R
Raghunathan Rengaswamy
Researcher at Indian Institute of Technology Madras
Publications - 225
Citations - 10538
Raghunathan Rengaswamy is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Proton exchange membrane fuel cell & Fault detection and isolation. The author has an hindex of 39, co-authored 210 publications receiving 9632 citations. Previous affiliations of Raghunathan Rengaswamy include Indian Institute of Technology Bombay & Bosch.
Papers
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Actuator network design to mitigate contamination effects in Water Distribution Networks
TL;DR: The design problem considered in this work is to determine pipes where the shut-off valves can be optimally located such that it is possible to prevent the contaminated water from reaching any demand point, regardless of the source node from where the contamination has originated.
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A Novel Interval-Halving Algorithm for Process Trend Identification
TL;DR: This paper proposes a novel approach to automatically identify the qualitative shapes of trends using an interval-halving based polynomial-fit technique that is illustrated on both simulated and industrial data.
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Metabolic modeling of host–microbe interactions for therapeutics in colorectal cancer
Prerna Bhalla,Raghunathan Rengaswamy,Devarajan Karunagaran,G. K. Suraishkumar,Swagatika Sahoo +4 more
TL;DR: In this paper , a detailed system-level understanding of ROS metabolism in Enterococcus durans (E. durans ), a representative gut microbe, was gained using constraint-based modeling, wherein, the critical association between ROS and folate metabolism was established.
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Optimal Sensor Placement for Fault Diagnosis Using Magnitude Ratio
TL;DR: In this paper, the authors proposed an algorithm for identifying the optimal number, type, and location of sensors for fault detection and diagnosis in large-scale, chemical process plants using signed directed graph (SDG) models.
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Droplet digital signal generation in microfluidic networks using model predictive control
TL;DR: In this article, the authors explore the ability of the MPC framework for more intricate control, where the relative drop distances at the exit of a loop are required to conform to desired profiles.