{"title":"MATLAB PROGRAM FOR RATING SOILS BASED ON ENGINEERING BEHAVIOURS","authors":"E. Ekeoma, U. N. Okonkwo, A. Odumade","doi":"10.33736/jcest.5078.2023","DOIUrl":null,"url":null,"abstract":"Engineering behaviour of soils is an important attribute to be considered as the foundation or even construction materials for civil engineering structures. One critical issue encountered by geotechnical engineers in construction works is predicting the engineering behaviour of soil with a view to assessing its suitability for any given construction purpose. Rating of soils based on their engineering behaviours can be achieved by classifying the soil into different groups and sub-groups of similar characteristics. Soil classification systems usually involve the use of charts, tables and curves, which is no longer fashionable because it might be very rigorous when many soils are involved. The use of software techniques simplifies the whole process. This study developed an algorithm in the form of a MATLAB program for easy classification of soil based on the Unified Soil Classification System (USCS), American Association of State Highway and Transport Officials (AASHTO), Plasticity Chart and the Indian Soil Classification Systems (ISCS), which makes the program unique. Soil samples used for illustration were collected and characterised depending on particle size analysis as well as consistency indices. A comparative study was carried out between classifying the soil using a manual approach and the MATLAB program. The MATLAB program rated Soil Sample A to be fine-grained, which belongs to soil groups A-7-6(15), CL (inorganic clay that has medium plasticity) and MI or OI (inorganic silt of medium plasticity or organic silt of medium plasticity) while Soil Sample B was rated to be coarse-grained belonging to A-1-b (0), SM (Silty Sand) and SM (Silty Sand) in the AASHTO, USCS and ISCS classification systems respectively. The results of the classification systems from the MATLAB program were completely in conformity with the results obtained from the manual approach. Thus, the MATLAB program gave a very high degree of accuracy of almost 100%.","PeriodicalId":346729,"journal":{"name":"Journal of Civil Engineering, Science and Technology","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Civil Engineering, Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33736/jcest.5078.2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Engineering behaviour of soils is an important attribute to be considered as the foundation or even construction materials for civil engineering structures. One critical issue encountered by geotechnical engineers in construction works is predicting the engineering behaviour of soil with a view to assessing its suitability for any given construction purpose. Rating of soils based on their engineering behaviours can be achieved by classifying the soil into different groups and sub-groups of similar characteristics. Soil classification systems usually involve the use of charts, tables and curves, which is no longer fashionable because it might be very rigorous when many soils are involved. The use of software techniques simplifies the whole process. This study developed an algorithm in the form of a MATLAB program for easy classification of soil based on the Unified Soil Classification System (USCS), American Association of State Highway and Transport Officials (AASHTO), Plasticity Chart and the Indian Soil Classification Systems (ISCS), which makes the program unique. Soil samples used for illustration were collected and characterised depending on particle size analysis as well as consistency indices. A comparative study was carried out between classifying the soil using a manual approach and the MATLAB program. The MATLAB program rated Soil Sample A to be fine-grained, which belongs to soil groups A-7-6(15), CL (inorganic clay that has medium plasticity) and MI or OI (inorganic silt of medium plasticity or organic silt of medium plasticity) while Soil Sample B was rated to be coarse-grained belonging to A-1-b (0), SM (Silty Sand) and SM (Silty Sand) in the AASHTO, USCS and ISCS classification systems respectively. The results of the classification systems from the MATLAB program were completely in conformity with the results obtained from the manual approach. Thus, the MATLAB program gave a very high degree of accuracy of almost 100%.