Dr. N. Rudraiah : a biobibliometric study

Dr. Rudraiah has worked in various fields in applied mathenlatics like fluid mechanics, magnetohydrodynamics, electrodynamics and smart materals of nanostructures. In his 43 pears of productive life, he has collaborated with 102 colleagues and students and has published 271 papers during 1962-2004. The collaboration co-efficient is 0.54. Highest collaborations were with M. Venkatachalappa (31), and B.C. Chandrasekhara (21). The core journals publishing his papers were: Indian Journal of Pure and Applied Mathematics, Current Science, International Journal of Heat and Mass Transfer, Acta Mechanica, Journal of Fluid Mechanics, Proc. Royal Cambridge Society of London and Physics of Fluid

Approximation of Entropy Numbers

The purpose of this article is to develop a technique to estimate certain bounds for entropy numbers of diagonal operator on spaces of p-summable sequences for finite p greater than 1. The approximation method we develop in this direction works for a very general class of operators between Banach spaces, in particular reflexive spaces. As a consequence of this technique we also obtain that the entropy number of a bounded linear operator T between two separable Hilbert spaces is equal to the entropy number of the adjoint of T. This gives a complete answer to the question posed by B. Carl [4] in the setting of separable Hilbert spaces.Comment: 10 page

Development of Carbonaceous Chemistry for Computational Modeling (C3M) with Application of Uncertainty Quantification (UQ) Analysis for Coal Gasification Kinetics in Computational Fluid Dynamics (CFD) Modeling

In association with Department of Energy.s National Energy Technology Laboratory (NETL), a software platform entitled Carbonaceous Chemistry for Computational Modeling (C3M) that can access a variety of kinetic processes and reaction mechanisms typically found in coal gasification, gas clean-up, and carbon capture processes, has been developed to overcome the limitations in terms of applicable operating conditions and fuel types. It interfaces with CFD software such as Multiphase Flow with Interphase Exchanges (MFIX) developed at NETL, ANSYS-FLUENT by ANSYS Inc., and BARRACUDA by CPFD Software and provides relevant parameters to simulate chemical kinetics and/or to replicate laboratory data. The reaction kinetics data in C3M are provided by one or more detailed reaction models such as PC Coal Lab (PCCL), Chemical Percolation Model for Coal Devolatilization (CPD), Solomon.s Functional-Group, Depolymerization, Vaporization, Cross-linking (FGDVC) model, or through experimental data generated at NETL. Algorithms were written to create this interface and to extract the kinetic information from all models. This functionality provides the CFD user with a framework to conduct virtual kinetic experiments to evaluate kinetic predictions as a function of fuel and sorbent type and/or operating conditions. The effort on the user.s part to search, analyze and to check the accuracy of the kinetics of interest is drastically reduced. Validity and compatibility of C3M kinetics were tested by implementing them in a (2-D) transport gasifier and in an industrial GE Texaco gasifier model (1-D). The predicted exit gas composition and trends of gas species matched very closely with the experimental and industrial data. To improve the kinetic database, a detailed coal/biomass derived soot literature review was completed. It was found that there is a gap in coal derived soot formation and gasification kinetics for high temperature and pressure operating conditions. In addition to the kinetic studies, uncertainty quantification (UQ) techniques were employed in the CFD models to study the variations of chemical reaction kinetics in a coal gasifier. The uncertainty in exit gas composition based on the variations in input parameters such as temperature, pressure, heating rate and coal feed composition were implemented. Changes in devolatilization product yields (such as mass fractions of CO, CO2, H2, tar, H2O, and CH4 along with total volatile yield) were used as response variables and were recorded and correlated based on distributions of input parameters such as temperature, pressure and heating rates. The correlations among the response variables and input parameters were investigated by computing a correlation matrix. The uncertainties in output responses were in close agreement with data reported in literature. This study strongly suggested the importance of considering uncertainties in chemical reaction kinetics in CFD modeling