AT model
AT model
AT model
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Approach<br />
Motivation<br />
Challenges<br />
Approach<br />
Methodology<br />
MV Modeling<br />
Detailed<br />
Modeling<br />
NN Modeling<br />
RT Enabled<br />
High Fidelity<br />
Integration<br />
CPU<br />
Comparison<br />
Conclusion<br />
• Construct sub-<strong>model</strong>s of varying levels of<br />
accuracies and numerical efficiencies<br />
– Mean value Model<br />
– Neural Network (NN) <strong>model</strong><br />
– Detailed <strong>model</strong><br />
• Making these sub-<strong>model</strong>s suitable for mix<br />
and match strategy<br />
• Making data exchange/coupling<br />
transparent<br />
5
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