Faculty of Engineering, Technology, Applied Design & FineArt (FETADFA)

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Open Access
Improving microstructural properties, mechanical performance, and processability of flux-engineered stir cast boron carbide (B4C)- reinforced AA6061 composites with K₂TiF₆ integration
(Taylor & Francis Group., 2025) Baraha, Obinna Onyebuchi; Bori, Ige; Otaru, Abdulrazak Jinadu; Khan, Hayat
Flux-assisted stir casting of AA6061–B₄C is limited by incomplete wetting, oxide films, and porosity. This study optimizes the K₂TiF₆-assisted process, defining a minimal effective flux window (0.5–1.0 wt%) while holding melt (≈750 °C), stirring (≈600 rpm, 10 min), and mold temperature (≈250 °C) constant and varying B₄C (4–12 wt%) in a single, industry-style rig. SEM/EDS/XRD indicate near-uniform dispersion to 10 wt% and mild clustering at 12 wt%. Measurable performance gains. Measured as group means ± SD (n = 3), microhardness (HV₀.₅) increased from 68 → 113 (+62%), and UTS rose from 142 → 215 MPa (+51.4%); porosity rose modestly (~1.5→3.5%). Rule-of-mixtures predictions reproduce the 4–12 wt% trend, supporting a mechanism in which low-dose K₂TiF₆ disrupts oxide films, enhances wetting, and improves load transfer. By quantifying a low-flux regime that limits Ti contamination and salt waste while delivering predictable structure–property outcomes, the work provides process-level guidance for scalable production of lightweight aluminum composites for weight-critical structural applications.
Open Access
TensorFlow-Native Implementation for Crack Detection in Concrete Structures
(Mesopotamian Journal of Civil Engineering, 2025) Ayebare, Memory; Chavula, Petros; Mugisha, Simon; Byamukama, Willbroad
This paper presents a TensorFlow-native implementation for automated crack detection in concrete structures, addressing the critical need for efficient and objective infrastructure monitoring. Leveraging a Convolutional Neural Network architecture with 24.8 million parameters, the model was trained on a large-scale dataset of 40,000 images, each with a 227x227 RGB resolution. The methodology, incorporating specific framework optimizations and a rigorous training configuration, achieved a remarkable overall classification accuracy of 99.375% on the validation dataset. The model demonstrated balanced performance with precision values of 0.993 and 0.994, recall values of 0.994 and 0.993, and F1-scores of 0.994 and 0.994 for both "No Crack" and "Crack" classes. This high accuracy, coupled with balanced metrics, underscores the model's effectiveness and reliability for practical applications. The proposed solution significantly enhances real-time structural health monitoring systems, mitigating the limitations of traditional manual inspections and facilitating proactive maintenance strategies for concrete infrastructure
Open Access
Socioeconomic sustainability of bioenergy exploitation in Uganda: A GBEP-indicator narrative review
(Elsevier, 2025) Sekajja, Robert Kakebe; Nabuuma, Betty; Lubwama, Michael; Kanyamumba, Liberty
The socioeconomic implications of bioenergy exploitation in Uganda have not been sufficiently assessed through comprehensive frameworks, such as the Global Bioenergy Partnership (GBEP) sustainability indicators. Existing studies are fragmented and primarily sector-specific, which limits the identification of cross-cutting challenges and constrains evidence-based policymaking. This study applies, for the first time in Uganda, a comprehensive set of GBEP socioeconomic indicators through a structured narrative review organized into seven thematic do-mains. The analysis focused on three dominant bioenergy pathways: firewood, charcoal, and organic residues/ waste, which define Uganda’s bioenergy landscape. Relevant publications were selected based on their alignment with the selected indicators and bioenergy pathways in Uganda. Despite the scarcity of empirical data, partic-ularly in peer-reviewed sources, the review demonstrates clear trends. Traditional bioenergy contributes significantly to employment and national energy access, while also presenting persistent gender disparities and environmental risks. Transitioning to modern bioenergy systems may exacerbate land tenure disputes and food security concerns. However, the sector holds notable untapped potential: bioenergy-based power generation has reached 112 MW, with an estimated capacity of 1.65 GW, and energy from residues and waste remains underutilized at 737.7 PJ/year. Key research priorities emerging from this assessment include cookstove per-formance metrics, the bioenergy–food nexus, human capital development, charcoal substitution strategies, and energy diversification. The findings not only underscore the novelty of applying GBEP comprehensively in Uganda but also provide actionable insights for policy aimed at balancing energy access, livelihoods, and sustainability.
