied environmental exposures. This study offers significant insights into enhancing environmental sustainability in construction through the optimisation of treated recycled aggregates in concrete manufacturing.

This research highlights the use of sugarcane bagasse fiber as a sustainable composite material for construction. It focuses on extracting fibers from bagasse using alkali treatment, which enhances fiber strength and bonding with polymers and binders. Treated fibers were used to produce composite panels with various binders, whose mechanical performance was evaluated through compressive and flexural tests. Results show that binder choice affects the mechanical, economic, and environmental feasibility of panels. Alkaline treatment improves fiber adhesion to binders, enhancing performance. Using locally available bagasse and materials reduces agricultural waste and promotes sustainable waste management and eco-friendly composite development.

The brittle nature of cement-based materials causes them to perform poorly in tension but well in compression. Incorporating fibers can help reduce the shrinkage cracks that eventually appear. Areca fiber (AF), a sustainable construction material made from agricultural waste, offers several advantages: it is lightweight, renewable, and provides better corrosion resistance. This study marks the first time AF has been used in a cement-based material. A study was conducted to examine the impact of adding AF (0%, 0.1%, 0.2%, 0.3%, 0.4%, and 0.5% by mortar volume) on the mortar's characteristics. Tests assessed mechanical strength (compressive, tensile, and flexural). Due to the lack of published data on concrete containing AF, the results were compared to those from control samples. At a 0.2% AF concentration, the concrete's mechanical strength increased. Beyond this point, the strength decreased but did not fall below the control mix level (0% AF). Additionally, an increase in AF percentage significantly mitigated shrinkage. The 0.2% AF mix exhibited better durability. According to this study, 0.2% AF performs exceptionally well in concrete compared to other mixes.

The innovative use of recycled bitumen aggregate and banana stem fiber in the development of Fiber Reinforced Cement Concrete (FRCC) as a sustainable construction material. In the construction industry, there is an increasing need to adopt green practices that minimize environmental impact. This study aims to address these demands by utilizing waste materials—recycled bitumen aggregate, derived from reclaimed asphalt pavement, and banana stem fiber, a natural by-product—as primary components in FRCC. By replacing conventional aggregates with recycled bitumen, the research seeks to reduce the environmental burden of landfills, contributing to circular economy practices in construction. Detailed testing was conducted on the materials, including cement, fine aggregate, coarse aggregate, and recycled bitumen aggregate, to establish baseline properties. The findings are expected to demonstrate the potential of FRCC with recycled and natural fibers to meet structural demands, paving the way for eco-conscious alternatives in modern construction. This research has broader implications for sustainable building practices, promoting the development of high-performance, low-impact construction materials aligned with green building standards.

This study looks into creating eco-friendly particleboards made from agricultural waste materials—sugarcane bagasse and rice husk—mixed with hydrated lime, sodium hydroxide, and sodium silicate as glue. The objective is to replace conventional wood-based boards and formaldehyde adhesives with eco-friendly alternatives. The effects of composition on dry density, moisture content, water absorption, pH, and static bending strength were evaluated. Among the mixtures, Mix M3 showed the best results,, with a dry density of 685.8 kg/m3, moisture content of 10.8%, water absorption of 78.7%, pH of 9.89, and bending strength of 11.5 kg. These results demonstrate the feasibility of agro-waste-based particleboards in sustainable construction applications. A press weight of one hundred tons is adequate to meet all standard criteria. The best results were obtained when it was left to dry for a full day following the press. This experiment has demonstrated that it is feasible to produce agro-waste particleboard from sugarcane bagasse and rice husk for use in construction, but further work needs to be done to improve the board's qualities in terms of particle size and shape as well as particleboard.

This study presents an innovative framework for enhancing labour productivity through the real-time monitoring of physiological parameters, leveraging IoT-enabled wearable technology. In the construction industry, productivity optimization remains critical, yet conventional approaches often fail to adequately address worker health and performance. This study introduces an advanced system that integrates sensors into a safety jacket to continuously track vital metrics, including pulse, body heat, blood oxygen saturation (SpO2), stress and steps taken. The system was developed using an Arduino ESP32 microcontroller, various physiological sensors, and a cloud-based interface for real-time data visualization and analysis. Firebase was utilized to create an intuitive platform for supervisors to monitor health indicators and promptly address issues such as fatigue or stress, thereby improving workplace safety and efficiency. The analysis revealed significant correlations between workers’ physiological states and their productivity (correlations (r = 0.86) between workers’ physiological states and their productivity), underscoring the utility of such a system in optimizing labour management. By implementing this system, the study establishes a robust and scalable framework for real-time IoT-enabled monitoring of worker productivity. The sensor data was cross-validated against certified medical equipment, showing deviations within acceptable error margins (±5% HR, ±3% SpO2, ±3% temperature). While tailored for the construction sector, the approach has the potential to be adapted across various industries dependent on manual labour. This work demonstrates how IoT technologies can transform workforce management, paving the way for safer and more efficient operational environments.

