Suivre
PALLAVI KUMARI
Titre
Citée par
Citée par
Année
A modified Bayesian network to handle cyclic loops in root cause diagnosis of process faults in the chemical process industry
P Kumari, B Bhadriraju, Q Wang, JSI Kwon
Journal of Process Control 110, 84-98, 2022
522022
An integrated risk prediction model for corrosion-induced pipeline incidents using artificial neural network and Bayesian analysis
P Kumari, SZ Halim, JSI Kwon, N Quddus
Process Safety and Environmental Protection 167, 34-44, 2022
472022
Root cause analysis of key process variable deviation for rare events in the chemical process industry
P Kumari, D Lee, Q Wang, MN Karim, J Sang-Il Kwon
Industrial & Engineering Chemistry Research 59 (23), 10987-10999, 2020
392020
Development of parametric reduced-order model for consequence estimation of rare events
P Kumari, B Bhadriraju, Q Wang, JSI Kwon
Chemical Engineering Research and Design 169, 142-152, 2021
262021
A unified causation prediction model for aboveground onshore oil and refined product pipeline incidents using artificial neural network
P Kumari, Q Wang, F Khan, JSI Kwon
Chemical Engineering Research and Design 187, 529-540, 2022
192022
A Direct Transfer Entropy-Based Multiblock Bayesian Network for Root Cause Diagnosis of Process Faults
P Kumari, Q Wang, F Khan, JSI Kwon
Industrial & Engineering Chemistry Research 61 (43), 16166-16178, 2022
142022
Control system design for energy efficient On-Target product purity operation of a High-Purity petlyuk column
P Kumari, R Jagtap, N Kaistha
Industrial & Engineering Chemistry Research 53 (42), 16436-16452, 2014
82014
Causation Analysis of Pipeline Incidents Using Artificial Neural Network
P Kumari, N Quddus
2020 Virtual Spring Meeting and 16th GCPS, 2020
22020
Discovery of Cyclic Loops in Bayesian Network for Root Cause Diagnosis of Process Faults
P Kumari, P Shah, Q Wang, F Khan, J Kwon
2022 AIChE Annual Meeting, 2022
2022
A Comprehensive Causation Prediction Model of Pipeline Incidents Using Artificial Neural Network
P Kumari, Q Wang, F Khan, J Kwon
2022 AIChE Annual Meeting, 2022
2022
Handling cyclic loops for accurate root cause diagnosis of rare events in chemical processes using modified Bayesian network
P Kumari, B Bhadriraju, Q Wang, JSI Kwon
2022 American Control Conference (ACC), 4292-4297, 2022
2022
Consequence Estimation and Root Cause Diagnosis of Rare Events in Chemical Process Industry
P Kumari
Texas A&M University, 2022
2022
Development of Computationally Efficient Dynamic Model to Estimate Consequence of Rare Events
P Kumari, B Bhadriraju, Q Wang, J Kwon
2021 AIChE Annual Meeting, 2021
2021
A Modified Bayesian Network to Handle Cyclic Causal Network in Root Cause Diagnosis of Rare Events
P Kumari, Q Wang, J Kwon
2021 AIChE Annual Meeting, 2021
2021
How Well CAN WE Predict Causes behind the Pipeline Incidents?
N Quddus, G Liu, M Boyd, M Yu, C Son, P Kumari
2021 AIChE Virtual Spring Meeting and 17th Global Congress on Process Safety, 2021
2021
Root Cause Analysis of Process Faults Using Penalized Piecewise Linear Multiple Birth Support Vector Machine (pPWL-MBSVM)
P Kumari, Q Wang, J Kwon
2020 Virtual AIChE Annual Meeting, 2020
2020
Root Cause Analysis of Key Process Variable Deviation for Rare Events
P Kumari, D Lee, Q Wang, MN Karim, JSI Kwon
2020 AIChE Spring Meeting & 16th Global Congress on Process Safety, 2020
2020
Development of a Prediction Model of Pipeline Failure Probability Using Artificial Intelligence
N Quddus, P Kumari, G Liu, M Boyd, J Holste
2020 PHMSA Pipeline Safety Research and Development Forum, Arlington, VA, 2020
2020
Risk Analysis of Rare Events By Modified Hierarchical Bayesian Modeling (mHBM)
P Kumari, N Karim
2019 Spring Meeting and 15th Global Congress on Process Safety, 2019
2019
Joint Probability Density Estimation for Complex Variables and Its Application to Dynamic Risk Assessment Using Bayesian Method
P Kumari, MS Mannan, N Karim
2018 AIChE Spring Meeting and 14th Global Congress on Process Safety, 2018
2018
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