Faculty of Engineering Q1

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    Investigating the mechanical and durability properties of locally sourced fly ash-based ternary cement paste to increase OPC replacement
    (Emerald Publishing, 2026-07-07) Gamage, O; Kulasuriya, C; Perera, S V T J
    The mechanical and durability performance of fly ash (FA)-based ternary blended cement pastes was investigated in an attempt to increase ordinary Portland cement (OPC) replacement while maintaining comparable strength and improved durability. This paper provides region-specific experimental data using locally sourced FA from Sri Lanka and imported ground granulated blast-furnace slag (GGBFS). A control mix (100% OPC), two binary blends and six ternary blends were tested for compressive strength at 3, 7 and 28 days, along with water absorption and resistance to sulfuric acid after 28 days. The results showed that OPC specimens achieved the highest early strength, while ternary blends with 25% and 40% OPC replacement achieved comparable 28-day strengths of 82.7 ± 4.8 MPa and 76.2 ± 3.2 MPa, respectively. GGBFS contributed to early strength gain, whereas FA enhanced long-term strength. Durability was improved significantly in the ternary blends. The F15S10 blend, with a higher GGBFS content, showed the greatest sulfuric acid resistance (4.8 ± 0.15% weight loss), while the F40S10 blend, with higher FA content, exhibited the lowest water absorption (6.0 ± 0.18%). Overall, ternary blends with 40% OPC replacement and low FA content are recommended for achieving balanced strength and superior durability in cement paste applications.
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    Joint Resource Allocation and Network Slicing in Hybrid RF/VLC Systems: A Proportional-Fairness Approach
    (Institute of Electrical and Electronics Engineers Inc., 2026-08-01) Rajahrajasingh, H; Jayakody, D. N. K.; Peha, J. M
    This article presents a joint resource allocation and network slicing framework for hybrid radio frequency (RF) and visible light communication (VLC) systems based on a proportional-fairness (PF) objective. The proposed approach formulates a convex optimization problem that jointly allocates bandwidth resources across multiple slices and access technologies to balance aggregate throughput and user fairness. A relaxed PF solution is first derived via projected gradient optimization, followed by two practical rounding strategies: a simple threshold-based method and a greedy assignment heuristic that produce integer allocations with low complexity. Simulation results for a 20 MHz hybrid RF/VLC system (10 MHz/band) demonstrate that the proposed PF-based allocation achieves aggregate sum-rates of approximately 450-500 Mb/s with Jain's fairness indices greater than 0.9, thus outperforming static and rounding baselines by 10%-15% in throughput while maintaining high fairness. The analysis is further extended to asymmetric RF/VLC bandwidth conditions, demonstrating that the proposed PF-based slicing maintains high fairness while scaling throughput effectively. These results confirm that the PF formulation effectively captures the throughput fairness tradeoff and provides near-optimal slicing performance under realistic indoor bandwidth and power constraints.
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    OcupHI: knowledge-driven colorimetric interpretation framework for high-precision real-time ocular pH diagnostics
    (Springer Nature, 2026-08-12) Kahandawala, B, S; Sandaruwan, H. H. P. B; Liyanage, P; Dassanayake, R.S; Costha, N.P; Liyanage, R.N; Wijenayake, U; Wijesinghe, R.E; Silva, B.N; Manatunga, D.C
    Ocular injuries due to chemical spills pose a substantial concern, representing 10–22% of all ocular trauma. Although precise detection of ocular pH is crucial for determining the optimal medical treatment, many existing methods remain invasive, biased, or insufficiently precise. Reliance on subjective visual assessment of subtle color differences limits the objectivity and hinders high-throughput analysis. Therefore, an advanced colorimetric knowledge-driven ocular pH detection method was developed using a biosensor (OcupHI) based on a Clitoria ternatea (Butterfly Pea) anthocyanin sensing agent. The proposed work delivers fast, high-precision, and easily measurable pH prediction across clinically relevant ranges, while supporting real-time decision support for eye physicians. The pH range from 1 to 12 was tested and compared with six different anthocyanin concentrations: 5, 10, 20, 30, 40, and 50 ppm, and five different machine learning models, namely, Decision Tree (DT), K-Nearest Neighbors (KNN), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machines (SVM). The results revealed that the 40 ppm anthocyanin concentration trained with the XGBoost model produced the most accurate ocular pH values, achieving superior performance with an overall accuracy of 96%, a significantly higher F1-score for early detection. Experimental validation clearly demonstrates strong predictive accuracy, robustness, and interpretability, highlighting the potential for next-generation ocular diagnostics. Further research findings support Sustainable Development Goal (SDG) 3 – good health and well-being through a real-time ocular pH monitoring kit, and SDG 12 – responsible consumption and production by optimizing the use of the natural colorant anthocyanin for sensor development.
