FACULTY OF ENGINEERING

The discharge of untreated textile wastewater containing synthetic dyes poses significant environmental and public health risks due to its toxicity and resistance to conventional degradation processes. This research explores a sustainable and cost-effective solution by developing and evaluating a novel activated carbon (AC) adsorbent derived from a blend of two abundant agricultural wastes: Palm Kernel Shell (PKS) and Coconut Shell (CS).This study aimed to treat synthetic wastewater contaminated with Methyl Red dye. The PKS and CS were individually carbonized and chemically activated using potassium hydroxide (KOH). The resulting activated carbons were blended in a 1:1 ratio to create a composite adsorbent (PKS-CS AC). The adsorbent was extensively characterized using Brunauer-Emmett-Teller (BET) analysis, which revealed a specific surface area of 275.762 m²/g and a well-developed microporous and mesoporous structure, complemented by Fourier-Transform Infrared Spectroscopy (FTIR) that identified key functional groups (O-H, C=O, C-O) crucial for adsorption.A series of batch adsorption experiments were conducted, and the process was optimized using Response Surface Methodology (RSM) based on a Central Composite Design (CCD). The influence of critical operational parameters—adsorbent dosage (PKS-AC and CS-AC), contact time, and initial dye concentration—on Methyl Red removal efficiency was investigated. The ANOVA of the quadratic model confirmed its high significance, with an R² value of 0.9501, indicating the model accurately represented the experimental data. The optimization results identified the optimal conditions as 1.65 g/L of CS-AC, 6.13 g/L of PKS-AC, a contact time of 70.75 minutes, and an initial dye concentration of 328.1 mg/L, achieving a predicted dye removal efficiency of 93.75%

Marine pollution represents a significant threat to global biodiversity and sustainable development. The introduction of pollutants—ranging from discarded plastics to industrial chemicals and nutrient-rich agricultural runoff—disrupts fragile marine ecosystems, leading to habitat degradation, species endangerment, and the overall loss of biodiversity (Barnes & Hughes, 1999). This complex problem has been a subject of increasing concern since foundational environmental texts highlighted the pervasive nature of pollutants and their far-reaching consequences (Carson, 1962). The issue is not confined to a single source. Roughly 80% of all marine pollution originates from land-based activities, a finding corroborated by reports from the Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP) . A significant portion of this is plastic waste, with an estimated millions of metric tons entering the ocean annually (Jambeck et al., 2015). These pollutants undergo a journey from land to sea, often traveling through rivers and waterways, where they accumulate in coastal zones before dispersing into the open ocean

The analysis of hydraulic flow in looped pipe networks is a fundamental yet computationally intensive task in civil engineering, traditionally addressed using the Hardy Cross method. Manual application of this method, however, becomes increasingly time-consuming and error-prone as network complexity grows. This study aimed to develop and validate an efficient computational tool for automating the Hardy Cross method using the Python programming language. The primary objectives were to implement the iterative algorithm, model hydraulic networks via structured Excel input, and rigorously validate the program's accuracy against benchmark problems. The methodology involved designing a modular Python program that utilized the pandas and NumPy libraries for data handling and numerical computations. The implementation supported both the Darcy-Weisbach equation, with friction factors calculated via the Swamee-Jain formula, and the Hazen-Williams equation for head loss determination. Network data including pipe length, diameter, roughness, and initial flow rates were organized in an Excel workbook, with each worksheet representing a distinct loop. The core algorithm iteratively computed flow corrections (ΔQ) for each loop until convergence was achieved, dynamically handling missing parameters and common pipes shared between loops using a sparse matrix approach.

This study investigates the properties of limestone calcined clay cement (LC3) with a water/cement ratio of 0.5 and cement/sand ratio of 1:2.75 produced using clay sourced from Uzebba, Nigeria. The kaolinitic Uzebba clay was calcined at 600°C, 700°C and 800°C to activate it's pozzolanic properties. Mortar cubes were cast and cured in lime water and by air. A total of 120 mortar cubes were prepared for compressive strength testing and water absorption test. For compressive test, 9 cubes were mixed and cured in lime water and air serving as the control, 27 cubes were mixed for LC 3 calcined at 600°C, 700°C and 800°C for 30% and 40% replacement and cured in lime water and by air. Additionally, this study utilized other tests like sieve analysis of fine aggregate, standard consistency test, setting time of cement and bleeding tests. The average compressive strength for 30% and 40% mortar cubes cured in lime water ranged from 9.44N/mm2 - 17.12N/mm2 and 7.47N/mm2 - 12.16N/mm2 respectively, while for 30% cured in air ranged from 5.70N/mm2 - 15.91N/mm2 For water absorption test, 12 cubes were mixed and cured in lime water to determine the amount of water absorbed by the cubes for the control and replacement.

This study investigates the simulation of the actual maximum stress in Tungsten Inert Gas (TIG) weldment using SIMUFACT Welding software. The research aimed to compare the simulated stress values with experimental results obtained in a controlled environment under varying process parameters such as current, voltage, and gas flow rate. During the design of experiment, twenty experimental runs was generated by the Central composite design and it was used to carry out TIG welding on mild steel plates. A universal testing machine was used to record the actual maximumm stress on the welded joint and recorded as experimental values. The data generated from the CCD matrix was then feed into an expert system (SIMUFACT 2024) which was used to carry out TIG welding simulations with its corresponding actual maximum stress recorded alongside as the SIMUFACT result.
Results from this study revealed that that increasing welding current reduces the maximum stress due to higher heat input and lower cooling rate, while voltage variation influences arc width and stress distribution. The actual maximum stress values from both datasets were analyzed and compared. The results revealed close agreement between experimental and simulated values, a fitted line plot was used to ascertain the degree of correlation between both results and a correlation coefficient of 0.98 was observed, indicating a very strong positive correlation degree between the experimental result and the SIMUFACT result. A time series plot was then used to compare if both data sets assumed the same trend. The SIMUFACT welding simulation analysis proved to be a reliable tool for simulating and predicting the actual maximum stress in TIG-welded joints thereby aiding in the optimization of welding parameters for an improved structural integrity.

