2024 AIChE Annual Meeting

Session: 10B: Interactive Session: Systems and Process Control

This poster session showcases contributions pertaining to the development of new process control methods and/or the application of control methods to novel processes and industrial applications. It also welcomes contributions related to the application of AI/ML technologies for control and estimation.

Chair

Co-Chairs

Durand, H., Wayne State University
Shah, U., The Ohio State University

Presentations

(372r) Numerical Investigation into the Gasification of Industrial Organic Waste in Entrained-Bed Reactors Utilizing Detailed Chemical Kinetic Mechanisms
(372ab) Development of a Model Based on Deep Reinforcement Learning, Lstm Network, and TD3 Algorithm for Optimization and Control of MAb Production in Mammalian Cell Cultures
(372l) Accelerating Formulation Discovery Using First-Principles Hansen Solubility Parameter (HSP) and Optimization
(372y) Invertible Neural Networks As Discrete Time Process Models for Correlated Non-Gaussian Noise
(372k) Development of a Black-Box Parameter Estimation Methodology of a Batch Anti-Solvent Protein Crystallisation Process with Sparse Measurements
(372j) Digital Integration of Fermentation and Centrifugation Processes: Optimizing Pilot-Plant Biomanufacturing for Enhanced Efficiency
(372t) Data-Driven Approach to Automated Reaction Process Analysis
(372am) Learning Production Planners’ Unknown Objectives Via Inverse Optimization
(372u) Learning a Data-Driven Reactor Model from Experimental Data of a Continuously Operated Fixed-Bed CO2 methanation Reactor on Pilot-Scale
(372q) Multiscale Modelling of Trickle Bed Reactors for Biological Methanation
(372p) A Novel Bidding Methodology for Power Trading in a Local Energy Market
(372n) Development of a Curie Pendulum-Based, Non-Electrical Temperature Control for Thermal Cyclers
(372w) Design of Experiments Based on Precise Data-Quality Assessment Using Finite-Sample Data
(372af) Scheduling of State Task Network Under Uncertainty Via a Hybrid Reinforcement Learning Agent with Partial Observability
(372aa) Fixed/Mobile Detector Placement Optimization and Validation System Using Differentiable Physics-Based Surrogate Models for Chemical Leak Dispersions
(372c) Adaptive Model Predictive Control for Optimal Irrigation Scheduling
(372s) Data-Driven Model for Boil-Off Gas Estimation in a Liquefied Natural Gas Regasification Terminal
(372e) Encrypted Distributed Control of Nonlinear Processes
(372ag) Variable Extraction and Equivalence Judgment with BERT Model Pre-Trained on Chemical Engineering-Related Papers
(372d) Explicit Machine Learning-Based Model Predictive Control of Nonlinear Processes
(372ac) Using Artificial Neural Networks to Predict Chemical System Stability for Design
(372ah) Similarity-Based Machine Learning for Small Datasets; Application in Predicting Bio-Lubricant Properties
(372o) Optimizing Affordable Electrified Multifamily Housing: A Novel Non-Cooperative Stackelberg Game Approach for Grid Profitability and Tenant Affordability
(372v) Causality-Guided Observer Model Minimization of an Acetaminophen Chemical Production Process
(372a) Automation and Control of Continuous Countercurrent Tangential Chromatography
(631b) Process Modeling and Optimal Operational Strategies for Integrated Chemical Looping Hydrogen Production and Biomass Gasification Under Feedstock Uncertainty
(372z) Time Series Modelling of an Industrial Desiccant Dryer
(372al) Pinn-Based Modular Digital Twin Development for Sustainable Electroplating Manufacturing
(372ad) Leveraging Large Language Models for the Identification, Annotation, and Substrate Prediction of Transporter Proteins
(372h) Understanding and Modeling Corrosion in CO2 Transportation Pipelines: Findings from the Carbon Adapt Project
(372b) Battery Thermal Management of Electric Vehicles through Optimal Control of Battery Cooling and Refrigerant Circuits
(372g) Learning Based Real-Time Batch Tracking of Multi-Product Pipeline Systems