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DEMO.m
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DEMO.m
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%%% project: morgen - Model Order Reduction for Gas and Energy Networks
%%% version: 1.2 (2022-10-07)
%%% authors: C. Himpe (0000-0003-2194-6754), S. Grundel (0000-0002-0209-6566)
%%% license: BSD-2-Clause (opensource.org/licenses/BSD-2-clause)
%%% summary: Basic demonstration of simulation and model reduction.
morgen('pipeline', ... % Network
'day', ... % Scenario
'ode_end', ... % Model
'imex1', ... % Solver
{ ... % Reductors:
'pod_r', ... % Proper Orthogonal Decomposition (Reachability-Based)
'eds_ro_l', ... % Empirical Dominant Subspaces (Reachability-Observability-Based) Primal-Dual Variant
'eds_wx_l', ... % Empirical Dominant Subspaces (Minimality-Based) Primal-Dual Variant
'eds_wz_l', ... % Empirical Dominant Subspaces (Averaged-Minimality-Based) Primal-Dual Variant
'bpod_ro_l', ... % Balanced Proper Orthogonal Decomposition (Reachability-Observability-Based) Primal-Dual Variant
'ebt_ro_l', ... % Empirical Balanced Truncation (Reachability-Observability-Based) Primal-Dual Variant
'ebt_wx_l', ... % Empirical Balanced Truncation (Minimality-Based) Primal-Dual Variant
'ebt_wz_l', ... % Empirical Balanced Truncation (Averaged-Minimality-Based) Primal-Dual Variant
'gopod_r', ... % Goal-Oriented Proper Orthogonal Decomposition (Reachability-Based)
'ebg_ro_l', ... % Empirical Balanced Gains (Reachability-Observability-Based) Primal-Dual Variant
'ebg_wx_l', ... % Empirical Balanced Gains (Minimality-Based) Primal-Dual Variant
'ebg_wz_l', ... % Empirical Balanced Gains (Averaged-Minimality-Based) Primal-Dual Variant
'dmd_r', ... % Dynamic Mode Decomposition Galerkin (Reachability-Based)
}, ... % Ad-hoc configuration:
'dt=10', ... % Use 10s time-steps
'ord=50', ... % Maximum reduced order 50 (computation and evaluation)
'compact'); % Make compact plot instead of individual plots