Open Access
Experimental and analytical study of lightweight foamed concrete reinforced with sugarcane bagasse fiber
(Scientific Reports, 2025) Sattar, Afiya Abdul; Mydin, Md Azree Othuman; Taqieddin, Ziad N.; Jagadesh, P.; Omar, Roshartini; Abdullah, Mohd Mustafa Al Bakri; Awoyera, Paul O.; Fadugba, Olaolu George; Vasić, Milica V.
Growing environmental concerns have intensified research into sustainable construction materials, such as natural fiber-reinforced concrete. Among these, lightweight foamed concrete (LFC) stands out for its reduced material consumption, improved thermal insulation, and lower environmental footprint. The integration of natural fibers, such as sugarcane bagasse fiber (SBF), into LFC has the potential to further enhance its performance. This study investigates the influence of varying SBF weight fractions (0%, 1%, 2%, 3%, 4%, and 5%) on the physical, mechanical, and durability properties of LFC with a target density of 1000 kg/m3. The primary objective was to determine the optimal SBF content for achieving superior material characteristics. Experimental results revealed that the inclusion of 4% SBF provided the best overall performance, improving compressive strength by 53%, increasing ultrasonic pulse velocity (UPV) by 17%, and reducing drying shrinkage by 58% compared to the control mix. Additionally, slump flow decreased progressively with higher fiber content, indicating enhanced cohesion. Water absorption and porosity were significantly reduced with increasing SBF, with the 5% mix showing up to a 19% decrease in water absorption. Thermal conductivity also declined slightly, suggesting improved insulation properties. Microstructural analysis confirmed better fiber-matrix bonding at the optimal fiber content, contributing to the observed improvements in performance. This study offers valuable insights into the mechanical, thermal, and durability characteristics of LFC-SBF composites, highlighting their potential as sustainable construction materials.
Open Access
Mechanical and microscale characterization of foamed concrete with Tianqi aluminosilicate binder
(Scientific Reports, 2025) Sattar, Afiya Abdul; Mydin, Md Azree Othuman; Nadimalla, Altamashuddinkhan; Abdullah, Mohd Mustafa Al Bakri; Awoyera, Paul O.; Fadugba, Olaolu George
Persistent research work has aided the development of supplementary cementitious materials, contributing to both sustainable development and mitigating environmental impacts. This study utilized Tianqi aluminosilicate (TAS) as partial replacement for Ordinary Portland Cement (OPC) in foamed concrete (FC) mix. The mechanical, transport, and microstructural characteristics of the concrete were explored. The formed concrete mixes were developed by varying TAS from 0 to 40%, in steps of 10% for OPC to identify optimal performance. The mechanical characteristics (compressive, flexural, splitting tensile, and elastic modulus) improved by 18–25% over control and peaked at 20% TAS. At 20% TAS substitution, the transport properties (water absorption and permeability) improved significantly, which corresponds to 35% and 28%, reduction, respectively. SEM analysis revealed that TAS refined pore structure, yielding a denser matrix with homogeneous hydration product distribution. The result revealed foam stability and uniformity in mixes containing TAS, and an improvement in mechanical and durability of the concrete. Filler effect and pozzolanic activities of TAS were identified as two key factors responsible for the observed results. There was pore refinement improved secondary hydration in the concrete matrix. The results show that 20% TAS substitution improves strength and durability while lowering OPC use and striking the ideal performance balance. From the results, TAS proved to be a sustainable supplementary cementitious material aiding the durability of the mixes. This work advances eco-friendly construction practices by demonstrating TAS’s viability in high-performance FC applications.
Open Access
Green construction with sustainable foam mortar utilizing recycled polyethylene terephthalate waste for enhanced thermal insulation and durability properties.
