339 Interactive Session: Data and Information Systems

Friday, November 20, 2020: 8:00 AM - 9:00 AM
Computing and Systems Technology Division (10) (Poster Gallery)

Description:
This session solicits posters in the broad area of Data and Information Management in the chemical engineering domain. Abstracts describing methods, applications, challenges, and tools are all welcome.

Sponsor:
Information Management and Intelligent Systems
Co-Sponsor(s):
Poster Sessions (POSTERSESSIONS)
Chair:
Bethany Nicholson Email: blnicho@sandia.gov


(339a) Fast, Efficient & Reliable Chemical Properties Estimation through a New Class of Software Tools
Nichakorn Kuprasertwong, Arisa Robin, Orakotch Padungwatanaroj, Surat Areerat, Anjan Kumar Tula, Lei Zhang and Rafiqul Gani


(339c) Chemical Process Fault Diagnosis Approach Based on Graph Convolutional Network
Deyang Wu and Jinsong Zhao


(339e) Systematic Multivariate Analysis (sMVA) Strategy for Improved Process Understanding of Industrial Biorefinery Processes with Applications in Fatty Acid Production
Pieter Nachtergaele, Joris W. Thybaut, Steven De Meester, David Drijvers, Wouter Saeys and Jo Dewulf


(339f) Data-Driven Optimization of Integrated Planning and Scheduling Problems Under Demand Uncertainty
Burcu Beykal, Styliani Avraamidou and Efstratios N. Pistikopoulos


(339h) Mechanism Discovery and Model Identification Using Genetic Feature Extraction and Statistical Testing
Abhishek Sivaram, Arijit Chakraborty, Lakshminarayanan Samavedham and Venkat Venkatasubramanian


(339i) Development of AI Platform Based on Machine Learning for Separation Process
Hyundo Park, Hyukwon Kwon, Il Moon, Hyungtae Cho and Junghwan Kim


(339j) Optimal Communication Topologies for Particle Swarm Optimization Under Hostile Environments
Vipul Mann, Abhishek Sivaram, Laya Das and Venkat Venkatasubramanian


(339l) Development of Data Based Prediction Model for Yield and Composition of Distillate from Vdu Process
Yo Sung Yoon and Jay H. Lee


(339m) Modeling the Impact of Environmental Toxicants on the Estrogen Receptor Using Combined Image-Analysis, Big-Data Analytics, and Machine-Learning
Hari S. Ganesh, Burcu Beykal, Adam T. Szafran, Fabio Stossi, Fred A. Wright, Lan Zhou, Michael A. Mancini and Efstratios N. Pistikopoulos


(339n) Machine Learning Models for Water Use Patterns Analysis in Small Rural Agricultural Communities for Informed Design and Deployment of Membrane-Based Water System
Bilal Khan, Jin Yong Choi, Anditya Rahardianto, Zhou Yang and Yoram Cohen


(339p) Fault Detection and Diagnosis in Refinery Operations: A Case Study on Rotating Equipment and Continuous Catalytic Reforming Unit
Cagla Odabasi, Pelin Dologlu, Gizem Kusoglu, Mert Urus, Omer Yurttas, Murat Kulahci and Ahmet Palazoglu


(339q) Supply Chain Monitoring Based on Principal Component Analysis
Jing Wang, Christopher L. E. Swartz and Kai Huang


(339s) A Self-Labeled Deep Learning Method for Semi-Supervised Chemical Process Fault Diagnosis
Shaodong Zheng and Jinsong Zhao


(339t) Early Identification of Process Deviation Based on the Statistical Feature of Prediction Residuals
Fangyuan Ma, Dexi Lin, Mingyang Xu, Cheng Ji, Jingde Wang and Wei Sun


(339u) A Data-Driven Process Monitoring and Fault Diagnosis Method for Multi-State Industrial Process Operations
Cheng Ji, Fangyuan Ma and Wei Sun
See more of this Group/Topical: Computing and Systems Technology Division
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