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    Spatial distribution and hydrological influences of microplastic contamination in the upstream reach of the ambathale water treatment plant intake, Sri Lanka
    (Springer Science and Business Media, 2026-08-07) Rathnayake, D; Miguntanna, N; Rathnayake, U
    Microplastic contamination has emerged as a global environmental concern, with rivers serving as important pathways for the accumulation and transport of these particles. This study investigated the spatial distribution of microplastic contamination and the influence of hydrological and physicochemical factors on microplastic occurrence in the upstream reach of the Ambathale Water Treatment Plant intake along the Kelani River, Sri Lanka. Water samples were collected from four locations within the study area, including three upstream sites and one downstream site. Microplastics were detected at all sampling locations, with Kelaniya recorded the highest microplastic concentration (20.08 ± 10.19 mg/L), while Ambathale had the lowest (9.12 ± 3.89 mg/L). Three main microplastic types were identified: fibers, fragments, and films. Fibers and fragments were the most abundant microplastic types across all sampling locations, while films occurred at comparatively lower concentrations. Statistical analyses revealed a significant positive correlation between river water level and microplastic concentration (r = 0.883, p = 0.001), indicating the importance of hydrological conditions in microplastic transport. Fiber and film concentrations exhibited particularly strong positive relationships with water-level fluctuations (r = 0.940 and r = 0.904, respectively; p < 0.01). Furthermore, positive associations between microplastic abundance and suspended solids suggest that particulate matter plays an important role in the transport and distribution of microplastics within the river system. The findings demonstrate significant spatial variability in microplastic contamination and highlight the influence of hydrological processes on microplastic occurrence and transport in the Kelani River. This study provides baseline information for future monitoring and contributes to a better understanding of microplastic dynamics in tropical freshwater environments.
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    PublicationOpen Access
    CALCOM: An integrated techno-economic and life-cycle environmental framework for electric vehicle assessment in Sri Lanka
    (Elsevier B.V., 2026-08-01) Abeygunawardena, N; Wijayapala, A; Jathunga, T
    Electric vehicle (EV) adoption is accelerating worldwide, creating a need for comprehensive frameworks that assess economic feasibility and environmental performance. This study presents a context-adaptive levelized cost of mileage (CALCOM) framework to evaluate the economic and environmental performance of battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), and internal combustion engine vehicles (ICEVs) under Sri Lankan conditions. The framework integrates discounted life-cycle cost (LCC), net present value (NPV), and greenhouse gas (GHG) emissions into a unified assessment model. Real-world operational ad cost data were collected from owners representing Nissan Leaf (BEV), Toyota Aqua (HEV), and Toyota Vitz (ICEV). The analysis included purchase cost, energy consumption, maintenance, battery replacement, salvage value, and environmental costs over a 10-year ownership period. The BEV achieved the lowest levelized cost of mileage of 0.080 USD/km which further decreased to 0.050 USD/km under renewable charging. Life-cycle GHG emissions were 59% lower than those of ICEV. Sensitivity analysis identified electricity price, annual distance travelled, and charging efficiency as the primary determinants of BEV competitiveness. Threshold analysis indicated that BEVs remain economically attractive when domestic electricity tariffs are maintained below 0.32 USD/kWh. The findings demonstrate that BEVs offer the greatest economic and environmental benefits and offer evidence-based guidance for policies supporting electric mobility in developing countries.