The purpose of this research is to have an affordable and clean energy supply in our household. Inadequate power supply in Nigeria has been a major challenge bedeviling our institutions. Some areas connected to the distribution companies (DISCOs) have what is referred to as a regimented load shedding where power supply may range from 6.00 to 12.00 hrs within 24 hrs. Homes and offices have resolved to sourcing for alternative power supply such as generator plants, solar PVs, inverters, etc. Thus, the 2.5KVA inverter system was proposed to serve as a backup once there is power outage from the DISCOs. An inverter system enables the conversion of direct current (DC) from batteries to alternating current (AC) needed to run the office appliances at a minimal cost and optimal efficiency. The project focuses on the design and construction of a pure sine wave 2.5KVA 50Hz inverter system to deliver 220V AC using 2 Nos 12V DC batteries (rated 200A) connected in series.

This project work titled "The effects of the partial replacement of fine aggregate in concrete with recycled metallic filings" aims to investigate the viability and impact of using Recycled metallic filings as a sustainable alternative to traditional fine aggregates in concrete mixtures. This project explores the use of recycled metallic filings as a partial replacement for fine aggregates in concrete production to address environmental and financial challenges. The study aims to examine the impacts of recycled metallic filings on compressive strength and durability, as well as the properties of concrete mixtures containing different percentages of metal scraps. Preliminary findings suggest that incorporating recycled metallic filings can improve concrete's compressive strength due to their unique physical properties and ability to act as granules for cement hydration. However, there are concerns about corrosion due to the presence of metals like iron in the filings, and the workability of concrete mixtures containing metallic filings can be affected. In conclusion, this project aims to explore the feasibility and potential benefits of partially replacing fine aggregates in concrete with recycled metallic filings, suggesting that this innovative approach can lead to improved compressive strength while addressing environmental and economic concerns.

This study explored the optimization of the microwave aided biodiesel production from neem oil with a bio-waste catalyst derived from cow bones and rice bran using central composite design, an experiment analysis on response surface model. The bio-waste catalyst was synthesized by the carbonization and sulphonation of rice bran to produce an acid precursor, while cow bones was calcined and treated with KOH to create the basic precursor. Both precursors were then impregnated using the wet-impregnation method. Also, a model was developed to simulate the process and examine the interactive effect of process input variables on neem oil biodiesel yield using the central composite approach. These inputs generated about 50 runs to be carried out with the catalyst using methanol under optimal conditions. In this study, we aimed to optimize biodiesel production from neem oil using a microwave- assisted process with a bifunctional heterogeneous catalyst synthesized from cow bones and rice bran. Oil characterization was carried out according to the ASTM standards, the catalyst failed to facilitate the transesterification reaction resulting in no biodiesel formation. Biodiesel production was carried out using sodium hydroxide which proved the viability of the oil and this outcome underscores the critical importance of proper catalyst synthesis and activation in biodiesel production. Additionally, the presence of impurities or moisture during catalyst preparation could have led to deactivation, further inhibiting the reaction. Fresh catalyst samples have been impregnated and are awaiting analysis results

In many institutions, business firms and organizations, the collection of attendance data is taken very seriously as the management at these organizations tend to dislike absenteeism, late coming and these organizations seem to sanction the individuals involved. These organizations also hope to encourage punctuality by rewarding people who are perpetually on time. Traditionally, the method of attendance taking used to be done manually using a physical register booklet. This method is prone to manipulation and impersonation. The attendance register could get damaged, stolen or lost. Therefore, several electronic techniques were developed to counter some notable flaws typical with the traditional method. These electronic techniques are not without flaws and drawbacks as well. This project implements a solution that makes use of an electronic technique (Biometric Fingerprint Recognition) for human identification as well as some other novel techniques to battle gaffes present in currently used technologies.

The oil and gas industry in the Niger Delta faces a significant challenge with heterogeneous datasets fragmented across multiple platforms and stored in diverse file formats, a situation that impedes efficient research and operational optimization. To address this problem, this study develops a Unified Field Model (UFM) designed to aggregate, harmonize, and standardize these varied petroleum engineering datasets, including well logs, seismic data, and production logs, using scalable cloud storage and data processing pipelines. The core of the research involves creating a durable and adaptable data structure capable of handling both structured and unstructured data while preserving relational attributes. This process is supported by rigorous data quality assurance techniques, such as feature engineering, anomaly detection, and petroleum engineering domain-specific imputation strategies. This UFM then serves as the foundation for a web-based data brokerage platform, known as Petroleum Engineering Research Datasets (PERD), which enables researchers and industry operators in the Niger Delta to efficiently access high-quality petroleum datasets. This study provides a foundational improvement for the sector, enhancing operational efficiency, improving data interoperability, and allowing for the better use of computational tools to tackle complex Petroleum engineering challenges, thereby improving study reproducibility and performance in the region.