This study investigates the integration of artificial intelligence (AI) techniques specifically support vector regression (SVR) and genetic algorithms (GA) for optimizing the thermal performance of residential buildings in extreme cold climates, with a focus on the himalayan region. SVR is employed to model the nonlinear relationship between indoor-outdoor temperature differentials and heat loss through building envelopes, achieving a high predictive accuracy (R2 = 0.9915) and outperforming traditional linear regression (R2 = 0.9832). To enhance insulation performance, a genetic algorithm is utilized to optimize wall configurations by adjusting material properties and layer thickness based on thermal conductivity and resistance parameters. A case study of a masonry residential structure in kashmir, monitored during the winter season of 2023–24, demonstrated a 28.3% reduction in total heat loss and a substantial increase in wall thermal resistance from 1.80 to 7.60 m2·K/W through the AI-optimized design. The SVR model predictions were validated against EnergyPlus simulations calibrated with empirical field data, confirming a low prediction error (<3%). The proposed AI-driven framework enables intelligent material selection and performance-based envelope design, offering a robust, scalable solution for enhancing energy efficiency, indoor thermal comfort, and sustainability in thermally sensitive regions.

The construction sector contributes substantially to urban waste, yet conventional waste management practices remain labor-intensive, inconsistent, and lack traceability. This study presents a field-validated AI-Blockchain framework designed to improve real-time construction waste classification and accountability. A Convolutional Neural Network (CNN) was trained on 2,800 labeled images captured over a 30-day period at a G + 12 commercial construction site. The model achieved a validation accuracy of 88.6% and classified waste into five categories with an average inference time of 1.6 s per image. Simultaneously, 960 waste-related events were recorded using a private Ethereum blockchain network integrated with smart contracts to ensure tamper-proof, verifiable logging of waste disposal activities. The system achieved a 21.2% improvement in sorting accuracy (from 69% to 90.2%), a 70.5% reduction in average processing time, and an estimated operational cost saving of ₹48,000 within the observation period. Unlike prior theoretical studies, this work demonstrates a live deployment of an AI-Blockchain system in a construction environment, offering a scalable, secure, and transparent solution for real-time waste management aligned with circular economy goals. This field-based study highlights the transformative potential of digital technologies in driving operational efficiency and regulatory accountability in construction waste practices.

This research proposes a hybrid model combining Smart Home Technologies with Crime Prevention Through Environmental Design (CPTED) to create cost-effective, secure housing for India’s urban middle class in Delhi, Maharashtra, Karnataka, Uttar Pradesh, and Tamil Nadu. Analyzing NCRB crime data (2018–2022), the study identifies patterns in burglary, theft, and domestic violence. Using QGIS for crime mapping and AutoCAD for 3D home models, it integrates AI-driven IoT devices (e.g., smart locks, cameras) with CPTED strategies like natural surveillance and territorial reinforcement. Locally sourced materials (e.g., rammed earth) and modular designs ensure affordability and sustainability, offering a scalable blueprint for safer urban homes.

Formwork is critical in concrete construction, requiring substantial time and financial resources. Traditional formwork methods encounter several challenges, such as prolonged construction timelines, substantial labor demands, and increased costs. This research investigates the application of 3D printing technology for formwork production, specifically focusing on its potential to advance lean construction principles through waste reduction and cost optimization. An experimental research design was employed to evaluate bio-based 3D printed formwork along with modular design for both standard and complex structures. Following a comprehensive literature review, Polylactic Acid (PLA) was identified as the optimal printing material due to its superior tensile properties, compressive strength, and cost-effectiveness. The study assessed the mechanical properties, printability, and durability of PLA material, along with the feasibility of integrating 3D printed formwork into existing construction workflows. As a biodegradable polymer derived from corn starch, PLA offers environmental advantages while maintaining suitable physical and mechanical properties that can be tailored through processing. The research findings contribute to the development of more sustainable and efficient concrete construction practices by addressing traditional formwork challenges including extended construction periods, high labor requirements, and elevated costs.

