Workflow for Building and Analyzing Machine Learning Models based on Rigorous Flowsheet Simulations - Simulate 365

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DWSIM Tutorials: We have selected the top-10 DWSIM tutorials from YouTube for you

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Hypothetical compounds
Multicomponent distillation
Shell and Tube Heat Exchanger
Custom Property Package
Custom Unit Operation
Continuous Stirred Tank Reactor (CSTR)
Pressure Swing Azeotropic Distillation (PSAD)
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Flowsheet Copilot
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AI-Based Supervision for a Stirred Extraction Column Assisted with Population Balance-Based Simulation
Ammonia Syngas Plant: Process Improvement Using Multi-Input-Multi-Output (MIMO) Surrogate Models
Workflow for Integrating Surrogate Models into a Complex Flowsheet
Python in Chemical Process Simulation
Python in Chemical Process Simulation
Python in Chemical Process Simulation
Workflow for Building and Analyzing Machine Learning Models based on Rigorous Flowsheet Simulations
Plant-Wide Optimization Using Multivariate Sensitivity Studies
Explaining and Integrating Machine LearningModels with Rigorous Simulation
Motivation Through Practical Relevance – Didactic Benefits of Process Simulators
Dynamic Optimization with a Flowsheet Simulator Using the Example of Minimization of Product Changeover Times
A Blueprint for Software Architectures in Process Optimization
Motivating Students through Practice-Oriented Challenges – Didactic Behind the Flowsheet Simulators
„Ist das jetzt der optimale Prozess?” fragte der Kaufmann. „Vermutlich nicht” antwortete der Ingenieur.

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AI in Process Simulation 28.03.2023

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Workflow for Building and Analyzing Machine Learning Models based on Rigorous Flowsheet Simulations

Schöneberger, Jan C.; Fricke, Armin (2021): Workflow for Building and Analyzing Machine Learning Models based on Rigorous Flowsheet Simulations. 13th European Congress of Chemical Engineering and 6th European Congress of Applied Biotech-nology. DECHEMA, 21.09.2021.

Explaining_and_Integrating_Machine_Learning_Models

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