(Scientific Reports, 2025) Mydin, Md Azree Othuman; Awoyera, Paul. O; Taqieddin, Ziad. N; Özkılıç, Yasin Onuralp; Fadugba, Olaolu George; Abdullah, Mohd Mustafa Al Bakri; Omar, Roshartini; Datta, Shuvo Dip; Olalusi, Oladimeji. B
This study explores the development of a sustainable foam mortar incorporating recycled polyethylene terephthalate (PET) waste as a partial sand replacement to enhance thermal insulation and promote circular economy practices. Foamed mortars incorporating recycled polyethylene terephthalate (PET) waste were developed in this study, with the overall goal of addressing the dual challenge of waste management and resource depletion. PET waste, commonly discarded as environmental pollutants, was processed into fine aggregate sizes and used as a partial replacement for sand. There were six mix proportions with PET replacement ratios (0, 5, 10, 15, 20, and 25%). PET improved thermal insulation by lowering thermal conductivity from 0.31 W/mK to 0.26 W/mK and reducing density by up to 15%. At 28 days, the compressive strength varied between 12.5 MPa (0% PET) and 9.8 MPa (25% PET), suggesting that it is viable for non-structural applications. Similar declines of 25–30% and 20–25%, respectively, in flexural and tensile strengths were ascribed to weakened interfacial bonding between PET and the cement matrix. At higher PET levels, durability increased, with a 20% decrease in water absorption and a substantial decrease in chloride ion penetration. The use of PET significantly improved thermal properties, and microstructural analysis confirmed more refined pore structures and homogeneous dispersion of PET particles. These results show that PET can be a sustainable alternative to foam mortar, promoting environmentally friendly construction methods and the concepts of the circular economy
Open Access
Assessment of Uganda’s bioenergy sector for environmental sustainability
(Elsevier Ltd., 2025) Sekajja, Robert Kakebe; Nabuuma, Betty; Lubwama, Michael; Kanyamumba, Liberty
Bioenergy remains Uganda’s dominant energy source, yet its environmental sustainability impacts remain dispersed and sparsely documented, limiting informed policy development. This study addresses this gap by applying eight Environmental Sustainability Indicators (ESIs) from the Global Bioenergy Partnership (GBEP), covering greenhouse gas emissions, soil and water impacts, biodiversity, land-use change, wood harvest levels, and air pollution. Data were synthesized from peer-reviewed literature and grey sources using the GBEP methodological framework. Findings reveal that woody biomass demand significantly exceeds sustainable supply, accelerating deforestation and forest degradation, while reliance on traditional bioenergy combustion drives indoor air pollution with serious public health risks. Uganda’s largely informal bioenergy sector, coupled with limited geospatially referenced data on biomass distribution and land-use change, constrains the accuracy of assessments. Despite these limitations, the study represents the first integrated application of the GBEP ESIs framework for evaluating Uganda’s bioenergy-environment nexus to date. It benchmarks specific indicator performances in Uganda against regional and global standards, highlights critical sustainability gaps, and underscores the urgency of adopting stronger governance, ICT-enabled monitoring, financing mechanisms, and coherent institutional frameworks. By establishing an evidence base, the study supports policy reforms and the transition toward modern, sustainable bioenergy systems aligned with Uganda’s climate and development goals.
Open Access
Effect of varying nano-boron nitride content on foamed concrete containing titanium dioxide nanoparticles
(Scientific Reports, 2025) Mydin, Othuman Md Azree; Sor, Nadhim Hamah; Ziad N. Taqieddin; Isleem, Haytham F.; Abdullah, Mohd Mustafa Al Bakri; Awoyera, Paul O.; Fadugba, Olaolu George; Tawfik, Taher A.