The advancement of Artificial Intelligence (AI) has transformed civil engineering, enabling innovative approaches to complex decision-making processes. This research presents an AI-enhanced contractor evaluation framework designed to optimize selection processes in civil engineering projects. Built on the principles of the Analytical Hierarchy Process (AHP), the model ensures systematic, objective, and transparent decision-making. The evaluation focuses on key criteria, including cost, annual turnover, labor availability, prior experience, equipment resources, and project completion timelines, with weights assigned using AHP. AI integration significantly enhances the traditional contractor evaluation process, incorporating machine learning models to predict contractor reliability, clustering algorithms to group contractors based on similar performance characteristics, and a rule-based logic system for risk assessment. Normalization techniques standardize contractor scores, enabling equitable comparisons for informed decision-making. Interactive visualization tools provide stakeholders with a clear, data-driven understanding of contractor performance and risk levels, facilitating real-time exploration of results. This case study on real-world contractor data demonstrates the framework’s effectiveness in automating evaluations, reducing human bias, and improving decision quality. By combining AHP with advanced AI-driven techniques, the proposed solution is scalable and adaptable to various project types, offering a comprehensive tool for efficient resource management and risk mitigation.

The construction industry deals with many risks worldwide, which can cause delays, cost overruns, and inefficiencies. In India, things are even tougher due to rapid urban growth, limited resources, and poor data usage. Most traditional risk management strategies are pretty theoretical and don’t apply in real-life situations. This study aims to create a framework that helps tackle uncertainties in construction risk management by using Big Data and Predictive Analytics. The goals are to understand current risk management practices, pinpoint key factors, evaluate how effective predictive analytics can be, and suggest ways to integrate big data into construction projects. To do this, the research uses the random forest method, which is a machine learning technique that processes real-world data to check predictive capabilities. By focusing on real-world applications, this investigation aims to tackle the limitations of previous studies that have mostly remained theoretical. The results show that predictive analytics can significantly improve how risks are identified and assessed. The framework provides practical insights that can help enhance decision-making and make better use of resources. Recommendations include using real-time data integration tools and encouraging collaboration among stakeholders to manage risks proactively. This research is useful for policymakers, project managers, and industry experts, helping them create more resilient and efficient construction practices. Overall, it contributes to moving construction management from theoretical ideas to practical, data-driven solutions.

Predictive modeling is fundamental to advancing scientific and engineering disciplines, offering critical insights that enhance innovation and improve decision-making processes. However, accurately forecasting the compressive strength of High-performance Concrete (HPC) is still difficult, even with major advances in material science and engineering. This is mostly due to the complexity of its components, the fluctuating environmental factors, and the shortcomings of conventional testing techniques. Furthermore, there is lack of in-depth comparative studies that evaluate multiple advanced machine learning models using various performance metrics. Additionally, the development of a standardized interface to enhance the flexibility and applicability of top-performing models has not been sufficiently explored. By examining the effectiveness of eleven prediction models including techniques like Linear Regression, Random Forest, Support Vector Machines, CatBoost, and XGBoost, this study seeks to address these issues. A carefully selected dataset from earlier research was divided into training and testing sets. Key performance indicators like the R2 coefficient, Mean Absolute Error (MAE), and Root Mean Squared Logarithmic Error (RMSLE) were used to assess the models. Results indicate that the Cat Boost Regressor demonstrated superior predictive accuracy, with an R2 value of 0.96 and notably low errors (MAE = 2.2, RMSLE = 0.12) on the testing set, significantly outperforming conventional models like Linear Regression. These findings underscore the potential of advanced models like Cat Boost Regressor to completely transform HPC Compressive Strength prediction, promoting more effective material design and environmentally friendly building techniques in both theoretical and real-world applications.