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    Fusion of Lean Six Sigma-DMAIC Tools and Techniques into Construction Variation Management: Barriers and Strategies
    (American Society of Civil Engineers (ASCE), 2026-11-01) Shashini, T.W.K.N; Jayanetti, J.K.D.D.T; Disaratna, V; Ranadewa, T; Perera, B.A.K.S
    Variations in construction projects pose a significant challenge to achieving successful project outcomes. Lean Six Sigma has the potential to manage variations in the construction industry. This study aims to explore the fusion of lean Six Sigma (LSS)-Define, Measure, Analyze, Improve, and Control (DMAIC) tools and techniques into construction practice to manage variations. Adopting a pragmatic stance and a qualitative approach, empirical data were collected through a three-round Delphi expert survey using semistructured interviews, with the data analyzed through content analysis. The findings reveal that 25 LSS-DMAIC techniques and tools can be effectively applied to manage variations in the construction sector. In addition, 17 barriers and 21 strategies were identified, and a mapping was undertaken to align each barrier with suitable strategies. This research addresses a gap in existing literature by extending investigations of LSS-DMAIC in construction to the specific context of managing variations, identifying barriers to implementation, and proposing strategies, an area that has not been explicitly examined previously. By investigating the barriers to implementing LSS-DMAIC and by suggesting tailor-made strategies for overcoming each barrier, the study makes both theoretical and practical contributions. It provides a framework for on the applicability of LSS-DMAIC in developing countries while offering construction managers context-specific solutions to enhance project outcomes and improve stakeholder satisfaction.
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    PublicationOpen Access
    Anthocyanin (ATH)-incorporating polyvinylpyrrolidone-ethyl cellulose-(2-hydroxypropyl)-β-cyclodextrin (PVP–EC–BCD) nanofiber-based pH sensor for ocular pH detection during accidental chemical spills
    (Royal Society of Chemistry, 2026-02-03) Sandaruwan, B; Liyanage, R; Costha, P; Dassanayake, Rohan S; Wijesinghe, R, E; Herath H.M.L.P.B; Nalin de Silva K.M.; de Silva, Rohini M; Rajapaksha, Suranga M; Wijenayake, U; Manatunga, Danushika C
    The existing ocular pH detection methods encounter numerous limitations, including low accuracy, poor sensitivity across a wide pH range, and patient discomfort, highlighting the need for innovative approaches. A novel biosensor for ocular pH detection has been developed to assess ocular health and chemical injuries in clinical settings. This study uses the pH-sensitive properties of anthocyanins (ATHs), natural pigments extracted from butterfly pea flowers, to develop a novel pH-responsive nanofiber mat. ATHs are integrated into a polymer blend containing polyvinylpyrrolidone (PVP), ethyl cellulose (EC), and (2-hydroxypropyl)-β-cyclodextrin (BCD) to fabricate electrospun nanofibers. The acquired characterization, employing scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and thermogravimetric analysis (TGA), confirmed the successful fabrication of the ATH-infused nanofibers with a mean diameter ranging from 121 to 396 nm. Four formulations were tested: PVP:EC:BCD:ATH (18 ppm), PVP:EC:BCD:ATH (25 ppm), PVP:EC:BCD:ATH (35 ppm), and PVP:EC:BCD:ATH (50 ppm). Among them, the 50 ppm ATH-incorporating nanofiber mat exhibited the best performance in terms of color clarity, response time, and pH sensitivity. The fabricated 50 ppm ATH incorporating nanofiber mat demonstrated a rapid pH response time of less than 5 seconds (s) while exhibiting a color variation from pink to blue to green across the pH range of 1 to 12, providing a rapid and accurate method for visual pH detection. Based on the color performance of the 50 ppm ATH-incorporating system, a standardized color reference chart was developed to serve as a practical and visual guide for estimating pH levels in clinical applications. Zebrafish toxicity assays were conducted further to validate the safety and biocompatibility of the developed sensor, revealing no significant toxic effects across the range of ATH concentrations.
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    PublicationOpen Access
    PV-Assisted Charging for Electric Three-Wheelers in Sri Lanka: A Comparative TCO and Sensitivity Analysis
    (Algerian Centre for the Development of Renewable Energy, 2026-05-24) Abeygunawardena, Nuwanthi; Jathunga, T; Rodrigo, M
    This research explores the potential of solar-powered electric three-wheelers as a sustainable and cost-effective transportation solution in Sri Lanka. Traditional three-wheelers contribute to air pollution and fuel dependency, while electric three-wheelers offer a cleaner alternative. By integrating solar power, these vehicles can further reduce emissions and operational costs. The study examines the economic benefits of three types of three-wheelers, covering fuel-based, electric, and solar-powered electric three-wheeler categories. Survey-based findings are used to calculate the total cost of ownership of tuk-tuks. Fuel and electricity costs, operational and maintenance costs, and more parameters are incorporated for the study. The findings suggest that solar-powered electric three-wheelers offer a promising solution for sustainable transportation solutions for the Sri Lankan context.
