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πŸ’» Process Simulation and Digital Twins - Complete Guide

Use of computational tools to model, optimize, and monitor chemical processes in real time and virtual environments.

14
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Interactive Tools
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Case Studies
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Resources
22
Lessons
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Process Simulation and Digital Twins - Complete Guide

Process simulation and digital twins are like building a virtual copy of a chemical plant on a computerβ€”so engineers can...

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Quick Start

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Knowledge Base

14 pages
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Key Concepts

Process Simulation
and Digital TwinsFirst-Principles vs.Data-Driven ArchitecturesDynamic Process Modeling
with DAEs & ODE Solvers
Real-Time Data Integration:OPC UA, MQTT, Edge-to-CloudModel Calibration:Kalman, Bayesian InferenceThermodynamic PropertyEstimation (Multiphase)Surrogate Modeling:GP, Polynomial ChaosV&V Framework:ASME V&V 40 / ISO 5607Cybersecurity forIndustrial Digital Twins

Visual overview of key concepts and their relationships

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Real Projects

3 cases

Pharmaceutical Batch Reactor Deviation Mitigation (FDA-Approved Twin)

End-to-end digital twin for API crystallization suite at a GMP facility

Challenge: Batch-to-batch variability causing 12% reject rate and regulatory scrutiny
FCC ReactorRegeneratorMulti-Physics Twin(Reactor + Regen + Catalyst Flow)Unplanned Shutdowns17 hrs/unit/yrCost per Event$1.2MΔṁ_cat = +4.2 t/hβˆ‡T = βˆ’82Β°CUKF State Estimation Embeddedβœ“ Real-time Correction

Refinery FCC Unit Predictive Maintenance Twin

Digital twin deployment across 4 fluid catalytic cracking units in Texas Gulf Coast refinery

Challenge: Unplanned shutdowns averaging 17 hrs/unit/yr costing ~$1.2M each
Bioreactor Scale-Up Twin for Cell Therapy Manufacturing Challenge: Viability loss >30% & inconsistent glycosylation Lab Scale V = 2 L Production Scale V = 200 L CFD-Metabolic Twin Monod + kLa Corr. Tracer Studies Off-Gas Analysis Scaling Metrics kLa ∝ (P/V)⁰·⁴·N⁰·⁡ = 0.78 Ο„β‚˜β‚β‚“ = 10·ρ·NΒ²Β·DΒ² = 1.4 Pa

Bioreactor Scale-Up Twin for Cell Therapy Manufacturing

Closed-system bioreactor digital twin supporting clinical-to-commercial scale-up (5 L β†’ 200 L β†’ 2,000 L)

Challenge: Loss of viability (>30%) and inconsistent glycosylation profiles during scale-up
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Downloads

6 resources
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Learning Path

22 lessons

Master Process Simulation and Digital Twins through a structured learning path β€” from fundamentals to advanced applications.

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