This paper examines the implementation of biomimicry ideas in structural engineering, concentrating on serpentine curves derived from natural systems. The aim is to investigate how serpentine shapes can augment the seismic resistance of structures by enhancing energy absorption and adaptation. A multidisciplinary approach is employed, incorporating structural analysis, computational modelling, and additive manufacturing methods. Structural components with serpentine layouts are engineered and analysed at different winding angles to determine their performance under seismic loads. The findings demonstrate that serpentine-inspired structures show improved energy dissipation and structural flexibility, presenting a viable approach for creating durable and flexible elements in earthquake-resistant architecture.

Artificial Intelligence (AI) is revolutionizing structural engineering by improving design accuracy, efficiency, and automation. This study specifically investigates the role of AI in the design and drafting of Reinforced Cement Concrete (RCC) beams, in accordance with IS 456:2000 standards. The research focuses on four distinct types of RCC beams: simply supported beams, doubly reinforced beams, cantilever beams, and continuous beams, utilizing Python programming for automating computations, dataset handling, and model integration. To ensure precise structural calculations, the project creates structured datasets incorporating design parameters such as span length, load, and reinforcement percentage, helping to reduce human errors and improve the reliability of the design process. By incorporating AI-driven algorithms, the design process is streamlined, allowing for the rapid generation of accurate beam designs that comply with industry standards. A key aspect of the project is the development of a web-based interface using HTML and Python. This interface serves as an easy-to-use platform where users can input the necessary design parameters for RCC beams. After the data is entered, the system generates optimized designs that are fully compliant with IS 456:2000 and provides downloadable, detailed design drawings. This approach reduces manual intervention and improves the speed of design output. The integration of AI in this process achieves precision within a 2% variance compared to conventional manual methods and facilitates the creation of cost-effective and durable structural solutions. This project highlights the impact of AI in enhancing automation and accuracy in structural engineering and sets the stage for its future application in designing other critical structural elements such as columns, slabs, and entire buildings. Looking to the future, the research anticipates further advancements in AI integration, particularly through potential collaborations with specialized structural analysis software like STAAD. Such integration would expand the system's capabilities, enabling more advanced automation, accuracy, and functionality in structural analysis and design.

This study investigates the relationship between road geometry and driver workload, with a focus on Driver Eye Blink Rate (EBR) as a key indicator of cognitive load. Using an AI driven approach, advanced computer vision techniques are employed to automate blink detection from driver camera footage. Facial landmark models are applied to calculate the Eye Aspect Ratio (EAR), which serves as the foundation for identifying blink events. Road segments, such as curves, tangents, and transitions, are analysed through colour coded durations extracted from annotated Excel sheets, allowing for a detailed exploration of how these features influence driver attention. By correlating EBR data with road geometry characteristics, the study uncovers patterns and associations that provide valuable insights into the relationship between road design and cognitive workload. The methodology offers a robust framework for real time monitoring and assessment, with results organized into comprehensive data outputs for further analysis. These findings highlight the potential of AI enhanced systems to improve the precision and scalability of workload assessment, ultimately contributing to safer and more efficient road design strategies.

This study presents an analytical investigation of compressive strength of seaweed gel modified concrete, with gel content varying from 1% to 5% with 1% increment. The experimental results obtained from the laboratory are cross verified with two different statistical tools to evaluate the predictions of the compressive strength with RSM and ANN method. The regression analysis using RSM method with SWS gel gave high predictive accuracy of 91.57%. In the comparative analysis, ANN showed a sin curve trend with initially linear growth at 1% addition then steep slope at 2% of SWS gel which is the same result for all the methods except python. There was a slight growth in the strength at 3% then it was drastically reduced at 4% and 5% for achieving compressive strength of 28 and 60 days. These findings underline the efficacy of the analytical and statistical tools in optimizing concrete mix design and offer a sustainable approach for enhancing compressive strength in civil engineering applications.

This research investigates the mechanical characteristics of epoxy matrix composites augmented with graphite filler particles at different loadings (0–7 wt.%). Results indicate that tensile and flexural strength significantly increase at 3 wt.% graphite loading, followed by a decline at higher concentrations. Similarly, impact resistance and hardness improved up to 3 wt.%, with no further enhancement beyond this threshold. Artificial Neural Networks (ANN) were employed to develop predictive models, demonstrating high accuracy (R > 0.96) across the training, testing, and validation phases. The ANN model effectively forecasts the mechanical behavior of graphite/epoxy composites, aiding material design optimization. These findings highlight the optimal graphite content for enhanced performance and the potential of machine learning in material science applications. This research advances the development of high-performance composite materials with customized mechanical properties for diverse engineering applications.

