2023 AIChE Annual Meeting

Session: Interactive Session: Data and Information Systems

Chair

Salvador García-Muñoz, Eli Lilly and Company

Co-Chair

Maria Papathanasiou, Imperial College London

Presentations

03:30 PM

(59am) Self-Optimizing Control Methodology Using Surrogate Models for Complex Systems: A Jupyter-Based Application for Flexible Exploration and Adjustment
Heleno Bispo, Antônio Tavernard, Marcilio Maximo, Herbert Teixeira
(59c) Towards an Integrated Approach for Upstream Field Recovery
Shakeel Ramjanee
(59o) Development of Algorithms for Mass and Energy Constrained Dynamic Neural Network Models
Angan Mukherjee, Debangsu Bhattacharyya
(59t) Improving Industrial-Scale Bioreactor Performance: Development and Validation of Computationally Efficient Compartment-Based Models Using Real Plant Data
Parth Shah, Joseph Kwon
(59z) Combined Use of Recursive Neural Network (RNN), Convolutional Neutral Network (CNN), and Attention Mechanism on Cycling Data of Lithium Ion Battery for Lifespan Prediction
Jay Hyung Lee, Jaewook Lee
(59an) Chemical Substance Diagnosis System Based on Knowledge Inference and Machine Learning for Chemical Exposure Symptoms
Kangseop Kim, Dongil Shin
(59p) Design of Microfluidic Chromatographs through Reinforcement Learning
Mohammad Shahab, Raghunathan Rengaswamy
(59d) Hybrid Bayesian-Based Surrogate Optimization for Sustainable Process Design within Planetary Boundaries
Sachin Jog, Daniel Vázquez, Lucas Francisco Dos Santos, Jose A. Caballero, Gonzalo Guillén-Gosálbez
(59y) Optimal Sensor Network Design for Maximizing Net Present Value and Its Application to Corrosion Monitoring in a Power Plant
Chandra Sekhar Somayajula, Debangsu Bhattacharyya, Xingbo Liu, Shanshan Hu
(59aa) Adversarial Data in Demand Side Management
Eike Cramer
(59ao) Augmented Control Using Reinforcement Learning and Conventional Process Control
Debangsu Bhattacharyya, Daniel Beahr, Douglas A. Allan, Stephen Zitney
(59e) Probabilistic Lifespan Prediction of Lithium-Ion Batteries Under Varying Operating Protocols Using Gaussian Process Regression
Seyeong Park, Jaewook Lee, Jay Hyung Lee
(59ap) Intelligent Size Characterization of Granules By Machine Learning Method
Mehrdad Khakbiz, Maryam Rezaeizadeh, Gerardo Callegari, Fernando Muzzio
(59f) Automated Synthesis of Hybrid Models for Ionic Separations
Luis Briceno-Mena, Teslim Olayiwola, Christopher Arges, Tanmay Kulkarni, Revati Kumar, Jose A. Romagnoli
(59ar) Designing pH-Temperature Responsive Microgels with Targeted Transition Temperature Using a Novel Partial Least Squares (PLS) Model Inversion Technique
Prashant Mhaskar, Todd Hoare, Seyed Saeid Tayebi
(59as) Prediction of Chemical Toxicity and Exposure Symptoms Based on Knowledge Graph Embedding and Language Models
Kangseop Kim, Dongil Shin, Young Min Jung, Jinkyung Son
(59b) Real-Time Fault Detection Models for Smart Manufacturing: A Case Study with Heat Exchanger Equipment and Innovation Platform
Lucky Yerimah, Mrunal Sontakke, Andreas Rebmann, Sambit Ghosh, Ronald Hedden, B. Wayne Bequette
(59ab) Generalization Error Bounds for Neural Networks Modeling Two-Time-Scale System Dynamics with Application to Model Predictive Control of Nonlinear Processes
Aisha Alnajdi, Atharva Vijay Suryavanshi, Fahim Abdullah, Panagiotis Christofides
(59at) Data-Driven Adaptive Sparse Identification of Time-Varying Nonlinear Dynamics for 2,3-Bdo Distillation Column