This study focused on investigating mixing boron nitride (BN) and titanium dioxide (TiO₂) nanoparticles in enhancing the foamed concrete (FC) characteristics. Despite the presence of independent studies on each material addition, there is little study on their combined effects, especially with enhancements in durability, mechanical properties, and thermal performance of FC for sustainable building usage. The current research aims to examine the effects of varying BN doses (0.025–0.1% by weight of cement) with the use of constant 1% TiO₂ on fresh characteristics, microstructure, pore structure, mechanical performance, shrinkage, and thermal behavior. The results showed a slight reduction in slump and setting time, accompanied by a rise in dry density. At 0.075% BN, the 28-day compressive, flexural, and splitting tensile strengths increased by 44.27%, 52.1%, and 57.14%, respectively. Thermal conductivity increased by 7.2%, whereas shrinkage decreased by 52.30% at 28 days. Mercury intrusion porosimetry (MIP) proved the enhanced pore architecture characterized by a reduced average pore diameter and an increased volume proportion of fine capillary pores. The findings demonstrate the capability of the BN–TiO₂ hybrid system to greatly improve the durability and thermal performance of FC, causing an increase in service life and a decrease in environmental impact.
Open Access
Optimal Pavement Maintenance Strategy Based on the Relationship Between Pavement Condition Index and Roughness
(7th FUTA Engineering Conference, 2024) Kabiru, R. U.; Abbas, U.; Hassan, Aliyu; Terseer, A; Muhindo, D
Pavement maintenance is crucial for ensuring road safety, reducing congestion, and minimizing repair costs. However, determining the optimal timing and strategy for pavement maintenance remains a challenge. This study investigated the correlation between the Pavement Condition Index (PCI) and Roughness Index (RI) to develop a numerical model for describing relationship of the two indices for pavement maintenance decision-making. Using statistical analysis and data visualization techniques, a significant correlation was found between PCI and RI. The study revealed a moderate correlation between PCI and IRI (R² = 0.47), indicating that 47% of PCI variations can be explained by IRI. While this suggests that the model is capturing a significant amount of the relationship between PCI and IRI, there is still room for improvement, as about 53% of the variance in PCI is not explained by the model. Since the PCI is a measure of road pavement conditions (on a scale typically ranging from 0 to 100), an RMSE of 7.77 means that the model's predictions for PCI are, on average, about 7 to 8 PCI units off from the actual value. The study established a clear relationship between pavement condition and surface roughness, enabling the development of a model to guide maintenance decisions. The study recommends prioritizing roads with PCI ≥ 50.3 and RI ≤ 5.12 m/km, alongside regular monitoring to ensure timely, cost-effective maintenance. Regular monitoring of PCI and RI values is also recommended to ensure timely maintenance and prevent costly repairs.
Open Access
Soft Computing Solutions for Reducing the Carbon Footprint of Fly Ash Based Concrete. Advances in Civil Engineering
(John Wiley & Sons Ltd., 2025) Awoyera, Paul O.; Adetola, Joshua; Nayeemuddin, Mohammed; Mewada, Hiren; George Fadugba, Olaolu
The construction industry significantly contributes to environmental degradation,with many structures exhibiting high carbon footprints throughout their construction processes and lifespans.Activities such as cement hydration and other commoncon-struction practices substantially influence environmental conditions overtime,necessitating a critical evaluation of material and design choices.This study reported the environmental impact of fly ash(FA),which is largely used to enhance concrete strength.A prediction of two end point indicators,that is,global warming potential(GWP)and CO2 emission using soft computing methods are presented,which are particularly effective for handling complex,non linear relationships in environmental data.To achieve this, two machine learning approaches,the random forest(RF)and decision tree(DT)models,are employed to assess the environ- mental impact of structural materials and designs.Two data sets were obtained from reputable databases,including ResearchGate, Science Direct, Semantic Scholar,and Mendeley Data.The models are trained to explore the potential for optimizing structural designs and material selection stominimize environmental impacts.Feature importance is analyzed using Shapley values,providing insights into the most influential factors affecting GWP and CO2 emission Model performance is evaluated using R2 and root mean square error(RMSE) metrics. Notably, the RF model achieved an R2 score of 91% for GWP and 97% for CO2 emission, demonstrating superior predictive accuracy compared to the DT approach.The findings demonstrate the effectiveness of these machine learning techniques in enhancing the sustainability of construction practices,offering a pathway for informed decision-making. This study highlights the urgent need for innovative approaches in the built environment to support sustainable development and mitigate the carbonfootprint associated with structural engineering.
