| 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 | 35 | 2022 |
| 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 | 32 | 2020 |
| 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 | 28 | 2022 |
| 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 | 19 | 2021 |
| 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 | 10 | 2022 |
| 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 | 10 | 2022 |
| 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 | 7 | 2014 |
| Causation Analysis of Pipeline Incidents Using Artificial Neural Network P Kumari, N Quddus 2020 Virtual Spring Meeting and 16th GCPS, 2020 | 2 | 2020 |
| 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 |
| 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 |
Joseph Sang-Il KwonKenneth R. Hall Associate Professor, Artie McFerrin Department of Chemical Engineering, TAMUVerified email at tamu.edu
