G
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.
Papers
More filters
Journal ArticleDOI
HiGee Stripper-Membrane System for Decentralized Bioethanol Recovery and Purification
TL;DR: In this article, the HiGee (short for high gravity) stripper combined with a membrane (HSM) process for concentrating bioethanol is compared with one of the best energy-efficient process for bio-ethanol purification in the literature.
Journal ArticleDOI
Modeling and Analysis of Hybrid Reactive Stripper-Membrane Process for Lactic Acid Recovery
TL;DR: In this paper, a hybrid reactive stripper-membrane (RSM) technology was proposed for producing lactic acid (LA) from dilute fermentation broth and its further concentration.
Journal ArticleDOI
Attainment of PI Achievable Performance for Linear SISO Processes with Deadtime by Iterative Tuning
TL;DR: In this article, the authors present a practical scheme to attain PI achievable performance (the performance achievable with a proportional integral (PI) controller) for linear SISO processes with dead time driven by stochastic disturbances.
Journal ArticleDOI
Assessment of capabilities and limitations of stochastic global optimization methods for modeling mean activity coefficients of ionic liquids
TL;DR: In this paper, the capabilities and limitations of seven stochastic global optimization methods to model mean activity coefficients of ammonium aqueous electrolytes using the electrolyte NRTL model were studied and analyzed.
Journal ArticleDOI
Mixed-Integer dynamic optimization of conventional and vapor recompressed batch distillation for economic and environmental objectives
TL;DR: A unique multi-objective mixed-integer dynamic optimization problem considering two conflicting objectives, namely, maximization of amount of product per dollar while minimizing CO2 emission is formulated and solved using the elitist non-dominated genetic algorithm for both conventionalbatch distillation and vapor recompressed batch distillation operating at constant reflux mode.