Open Access
Bamboo stem ash as a sustainable cement replacement in lightweight foam mortar enhancing mechanical thermal and microstructural properties.
(Scientific Reports, 2025) Mydin, Md Azree Othuman; Azman, Nurul Zahirah Noor; Awoyera, Paul O.; Özkılıç, Yasin Onuralp; Fadugba, Olaolu George; Abdullah, Mohd Mustafa Al Bakri; Omar, Roshartini; Datta, Shuvo Dip
This study presents a novel approach to enhancing the properties of lightweight foam mortar (LFM) by utilizing bamboo stem ash (BSA) as a partial cement replacement. Unlike traditional supplemental cementitious materials (SCMs) like fly ash or silica fume, BSA provides a special blend of lightweight properties and a high silica concentration. Thus, the effect of BSA (in proportions of 0–25% and steps of 5%) on the mortars’ fresh, hardened, microscale properties, such as workability, density, strength, durability, and microstructural characteristics, was explored. At 15% BSA replacement, the compressive strength reached 8.25 MPa at 28 days, 7% higher than the control mix (7.7 MPa). The study identifies 15% BSA as the optimal replacement level, striking a balance between mechanical strength, durability, and thermal insulation. Beyond 15%, increased porosity begins to reduce strength, while thermal resistance continues to improve. Thus, a 10–15% replacement range is recommended for applications requiring structural integrity and insulation. The density of the foam mortar decreased from 1000 kg/m3 for the control mix to 960 kg/m3 at 20% BSA replacement, improving the material’s lightweight characteristics. Also, the porosity increased from 24.8% (control) to 30.2% (25% BSA), positively influencing thermal insulation properties. Thermal conductivity measurements indicated a reduction from 0.25 W/mK (control) to 0.18 W/mK at 25% BSA replacement, demonstrating improved thermal resistance. BSA incorporation improves the pore structure and fosters stronger interfacial bonding within the matrix, especially at 15% replacement, according to microstructural investigation using SEM. The water absorption rate increased slightly from 18.2% (control) to 21.6% (25% BSA), still within reasonable bounds for lightweight construction applications. As demonstrated by the mortars’ notable performance, BSA may effectively replace OPC in LFM, improving its mechanical, thermal, and environmental qualities. With the results, BSA has shown potential for developing eco-friendly building materials and aiding in reducing carbon emissions in the built environment. These results show that BSA can be a green and practical substitute for OPC in lightweight building applications, especially for prefabricated panels, insulation layers, and non-load-bearing walls. Its ability to enhance mechanical strength while reducing thermal conductivity makes it a promising material for energy-efficient and sustainable building solutions.
Open Access
Battery Management System for Solar Power Plants in Uganda: An IoT-Driven Approach
(MECS Press, 2025) Ssembalirwa, Denis; Cartland, Richard; Bature, U. I.; Kitone, Isaac
In Uganda, the efficiency and reliability of solar power plants are often compromised due to inadequate battery management, leading to reduced battery lifespan and suboptimal performance. To address this challenge, this project develops and prototypes a smart Battery Management System (BMS) tailored for solar power plants. The system continuously monitors key battery parameters, including voltage, load current, and temperature, while leveraging Internet of Things (IoT) technology for real-time data transmission and remote monitoring. Intelligent algorithms autonomously regulate charging and discharging cycles to prevent overcharging and deep discharge, optimizing battery performance. Testing demonstrated that the BMS significantly improved battery lifespan and energy efficiency by disconnecting charging at 100% and isolating the load at 10% discharge to prevent battery degradation. Additionally, the system disconnects power when battery temperature exceeds 30°C (ambient temperature: 25°C) and detects abnormal current levels above 0.16A to mitigate faults such as short circuits. These automated protections enhance battery reliability and longevity. By implementing proactive battery management strategies, the developed BMS contributes to more efficient and resilient energy storage systems, promoting sustainable energy development in Uganda.