Yeongryeol Choi, Bhavana Bhadriraju, Hyungtae Cho, Jongkoo Lim, Il Moon, Joseph Kwon, Junghwan Kim
(59g) Modeling and Predictive Control of Hybrid Dynamical Systems Using Machine Learning Methods
Zhe Wu, Cheng Hu, Ming Xiao
(59s) Investigating the Effects of Tunable Experimental Parameters on hiPSC-Cms Maturation Via Clustering Techniques
Shenbageshwaran Rajendiran, Selen Cremaschi
(59ac) Control Lyapunov-Barrier Function-Based Safe Reinforcement Learning for Nonlinear Optimal Control
Zhe Wu, Yujia Wang
(59ad) Reinforcement Learning (RL)-Based Process Controller Design: An Implementable Approach
Hesam Hassanpour, Prashant Mhaskar, Brandon Corbett, Xiaonian Wang
(59a) Measure This, Not That: Pareto Optimal Trade-Offs between Model-Based Information Content and Measurements Cost (Poster corresponding to plenary presentation)
Jialu Wang, Alexander Dowling
(59ae) Efficient Hybrid Modeling and Sorption Model Discovery for Non-Linear Advection-Diffusion-Sorption Systems: A Systematic Scientific Machine Learning Approach
Vinicius Viena Santana, Erbet Costa, Carine Rebello, Ana M. Ribeiro, Christopher Rackauckas, Idelfonso Nogueira
(59h) Smells like AI: Harnessing Machine Learning for Advanced Olfactory Experience Reproduction and Odorant Optimization
Vinicius Viena Santana, Bruno Rodrigues, Sandris Murins, Idelfonso Nogueira, Nadia Shardt
(59af) Using Artificial Neural Networks for Real-Time Tuning of PID Controllers
Tate Bestwick, Kyle V. Camarda
(59i) A Novel Recurrent Neural Network for Hydroprocessing Unit Modeling Using Neural Circuit Policies and Attention-Based Encoder-Decoder
Shu-Bo Yang, Zukui Li
(59j) A Parametric Cost Function Approximation Algorithm for Multiscale Decision-Making
Kaiyu Cao, Can Li, Asha Ramanujam
(59ag) Chemistry-Aware Retrosynthesis and Forward Reaction Prediction Using Smiles Grammar Tree Transformer
Vipul Mann, Kevin Zhang, Venkat Venkatasubramanian
(59ah) Control Invariant Set Enhanced Reinforcement Learning for Process Control: Improved Sampling Efficiency and Guaranteed Stability
Song Bo, Yin Xunyuan, Jinfeng Liu
(59k) Data-Driven Linear Predictive Control of Nonlinear Processes Based on the Reduced-Order Koopman Operator
Xuewen Zhang, Xunyuan Yin, Minghao Han
(59ai) A Comprehensive Decision Making and Networking Facility for the Biorefining Community
Edlira Kalemi, Franjo Cecelja
(59w) Automating the Discovery of Reaction Networks for Complex Reaction Systems from Spectroscopic Measurements
Karthik Srinivasan, Vinay Prasad
(59l) Modelling of Non-Conventional Streams in the Context of Circular Economy-the Case of Hydrothermal Liquefaction
Antonios Kokosis
(59x) Data-Driven Supply Chain Monitoring Based on Canonical Variate Analysis
Jing Wang, Christopher Swartz, Kai Huang
(59m) Data Embedding and Hybrid Modeling for Industrial Fluid Catalytic Cracking
Antonios Kokosis, Dimitrios Blitas
(59ak) Structure-Based Prediction of Kinase Activation amidst a Varied Mutational Landscape Using Privileged Learning
Yiming Wang, Ravi Radhakrishnan, Cesar de la Fuente-Nunez, Jonathan Nukpezah, Zhangtao Chen, Fangping Wan
(59n) A Graph Attention Network Based Approach for Interpretable and Domain-Aware Modeling of a Wellhead Water Treatment System
Jasmine Sekhon
(59u) Learning Dynamical Process Models Using Plant Data: A Real-World Case Study in the Sustainable Manufacturing of Insulation Products
Mayuresh Kothare, Siddharth Prabhu, Srinivas Rangarajan