Parham Mobed
Texas Tech University
7 Papers
32 Citations
Parham Mobed is an academic researcher from Texas Tech University. The author has contributed to research in topics: Extended Kalman filter & Algebraic equation. The author has an hindex of 4, co-authored 7 publications. Previous affiliations of Parham Mobed include Purdue University.
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Papers
State and Parameter Estimation in Distributed Constrained Systems. 1. Extended Kalman Filtering of a Special Class of Differential-Algebraic Equation Systems
Parham Mobed,Sudhakar Munusamy,Debangsu Bhattacharyya,Raghunathan Rengaswamy,Raghunathan Rengaswamy +4 more
TL;DR: In this paper, a modified extended Kalman filter (EKF) approach is proposed to handle uncertainties in both differential and algebraic equations, and equality constraints are applied to a water gas shift reactor.
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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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Data Reconciliation and Dynamic Modeling of a Sour Water Gas Shift Reactor
TL;DR: In this article, a 1-D mathematical model of a sour water gas shift (WGS) reactor has been developed for integrated gasification combined cycle (IGCC) plants with CO2 capture.
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Very large scale droplet microfluidic integration (VLDMI) using genetic algorithm
TL;DR: A genetic algorithm optimization-based design tool for discovering very large-scale integration of discrete microfluidic networks for a given objective function and can be a significant step toward drastically cutting down on the laborious trial-and-error design process.
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Optimal Multicomponent Distillation Column Sequencing: Software and Case Studies
Radhakrishna Tumbalam Gooty,Parham Mobed,Mohit Tawarmalani,Rakesh Agrawal +3 more
- 01 Jan 2018
TL;DR: A tool is described that screens through the entire search space to identify a handful of distillation configurations that are attractive for an application and formulate a novel Mixed Integer Nonlinear Program (MINLP) using Underwood’s method to estimate the vapour duty in each column.
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