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    PublicationOpen Access
    Nature-Based Solutions: Evaluation of Natural Plant-Derived Coagulants for Sustainable Water Treatment
    (Multidisciplinary Digital Publishing Institute (MDPI), 2026-06) Perera, N; Miguntanna, Nadeeka; Miguntanna, Nandika; Rathnayake, U
    This study evaluates the performance of natural plant-derived coagulants as sustainable alternatives to conventional chemical coagulants in water treatment. Surface water samples were collected from the Meda Ela stream in Karadiyana, Sri Lanka, which is an urban water body impacted by leachate from the Karadiyana dumpsite, industrial discharges, and urban runoff. Grab samples were analyzed for key water quality parameters, including pH, conductivity, turbidity, dissolved oxygen (DO), chemical oxygen demand (COD), biochemical oxygen demand (BOD5), settleable solids, total solids (TS), total dissolved solids (TDS), total suspended solids (TSS), total nitrogen, and total phosphorus. Several parameters exceeded permissible standards established by the Central Environmental Authority (CEA) of Sri Lanka, including turbidity (35 NTU; limit: 20 NTU), COD (80 mg/L; limit: 15 mg/L), TDS (1000 mg/L; limit: 500 mg/L), and TSS (100 mg/L; limit: 40 mg/L), indicating significant pollution levels. Jar test experiments were conducted to compare the coagulation efficiency of cowpea seeds (75.8%), fenugreek seeds (69.2%), papaya seeds (72.5%), okra pods (84.6%), and Moringa oleifera (drumstick) leaves (87%) with conventional alum (94.2%) at an optimum dosage of 12 mL/L. Among the tested plant-derived coagulants, Moringa oleifera leaves demonstrated the highest turbidity removal efficiency, reducing residual turbidity to 4.54 NTU. A low-cost integrated treatment system incorporating coagulation, flocculation, sedimentation, and filtration using sawdust and cotton wool was developed, achieving average removal efficiencies of 90.13% for turbidity, 88.57% for COD, 83.46% for TDS, and 74.83% for TSS, with all effluent parameters maintained within CEA permissible limits. The results confirm that locally available plant-derived coagulants, particularly Moringa oleifera leaves, offer an effective, environmentally friendly, and economically viable approach for sustainable water treatment, highlighting the potential of nature-based solutions in strengthening climate-resilient water management strategies.
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    Fusion of machine learning to enhance the adaptability of lean construction maturity models (LCMMs)
    (Emerald Publishing, 2026-06-09) Jayanetti, J.K.D.D.T; Fernando, M. H; Ranadewa, K.A.T.O; Perera, B.A.K.S.
    Purpose – Lean construction maturity models (LCMMs) offer a structured approach to guide the implementation of lean practices in construction organisations. However, in developing countries such as Sri Lanka, their adaptability is constrained by contextual barriers and limited technological integration. Although numerous emerging technologies are available, the integration of machine learning (ML) into LCMMs remains largely unexplored. Thus, this study aims to investigate how ML can be fused with LCMMs to improve their adaptability in the Sri Lankan construction context. Design/methodology/approach – Rooted in pragmatism, the research adopted a qualitative choice, using the Delphi technique. Three rounds of semi-structured interviews were conducted in eight phases to collect data from 25 experts. Data were validated via two cases and analysed using code-based content analysis. Findings – The study identified a seven-stage LCMM, with the seventh level being the “Lean Ideal Level”. In total, 25 barriers were mapped across these seven stages. To address these, ten ML attributes were identified, and their suitability was assessed across each level. A comprehensive integration framework was developed, outlining relevant ML tools, techniques and fusion methods. Organisations at early maturity levels face more barriers, which decrease with progression, while ML attribute suitability shows the opposite trend, with fewer applicable attributes in early stages and more at advanced levels. Originality/value – To the best of the authors’ knowledge, this is the first study to bridge ML and LCMMs for developing countries, offering a structured, evidence-based framework that aligns ML capabilities with maturity stages. It advances theoretical understanding of LCMM adaptability while introducing a novel integration pathway tailored for resource-constrained contexts.