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National Energy Technology Laboratory Dirk Van Essendelft (PI) Terry Jordan, Philip Nicoletti, Tingwen Li (Team Members) Multiphase Flow Team, CSED August 13, 2015 Recent Developments and Accomplishments in C3M
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What Does C3M Bring to the User? – Easy, Intuitive, Reliable, and Graphical User Interface – Comprehensive interface between reliable sources of kinetic data and reacting, multi-phase CFD models – “Virtual Kinetic Laboratory” for quickly assessing the validity of a chemical equation sets before going to full scale, expensive models – Seamless formatting and units management for code specific implementation – Advanced Chemistry Analysis and Development Tools – Open source for collaboration and development What is C3M? C3M is Chemistry Support for the Computational Modeler 124+ User Downloads Since April 1st 100+ Version 2015 Downloads 124+ User Downloads Since April 1st 100+ Version 2015 Downloads
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Recent Developments in C3M Virtual Experimental Capability (TGA/Drop Tube)Neural Network Surrogates User Defined Chemistry 1) Select Species 2) Define Chemistry User Defined Modules
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Neural Network Pyrolysis TGA Demonstration
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Neural Network Gasification Demonstration
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Adaptive NN Training – Next Generation Technology
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User Defined Chemistry and Module Demonstration
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1.US-Canada Clean Energy Dialogue (CANMET Collaboration) – Work with CANMET to compare the Neural Network surrogate model to their existing CFD models and data – Work with CANMET to integrate the ROM based model of their PWR style test reactor and do a UQ study with it 2.Direct from Experiment to Modeling Capability – Collaborate with Advance Combustion folks – Direct from TGA to CFD capability 3.Large Model Reduction Using Neural Networks – Apply our advanced Neural Network Training Ability to large scale chemistry problems like advanced hydrocarbon combustion (many hundred step mechanisms) using and reduce them to a Neural Network that can run in a large scale CFD simulation 4.OpenFOAM Support – Write an exporter for OpenFOAM (another popular multiphase, open source CFD code) Where Do We Go from Here?
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Move From an Ad Hoc Research Code to Finalized and Polished – Check against all sources of information, units – Annotate Equation – Finalize Export Code Acts as Benchmark Point to Ensure Consistency Subtask 2.3: Verify and Finalize Existing Gasification Chemistry
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Subtask 2.3: Neural Network Surrogates Basic/Traditional C3M Limited Local Information Low Accuracy No Speed Sacrifice Unknown Error Very Litd. Complexity
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Subtask 2.3: Neural Network Surrogates Limited Domain Scale Information Limited Local Information Explicit Surrogate C3M Medium Accuracy Small Speed Sacrifice Known Error Limited Complexity
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Subtask 2.3: Neural Network Surrogates Unlimited Local Information Unlimited Domain Scale Information Reaction Rates Neural Network C3M High Accuracy Small Speed Sacrifice Known Error Unlimited Complexity
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Subtask 2.3: Neural Network Surrogates Simplified PSDF Riser Model Proof of Concept for Surrogate Implementation Functioning reacting model Not Validated, still in alpha release form
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