Member activity: Spring 2017 to present
Research
Risk analysis for rare events: Study of dependence of control layers for rare events and its application to dynamic risk assessment
Process variable upsets in a process operation is caused by different sources, such as variation in feed specifications, wrong settings, control system malfunctions and operator error. These upsets leads to unprofitable process operation due to production of sub-quality products and increased energy usage resulting from a deviated process variable, and subsequently to near miss or incidents if not stopped by control layers and safety system in place. The near misses or incidents are the outliers originating from the failure of control layers. This project first aims to identify the significant process variable associated with an incidents, and then study the dependence of control layers for the identified process variable upset in outlying region and predict the frequency and probability of near misses based on that.
Education
- B.Tech – M.Tech Dual Degree, Chemical Engineering, IIT Kanpur, Kanpur, India, 2014
Presentations
Pallavi Kumari, M. Sam Mannan, and Nazmul Karim, “Joint Probability Density Estimation for Complex Variables and Its Application to Dynamic Risk Assessment Using Bayesian Method,” 2018 Spring Meeting and 14th Global Congress on Process Safety