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UID:pretalx-amfc2026-FSUHEP@modelica.simtek.cc
DTSTART;TZID=CST:20260921T114000
DTEND;TZID=CST:20260921T120500
DESCRIPTION:Repeated transient simulations of Brayton cycles are often requ
 ired during parameter studies\, control assessment\, and design iteration\
 , whereas direct Modelica simulation under many conditions can remain inef
 ficient despite its flexibility for system-level dynamic modeling. A param
 etric reduced-order modeling method is developed for fast transient predic
 tion of Modelica-based Brayton cycles under unseen parameters and new oper
 ating conditions. Transient data from a Modelica model of a Helium-Xenon B
 rayton cycle are used to construct a baseline-regularized Dynamic Mode Dec
 omposition with control reduced-order model\, in which state trajectories 
 are formulated as deviations from local steady baselines and measured auxi
 liary inputs are incorporated through the control channel. A Secondary Dyn
 amic Mode Decomposition strategy is further introduced to generalize reduc
 ed-order quantities along the parameter direction. Results show accurate i
 nterpolation and stable extrapolative prediction against Modelica referenc
 e simulations\, supporting rapid transient evaluation of Brayton cycles an
 d offering a new perspective for broader fast transient prediction.
DTSTAMP:20261004T070643Z
LOCATION:Modelica Technology & AI (R1001)
SUMMARY:A Novel Parametric Reduced-Order Modeling Method for Transient Pred
 iction of Modelica-Based Brayton Cycles - Ao Zhang\, Xiang Wang
URL:https://modelica.simtek.cc/amfc2026/talk/FSUHEP/
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