DEPARTMENT OF CIVIL ENGINEERING

The aim of this project is assess bamboo as an alternative to steel reinforcement in concrete structures which offers similar performance as steel reinforced concrete which can be used in areas where bamboo is abundant. Three samples each of dimension 500×100×100mm of plain, bamboo and steel reinforced concrete beam of seven, fourteen and twenty-one days after curing were subjected to a flexural test to measure their flexural strength. This test was conducted with a four point load flexural machine, with load applied on the beams to determine the ability of the beam to withstand bending forces. The beam samples were weighed before and after curing to obtain their weight gain and water absorption rate. The average flexural strength obtained from the plain, bamboo and steel reinforced beams of a period of seven days, fourteen days and twenty-one days was recorded. The result showed that for a period of seven days, the plain, bamboo and reinforced steel beam had a flexural strength of 9 N/mm², 16.67 N/mm² and 25 N/mm². Fourteen days 15N/mm², 23.33N/mm² and32.33N/mm². Twenty-one days 19N/mm², 29.67N/mm² and38.33N/mm². For water absorption the percentage is consistently higher compared to the plain and steel beam at each time interval. At seven days the water absorption was at 1.55%, and it increases further at fourteen days at 1.79% and twenty-one days 1.62%. based on the acquired results bamboo reinforced concrete can be suitable for structures such as farm sheds, rural housing and low-rise residential building for element such as walls.

Highway accidents are a significant concern worldwide, leading to substantial loss of life, property, and economic productivity. This study aims to conduct a comprehensive analysis of highway accidents by investigating their frequency, underlying causes, and exploring effective preventive measures. Through an extensive review of historical accident data, this research will assess key factors contributing to highway accidents, including human behavior, vehicle conditions, environmental influences, and road infrastructure. Special attention will be given to identifying accident-prone areas (blackspots) and determining the most common types of accidents, as well as the timeframes in which they frequently occur. To better understand the root causes of these accidents, the study will employ statistical analysis and machine learning techniques on data sourced from government databases and highway safety reports. The study will focus on critical factors such as driver error, vehicle malfunctions, poor road design, adverse weather conditions, and inadequate traffic management systems. It will also analyze the effectiveness of existing safety measures like traffic signals, road signage, and speed limits, while proposing new, data-driven interventions for improving highway safety. The expected results of this research include a clearer identification of high-risk areas and times for highway accidents, as well as the discovery of key accident causative factors. Based on these findings, the study will propose targeted solutions, such as enhancing road infrastructure, increasing public awareness campaigns on safe driving, implementing stricter vehicle inspection protocols, and adopting advanced traffic monitoring systems. Ultimately, the results are expected to provide actionable insights for policymakers and highway authorities to reduce accident rates and improve overall road safety.

Open drain channels play a vital role in stormwater management and flood prevention in urban and agricultural environments. However, factors such as complex channel geometry, surface roughness, sediment accumulation, and turbulence often reduce their efficiency, leading to flooding and waterlogging. This study aimed to analyze fluid flow in an open drainage channel using Computational Fluid Dynamics (CFD) to understand flow behavior, identify hydraulic inefficiencies, and recommend design improvements for enhanced drainage performance. The study focused on an open drainage channel within the University of Benin, Ugbowo Campus, Benin City, Nigeria. Data on channel dimensions, flow conditions, and physical characteristics were obtained through site investigations and measurements. A three-dimensional model of the channel was developed and simulated using CFD techniques in SolidWorks Flow Simulation. The governing equations of fluid flow, including the continuity and Navier-Stokes equations, were solved under appropriate boundary conditions to evaluate velocity distribution and free- surface flow characteristics. The simulation results showed that flow velocity increased gradually along the channel length, with the highest velocities occurring near the outlet region. The free surface remained stable throughout the simulation, indicating efficient water conveyance under the specified flow conditions. The study concluded that CFD is an effective tool for predicting flow behavior and evaluating the hydraulic performance of open drainage systems. The findings provide valuable insights for improving drainage design, reducing flood risks, and promoting sustainable stormwater management.

