Pub Date : 2023-12-01DOI: 10.9734/jerr/2023/v25i111029
Shilei Qian
The use of coal gangue as coarse aggregate alleviates the dependence of concrete on natural aggregates and improves the utilization rate of coal gangue resources. The direct use of coal gangue coarse aggregate in the preparation of concrete limits the scope of its use due to the deterioration of its performance. Therefore, the improvement of the performance of coal gangue coarse aggregate concrete should become a research focus. This article briefly describes the basic characteristics that coal gangue coarse aggregate should have and the shortcomings of existing research. It summarizes the existing methods for improving the performance of coal gangue coarse aggregate concrete. After pre wetting treatment, calcination, slurry coating, and material adjustment, the performance of coal gangue coarse aggregate concrete is improved. Multiple methods of collaborative treatment can improve the comprehensive performance of coal gangue coarse aggregate concrete, to provide some reference for achieving efficient utilization of coal gangue.
{"title":"A Review Study on Performance Improvement of Coal Gangue as Coarse Aggregate in Concrete","authors":"Shilei Qian","doi":"10.9734/jerr/2023/v25i111029","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111029","url":null,"abstract":"The use of coal gangue as coarse aggregate alleviates the dependence of concrete on natural aggregates and improves the utilization rate of coal gangue resources. The direct use of coal gangue coarse aggregate in the preparation of concrete limits the scope of its use due to the deterioration of its performance. Therefore, the improvement of the performance of coal gangue coarse aggregate concrete should become a research focus. This article briefly describes the basic characteristics that coal gangue coarse aggregate should have and the shortcomings of existing research. It summarizes the existing methods for improving the performance of coal gangue coarse aggregate concrete. After pre wetting treatment, calcination, slurry coating, and material adjustment, the performance of coal gangue coarse aggregate concrete is improved. Multiple methods of collaborative treatment can improve the comprehensive performance of coal gangue coarse aggregate concrete, to provide some reference for achieving efficient utilization of coal gangue.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"121 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138608311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-28DOI: 10.9734/jerr/2023/v25i111028
Qiang Wang
Subgrade defects classification is one of the important means for highway management and maintenance departments to prevent and reduce disaster, and it is also the basis for using engineering analogy methods to prevent subgrade defects. For this reason, firstly, subgrade defects are divided into slope defects and subgrade subsidence defects according to the definition. and the existing subgrade defects classification methods are divided into single-factor index classification method and multi-factor index classification method, and through comparison, it is concluded that the multi-factor index classification method is better. Finally, the prevention and control measures of the existing subgrade defects are summarized from three aspects: optimization design, foundation reinforcement and improvement of drainage facilities. This will provide reference and ideas for the classification and prevention of subgrade defects.
{"title":"Review of Classification and Prevention of Subgrade Defects","authors":"Qiang Wang","doi":"10.9734/jerr/2023/v25i111028","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111028","url":null,"abstract":"Subgrade defects classification is one of the important means for highway management and maintenance departments to prevent and reduce disaster, and it is also the basis for using engineering analogy methods to prevent subgrade defects. For this reason, firstly, subgrade defects are divided into slope defects and subgrade subsidence defects according to the definition. and the existing subgrade defects classification methods are divided into single-factor index classification method and multi-factor index classification method, and through comparison, it is concluded that the multi-factor index classification method is better. Finally, the prevention and control measures of the existing subgrade defects are summarized from three aspects: optimization design, foundation reinforcement and improvement of drainage facilities. This will provide reference and ideas for the classification and prevention of subgrade defects.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139226941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-27DOI: 10.9734/jerr/2023/v25i111026
Akaolisa Chukwuebuka C., Iweriolor Sunday, Uzochukwukanma M. C., Ezeliora C. D., Umeh Maryrose N.
The study focused on the evaluation and prediction of a production yield in Finoplastika plastic manufacturing industry. The study investigates the need of prediction and continuous improvement of production plastic yield in manufacturing industries. The literature reveals the related research works in manufacturing industries and found a gap in application of predictive tools to appraise the plastic production yield in the case company. The use of artificial neural network serves as the method of data analysis applied to achieve the aim of this study. The application of artificial neural network for the predicted solutions of the response variables of 110mm waste plastic pipe, 20mm pressure plastic pipe, 50mm waste plastic pipe and 32mm pressure plastic pipe are 31149, 45171, 13412, and 12891 respectively. The results for predicted solutions are recommended to the case company and other plastic companies for their wider use and applicability in other to achieve their optimal results and to support decision making during, inventory system, production process, production planning and control.