Precise cost estimation is a critical component of construction project management with far-reaching consequences for financial planning, resource allocation, and contract negotiations. Traditional cost estimation methods, which are mostly expert opinion and history-based, have a tendency to ignore real-time market forces, labor cost fluctuations, and material price fluctuations. The present study aims to overcome these shortcomings by employing predictive modeling and machine learning (ML) algorithms to enhance the accuracy of cost estimates. A data-driven model is proposed that employ structured datasets in conjunction with advanced analytical models to predict construction costs from the pre-bid stage to contract award. Trained models such as Linear Regression, Random Forest, and Gradient Boosting are employed to evaluate the predictive precision of these models in predicting contract award costs. Model analysis employs assessment metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R2 Score to evaluate the robustness and consistency of these models. The findings confirm that ML models substantially outperform traditional methods, with Random Forest providing the highest level of accuracy by identifying complex, non-linear relationships between cost determinants. The proposed framework enhances decision-making by reducing cost variances and enhancing financial control. The study contributes to the knowledge base on building cost estimation by highlighting the potential of ML-based predictive analytics in minimizing financial risks and enhancing the precision of project budgets. The findings provide a scalable and flexible model for stakeholders to obtain accurate cost forecasts, reducing budget overruns and enabling the effective allocation of resources across different construction scenarios.

3D printing in construction has driven research on optimizing printable mix formulations. Key parameters like water-cement (W/C) ratio, sand-cement (S/C) ratio, and superplasticizer dosage influence mix rheology and extrudability. This study investigates how variations in these ratios affect printability using a lab-scale extrusion setup. Slump cone and flow table tests assess extrudability. Lower W/C ratios improve extrusion by reducing mix viscosity. Proper superplasticizer levels enhance flowability by dispersing cement particles. However, excessive dosage can cause segregation and slump loss. The findings help identify optimal mix proportions, supporting advancements in 3D concrete printing.

With the increasing need for sustainable infrastructure, minimizing carbon emissions in bridge construction especially for railway projects has become a key concern. This study focuses on assessing the embodied carbon footprint during the construction phase of a railway bridge by integrating Building Information Modeling (BIM) with the Carbo Life Calculator, a BIM-compatible Life Cycle Assessment (LCA) tool. A detailed 3D model of the railway bridge was developed in Autodesk Revit, including all major structural components such as deck slabs, piers, abutments, piles, and pile caps. The material quantities were accurately extracted from the BIM model and used within the Carbo Life Calculator to estimate the environmental impact of different construction approaches, specifically comparing precast and cast-in-situ methods. The integration of BIM and LCA tools not only made the carbon assessment process more efficient but also helped in identifying opportunities to reduce emissions early in the design stage. The findings suggest that such digital tools can support engineers and designers in making more sustainable choices throughout the project lifecycle. This approach encourages the adoption of environmentally responsible practices in future railway bridge construction.

Effective risk management and cashflow monitoring are globally critical for construction project success. This study develops a risk assessment model integrated with Power BI for real-time monitoring of cashflow and schedule tracking, ensuring efficient and risk-free project management. The research begins with a bibliometric survey to analyse existing studies on risk assessment and cashflow automation, identifying research gaps and industry trends. It identifies key risks, including financial, scheduling, technical, and environmental, and examines their relationship with payments and delays. A weighted risk assessment model evaluates individual risks’ impact on cashflow and timelines. Power BI is employed to visualize real-time data trends, enabling stakeholders to identify deviations and take corrective actions. Case studies and simulations validate the model’s effectiveness, while interactive Power BI dashboards offer dynamic insights for decision-making. Notably, unused contingency funds are reallocated to budgets when risks do not materialize, optimizing resource utilization. The findings show that integrating risk assessment with cashflow automation enhances transparency, minimizes delays, and supports informed decisions. The study recommends adopting such systems industry-wide and emphasizes the need for training in tools like Power BI to overcome implementation challenges.