This study assessed the levels of air and noise pollution generated by sawmill activities in selected locations within Benin City, Edo State, Nigeria. The investigation focused on key air quality parameters including particulate matter (PM₂.₅ and PM₁₀), ozone (O₃), formaldehyde (HCHO), total volatile organic compounds (TVOC), carbon dioxide (CO₂), as well as environmental noise levels. Measurements were carried out using calibrated portable air quality monitors and sound level meters across five major sawmill locations. The aim was to determine the extent of environmental pollution, evaluate compliance with recommended standards, and examine potential health risks to workers and nearby residents. Results revealed that PM₂.₅ concentrations ranged from 24 µg/m³ to 43 µg/m³, while PM₁₀ values ranged from 46 µg/m³ to 68.5 µg/m³ across the sampled locations. Noise levels varied between 68.35 dB(A) and 74.8 dB(A). Ozone concentrations ranged from 0.01 ppm to 0.08 ppm, while CO₂ levels were recorded between 408 ppm and 482 ppm. In several locations, particulate matter levels exceeded the World Health Organization (WHO) 24-hour guideline limits, indicating degraded air quality. Noise measurements in most sites were also above the recommended 55 dB(A) limit for residential environments, suggesting potential risks of long-term exposure. The findings confirm that sawmill operations significantly contribute to environmental pollution within the study area. Elevated concentrations of PM₂.₅ and PM₁₀ pose respiratory health risks, while persistent exposure to high noise levels may result in hearing impairment, stress, and reduced productivity. The study highlights the need for stricter enforcement of environmental regulations, installation of dust control systems, proper zoning of industrial activities, and routine environmental monitoring. Implementing these measures will improve occupational safety and protect the health of surrounding communities.

Flooding remains one of the most pressing environmental challenges in the Niger Delta region of Nigeria, where rapid urbanization, land degradation, and climate variability interact to intensify hydrological extremes. This study evaluates the combined impact of land use/land cover (LULC) changes and climate variability on flooding in the Lower Niger Region, focusing on Edo, Delta, Bayelsa, and Rivers States. An integrated methodological framework was developed using remote sensing (RS) and machine learning (ML) techniques implemented on the Google Earth Engine (GEE) platform. Rainfall and temperature datasets were obtained from multiple satellite products, CHIRPS, PERSIANN-CDR, PERSIANN-CCS, ERA5, and CPC, and validated against observations from the Nigerian Meteorological Agency (NiMET). LULC classification was conducted using Random Forest (RF) and Support Vector Machine (SVM) algorithms applied to Sentinel-2 and Landsat-8 imagery, generating five major land cover classes: water bodies, forest, barren land, vegetation, and built-up areas. Flood dynamics were assessed using multiple spectral indices, including AWEI, FWI, NDWI, MNDWI, WRI, and NDVI, evaluated across different temporal scales to capture hydrological variations. The results reveal significant interannual and seasonal rainfall variability, with the Standardized Precipitation Index (SPI) effectively identifying alternating wet and dry cycles, although long-term annual rainfall trends were largely non-significant. There is, however, evidence of increasing frequency of extreme rainfall events, particularly in Delta and Rivers States. Temperature analysis (1971–2023) indicates a statistically significant warming trend, with minimum temperatures rising faster than maximum temperatures—most notably during the dry season (DJF). LULC assessment confirmed the superior performance of the RF classifier over SVM and showed a consistent pattern of urban expansion at the expense of vegetation and wetlands. Flood analysis revealed a persistent hotspot occurring along river corridors, low-lying floodplains, and southeastern basins. Overall, the findings demonstrate that while climate variability influences hydrological extremes, LULC transformations, particularly urban encroachment into natural flood buffers, have been a more decisive factor driving flood vulnerability in the Lower Niger Region.

This study, the effect of groundwater table on the bearing capacity of shallow foundation, aimed to evaluate how varying groundwater table levels affect the bearing capacity of
soil through an analytical method using Terzaghi’s equation for foundation bearing capacity. Soil samples were collected using manual hand auger at a depth of 2m from a site in Oleh, Delta state where the groundwater table was close to the surface. The soil samples were then taken to the University of Benin, Civil Engineering Laboratory where the specific gravity, compaction, sieve analysis, atterberg and triaxial shear tests were carried out, in order to find the physical and strength properties of the soil. The liquid limit of the samples showed a range from 20.0-19.5%, the plastic limit, a range from 12.5-13.0% and a plastic index, from 7.5-6.5%. The samples had MDD ranging from 1.95 − 1.91�/𝑐3, OMC ranging from 9.5-7.8%. The sample showed Ф values to range from 32-30ͦ and C values to range from 15-12kPa. The study showed that high groundwater table significantly reduces soil bearing capacity. The control sample (normal water table) exhibited superior performance across all parameters (such as 1122kpa bearing capacity which showed a drop to 951 in the 2m depth). High water table conditions led to a reduction in allowable bearing capacity, with the most severe impact observed at 2m depth. These findings emphasize the importance of proper site investigations and making informed construction decisions

