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020 _aTHE0010527 (Local)
_qHardback
040 _aUMPSA
_beng
_cUMPSA
_erda
090 _aFTKA .F35 2025 r Thesis
100 0 _aAhmad Faiz Bin Salmanfarsi,
_eauthor.
245 1 0 _aDeveloping relationship between parameters of rock mass classification and rock slope failure from granitic rock /
_cAhmad Faiz Bin Salmanfarsi
264 1 _aKuantan, Pahang :
_bUMPSA,
_c2026
264 4 _c© 2026
300 _axxviii, 607 pages :
_billustrations (some color) ;
_c30 cm. +
_e1 CD-ROM.
336 _2rdacontent
_atext
337 _2rdamedia
_aunmediated
338 _2rdacarrier
_avolume
347 _2rda
_atext file
_bPDF
500 _aFaculty of Civil Engineering Technology
502 _aThesis (Doctor of Philosophy in Civil Engineering) -- Universiti Malaysia Pahang Al Sultan Abdullah - 2026
504 _aIncludes bibliographical references
520 3 _aRock-slope failures in Malaysia are serious natural disasters that are on the rise alongside the increase in development. Construction of highways and roads leads to the blasting of large surfaces of rocks, which are subjected to potential slope failures. Over the years various methods have been used for assessment of rock slopes. The ever-developing rock mass classifications are still not as widely used amongst local practitioners as compared to other method such as the kinematic analysis. In addition, majority of rock mass classifications uses discrete ratings, which has a lot of subjectivity during the assessment as compared to continuous functions rating. This research aims to tackle the issue by setting out to determine the geological characterisation of the rock slopes through combination of field mapping, remote sensing, and geophysical surveying. From this, the research aims to establish a more comprehensive assessment of rock slopes and present index properties of weathered slope. Next, the research aim is to analyse the relationship between the different rock mass classifications from stability analysis carried out through kinematic analysis and rock mass classification systems. Lastly, the research aim is to develop a more comprehensive analysis of rock mass classification by correlating the parameters of the rock mass classifications using values from field mapping and laboratory testing, from which predictive models of rock mass classification is presented. For this purpose, selected sections along Lebuhraya Pantai Timur (LPT) were chosen as study sites, focusing on granitic rock slopes. Field measurement was through field mapping, Terrestrial Laser Scanning (TLS), and electrical resistivity surveys. Samples across the different weathering grades of granite were collected for mineralogy, physical, and strength tests. Slope assessments were done through selected rock mass classifications and kinematic analysis. Regression analysis were carried out to determine the relationship between the different rock mass classifications, as well as with the engineering properties of the rock materials. Multiple regression analysis of the engineering properties of specific gravity, porosity, moisture content, and ultrasonic pulse velocity in relation to the parameters of point load strength, uniaxial compressive strength, Schmidt Rebound hammer, and Slake durability index have found significant amount of determination coefficient (R2 value of 0.73, 0.92, 0.86, and 0.90 for the parameters respectively). These predicted parameters model were then calculated as parameters in selected continuous functions in the rock mass classification system of the Rock Mass Rating (RMR). Analysis through the 45°-line plot and paired T-test have found most of the predicted parameters to be statistically significant in predicting the value of rock mass classification, p values that are statistically significant (p <0.05) and high determination coefficient (R2 values ranges from 0.89 onward). Overall, statistical analysis of engineering properties weathered granite were found to be statistically significant in predicting parameters of the RMR. Further studies could explore application of similar predictive models for other rock types in slope assessments for assessing the stability of rock slopes.
610 2 0 _aFaculty of Civil Engineering Technology
_xDissertations
650 0 _aUniversities and colleges
_xDissertations
942 _2lcc
_cTHESIS
999 _c104892
_d104898