School of Infrastructure Process Engineering and Technology (SIPET)
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School of Infrastructure Process Engineering and Technology (SIPET)
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Item Electrochemical Characterization of Stainless-Steel Mesh and carbon-felt Electrodes for Enhanced Power Generation in Terrestrial Microbial Fuel Cells.(School of Physical Sciences, FUTMINNA, 2024-04-24) Simeon, Meshack Imologie; Alaka, Amarachi C.; Daniela, P.; Olalekan, D. AdeniyiTerrestrial Microbial Fuel Cells (MFCs) represent a promising avenue for sustainable energy production, leveraging microbial metabolism to convert organic matter in the soil into electricity. Crucial to MFC performance is selecting electrode materials, which directly interface with electroactive microbes for electron transfer. This study conducts a comparative analysis of surface-modified stainless-steel mesh (SMS) and carbon felt (CF) electrodes in terrestrial MFCs, evaluating their performance metrics and impedance spectroscopy. The SMS electrode, fabricated using the pasting and reinforcement process, demonstrated superior performance with a maximum power of 859 µW compared to the 234 µW power of the commercially available CF electrode. This better performance of the SMS electrode was attributed to its pseudocapacitive behavior, enhancing internal charge storage capacity and overall MFC efficiency. Electrochemical impedance spectroscopy revealed a substantially higher charge transfer resistance (Rct) in the CF electrode, impeding electron transfer processes. Conversely, the SMS electrode exhibited lower Rct and improved diffusion characteristics, facilitating efficient electron transfer and mass transport. Notably, the Rct of the CF electrode was over 40 times higher, while its diffusion coefficient was approximately six times greater compared to the SMS electrode. These findings underscore the significance of tailored electrode materials in optimizing MFC performance and emphasize the utility of impedance spectroscopy in elucidating complex electrochemical processes within MFC systems, thus guiding future advancements in sustainable power production in terrestrial MFCs.Item Estimation of Pavement Temperature in Nigeria’s Climatological Zones(Proceedings of the Third International Civil Engineering Conference (ICEC, 2024), 2025) Ibrahim, A. I.; Abdulrahman, H. S.; Abubakar, MahmudItem Influence Of Roadcem Content on Mechanical Properties of Lateritic Soil for Pavement Applications(Proceedings of the Third International Civil Engineering Conference (ICEC, 2024), 2025) Illo, N. A.; Abubakar, Mahmud; Abdulrahman, H. S.; Kolo, D. N.Studies on lateritic soil had been carried by numerous researchers across the globe with a view of improving it for the purposes of road pavement and other civil engineering constructions. The main aim of this paper is to examine the impact of varying Roadcem (RC) content on the mechanical properties of lateritic soil for pavement applications which was found to be an A-7-5 soil according to AASHTO. The soil sample was treated with RC at 0, 1,2,3,4, and 5%. Laboratory test such as particles size distribution, unconfined compressive strength (UCS) test for the treated and untreated samples was carried out. Three samples on each dosage were compacted and molded in cylindrical molds and cured two of each sample for 7 days, one each for 28 days. X-ray Diffraction Analysis (XRD), was also carried out on the two samples to reveals their crystalline phases and shows high intensity of CaO and Quartz on the two samples respectively. The UCS results shows insignificant variations in the dosage of RC even at 28 days. The study concluded that A-7-5 soils does not respond to treatment with RC beyond 1% due to its high plasticity and poorly graded and therefore recommend the use of the RC as an additive, at lesser percentage, or on cohesionless soils like sand for road pavement applications.Item Effects of blending on the phytochemical, functional and proximate properties of Mucuna solannie-based composite flour(2022-09-30) Asoiro, Felix; Simeon, Meshack Imologie; Azuka, CE; Orji, Precious ChimaraogeBrachystegia eurycoma (BE), Afzelia