Open Access
Bibliometric Insights into Advances in Nondestructive Testing Techniques for Delamination Detection
(Mesopotamian Journal of Civil Engineering, 2025-04-11) Abdulwahd, Abdulrazaq. K.; Mugisha, Simon; Chavula, Petros; Kayusi, Fredrick
This study presents a comprehensive bibliometric analysis of advances in nondestructive testing (NDT) techniques for delamination detection, based on 4,382 publications indexed in Scopus from 2021 to 2025. Using advanced bibliometric methods and the biblioshiny package in R, the analysis evaluates annual scientific production, citation trends, thematic focus, and collaboration patterns. The results reveal a peak in research output in 2024, followed by a marked decline in 2025, alongside a steady decrease in average citations per article. “Delamination,” “composite,” “ultrasonic,” and “infrared thermography” are identified as core research themes. The field is dominated by a few prolific journals, authors, and institutions most notably in China which account for the majority of scientific output and impact. These findings illuminate evolving research priorities, highlight central contributors, and offer critical perspectives on the development, concentration, and future directions of NDT for delamination detection.
Open Access
Geostatistical-based spatial distribution of in-situ groundwater quality parameters in the crystalline basement aquifer in urban and peri-urban city:
(KIU Journal of Science, Engineering and Technology, 2025) Fadugba, O. G.
This study examines the spatial distribution of in-situ groundwater quality parameters in the crystalline basement aquifer in Akure City, Nigeria using geostatistical methods. The area was divided into urban and peri-urban areas. Water samples were taken to the laboratory for characterization of the water quality parameters in the water samples obtained in the study area. The oil/water interphase meter was used to determine the depth to the surface of the selected wells in the study area. The depth of the well is between 3.07 and 7.03 meters. The well depth was divided into four categories: Low (3.07 to 7.03 m), Moderate (4.88 to 5.05 m), High (5.06 to 5.22 m), and Very High (5.23 to 7.03 m). Four categories were used to classify the well depth: Low (2.27 to 4.18 m), Moderate (4.19 to 4.29 m), High (4.30 to 4.41 m), and Very High (4.42 to 6.32 m). The pH scale is 5.48 to 6.71. Four pH ranges were identified: Low (5.48 to 5.91), Moderate (5.92 to 6.20), High (6.21 to 6.41), and Very High (6.42 to 6.71). Four categories were assigned to the ORP: Low (29.71% to 45.63%), Moderate (45.64 percent to 57.42%), High (57.43 percent to 66.16%), and Very High (66.17 percent to 77.95%). There were four categories for the Electrical Conductivity distribution (EC): Low (100.64 µS/cm to 242.50 µS/cm), Moderate (242.51 µS/cm to 347.61 µS/cm), High (347.52 µS/cm to 425.49 µS/cm), and Very High (425.50 µS/cm to 483.20 µS/cm). There were four categories for the Total Dissolved Solid (TDS): Low (50.87 ppm to 120.75 ppm), Moderate (120.76 ppm to 172.53 ppm), High (172.54 ppm to 210.89 ppm), and Very High (210.90 ppm to 239.32 ppm).
Open Access
Mechanical performance of structural concrete utilising porcelain insulator ceramic waste as partial replacement for coarse aggregates
(2025) Kabiru, R. U; Abbas, U.; Hassan, A.; Muhindo, D.
The increasing environmental impact of natural aggregate extraction and the growing accumulation of ceramic waste have prompted the search for sustainable construction materials. This study investigates the feasibility of using ceramic waste from waste electric insulators as partial replacement for natural coarse aggregates in concrete production. The ceramic waste from waste electric insulators termed here as porcelain insulator ceramic waste (PICW) sourced from local dumpsites was processed and incorporated into concrete mixes at replacement levels of 0%, 15%, 30%, 50% and 75%. Coarse aggregates of maximum size 20 mm were used in this study. The ceramic waste from waste electricity insulators was crushed using a hammer up to size 20 mm as indicated in the particle size distribution. Grade 25 of concrete was designed for in the mix design. Laboratory tests, including sieve analysis, moisture content, specific gravity, water absorption, workability (via slump testing), and compressive strength were conducted to assess the mechanical and physical properties of both fresh and hardened concrete at curing intervals of 7, 14, and 28 days. The findings indicate that concrete containing up to 30% ceramic waste exhibits highest cempressive strength and workability comparable to conventional concrete without compromising its durability and workability, demonstrating its potential as a viable and eco-friendly alternative. The highest compressive strengths were recorded with 15% and 30% at 25.7 and 25.5 MPa respectively. Conversely, tensile strength declines with increasing PICW replacement at 28 days thus 3.32, 3.16, 2.99, 2.31 MPa. The study underscores the dual benefits of reducing construction costs and promoting sustainable waste management, making ceramic waste a promising material in the pursuit of green construction practices i.e., sustainable construction by mitigating environmental degradation and promoting circular waste utilization. The study offers valuable insights for future standards development and large-scale industrial applications.