{"title":"Evaluation and Prediction of Production Yields in Plastic Manufacturing Industry Using Artificial Neural Network","authors":"Akaolisa Chukwuebuka C., Iweriolor Sunday, Uzochukwukanma M. C., Ezeliora C. D., Umeh Maryrose N.","doi":"10.9734/jerr/2023/v25i111026","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111026","url":null,"abstract":"The study focused on the evaluation and prediction of a production yield in Finoplastika plastic manufacturing industry. The study investigates the need of prediction and continuous improvement of production plastic yield in manufacturing industries. The literature reveals the related research works in manufacturing industries and found a gap in application of predictive tools to appraise the plastic production yield in the case company. The use of artificial neural network serves as the method of data analysis applied to achieve the aim of this study. The application of artificial neural network for the predicted solutions of the response variables of 110mm waste plastic pipe, 20mm pressure plastic pipe, 50mm waste plastic pipe and 32mm pressure plastic pipe are 31149, 45171, 13412, and 12891 respectively. The results for predicted solutions are recommended to the case company and other plastic companies for their wider use and applicability in other to achieve their optimal results and to support decision making during, inventory system, production process, production planning and control.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139230011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-27DOI: 10.9734/jerr/2023/v25i111027
Uwandu I. G., Ejikeme J. O., Chukwu F. N.
In recent times, communities along the Otamiri River Basin in Imo State have been grappling with flooding issues, especially during the rainy season. This occurs despite the presence of underground drainage systems. The primary concern is heavy rainfall causing the river to overflow and lead to flooding. Hence the study aimed at identifying the flood-prone areas in the Otamiri River Basin in Owerri, Imo State. The objectives are to establish factors for evaluating flood vulnerability within the study area; to classify and standardize the factors according to levels of vulnerability; to determine the reliability of the classified factors; and to produce a flood vulnerability map showing vulnerable areas in the study area. The methodology involved collecting Shuttle Radar Topography Mission and Sentinel 2A imagery of July 2022, and processing the data with ArcGIS and QGIS software to determine the topography and vulnerability areas through geo-referencing and classification. The Analytical Hierarchy Process (AHP) model was employed to identify high flood risk areas, considering factors like drainage density, slope, soil type, precipitation, population density, Euclidean distance, and land use. The study's results categorized vulnerability into five levels: Very Low (0.09% of Owerri, minimal risk), Low (12.93% with lower risk), Moderate (68.83% facing substantial risk), High (18.18% with significant risk), and Very High (0.03% posing extreme risk). These findings are recommended as foundational data for future flood studies in the region.