Africana (AA) and Mucuna solannie (MS) flours were blended (%, w/w) at varying proportions: 50:50, 60:40, 70:30, 80:20 and 100:0, with 100% of flours as the control; then analyzed based on the phyto-chemical, functional and proximate compositions. Tanin, saponin, alkaloid and flavonoid values were 4.19, 1.47, 1.49 and 1.15 mg 100 g-1 dm; 3.44, 0.45, 1.34 and 1.13 mg 100 g-1 dm; and 4.1, 0.61, 1.36 and 1.18 mg 100 g-1 dm in MS, AA and BE flours respectively. Increased AA and BE proportions in MS flour increased the swelling index (1.49% -1.76%) whereas AA and BE inclusions (%) resulted in significant (P≤0.05) increase in the moisture content of the composite flours (8.3% - 14%). Increase in % AA flour inclusion resulted in significant improvement in carbohydrate content while % BE flour inclusion recorded a decrease. As % BE flour inclusion increased from 20% to 40%, % protein content in the blends significantly improved (15.65% - 16.25%) while % AA inclusion, increased protein content by 30%. The study could help to optimize the products made from MS, AA and BE flour blends, in terms of their properties than products made solely from single flour.Item Stabilization characteristics of cemented lateritic soil produced with selected cement types(Elsevier, 2025-01-10) A.A. Amadi; S.S. Kolo; YUSUF, Abdulazeez; F.E. Eze; U. SalihIt is recognized that different cements have different properties and stabilization effectiveness for different ap plications. The challenge of using the right type of cement should be a concern for practitioners in civil engi neering construction. In this study, an experimental testing programme was conducted to evaluate and compare the stabilizing effects of CEM I 42.5 N, CEM II/B-L 42.5 N and CEM III/A 42.5 N types of cement on some physical and mechanical properties of lateritic soil. Laboratory tests performed on soil mixtures containing the selected cements added to constitute 0, 3, 6, 9 and 12 % of the dry weight of the composite materials include the con sistency and compaction tests determined on the basis of fresh mixtures. In addition, unconfined compressive strength (UCS) test on specimens compacted at optimum moisture conditions with the British Standard Light (BSL) compaction effort and cured for 7, 28 and 90 days was performed. In equal proportions, soil mixtures prepared with the different types of cements yielded comparable results in terms of reducing the plasticity index (PI) from values as high as 60 % in untreated state to 5.05 %, 7.05 % and 8.2 % respectively for CEM I, CEM II and CEM III at 12 % cement content. Addition of cement also increased both the maximum dry unit weight (γ dmax ) and optimummoisture content (OMC) of the soil with CEM I cement having the greatest effect while CEM III cement affected the γ dmax γ dmax 3 =1.95 kN/m of the soil the least. For example, when compacted with BSH effort, CEM I achieved 3 and OMC =25 %,while for CEM III, γ γ dmax 3 of 1.53 kN/m dmax =1.63 kN/m and OMC =22.6 % compared to and OMC of 21.1 % for the untreated soil. Regardless of the cement type, there was an overall improvement in the strength properties of the lateritic soil represented by a range of 11– 14 times for UCS and31-62folds for E 50 at 12 %cementafter 90 days curing duration in comparison with the untreated soil. While strength gain was higher in CEM I based mixtures at early (7 day) age (1635.44, 1622.85 and 1599.55 kN/ m2 for CEM I, CEM II and CEM III respectively at 12 % cement content), CEM III provided superior strength improvement at the long term (90 day) curing period (2566.25 compared to 2444.58 and 2465.77 kN/m α 2 respectively for CEM I and CEM II at 12 % cement content). Using the variance analysis (ANOVA) at a signifi cance level ( ) of 0.05, the influence of cement type was statistically confirmed for the liquid limit, optimum moisture content and UCS at 28 and 90 days curing ages.Item POTENTIALS OF DEKINA CASSAVA PEEL ASH IN CONCRETE PRODUCTION(3RD INTERNATIONAL CIVIL ENGINEERING CONFERENCE, 2024-02-28) Ismail, S. P; Kolo, D. N; YUSUF, AbdulazeezBasic conventional building materials like cement and aggregates are becoming increasingly expensive due to high cost incurred in their processes, production