Open Access
An expert analytical approach to reducing construction project delays from ineffective scheduling
(KIU Journal of Science, Engineering and Technology, 2025) Joseph, O. S; Fadugba, O. G; Oluyemi-Ayibiowu, B. D; Uduebor, M. A; Olu-Matins, O. A
The study investigated the effects of ineffective scheduling on the completion of construction projects, identified causes of poor planning and scheduling, and provided expert-recommended solutions. Using a mixed-method approach including online surveys, physical questionnaires, and statistical analysis (Relative Importance Index - RII, Reliability Test, and SPSS), the research analyzed data from 130 construction professionals in Nigeria. The most significant effects of ineffective scheduling were "Time Overrun" (RII = 0.8892) and "Cost Overrun" (RII = 0.8246), followed by "Compromise of Project Quality" (RII = 0.8077). The top causes identified were "Poor Decision-Making Regarding Activity Criticality" (RII = 0.8631), "Lack of Finance for Project Execution" (RII = 0.8492), and "Lack of Expertise in Scheduling" (RII = 0.8123). The study concludes by offering a comprehensive roadmap for stakeholders to enhance scheduling efficiency, reduce delays, and improve overall project performance through practical strategies such as accurate cost estimation, effective planning, stakeholder engagement, and the use of scheduling software.
Open Access
Developing High-Performance Low-Carbon Concrete Using Ground Coal Bottom Ash and Coconut Coir Fibre
(Elsevier, 2025) Ahmed, Muneer; Khan, Suliman; Bheel, Naraindas; Awoyera, Paul.O; Fadugba, Olaolu George
This study addresses the need for eco-friendly concrete by incorporating agro-industrial waste, ground coal bottom ash (GCBA) and coconut coir fibre (CF), as partial replacements for Ordinary Portland Cement. A total of150 samples were tested using Scanning Electron Microscopy (SEM), Fourier-transform infrared (FTIR), X-ray Fluorescence (XRF) and mechanical methods. Optimal results were achieved with 4.31 % CF, 0.4 % superplasticizer, flexural performance. The addition of CF reduced cracking and improved durability and GCBA enhanced long-term performance through improved particle packing and pozzolanic reactions. The GCBACF mixtures also lowered embodied carbon by 194 kg CO₂/m³ and energy by 970 MJ/m³, achieving higher Eco efficiency than traditional concrete. This research supports the development of sustainable, high-performance concrete aligned with circular economy and sustainability goals.
