Prediction of unconfined compressive strength of cement stabilized pavement materials | |
| Author | Premarathne, Piyumee Kaushalya |
| Call Number | AIT Caps. Proj. no.CIE-17-59 |
| Subject(s) | Strength of materials Pavements, Concrete--Materials |
| Note | A capstone project report submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Engineering Civil and Infrastructure Engineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Caps. Proj. ; no. CIE-17-59 |
| Abstract | The purpose of this study is to evaluate and justify suitable prediction equations for predicting the unconfined compressive strength (UCS) of cement stabilized pavement materials. It involves derivation of regression equations by multiple linear regression for prediction of UCS and analyzing them in a statistical approach with UCS prediction equations proposed by past researches. Data for analysis were collected from Bureau of Material, Analysis, and Inspection, Department of Highways (DOH), Thailand. Data were obtained from two highway construction projects located in Nakornsawan-Tak and Tak-Payao, Thailand involving pavement recycling base layer and pavement recycling subbase layer. Multiple linear regression analysis was done using IBM SPSS software. Both stepwise method and enter method were used in multiple linear regression analysis. Three UCS prediction equations were obtained from multiple linear regression and three UCS prediction equations were obtained from past researches (Sunitsakul et al. (2012), Sawangsuriya (2016) and Jaritngam (2012)). Two criterions were considered in the selection of the suitable UCS prediction equation and to check the accuracy and precision of each prediction equation. First criterion consisted of Predicted UCS vs. Actual UCS graph. The slope value and interception value of each graph were considered as it is very important to evaluate prediction equations by regressing actual and predicted values and to test the significance of slope value = 1 and interception value = 0. Second criterion used two indices specifically Ranking Distance (RD) and Ranking Index (RI). For a good correlation, both these indices shall approach zero. Considering the outputs given by statistical analysis for above two criterions, relationship between UCS and CBR/ (w/c) proposed by Sunitsakul et al. (2012) was justified as a very good prediction equation to predict the UCS of cement stabilized pavement materials. Study also confirmed that the relationship proposed by Sawangsuriya (2016) for fine-grained soil with plasticity index is not suitable for the prediction of UCS as the majority of the mix is non-plastic. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Caps. Proj. ; no. CIE-17-59 |
| Type | Capstone Project |
| School | School of Engineering and Technology (SET) |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Civil and Infrastructure Engineering (CIE) |
| Chairperson(s) | Auckpath Sawangsuriya ;Kunnawee Kanitpong; |
| Examination Committee(s) | Surachet Pravinvongvuth; |
| Degree | Capstone Project (B.Sc.)-Asian Institute of Technology, 2017 |