and transportation. The utilization of locally available materials such as cassava peel ash that can either reduce or replace the conventional ones is being considered. Following review paper summarizes the mechanical and durability characteristics of cassava peel ash compared with ordinary Portland cement. The cassava peel ash was obtained by calcinations of cassava peel to 7000 c temperature. The sample was investigated using XRS-FP Analysis, for evaluating the concentration of each component such as SiO2, Al2O3, Fe2O3, CaO, MgO, SO3, K2O Na2O, LoI, the phase composition, mechanical and durability properties evolution. From this review is obvious that significant analytical techniques have been successfully carried out and a significant concentration of 81.14% was obtained. These analyses have shown that natural pozzolan based geopolymer has potential to be used as sustainable building materials. It was discovered that the cassava peel ash contains all the main chemical constituents of cement though in lower percentage compared with OPC which shows that it can serve as a suitable replacement if the right percentage is used. However, its durability and sulphuric acid resistance improved considerably at greater replacement of cement with cassava peel ash. The study recommends that concrete made with cassava peel ash can be used for light construction works where high strength is not major requirement but where durability is a major concern.Item OPTIMIZATION OF COMPRESSIVE STRENGTH OF PERIWINKLE SHELL CONCRETE USING SCHEFFE’S MODEL(3RD INTERNATIONAL CIVIL ENGINEERING CONFERENCE, 2025-02-28) Ibrahim A; Abbas., B.A; YUSUF, AbdulazeezThis study investigates the application of scheffe’s model in compressive strength optimization of periwinkle shell-coarse aggregate (PSCA) concrete. Physical properties of the aggregates such as specific gravity, bulk density, sieve analysis and workability of concrete were determined. Specific gravities of fine and coarse aggregates were 2.62 and 2.68 respectively, Moisture content for aggregate for fine and coarse aggregate were 7.08 and 3.03 respectively. The bulk densities were 1612.82kg/m3 and 1394.64kg/m3 respectively. From the sieve analysis test, the sand belonged to zone 2 and well graded with coefficient of gradation of 1.04. Ninety 150mm x150mm x 150mm cube specimens were produced for the compressive strength test. Model was fitted to data obtained on the compressive strength and mathematical model was developed based on Scheffe’s model. The formulated model was tested for adequacy at 95% level of confidence using t-statistic. The compressive strength of concrete was observed to decrease with increase in the percentage replacement of periwinkle shells (PS). The reduced value of the compressive strength may be due to lower specific gravity, water absorption capacity value of periwinkle shell compared to that of crushed granite. The blending of the two materials caused a reduction in strength value of the end product since specific gravity is strength related. The reduced compressive strength value may also be due to the fact that periwinkle shell has fewer binding properties compared to crushed granite. After 28 days of water curing, the concrete gave an average optimum compressive strength value of 25.78N/mm2 corresponding to a mix proportion of 1, 0.1, 1, 1.9 (cement, periwinkle shell, sand, granite) at a water-cement ratio of 0.4. This compressive strength value obtained at 5% replacement is within the recommended value required for plain concrete works, lean concrete, simple foundations, masonry walls and other simple construction works in low- cost housing constructionsItem Development of Models for Prediction of Soil Cohesion Using Machine Learning Algorithms(Department of Civil Engineering, FUT Minna, 2024-12-12) Muhammed, R. O.,; Adejumo, T. E.; Alhaji, M. M.; Kolo, D. N.; Eze, F. E.Accurate prediction of soil cohesion is crucial for the safe and economical design of geotechnical structures. This study employed five machine learning models—Artificial Neural Network (ANN), Random Forest (RF), Support Vector Regression (SVR), Gradient Boosting (GB), and Decision Tree (DT)—to predict cohesion (c) using a laboratory dataset