https://www.oceanexpert.net/expert/gangadharan%20muraleedharan

D.Sc (Doctor of Science, post-doctorate degree)

Research

Physical Oceanography

1.   PROBABILISTIC MODELS OF WAVE PARAMETERS,

2.    QUANTILE FUNCTIONS,

3.   OCEAN WAVE CLIMATOLOGY,

4.   REGIONAL FREQUENCY ANALYSIS BASED ON L-MOMENTS,

5.   OPEN OCEAN AND COASTAL WAVE HYDRODYNAMICS,

6.   TSUNAMI AND STORM SURGE INUNDATION MODELLING

7.   PROBABILITY BASED ENGINEERING

8.  DERIVATION OF STATISTICAL TOOLS FOR ESTIMATION OF VARIOUS WAVE STATISTICS

North Atlantic Ocean
Arabian Sea
Bay of Bengal
Indian Ocean

FORTRAN CODING, EXCEL, ORIGIN, PHYSICAL OCEANOGRAPHY, DISTRIBUTION THEORY, PROBABILISTIC MODELLING

English

ResearchGate

·     SIGNIFICANT RESEARCH ACHIEVEMENTS 

    Provided a general statistical formula for the estimation of significant wave height (Hs) and period (Ts) 

 ·         Derived a statistical formula (using general formula) from generalised Pareto distribution (GP3) for estimation of significant wave period Ts (also significant wave height Hs). 

 ·         Suggested alternative method for estimation of Hs and Ts as well as H1/10 and T1/10 from the functional forms of average conditional exceedance of wave heights and periods derived from the distributions of wave heights and periods.   

 ·         Suggested a novel method of selection of the appropriate distribution function of an environmental parameter from the knowledge of the functional form of average conditional exceedance of the environmental parameter m (.). Since m (.) determines the distribution of the parameter uniquely, it is sufficient to find the functional form of m (.) consistent with the data.   

 ·         Provided the procedure and programmed as FORTRAN routine the estimation of three-parameter Weibull distribution by the method of L-moments.

 ·         Suggested Weibull and GP3 distributions as the long-term distributions of wave heights in terms of intensity function. Empirical analysis also supports the same view point.

 ·         Various parametric relations are derived from Weibull distribution to estimate the wave statistics such as i) mean wave height, ii) mean maximum wave height, iii) most frequent maximum wave height, iv) significant wave height, v) extreme wave height, vi) return period of an extreme wave height and vii) probability of realizing an extreme wave height in a time less than the designated return period and are validated.

 ·         Big data analyses were carried out by Programming as FORTRAN routines for extraction of joint distributions of : significant wave heights and associated periods(peak and energy periods), daily or every 2nd , 3rd … maximum significant wave heights and associated periods (peak and energy periods), marginal distributions of significant wave heights, peak periods and energy periods from 44 years North Atlantic Ocean Wave Data generated under the ´Hindcast of the Dynamic Processes of the Ocean and Coastal Areas of Europe (HIPOCAS)´ project and 34 years SWAN generated data.

 ·         Programmed as FORTRAN routines for the estimation of various wave statistics by the parametric relations derived from probabilistic models. 

 ·         Derived the characteristic and moment generating functions of generalised Pareto and three parameter Weibull distributions.

·         Suggested a theoretical spectrum from modified Weibull distribution for deep water significant wave height estimations.

 ·         Simulated the Boxing Day tsunami of the Indian Ocean using the fundamental relation that connects the extreme wave heights and return periods derived from tuning and calibration coefficient incorporated modified Weibull distribution.  

 ·         Provided a predictive model based on work-energy theorem for the estimation of beach run-up heights and inundation by long gravity waves.

 ·         Initiated statistical modelling of wave heights with quantile functions which is a replacement of the classical approach to modelling but as a useful supplement

 ·         Introduced regression quantile function concepts as a better tool for extreme wave height estimations

 ·         Initiated weather window analysis using probabilistic models.

 ·         Initiated regional frequency analysis (RFA)-an approach based on L-moments for extreme wave height estimations. 

 ·         RFA involves considerable amount of computations and hence the numerical methods have been programmed as FORTRAN routines- The L-moments package contains 303 FORTRAN routines. The FORTRAN routines were executed for the effective implementation of the various steps in RFA.