{"title":"GIS-Based Analytical Hierarchy Process Modeling for Flood Vulnerability Assessment of Communities Along Otamiri River Basin Imo State, Nigeria","authors":"Uwandu I. G., Ejikeme J. O., Chukwu F. N.","doi":"10.9734/jerr/2023/v25i111027","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111027","url":null,"abstract":"In recent times, communities along the Otamiri River Basin in Imo State have been grappling with flooding issues, especially during the rainy season. This occurs despite the presence of underground drainage systems. The primary concern is heavy rainfall causing the river to overflow and lead to flooding. Hence the study aimed at identifying the flood-prone areas in the Otamiri River Basin in Owerri, Imo State. The objectives are to establish factors for evaluating flood vulnerability within the study area; to classify and standardize the factors according to levels of vulnerability; to determine the reliability of the classified factors; and to produce a flood vulnerability map showing vulnerable areas in the study area. The methodology involved collecting Shuttle Radar Topography Mission and Sentinel 2A imagery of July 2022, and processing the data with ArcGIS and QGIS software to determine the topography and vulnerability areas through geo-referencing and classification. The Analytical Hierarchy Process (AHP) model was employed to identify high flood risk areas, considering factors like drainage density, slope, soil type, precipitation, population density, Euclidean distance, and land use. The study's results categorized vulnerability into five levels: Very Low (0.09% of Owerri, minimal risk), Low (12.93% with lower risk), Moderate (68.83% facing substantial risk), High (18.18% with significant risk), and Very High (0.03% posing extreme risk). These findings are recommended as foundational data for future flood studies in the region.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139228761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-25DOI: 10.9734/jerr/2023/v25i111023
N. Tayisepi, Rindai Svosve, Godfrey Tigere, Albert Nkulumo Mnkandla, Innocent Mapindu
The rapid increase in electricity demand has resulted in the nation and state governments enforcing and implementing various forms of energy conservation conversations as well as seeking alternative energy sources in order to meet demand of the production sector. Manufacturing Industries of wood materials, in modern day trends, are principally focused on the achievement of highest quality products and quality planed surface generation at minimum input factor of resources such as machining energy. In wood artifacts manufacturing practice, the appropriateness of the cost-quality-time matrix normally depend on supreme selection of cutting parameters for the operation. Machining response factors, such as generation of smooth wood surface roughness is a vital metric of the product quality, granted it significantly influence the performance of machined wood parts, affects how the machined component will interact with the environment as well as impacting on the artifact production costs. Energy use optimisation, in order to continue and enhance competitiveness in business operations, is a prime priority concern for the modern day wood machining manufacturing industry. The challenges of ever increasing energy prices, against mounting demand for more energy demanding machinery, increasing pressure from environmentalists and increasing nation state legislation, for reduced energy generation prompted environmental pollution, mean that manufacturers are expected to pay more money and attention towards energy use reduction. Thus, it is imperative, during machining process planning of wood materials, to determine the optimum cutting parameters combination which fosters easy and economical machining which simultaneously deliver good surface quality at reduced energy consumption. This Taguchi design of experiment study analysed and comparatively optimised the cutting parameters of three wood species in order to realise consistent surface quality at minimum energy use during the planing machining of Pine, Saligna and Teak materials. Analysis of variance showed the dominant factors influencing the respective response parameters whilst the optimum cutting conditions were established with the aid of the main effects plot of the signal to noise ratio.
{"title":"Comparative Optimisation of the Cutting Parameters for Surface Quality and Energy Efficiency during the Machining Manufacturing of Teak, Saligna and Pine Wood Materials","authors":"N. Tayisepi, Rindai Svosve, Godfrey Tigere, Albert Nkulumo Mnkandla, Innocent Mapindu","doi":"10.9734/jerr/2023/v25i111023","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111023","url":null,"abstract":"The rapid increase in electricity demand has resulted in the nation and state governments enforcing and implementing various forms of energy conservation conversations as well as seeking alternative energy sources in order to meet demand of the production sector. Manufacturing Industries of wood materials, in modern day trends, are principally focused on the achievement of highest quality products and quality planed surface generation at minimum input factor of resources such as machining energy. In wood artifacts manufacturing practice, the appropriateness of the cost-quality-time matrix normally depend on supreme selection of cutting parameters for the operation. Machining response factors, such as generation of smooth wood surface roughness is a vital metric of the product quality, granted it significantly influence the performance of machined wood parts, affects how the machined component will interact with the environment as well as impacting on the artifact production costs. Energy use optimisation, in order to continue and enhance competitiveness in business operations, is a prime priority concern for the modern day wood machining manufacturing industry. The challenges of ever increasing energy prices, against mounting demand for more energy demanding machinery, increasing pressure from environmentalists and increasing nation state legislation, for reduced energy generation prompted environmental pollution, mean that manufacturers are expected to pay more money and attention towards energy use reduction. Thus, it is imperative, during machining process planning of wood materials, to determine the optimum cutting parameters combination which fosters easy and economical machining which simultaneously deliver good surface quality at reduced energy consumption. This Taguchi design of experiment study analysed and comparatively optimised the cutting parameters of three wood species in order to realise consistent surface quality at minimum energy use during the planing machining of Pine, Saligna and Teak materials. Analysis of variance showed the dominant factors influencing the respective response parameters whilst the optimum cutting conditions were established with the aid of the main effects plot of the signal to noise ratio.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"177 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139236412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-25DOI: 10.9734/jerr/2023/v25i111024
Olojede O. A., Igbokwe, J. I., Oliha, A. O., Ojanikele, W. A.