of 233 samples. The dataset, augmented to 5000 samples using Getel, was split into 70% training and 30% testing sets. Model performance was evaluated using R-squared and Mean Squared Error (MSE). Results showed that Random Forest outperformed other models, achieving the highest R-squared score of 0.622 and the lowest MSE of 56.74, indicating excellent model fit and high predictive accuracy. Feature importance analysis revealed that plasticity, primarily influenced by Liquid Limit (LL) with an importance score of 0.879606, and Plasticity Index (PI) with an importance score of 1.441646, significantly impacts cohesion. Natural Moisture Content (NMC) also showed significant influence with a score of 0.670434. Particle Size Distribution and Specific Gravity (Gs) also contributed to the predictions. This study demonstrates the potential of machine learning models to enhance the accuracy and efficiency of soil characterization and geotechnical engineering design in predicting soil cohesion.Item Artificial Intelligence and Structural Reliability Analysis in Nigeria: A Review(Department of Civil Engineering, FUT Minna, 2024-12-12) Olorunpomi, M. D; Kolo, D. N.; Abdullahi, A.; Agbese, E. O.Reliability is a probabilistic measure of structural safety. In Structural Reliability Analysis (SRA), both loads and resistances are modelled as probabilistic variables, and the failure of structure occurs when the total applied load is larger than the total resistance of the structure. This review presents the recent advances in using Artificial Intelligence (AI) in SRA; it explores the application of Artificial Intelligence (AI) in assessing the structural reliability of structures, particularly focusing on the integration of machine learning models, predictive analytics, and data-driven approaches. AI-based tools can enhance accuracy, speed, and efficiency in structural assessments, offering a potential solution to Nigeria's infrastructure challenges. Machine learning-based techniques have been introduced to SRA problems to deal with its huge computational cost and increase accuracy. ANNs and SVMs are two popularly used tools in the ML-based SRA literature. They have been widely used for the SRA because of their adaptability to different well-known reliability calculation methods such as MCS, FORM, and SORM. While these technologies have been successfully implemented in other parts of the world, its application in Nigeria faces challenges related to data availability, infrastructure, and expertise. Nonetheless, with the increasing adoption of digital technologies in Nigeria’s construction industry, AI offers a compelling opportunity for improving the safety and sustainability of concrete structures.Item Modal Analysis of Barikin Saleh Bridge Deck Using Finite Element Software Simulation Method(Department of Civil Engineering, FUT Minna, 2024-12-12) Rasaq, O. O.; Yusuf, A.; Kolo, D. N.; Abdulrahman, H. S.The increase in traffic along Barikin Saleh area of Minna Niger State calls for the analysis of the bridge deck due to the increasing and fluctuating traffic volume. In this paper, the modal analysis of the Barikin Saleh bridge deck based on finite element software simulation method was studied. The simulation was carried out to determine natural frequencies and the corresponding mode shapes of the bridge deck using ANSYS workbench software. The parameters of the bridge used in the simulation were Length,16m; Width, 10.75m; Second moment of inertia I, 4.16m4; Area A, .56m2; Young’s modulus E, 35300MPa; Density p, 2600 kg/m3, and Concrete Grade G, 50MPa. Based on the simulation output, the bridge exhibited six (6) clear mode shapes and corresponding natural frequencies of 0.299Hz,20.436Hz, 22.875Hz, 25.087Hz, 30.003Hz, and 35.205Hz. The highest natural frequency for the bridge was 35.205Hz, at the bridge deck mid-span. The implication of this is that the lifespan of the bridge might be reduced due to fatigue damage that can occur as a result of repeated loading and unloading of the bridge deck at this frequency. The findings from this study provide valuable insights into the dynamic behavior of Barikin Saleh bridge deck, which can be useful for its maintenance, repair and retrofitting.