The construction industry is undergoing a paradigm shift driven by the growing demand for greater flexibility, stakeholder engagement, and sustainable outcomes. Traditional project management (TPM) models, though universally used, do not offer adequate flexibility in changing situations. Agile project management (APM), being iterative and customer-centric, is a suitable choice—especially when combined with Lean and Hybrid approaches. This review synthesizes an extensive set of peer-reviewed papers from 2010 to 2024 to evaluate the contextual appropriateness, advantages, and disadvantages of Agile, Lean, Traditional, and Hybrid approaches in the construction industry. Major conclusions show Agile as ideal for planning and design phases, Lean for implementation, and TPM for governance and regulatory compliance. Phase-based hybrid models following these models per project phase have the most potential. The research suggests a four-phase integration model for organizational readiness, phase-based deployment, digital empowerment, and continuous feedback. It also outlines major enablers, such as leadership, technology integration, and training stakeholders, and prescribes barriers like cultural resistance, contractual inflexibility, and the absence of digital infrastructure. This paper adds a structured method to phased Agile implementation in construction, closing the gap between theoretical models and actual practice. It ends with tangible recommendations and areas of research—emphasizing longitudinal verification, industry-specific implementation, and incorporating sustainability—to further enhance future construction project delivery.

This study investigates the incorporation of single-walled carbon nanotubes (SWCNTs) into concrete to enhance its mechanical performance and sustainability. CNTs are known for their exceptional strength, high surface area, and ability to bridge microcracks, which can significantly improve the performance of cementitious materials. The research involved the preparation of concrete mixes with varying CNT dosages (0.075%, 0.1%, and 0.2% by weight of cement), followed by compressive strength, split tensile strength, and flexural strength tests, conducted as per Indian Standard specifications. The results demonstrated that the inclusion of CNTs enhanced compressive strength by up to 14.8% and split tensile strength by 30% compared to conventional M40 concrete. Furthermore, water permeability and absorption were significantly reduced, indicating improved durability. A simplified environmental analysis suggests potential reductions in cement demand and construction waste, supporting long-term sustainability goals. The findings highlight that even low CNT dosages can produce noTable improvements in strength and durability while offering environmental benefits, positioning CNT-reinforced concrete as a viable solution for high-performance and sustainable construction applications.

The housing sector is a significant contributor to economic development and social welfare. However, the high cost of building materials often limits the affordability of quality housing. Roof tiles, a critical housing component, are typically expensive, making them inaccessible for low-income communities. This project aims to design, develop, and manufacture durable, eco-friendly, and affordable roof tiles using Fibre Reinforced Polymer (FRP) waste. It is a viable option as it allows you to repurpose readily available scrap material, which can significantly reduce the cost of building a roof while still providing decent weatherproofing capabilities; this can be achieved by grinding the FRP waste into smaller particles, mixing it with a suitable resin binder, and molding it into roofing tiles, making it a cost-effective and environmentally friendly choice. Scrap FRP from manufacturing processes or old FRP structures can be readily sourced, often at a significantly lower cost than new materials. Utilizing recycled/crushed FRP significantly reduces the overall cost of the roofing project and reduces the need for producing new materials thus minimizing the environmental impact and FRP is a relatively lightweight material. The scope of the project is to research and design a production process that minimizes energy consumption and leverages local resources and develop and test prototypes and analyze the economic feasibility of large-scale production. The methods of recycling to be adopted are the mechanical recycling method. The expected outcomes of this project are affordable roof tiles with a 21% cost reduction compared to conventional tiles, providing improved housing quality for economically weaker sections, and utilizing FRP waste, which is a growing global concern in terms of waste disposal.

In India, the construction industry annually generates millions of tons of debris, leading to increased landfill and environmental impact. To address this issue, recycling concrete waste has become imperative. This study investigates the improvement of recycled coarse aggregates (RCA) through surface treatments, specifically acid treatment using hydrochloric acid and silica fume slurry coating, to enhance their mechanical performance in concrete. Three types of aggregates—untreated (RA), acid-treated (ARA), and silica fume-treated (SFRA)—are incorporated into concrete specimens (cubes, cylinders, and beams) with varying replacement levels of natural coarse aggregate (0% to 100%). Preliminary tests on aggregates include water absorption, sieve analysis, specific gravity, impact value, crushing value, and abrasion resistance. The mechanical properties of the resulting concrete are evaluated through compressive, split tensile, and flexural strength tests to assess the effectiveness of the treatments.