Continuous Geospatial studies of the transitions in Landuse and landcover are very important especially as it relates to baseline assessment as an approach for advising in policy formulations concerning the natural resources sector. This study aimed at mapping and modeling the urban landscape of Osogbo metropolis, Osun state Nigeria, using an artificial neural network with the view of providing a framework for sustainable development and as well as generating data on Landuse and landcover change transitions and maps for planning purposes. Its objectives are to; model and analyze Landuse and landcover changes in Osogbo metropolis for the last 30 years (1990 – 2020) using an artificial neural network; ascertain the trend, and characteristics of Landuse and landcover changes in Osogbo metropolis in the last 30 years; assess the urban landscape change across various terrain configurations with Osogbo Metropolis over the last 30 years, and predict the future urban landscape of Osogbo Metropolis in 2040 using artificial neural network. The methodology involved data acquisition of Landsat, Sentinel-2, and ALOS Palsar images, image preprocessing to correct the scan line error in Landsat 7 ETM+, development of classification scheme, identification of class features and image classification, trend analysis, land cover/land use transition, and prediction to 2040. The assessment of landcover/landuse change revealed significant LULC changes in the studied area. Over 30 years (1990–2020), the built-up area classes increased significantly by 111.97 km2, while vegetation, open space, and water body decreased by 189.33 km2, 7.26 km2, and 3.46 km2 respectively. In terms of increased built-up area, this is largely seen in flat and undulating terrains between 281m and 341m. According to the prediction, by 2040, built up area is expected to grow from 35.89 % to 64.48 % covering an area of 201.2 km2, water body is expected to decrease from 1.11 % to 1.07 % with an area of 3.33 km2, vegetation is expected to decrease from 60.68 % to 32.42 % with an area of 101.15 km2, open space is expected to decrease from 2.33 % to 2.03 % to an area of 6.34 km2. The study´s annual rate of change results is recommended as it reveals the annual decline vegetation within the study area, as a direct consequence can lead to an increase in urban heat islands within the study area.
{"title":"Mapping and Modelling of Urban Landscape of Osogbo Metropolis, Osun State Nigeria, Using Artificial Neural Network","authors":"Olojede O. A., Igbokwe, J. I., Oliha, A. O., Ojanikele, W. A.","doi":"10.9734/jerr/2023/v25i111024","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111024","url":null,"abstract":"Continuous Geospatial studies of the transitions in Landuse and landcover are very important especially as it relates to baseline assessment as an approach for advising in policy formulations concerning the natural resources sector. This study aimed at mapping and modeling the urban landscape of Osogbo metropolis, Osun state Nigeria, using an artificial neural network with the view of providing a framework for sustainable development and as well as generating data on Landuse and landcover change transitions and maps for planning purposes. Its objectives are to; model and analyze Landuse and landcover changes in Osogbo metropolis for the last 30 years (1990 – 2020) using an artificial neural network; ascertain the trend, and characteristics of Landuse and landcover changes in Osogbo metropolis in the last 30 years; assess the urban landscape change across various terrain configurations with Osogbo Metropolis over the last 30 years, and predict the future urban landscape of Osogbo Metropolis in 2040 using artificial neural network. The methodology involved data acquisition of Landsat, Sentinel-2, and ALOS Palsar images, image preprocessing to correct the scan line error in Landsat 7 ETM+, development of classification scheme, identification of class features and image classification, trend analysis, land cover/land use transition, and prediction to 2040. The assessment of landcover/landuse change revealed significant LULC changes in the studied area. Over 30 years (1990–2020), the built-up area classes increased significantly by 111.97 km2, while vegetation, open space, and water body decreased by 189.33 km2, 7.26 km2, and 3.46 km2 respectively. In terms of increased built-up area, this is largely seen in flat and undulating terrains between 281m and 341m. According to the prediction, by 2040, built up area is expected to grow from 35.89 % to 64.48 % covering an area of 201.2 km2, water body is expected to decrease from 1.11 % to 1.07 % with an area of 3.33 km2, vegetation is expected to decrease from 60.68 % to 32.42 % with an area of 101.15 km2, open space is expected to decrease from 2.33 % to 2.03 % to an area of 6.34 km2. The study´s annual rate of change results is recommended as it reveals the annual decline vegetation within the study area, as a direct consequence can lead to an increase in urban heat islands within the study area.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"120 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139236437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-25DOI: 10.9734/jerr/2023/v25i111025