Urbanization and population growth are two of the most significant drivers of waste generation globally. As people continue to move into cities and urban centers expand, the amount of municipal solid waste (MSW) being produced increases drastically. This waste includes everything from household garbage and food scraps to plastics, paper, textiles, and packaging materials. In many developing countries, waste management remains a critical challenge, as infrastructure development and policy implementation have not kept pace with the rate of waste production. As a result, open dumping, burning, and poorly managed landfills are still commonly used as disposal methods.

Air pollution arising from increasing vehicular activities has become a growing environmental concern in urban environments, including university campuses. Vehicular emissions contribute significantly to the release of particulate matter and gaseous pollutants, which may adversely affect human health and environmental quality. This study aimed to evaluate the spatial distribution of selected air pollutants around major car parks within the University of Benin (UNIBEN), Ugbowo Campus, using Geographic Information System (GIS) techniques. A field-based experimental research design was employed. Air quality data for particulate matter (PM₂.₅ and PM₁₀) and gaseous pollutants, including formaldehyde (HCHO), total volatile organic compounds (TVOCs), and carbon dioxide (CO₂), were collected from seven selected car parks using portable air quality monitoring devices. Geographic coordinates of sampling locations were obtained using GPS devices and integrated into a GIS environment for spatial analysis. Spatial interpolation using the Inverse Distance Weighting (IDW) method was applied to generate pollution distribution maps, while descriptive statistical analyses and comparisons with World Health Organization (WHO) air quality standards were performed. Results revealed spatial variations in pollutant concentrations across the study area. The Back Gate Car Park recorded the highest concentrations of PM₂.₅ (49 µg/m³) and PM₁₀ (55 µg/m³), while the Medical Complex and Hall 2 car parks exhibited comparatively lower concentrations. PM₂.₅ concentrations exceeded the WHO guideline value (15 µg/m³) at all sampling locations, whereas PM₁₀ slightly exceeded the guideline limit vi only at selected locations. Concentrations of HCHO, TVOCs, and CO₂ remained within acceptable limits. GIS analysis identified high-traffic areas as pollution hotspots, indicating that vehicular activities significantly influence air quality within the campus environment. The study therefore recommends improved traffic management, enforcement of no-idling policies, and increased vegetation cover to mitigate air pollution exposure on campus.

Fine aggregates used in concreting works posses different properties, thus affecting concrete quality and durability.. However, it was observed from previous literatures that these properties variation could adversely affect the performance of freshly mixed and hardened concrete, in terms of workability and strength. The aim of this study was to access the properties of fine aggregates sold at different locations in the Benin city by investigating their performance on concrete in both the fresh and hardened state. Concreting materials were procured from four different locations in Edo state namely; Okwae, Okun, Idugbo and Ovia areas of Edo state. Samples are to be labelled according to their locations. Experimental investigations were carried out to approved standards to produce fresh and hardened concrete. Slump and compressive tests was performed on all samples from the four different vendors at the end of 7, 14 and 28days respectively. Concrete prepared with constituents from the Okwae area, yielded favorable slump of 60.82mm and compressive strength of 13.72N/mm2 , thus proving its application in lightweight concreting works. However, concreting constituents from the Ovia area yielded slump value of 71mm and compressive strength of 11.92N/mm2 , proving its viability for use in plain concreting where strength is not the prevailing requirement. Concreting constituents from Idugbo and Okun yielded unfavorable values. The variations in the properties of concrete for all four vendors has no adverse effects on mix design calculations, only if the concrete would be used in light weight application. To ensure safety and economy in reinforced concrete construction, adequate quality control measures should be applied