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<title>Ajay K. Ray</title>
<copyright>Copyright (c) 2012  All rights reserved.</copyright>
<link>http://works.bepress.com/ajay_ray</link>
<description>Recent documents in Ajay K. Ray</description>
<language>en-us</language>
<lastBuildDate>Thu, 22 Nov 2012 19:02:43 PST</lastBuildDate>
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<title>Mathematical Methods in Chemical and Environmental Engineering</title>
<link>http://works.bepress.com/ajay_ray/6</link>
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<pubDate>Thu, 27 Mar 2008 07:46:17 PDT</pubDate>
<description>
	<![CDATA[
	<p>This comprehensive book covers a broad selection of mathematical topics that are essential for a modern chemical/environmental engineer. It features a blend of analytical and numerical techniques for solving problems in diverse areas, such as, heat and mass transfer, thermodynamics, fluid mechanics, reaction engineering, transport phenomena, and process systems engineering. This new text emphasizes problem solving, and deals extensively with methods for solving systems of linear and non-linear algebraic equations, systems of linear and non-linear ordinary and partial differential equations.</p>

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<author>Ajay K. Ray et al.</author>


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<title>Applications of the Non-Dominated Sorting Genetic Algorithm (NSGA) in Chemical Reaction Engineering</title>
<link>http://works.bepress.com/ajay_ray/5</link>
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<pubDate>Wed, 26 Mar 2008 14:43:25 PDT</pubDate>
<description>
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	<p>Most of the chemical reaction engineering optimization problems encounters more than one objective functions. A considerable amount of research has been reported on the multiobjective optimization of various chemical reactors using various non-dominated sorting genetic algorithms. This is reviewed in this paper. The introduction of the topic is given at the beginning, followed by the description of multi-objective optimization and Pareto set. We have then discussed various non-dominated sorting genetic algorithms and its applications in chemical reaction engineering. Some comments are also made on the future research direction in this area.</p>

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<author>Anjana D. Nandasana et al.</author>


<category>Modeling and Optimization</category>

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<title>Performance Enhancement of Photocatalytic Reactor Utilizing Flow Instability</title>
<link>http://works.bepress.com/ajay_ray/4</link>
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<pubDate>Wed, 26 Mar 2008 14:43:22 PDT</pubDate>
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	<p>A detailed analysis has been performed for a heterogeneous photocatalytic Taylor vortex reactor that uses flow instability to recirculate fluid continually from the vicinity of the rotating inner cylindrical surface (coated with catalyst) to the stationary outer cylindrical surface of an annulus. A detailed time accurate computation when the reactor is started impulsively shows the different stages of flow evolution and the effects of finite length of the reactor in creating eddies, the overall effects of which shows very high efficiency of photocatalytic conversion. The physical arrangement considered is such that pollutant degradation is maximized by a combination of the controlled periodic illumination effect and the motion of fluid particles in a specific regime of centrifugal instability. It was found out that optimum Reynolds's number is 380 as the system reaches steady state faster, number of vortices per unit length is more, vortices move faster towards center from end, and the magnitude of both axial and radial component of velocity is more than at higher or lower value of Reynolds's number.</p>

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</description>

<author>Kanheya Mehrotra et al.</author>


<category>Photocatalysis</category>

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<title>Optimization of Styrene Reactor Design for Two Objectives using a Genetic Algorithm</title>
<link>http://works.bepress.com/ajay_ray/3</link>
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<pubDate>Wed, 26 Mar 2008 14:43:20 PDT</pubDate>
<description>
	<![CDATA[
	<p>Optimization of industrial styrene reactor design for two objectives using the non-dominated sorting genetic algorithm (NSGA) is studied. Both adiabatic and steam-injected reactors are considered. The two objectives are maximization of styrene production and styrene selectivity. The study shows that styrene reactor design can be optimized easily and reliably for two objectives by NSGA. It provides a range of optimal designs, from which the most suitable design can be selected based on other considerations.</p>

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<author>Yue Li et al.</author>


<category>Modeling and Optimization</category>

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<title>Performance Improvement and Dynamical Behaviour Analysis of a Cascade of Two CSTRs</title>
<link>http://works.bepress.com/ajay_ray/2</link>
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<pubDate>Wed, 26 Mar 2008 14:43:17 PDT</pubDate>
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	<p>We revisit the analysis of a reactor network consisting of two coupled continuous stirred tank reactors (CSTRs) arranged in series (Chem. Eng. J. 59 (1995) 169). The main idea proposed in this earlier work is to improve process conversion by generating periodic behaviour in the first reactor (by appropriate choice of design and operational parameters) which then 'forces' the second reactor.  The performance of this cascade system was shown to be greatly enhanced using the above strategy. In this paper we show some conceptual errors in the analysis in the original paper. We also show that by employing a systematic bifurcation analysis, including the use of a path following software, greater insights can be gained regarding the system's behaviour. Using these techniques we show that operation and design parameters can be readily identified to ensure that the cascade has a superior performance to a single CSTR.</p>

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<author>Harvinder S. Sidhu et al.</author>


<category>Oscillatory Reactor</category>

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<title>Equilibrium and Optimum: How to Kill Two Birds with One Stone?</title>
<link>http://works.bepress.com/ajay_ray/1</link>
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<pubDate>Wed, 26 Mar 2008 14:43:14 PDT</pubDate>
<description>
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	<p>The concepts of equilibrium and optimum have always been placed at the heart of chemical engineering science. Their understanding is extremely important both from the academic and practical aspects. In this paper, a complete analysis of the concept of equilibrium and optimum in terms of how they are related conceptually, graphically and mathematically is provided. The analyzed problem can be considered as a ``Germinating Seed Problem (GSP)", which gives rise to a ``Growing Tree" of problems.</p>

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<author>Gregory Yablonsky et al.</author>


<category>Modeling and Optimization</category>

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