Okoye Akachukwu Hyacienth, Ainah P. Kenneth, Ibe Anthony Ogbonnaya
In recent times, there has been a notable increase in attention towards the reduction of greenhouse gas emissions and the enhancement of energy security. Over the past decade, there has been a significant increase in the incorporation of intermittent renewable energy sources (RESs), such as photovoltaic (PV) and wind energy, into the existing power system. However, the integration of this system hinders the reliable and steady running of the grid due to many operational and control challenges. Several challenges exist, including generation uncertainty, voltage and angular stability, power quality issues, reactive power support, and fault ride-through capabilities. The electricity produced by renewable energy sources (RESs) exhibits fluctuations due to meteorological phenomena beyond human control, such as wind speed and sunlight intensity. Energy storage systems (ESSs) play a crucial role in mitigating volatility by effectively storing excess electricity generated and facilitating its availability when needed. This study utilises the MATLAB/Simulink programme to develop an optimised configuration model for the wind hybrid power storage system.
{"title":"Modeling and Simulation of Energy Storage Performance of Renewable Energy Storage System","authors":"Okoye Akachukwu Hyacienth, Ainah P. Kenneth, Ibe Anthony Ogbonnaya","doi":"10.9734/jerr/2023/v25i111025","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111025","url":null,"abstract":"In recent times, there has been a notable increase in attention towards the reduction of greenhouse gas emissions and the enhancement of energy security. Over the past decade, there has been a significant increase in the incorporation of intermittent renewable energy sources (RESs), such as photovoltaic (PV) and wind energy, into the existing power system. However, the integration of this system hinders the reliable and steady running of the grid due to many operational and control challenges. Several challenges exist, including generation uncertainty, voltage and angular stability, power quality issues, reactive power support, and fault ride-through capabilities. The electricity produced by renewable energy sources (RESs) exhibits fluctuations due to meteorological phenomena beyond human control, such as wind speed and sunlight intensity. Energy storage systems (ESSs) play a crucial role in mitigating volatility by effectively storing excess electricity generated and facilitating its availability when needed. This study utilises the MATLAB/Simulink programme to develop an optimised configuration model for the wind hybrid power storage system.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139236839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-24DOI: 10.9734/jerr/2023/v25i111021
Igbokwe, J. I., Iwuanyanwu P. E., Oliha, A. O.
Site selection is one of the most important choices in the start-up, expansion, or relocation of any business. Construction of a new industrial system is a significant long-term investment, and identifying the site is a vital step on the path to the success or failure of the industrial system. Site suitability assessment in Southeast Nigeria, like elsewhere, is influenced by inherent conflicts and a complex network of socioeconomic and ecological constraints, necessitating the use of a flexible decision-making support tool capable of incorporating multiple evaluation criteria, including the perspectives of various decision-makers. In this study, a GIS-based multi-criteria approach was used for site suitability evaluation for the large-scale petrochemical industry in Southeast Nigeria. The objectives of the study include reviewing planning concepts and existing planning guidelines for the siting petrochemical industry, defining important factors and criteria needed for the establishment of the industry in the area, determining potential locations for the proposed industry through the combination of these factors, while considering constraints, using multi-criteria analysis and produce maps showing suitable sites. Datasets used for the study comprised satellite images for land use, SRTM, climate data, geology, soil, rainfall and disaster risk. The methodological approach enabled the evaluation of relative priorities of locating sites for the petrochemical industry, based on a set of criteria such as physiography, land slope, distance to river, soil type, rainfall, climate, land use land cover, distance to geological structures, land systems and geomorphology, distance from settlement, accessibility, distance from Central Business District (CBD), and disaster risk. Analytical Hierarchical Processes (AHP) were used in comparing criteria through matrix comparison and derive relative weights of the criteria. The weighted overlay was used to integrate suitability criteria maps to derive the final suitability map. An iterative post-aggregation constraint was applied ·to identify potential sites as a basis for delineating potential areas for the petrochemical industry. The final suitability map showed that 31% of the region was unsuitable for such industries due to the presence of developed areas such as built-ups, and residential and commercial areas. However, 35% of the region had less suitability while about 9% was highly suitable. In general, all the states in the southeastern region had high potential for large-scale petrochemical industries as 37 out of 95 local government areas in the region had highly suitable locations. It was recommended that demographic and environmental impact assessment be implemented in order to ensure suitable or potential sites would be effective and resourceful for the people, communities, and the region at large. In this way, industries can exist with less harmful impact on the environment while promoting economic growth