Open Access
Improving productivity and efficiency in banana processing: Advancements and challenges in matooke peeling techniques
(KIU Journal of Science, Engineering and Technology, 2025) Edeh, J. C; Kizanye, Stella; Onyeukwu, K. J; Nnamani, L.C
The processing of green bananas into various food products involves several critical post-harvest operations, with matooke fruit peeling being one of the most crucial steps to ensure quality, safety, and overall integrity of the derivative products. This study presents a comprehensive review of matooke peeling techniques, analyzing traditional, thermal, and mechanized methods, while also exploring the theoretical principles and operational concepts underpinning these processes. Parameter evaluation of crop-related physical and mechanical properties of the banana fruits is provided to identify key factors influencing the effective design of an efficient mechanized peeling system. These parameters, including fruit size, geometric mean diameter, peel thickness, moisture content, angle of repose, and shear stress, are shown to significantly impact peeling efficiency and system performance. The review emphasizes the potential of mechanical peeling as a viable solution for the full mechanization of matooke processing, eliminating the drudgery and contamination-prone manual intervention within the process. The success of the mechanized systems is highly contingent on the precise understanding and integration of these crop-specific characteristics. Based on these insights, the paper proposes a crop parameter-based design for an automated peeling system aimed at improving productivity, enhancing hygiene standards, reducing labor costs, and ensuring consistent peeling quality. This mechanized approach is positioned as a reliable, efficient, and cost-effective solution for small, medium and large-scale matooke processing, with good potential for value addition and significant advancements in the processing industry
Open Access
Advanced machine learning models for the prediction of ceramic tiles’ properties during the firing stage
(Scientific Reports, 2025) V. Vasic, Milica; Awoyera, Paul O.; Fadugba, Oladlu George; Barisic, Ivana; Nettinger Grubeša, Ivanka
The firing stage is a critical phase in ceramic tile production, where the interplay of raw material composition and thermal treatment determines essential properties such as water absorption (WA) and bending strength (BS). This study employs advanced machine learning (ML) models to accurately predict these properties by capturing their complex nonlinear relationships. A robust dataset of 312 ceramic samples was analyzed, including variables such as particle size distribution, chemical and mineralogical composition, and firing temperatures ranging from 1000 to 1300 °C. Among the four ensemble ML models evaluated, CatBoost demonstrated the highest predictive performance. Model accuracy was assessed using multiple evaluation metrics, including the coefficient of determination (R²), root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). To enhance interpretability, SHapley Additive exPlanations (SHAP) were used, revealing that clay mineral content and SiO₂ concentration were the most influential factors for WA, contributing approximately 40% and 30%, respectively. For BS, firing temperature (35%) and Al₂O₃ content (25%) were identified as the key predictors. Partial dependence plots further illustrated critical thresholds, such as a significant drop in WA above 62% SiO₂ and optimal BS values near 1200 °C, findings that align with known ceramic processing principles while offering new, data-driven formulation insights. These results demonstrate the value of explainable artificial intelligence (AI) in enabling real-time process optimization, enhancing product consistency, and supporting energy-efficient ceramic manufacturing. Future work will focus on extending the dataset to include a wider variety of clay compositions and investigating hybrid modeling approaches to further improve predictive performance.
Open Access
Development of a fundamental model for pelleting efficiency of an innovative hybrid fish feed processing system
(KIU Journal of Science, Engineering and Technology, 2025) Daniel C., Nnadi; John Chijioke, Edeh; Offiong Alexander, Aniekan; Aniekan, Offiong
The development of a fundamental model for predicting pelleting efficiency at variable feed rates and number of orifices was central to optimizing the performance of an innovative hybrid fish feed processing system. The system was designed for simplicity, quality, and precision in fish feed production. Machine parameters, derived from comprehensive design and parametric analysis, were used to establish input variables for the pelleting efficiency model, including feed rate and number of orifices. With a constant driving force of 713.38 N from a 3 hp electric motor, the system demonstrated pelleting efficiencies of 55 %, 70 %, and 88 % for 15, 20, and 25 orifices, respectively. At a fixed die orifice, increasing the feed rate from 10 to 20 mm/rev at interval of 5 mm/rev resulted in efficiencies of 60 %, 80 %, and 110 %. Evaluation of the combined effect of the factors predicted an optimum efficiency of 86.9 % at optimal settings of 20mm/rev and 15 orifices. The model’s experimental validation, conducted under optimized conditions, showed that the 20-orifice die produced a higher pelleting efficiency (97%) but with reduced pellet floatability, whereas the 15-orifice die yielded an efficiency of 86.21 % and better floatability. The prediction error of 0.69% validated the model’s accuracy at 99 %. In addition, an introduction of cassava starch constituent improved pellet floatability and surface finish. This study therefore, highlights the potential of the developed model to enhance pelleting performance, balancing efficiency and pellet quality, and providing a robust foundation for optimizing fish feed production processes.