Pawan Kumar Singh, and Diganta Goswami, Ranjeet Bahadur Singh
Abstract: With the interest of overcoming certain challenges like floods, shortage of electricity, drinking water, etc., river valley projects are taken which can serve the required purposes in the long run. Generally, the river valley projects which involve the construction of dam are situated in gorges where constructions are done through the rock masses. So, the specifications of the supports provided at the site can be utilized again for estimating the behaviour of the rock mass with the help of back calculation technique. Further, the determination of the properties of the rock mass at the site also aid in the assessment of stability, which can be done with the help of in-situ tests as well as laboratory tests. Since it is not feasible to conduct a large number of in-situ tests at site, one can find it advantageous to use the tools like Finite element codes like Plaxis 3D AE for determining the properties of the rock mass. In this research work, an attempt has been made to derive the properties of the rock mass by back calculation technique using the results of in-situ Plate load test. An appropriate material modelling is very important in any Finite Element analysis to arrive at solutions close to the exact values, necessitating the selection of appropriate constitutive model. In this context, the suitability of the four constitutive models viz. Jointed Rock mass model, Hoek- Brown model, Mohr-coulomb model and Hardening Soil model, appropriate to Pare Rock mass is examined. Through this study, a systematic approach has been adopted for the simulation of rock mass properties of the Pare Hydroelectric Project site with the help of numerical modelling. In addition to this, two different parameters viz. RMSE and MAPE values are computed to check the discrepancies among the field and the FEM values in the constitutive models for both loading and unloading conditions.
Keywords: Pare Hydroelectric Project, Plate load test, Finite Element Method, Back Calculation Technique, Root Mean Square Error, Mean Absolute Percentage Error.
Date Published: September 1, 2022 DOI: 10.11159/ijci.2022.012
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