{"title":"Determining Suitable Sites for Large-Scale Petrochemical Industry in South Eastern Nigeria Using GIS-Based Multicriteria Analysis","authors":"Igbokwe, J. I., Iwuanyanwu P. E., Oliha, A. O.","doi":"10.9734/jerr/2023/v25i111021","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111021","url":null,"abstract":"Site selection is one of the most important choices in the start-up, expansion, or relocation of any business. Construction of a new industrial system is a significant long-term investment, and identifying the site is a vital step on the path to the success or failure of the industrial system. Site suitability assessment in Southeast Nigeria, like elsewhere, is influenced by inherent conflicts and a complex network of socioeconomic and ecological constraints, necessitating the use of a flexible decision-making support tool capable of incorporating multiple evaluation criteria, including the perspectives of various decision-makers. In this study, a GIS-based multi-criteria approach was used for site suitability evaluation for the large-scale petrochemical industry in Southeast Nigeria. The objectives of the study include reviewing planning concepts and existing planning guidelines for the siting petrochemical industry, defining important factors and criteria needed for the establishment of the industry in the area, determining potential locations for the proposed industry through the combination of these factors, while considering constraints, using multi-criteria analysis and produce maps showing suitable sites. Datasets used for the study comprised satellite images for land use, SRTM, climate data, geology, soil, rainfall and disaster risk. The methodological approach enabled the evaluation of relative priorities of locating sites for the petrochemical industry, based on a set of criteria such as physiography, land slope, distance to river, soil type, rainfall, climate, land use land cover, distance to geological structures, land systems and geomorphology, distance from settlement, accessibility, distance from Central Business District (CBD), and disaster risk. Analytical Hierarchical Processes (AHP) were used in comparing criteria through matrix comparison and derive relative weights of the criteria. The weighted overlay was used to integrate suitability criteria maps to derive the final suitability map. An iterative post-aggregation constraint was applied ·to identify potential sites as a basis for delineating potential areas for the petrochemical industry. The final suitability map showed that 31% of the region was unsuitable for such industries due to the presence of developed areas such as built-ups, and residential and commercial areas. However, 35% of the region had less suitability while about 9% was highly suitable. In general, all the states in the southeastern region had high potential for large-scale petrochemical industries as 37 out of 95 local government areas in the region had highly suitable locations. It was recommended that demographic and environmental impact assessment be implemented in order to ensure suitable or potential sites would be effective and resourceful for the people, communities, and the region at large. In this way, industries can exist with less harmful impact on the environment while promoting economic growth","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"96 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139239848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-23DOI: 10.9734/jerr/2023/v25i111019
Ogbonnaya Paul Kanu, E. Ugwoha, N. Udeh, Victor Amah
The aim of this study was to model the groundwater quality of Aba in Abia state. To achieve the aim, thirty-two water samples were taken from sixteen boreholes during the rainy and dry seasons and analysed in the laboratory for pH, Electrical Conductivity, Total Hardness, BOD5, COD, Pb, Cd, Cr, NH3, TDS, SO4, NO3 and PO4. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were employed to extract the principal factors and develop a model for predicting water quality index for Aba, Abia State. In the dry season, water quality index could be estimated using the Water Quality Index (WQI) model with pH, PO4, COD, SO4 and Pb with Adjusted R2 = 0.999999999938 and standard error of 0.043868872. Meanwhile, in the rainy season, WQI could be estimated using the WQI model with Turbidity, PO4, NO3, COD, SO4 and Pb with Adjusted R2 = 0.999999997469 and standard error of 0.066697494. The one-way ANOVA for the parameters in the dry season with p = 0.000 < 0.05 indicated that leachate had a large effect on groundwater quality. During the rainy season, one-way ANOVA result with p = 0.000 < 0.05 asserted that leachate had a large effect on groundwater quality.
