AI SearchDeterminations of the correction factor for undrained shear strength and internal friction angle empirical models from CPT data : a case study of Bangladeshi soils
Call Number: AIT Thesis no.GE-22-10 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. GE-22-10Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2023Description: 99 leaves : illSubject(s): Online resources: Dissertation note: Thesis (M. Sc.) - Asian Institute of Technology, 2023 Summary: In situ subsurface testing methods like CPT and SPT are utilized worldwide to investigate the soil{u2019}s geotechnical properties. In Bangladesh, the utilization of CPT for both small and large projects is increasing day by day. The determination of soil parameters such as undrained shear strength (Su) and internal friction angle ({u03D5}) holds significant importance in the design of foundations. These parameters are obtained from laboratory tests of soil samples collected from the field during the SPT test. The CPT provides a range of Su values, comprising both the maximum and minimum limits. However, the challenge lies in determining the precise value that is suitable for design purposes. There is no direct correlation between laboratory tested soil parameters (Su and {u03D5}) and CPT data. In this study, the main goal is to determine the correction factor and establish empirical models of Su and {u03D5} for CPT to minimize cost and reduce time for Bangladeshi soils. This study first reviews the existing correlations between soil parameters and CPT in the literature. For the analysis required, 378 SPT boring points and 146 CPT data were collected from two organizations, LGED and RAJUK, in Bangladesh. All the collected data is classified and summarized into two categories: trained data sets and test datasets. Regression analyses are applied using trained data to determine the correction factor and develop empirical modes of Su and {u03D5} for CPT. Test datasets are employed on models to verify and validate the developed models. In this research, it is possible to find out the correction factor for CPT parameters and establish empirical models of Su and {u03D5} for CPT with reference to laboratory tested Su and {u03D5} for Bangladeshi soils. Any design engineer can apply this model to the design of a foundation without performing laboratory tests for soil parameters. The development of models will have a significant impact on society due to their potential to reduce the time required for laboratory testing and their economic design implications.
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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Geotechnical and Earth Resources Engineering
Thesis (M. Sc.) - Asian Institute of Technology, 2023
In situ subsurface testing methods like CPT and SPT are utilized worldwide to investigate the soil{u2019}s geotechnical properties. In Bangladesh, the utilization of CPT for both small and large projects is increasing day by day. The determination of soil parameters such as undrained shear strength (Su) and internal friction angle ({u03D5}) holds significant importance in the design of foundations. These parameters are obtained from laboratory tests of soil samples collected from the field during the SPT test. The CPT provides a range of Su values, comprising both the maximum and minimum limits. However, the challenge lies in determining the precise value that is suitable for design purposes. There is no direct correlation between laboratory tested soil parameters (Su and {u03D5}) and CPT data. In this study, the main goal is to determine the correction factor and establish empirical models of Su and {u03D5} for CPT to minimize cost and reduce time for Bangladeshi soils. This study first reviews the existing correlations between soil parameters and CPT in the literature. For the analysis required, 378 SPT boring points and 146 CPT data were collected from two organizations, LGED and RAJUK, in Bangladesh. All the collected data is classified and summarized into two categories: trained data sets and test datasets. Regression analyses are applied using trained data to determine the correction factor and develop empirical modes of Su and {u03D5} for CPT. Test datasets are employed on models to verify and validate the developed models. In this research, it is possible to find out the correction factor for CPT parameters and establish empirical models of Su and {u03D5} for CPT with reference to laboratory tested Su and {u03D5} for Bangladeshi soils. Any design engineer can apply this model to the design of a foundation without performing laboratory tests for soil parameters. The development of models will have a significant impact on society due to their potential to reduce the time required for laboratory testing and their economic design implications.
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