{"title":"地下土壤承载力测定与制图——以肯尼亚埃尔多雷特莫伊大学为例","authors":"Sum Kipyego, Davis Sagini, B. Omondi","doi":"10.7176/cer/12-7-05","DOIUrl":null,"url":null,"abstract":"Ground investigation is a prerequisite for any construction work that ultimately transfers its loads to the earth. Geotechnical investigation eliminates the uncertainties of ground conditions and can be planned for and considered accordingly during actual design and construction. In Kenya, ground investigation is not given the weight it deserves since most players in the sector use their experience and physical inspection to judge on the soil conditions. This is however very risky especially for high-rise buildings. Moi University, the case study, is one of the institutions that has in its plan, a series of construction developments. This study aimed at investigating, determining and mapping of index properties and bearing capacity of subsurface soil. Direct shear box and tri-axial tests results were used to map soil bearing capacity by geospatial interpolation within geographical information system platform (GIS). 9 trial pits mapped by triangulation and visual inspection were excavated and soil samples obtained at a depth of up to 3 m. The soil samples were tested for soil index and engineering properties and classified using the USCS approach. A relationship between tri-axial and direct shear box test results was developed by correlating soil bearing capacity results from the two tests. This paper provides a thematic map of the bearing capacity for the study area derived from spatial interpolation. Four geospatial interpolation methods namely; Ordinary Kriging (OK), spline, Natural Neighbour (NN) and Inverse Distance Weighting (IDW) were used. In this paper, the most suitable method for interpolating the soil bearing capacity of the four methods is provided. Six of nine sample test results were used for interpolation and the other three used for validation and error correction. Ordinary Kriging generated satisfactory results for soil bearing capacity for the study area with a relative error of 2.23 % and R 2 of 0.9993. From the safe bearing capacity map, the ground conditions of the study area varied gradually with the bearing capacity ranging from to . Generally, the amount of clay in the soil within the area affected to a large extent, the soil bearing capacity. Keywords: Soil bearing capacity, Geospatial interpolation, Deterministic interpolation, correlation. DOI: 10.7176/CER/12-7-05 Publication date: July 31 st 2020","PeriodicalId":10219,"journal":{"name":"Civil and environmental research","volume":"112 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determination and Mapping of the Bearing Capacity of Subsurface Soil: A Case Study of Moi University, Eldoret Kenya\",\"authors\":\"Sum Kipyego, Davis Sagini, B. Omondi\",\"doi\":\"10.7176/cer/12-7-05\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ground investigation is a prerequisite for any construction work that ultimately transfers its loads to the earth. Geotechnical investigation eliminates the uncertainties of ground conditions and can be planned for and considered accordingly during actual design and construction. In Kenya, ground investigation is not given the weight it deserves since most players in the sector use their experience and physical inspection to judge on the soil conditions. This is however very risky especially for high-rise buildings. Moi University, the case study, is one of the institutions that has in its plan, a series of construction developments. This study aimed at investigating, determining and mapping of index properties and bearing capacity of subsurface soil. Direct shear box and tri-axial tests results were used to map soil bearing capacity by geospatial interpolation within geographical information system platform (GIS). 9 trial pits mapped by triangulation and visual inspection were excavated and soil samples obtained at a depth of up to 3 m. The soil samples were tested for soil index and engineering properties and classified using the USCS approach. A relationship between tri-axial and direct shear box test results was developed by correlating soil bearing capacity results from the two tests. This paper provides a thematic map of the bearing capacity for the study area derived from spatial interpolation. Four geospatial interpolation methods namely; Ordinary Kriging (OK), spline, Natural Neighbour (NN) and Inverse Distance Weighting (IDW) were used. In this paper, the most suitable method for interpolating the soil bearing capacity of the four methods is provided. Six of nine sample test results were used for interpolation and the other three used for validation and error correction. Ordinary Kriging generated satisfactory results for soil bearing capacity for the study area with a relative error of 2.23 % and R 2 of 0.9993. From the safe bearing capacity map, the ground conditions of the study area varied gradually with the bearing capacity ranging from to . Generally, the amount of clay in the soil within the area affected to a large extent, the soil bearing capacity. Keywords: Soil bearing capacity, Geospatial interpolation, Deterministic interpolation, correlation. DOI: 10.7176/CER/12-7-05 Publication date: July 31 st 2020\",\"PeriodicalId\":10219,\"journal\":{\"name\":\"Civil and environmental research\",\"volume\":\"112 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Civil and environmental research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7176/cer/12-7-05\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Civil and environmental research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7176/cer/12-7-05","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determination and Mapping of the Bearing Capacity of Subsurface Soil: A Case Study of Moi University, Eldoret Kenya
Ground investigation is a prerequisite for any construction work that ultimately transfers its loads to the earth. Geotechnical investigation eliminates the uncertainties of ground conditions and can be planned for and considered accordingly during actual design and construction. In Kenya, ground investigation is not given the weight it deserves since most players in the sector use their experience and physical inspection to judge on the soil conditions. This is however very risky especially for high-rise buildings. Moi University, the case study, is one of the institutions that has in its plan, a series of construction developments. This study aimed at investigating, determining and mapping of index properties and bearing capacity of subsurface soil. Direct shear box and tri-axial tests results were used to map soil bearing capacity by geospatial interpolation within geographical information system platform (GIS). 9 trial pits mapped by triangulation and visual inspection were excavated and soil samples obtained at a depth of up to 3 m. The soil samples were tested for soil index and engineering properties and classified using the USCS approach. A relationship between tri-axial and direct shear box test results was developed by correlating soil bearing capacity results from the two tests. This paper provides a thematic map of the bearing capacity for the study area derived from spatial interpolation. Four geospatial interpolation methods namely; Ordinary Kriging (OK), spline, Natural Neighbour (NN) and Inverse Distance Weighting (IDW) were used. In this paper, the most suitable method for interpolating the soil bearing capacity of the four methods is provided. Six of nine sample test results were used for interpolation and the other three used for validation and error correction. Ordinary Kriging generated satisfactory results for soil bearing capacity for the study area with a relative error of 2.23 % and R 2 of 0.9993. From the safe bearing capacity map, the ground conditions of the study area varied gradually with the bearing capacity ranging from to . Generally, the amount of clay in the soil within the area affected to a large extent, the soil bearing capacity. Keywords: Soil bearing capacity, Geospatial interpolation, Deterministic interpolation, correlation. DOI: 10.7176/CER/12-7-05 Publication date: July 31 st 2020