{"title":"Modelling Groundwater Quality of Aba in Abia State Using Principal Component Analysis and Multiple Linear Regression","authors":"Ogbonnaya Paul Kanu, E. Ugwoha, N. Udeh, Victor Amah","doi":"10.9734/jerr/2023/v25i111019","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111019","url":null,"abstract":"The aim of this study was to model the groundwater quality of Aba in Abia state. To achieve the aim, thirty-two water samples were taken from sixteen boreholes during the rainy and dry seasons and analysed in the laboratory for pH, Electrical Conductivity, Total Hardness, BOD5, COD, Pb, Cd, Cr, NH3, TDS, SO4, NO3 and PO4. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were employed to extract the principal factors and develop a model for predicting water quality index for Aba, Abia State. In the dry season, water quality index could be estimated using the Water Quality Index (WQI) model with pH, PO4, COD, SO4 and Pb with Adjusted R2 = 0.999999999938 and standard error of 0.043868872. Meanwhile, in the rainy season, WQI could be estimated using the WQI model with Turbidity, PO4, NO3, COD, SO4 and Pb with Adjusted R2 = 0.999999997469 and standard error of 0.066697494. The one-way ANOVA for the parameters in the dry season with p = 0.000 < 0.05 indicated that leachate had a large effect on groundwater quality. During the rainy season, one-way ANOVA result with p = 0.000 < 0.05 asserted that leachate had a large effect on groundwater quality.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"8 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139243488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-23DOI: 10.9734/jerr/2023/v25i111020
M. Onugba, Lawrence Ademola Omisande, Yunusa Aminu AlhassVan, Abubakar Otu Abdullahi
The rising need for affordable and eco-friendly housing occasioned by a surge in global population growth, the ever-increasing cost of building materials and environmental concerns has been an issue of concern over the last few decades. This has necessitated continuous research and development of affordable and eco-friendly building materials for low- and middle-income earners. This research evaluated the effect of oil palm fibre on the compressive strength of compressed earth blocks. Oil palm fibre was added to the soil matrix at 0%, 0.5%, 1% and 1.5% by weight of laterite. The blocks were cured for 28 days after which they were tested. The results obtained indicate that the addition of palm fibre up to 1% in the matrix increased the compressive strength to a maximum of 1.38N/mm2. Further addition of palm fibre in the matrix resulted in a decrease of the compressive strength. An optimum reinforcement of the blocks with 1% palm fibre is recommended.
{"title":"Enhancing Earth-based Building Materials: Effect of Palm Fibre Reinforcement on Compressive Strength","authors":"M. Onugba, Lawrence Ademola Omisande, Yunusa Aminu AlhassVan, Abubakar Otu Abdullahi","doi":"10.9734/jerr/2023/v25i111020","DOIUrl":"https://doi.org/10.9734/jerr/2023/v25i111020","url":null,"abstract":"The rising need for affordable and eco-friendly housing occasioned by a surge in global population growth, the ever-increasing cost of building materials and environmental concerns has been an issue of concern over the last few decades. This has necessitated continuous research and development of affordable and eco-friendly building materials for low- and middle-income earners. This research evaluated the effect of oil palm fibre on the compressive strength of compressed earth blocks. Oil palm fibre was added to the soil matrix at 0%, 0.5%, 1% and 1.5% by weight of laterite. The blocks were cured for 28 days after which they were tested. The results obtained indicate that the addition of palm fibre up to 1% in the matrix increased the compressive strength to a maximum of 1.38N/mm2. Further addition of palm fibre in the matrix resulted in a decrease of the compressive strength. An optimum reinforcement of the blocks with 1% palm fibre is recommended.","PeriodicalId":340494,"journal":{"name":"Journal of Engineering Research and Reports","volume":"81 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139246048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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