2024 AIChE Annual Meeting

Session: Interactive Session: Data and Information Systems

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.

Chair

You, F., Cornell University

Co-Chairs

Papathanasiou, M., Imperial College London

Presentations

(375a) Physics-Informed Estimation of Thermodynamic Parameters of Biodiesel Production from Enteromorpha Compressa Microalgae
(375ab) Enhancing Li-Ion Battery Remaining Useful Life Prediction with a Physics-Constrained Bayesian Recurrent Neural Network
(375g) Fast, Accurate Process Monitoring Based on Multi-Block Mutual Information and Nonparametric Statistical Process Control
(375m) Leveraging Knowledge Synthesis and Transfer Learning in Photo-Bioproduction for Enhanced CO2 Capture and Upcycling
(375j) Probabilistic Distribution Reconstruction Model for Few-Shot Fault Monitoring in Chemical Processes
(375h) Online Fault Detection and Diagnosis of Industrial Processes Via Data Augmentation and Integrative Learning of Process Knowledge and Fault Propagation Map
(375c) Can Transfer Learning Assist in Resolving Missing Data for Enhanced Data-Driven Optimization ?
(375w) Symbolic Regression-Based Recursive Surrogate Model for a Manufacturing Process
(375ae) Policy Development for a Mobile Robot to Search for the Source of a Chemical Plume in an Urban Environment
(375z) Optimizing CO2 Utilization Efficiency through Physics-Informed Modeling of Membrane Reactors
(375f) Time Delayed Cointegration Analysis for Non-Stationary Process Monitoring
(375t) Neural Network Analysis of NMR and IR Spectra
(375ai) Data-Driven Multi-Objective Optimization for Canister Sampling Site Selection
(375e) Cyber-Attack Detection and Resilient Control Using Physics-Informed Machine Learning
(375d) A Distributed Data-Driven Predictive Modeling Approach for Cyber-Process Incident Identification Using Spectral Community Detection
(375p) Quantitative Evaluation of Catalyst Shape in SEM Images Using Gan and Semi-Supervised Semantic Segmentation
(375l) Harnessing the Power of Llms to Disentangle Complex Metabolic Models and Regulatory Networks
(375x) Prediction of Mineral Scale Formation in Bakken-Using Machine Learning
(375k) Towards a Thrombosis Detection System Based on High-Frequency Central Venous Pressure Data
(375r) Offline Rl for Optimal Bioprocess Production Scheduling
(375y) Enhancing Electrochemical Deionization Optimization through Integrated Physics and Machine Learning Models
(375ag) A Pre-Train and Fine-Tune Paradigm of Fault Prognosis for Chemical Process
(375n) Large Language Models for Discovering Equations
(375s) Artificial Intelligence (AI) for Oil & Gas Upstream Processes, KPIs and Potential Savings
(375q) Contrastive Learning to Improve Pharmaceutical Knowledge Graph Quality in Machine Learning
(375i) Detection of Faults in Multi-Modal Plant Operation Via Latent Space Models Based on First-Principles Plant Models
(375aa) Simultaneous Optimization Via Physics-Informed Neural Network Solvers with Compartment Models for Reactor Design
(375b) Artificial Intelligence-Based Bacteria Species Distinction Based on Raman Microscopy.
(375v) Machine Learning, Modelling, and Simulation for Problem-Solving in the Hydrogen Production Process
(375u) Time-Series Multiscale Computational Fluid Dynamics Data Modeling with Transformers for Atomic Layer Processing
(375o) Modelling Local Steady-State and Time-Dependent Reactive Dynamics in Porous Media By Multiscale Neural Networks