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Gade Pandu Rangaiah

Researcher at National University of Singapore

Publications -  282
Citations -  6739

Gade Pandu Rangaiah is an academic researcher from National University of Singapore. The author has contributed to research in topics: Multi-objective optimization & Global optimization. The author has an hindex of 42, co-authored 277 publications receiving 5737 citations. Previous affiliations of Gade Pandu Rangaiah include Indian Institute of Technology Kanpur & Nanyang Technological University.

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Design and analysis of an ethyl benzene production process using conventional distillation columns and dividing-wall column for multiple objectives

TL;DR: In this article, a typical industrial EB process including reaction, separation and heat exchangers, is first simulated rigorously and modified to improve the efficiency and performance of both individual units and the overall plant.
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The effect of short air exposure periods on the performance of cellulose acetate membranes from casting solutions with high cellulose acetate content

TL;DR: In this article, high productive cellulose acetate (CA) membranes were cast under conditions of very short air exposure periods from celluloseacetate-acetone-formamide casting solutions having a high CA content and lying close to the phase boundary.
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Process Retrofitting via Intensification: A Heuristic Methodology and Its Application to Isopropyl Alcohol Process

TL;DR: A heuristic-based systematic methodology is developed for process retrofitting via intensification/integration that focuses on exploring integrated retrofit solutions for conventional isopropyl alcohol process.
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Retrofitting amine absorption process for natural gas sweetening via hybridization with membrane separation

TL;DR: In this paper, an amine absorption process, which removes acid components from natural gas, is retrofitted by adding a membrane unit(s) to sweeten a new feedstock with increased CO2 mole fraction from 0082 to 020.
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A Time Delay Compensation Strategy for Uncertain Single-Input Single-Output Nonlinear Processes

TL;DR: In this article, a new time delay compensation strategy for single-input single-output nonlinear processes subject to modeling uncertainty is proposed to reduce the effect of modeling errors on the performance and robustness.