Browsing by Author "Patel, G, C, M."

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    Estimation of Monsoon Seasonal Precipitation Teleconnection with El Ni o-Southern Oscillation Sea Surface Temperature Indices over the Western Ghats of Karnataka
    (2019) Doranalu, Chandrashekar, V.; Shetty, A.; Patel, G, C, M.
    The Western Ghats (WG) of India are basically north-to-south oriented mountains with three distinct meteorological divisions. These mountains exhibit the characteristic features of precipitation and distribution during the summer monsoon season and possess latitudinal variations. It is a well-known fact that sea surface temperature (SST) combined with the El Ni o-Southern Oscillation (ENSO) enacts a predominant role in the precipitation over the entire Western Ghats during the summer monsoon season. Whereas the Ni o regions affect the variability of the Western Ghats precipitation in an asymmetric relationship. Nevertheless, the simulation of precipitation has been evidenced to be difficult. The current study attempts to predict the seasonal precipitation over the coastal region and the Western Ghats of Karnataka. The relationship between summer monsoon precipitation (SMP) and SST is examined up to eight seasons by conducting the correlation analysis with three seasons that lag before the onset of the monsoon season. The significant and positively correlated lagged Ni o indices with the SMP index are identified as the predictors. The selected predictors are used for predicting the SMP by using statistical models, the multiple linear regression model and the artificial neural network (ANN) model. The statistical models are based on the combined lagged indices and the principle component as the predictor. The results of the statistical models on comparison suggest that neural network models have a better predictive skill than the linear regression models. Neural network models with combined lagged indices being used as predictors are slightly better, but a few more climatic parameters must be verified and the usage of this method on other meteorological divisions of the West Coast of India needs to be further investigated. 2019, Korean Meteorological Society and Springer Nature B.V.
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    Modelling of squeeze casting process using design of experiments and response surface methodology
    (2015) Patel, G, C, M.; Krishna, P.; Parappagoudar, M.B.
    The present work makes an attempt to model and analyse squeeze casting process by utilising design of experiments and response surface methodology. The input output data for developing regression models and test cases is obtained by conducting the experiments. Surface roughness, ultimate tensile strength and yield strength have been measured for different combinations of process variables, namely, squeeze pressure, pressure duration, pouring temperature and die temperature. Two non-linear regression models based on central composite design (CCD) and Box-Behnken design (BBD) of experiments have been developed to establish the input output relationships. The effects of process variables on the measured responses have been studied using surface plots. The performances of the two non-linear models have been tested for their prediction accuracy with the help of 15 test cases. It is observed that, both CCD and BBD, the non-linear regression models are statistically adequate and capable of making accurate predictions. 2015 W. S. Maney & Son Ltd.