The increasing accumulation of electronic waste (e-waste) has raised significant environmental concerns, prompting the need for effective recycling solutions. This study investigates the potential use of crushed e-waste glass as a partial replacement for traditional fine aggregates in mortar and concrete, assessing its effects on the mechanical properties of these materials. Crushed e-waste glass was incorporated in varying percentages (5%, 10%, 15%, and 20%) into both mortar and concrete mixes, and the resulting materials were evaluated for their compressive strength, flexural strength, workability, and durability characteristics. The study found that the inclusion of crushed e-waste glass influenced the mechanical properties differently for mortar and concrete. In mortar, a significant improvement in strength was observed at 5% replacement, but further increases in e-waste content led to a decrease in strength due to the lower bonding potential of glass particles. In concrete, the optimal performance was noted at 10% replacement, where the compressive and flexural strengths were enhanced, and the workability of the mix was satisfactory. The study highlights the feasibility of utilizing crushed e-waste glass as a sustainable alternative in construction materials, suggesting it as an effective method to mitigate environmental impacts while enhancing the performance of concrete and mortar in specific applications. However, the long-term durability and environmental implications of such materials warrant further investigation.

Sustainable development is becoming more important in the construction business. Environmentally friendly building solutions are using locally accessible materials like soil such as soil. Understanding raw earth building’s behavior is important to its use in contemporary construction, and this paper presents an overview of the most current studies on this topic. Journals, articles and conference proceedings were chosen for the study based on the kind of material, form, compaction process, preparation and inclusion of industrial waste materials. Cement concrete or high temperature fired clay bricks are the two most common materials used to make traditional bricks, both of which have significant environmental disadvantages due to the amount of energy and raw materials they use and emit during production. In the framework of the circular economy, researchers have employed a variety of different various types of industrial waste materials to create blocks. Their goal was to do their part to protect the environment and help to the development of sustainable practices. The chemical composition, specific gravity, water absorption, particle size distribution, compressive, and flexural strength of the block were all assessed in research undertaken. The results demonstrate that using industrial waste materials is an interesting area for future research since it can give a long-term alternative to chemical stabilization.

Soil contamination with toxic heavy metals poses serious ecological and public health risks. Traditional remediation methods are often limited by cost and environmental impact. This study explores the potential of saponin, a biodegradable, plant-derived surfactant in foam-assisted bioremediation of artificially contaminated sandy soil. Foam was generated using saponin concentrations ranging from 5% to 20% and tested under varying flow rates, pressures, and treatment durations. The results showed a reduction in specific gravity and pH by 8.03% and 8.76%, respectively, and a 21.51% decline in the internal friction angle due to contamination. Post-treatment analysis revealed that saponin foam effectively restored geotechnical properties and enhanced heavy metal removal. FTIR analysis confirmed the interaction between saponin functional groups and metal ions, with 15% saponin yielding optimal performance. This study demonstrates that foam-based saponin application is a viable, eco-friendly alternative to conventional physico-chemical methods.

In recent years, phase change materials have attracted considerable interest for their distinctive capability to absorb and discharge heat during phase transitions like melting and freezing. This characteristic enables them to significantly improve energy efficiency and support effective thermal regulation in a wide range of applications. Green PCMs, a subset of PCMs derived from sustainable and eco-friendly sources such as fatty acids, bio-based polymers, and recycled materials, have emerged as a promising alternative to conventional PCMs. Unlike traditional PCMs, which are often derived from fossil fuels, green PCMs are renewable, biodegradable, and non-toxic, making them environmentally benign. Their low environmental impact aligns with global sustainability goals, such as reducing carbon emissions and promoting circular economy principles. This review delves into the classification, properties, and applications of green PCMs, with a particular focus on their use in building insulation and solar energy storage. The review also addresses challenges such as leakage and thermal instability, and cost-effective production methods that make green PCMs more accessible for large-scale applications. By highlighting the role of green PCMs in advancing sustainable energy solutions, this review underscores their potential to reduce carbon footprints and contribute to a more sustainable future.

Application of cold-formed steel is increased in civil engineering sectors, including railway carriages, bridges and trusses. This work focusses on the angle column under axial load. Geometric and material nonlinearity were added into the FE model, which improved accuracy and reliability. The FE model was checked using test data from research articles. The results revealed good agreement between the experimental data and FE model. In addition, parametric research was conducted to investigate the effect of two essential parameters: intermediate stiffeners and effective length, on the axial strength of CFS equal angles. The study attempted to determine the impact of these characteristics on the axial strength of the sections by altering them throughout a range of values. The collected data were analysed, and a design curve was created based on the findings.