PR 4/7: Pyomo multi-period DAE model#9
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bernalde wants to merge 1 commit intopr/pyomo-utils-singlestepfrom
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PR 4/7: Pyomo multi-period DAE model#9bernalde wants to merge 1 commit intopr/pyomo-utils-singlestepfrom
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This was referenced Mar 3, 2026
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This PR adds the core multi-period Pyomo model: lyopronto/pyomo_models/model.py (640 lines): - Multi-period differential-algebraic equation (DAE) formulation - Orthogonal collocation discretization for time integration - Physics constraints: vapor pressure, sublimation rate, heat transfer - Equipment capability constraints - Product temperature limits - Variable scaling for numerical stability - Support for both Tsh and Pch optimization Key features: - Uses Pyomo DAE transformations from IDAES - Implements same physics as scipy-based calculators - Warmstart from scipy solution for faster convergence - Configurable time discretization (number of periods) Tests (4 files): - test_model_multi_period.py: Multi-period model construction - test_model_advanced.py: Advanced model features - test_model_validation.py: Input validation - test_physics_equations.py: Physics equation verification This is the core model used by the optimizer functions (PR 5).
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Summary
Full trajectory optimization model. Discretizes the drying process into multiple time periods, encoding the physics (vapor pressure, product resistance, energy balance, mass transfer) as Pyomo constraints. Supports both finite-difference and collocation discretization. Log-transform for vapor pressure to avoid numerical issues with exponentials.
PR 4 of 7 in the Pyomo integration series.
Changes
lyopronto/pyomo_models/model.py— Full multi-period DAE modeltests/test_pyomo_models/test_model_multi_period.py— Multi-period tests (741 lines)tests/test_pyomo_models/test_model_advanced.py— Advanced model teststests/test_pyomo_models/test_model_validation.py— Validation against scipytests/test_pyomo_models/test_physics_equations.py— Physics equation testsKey Physics Encoded as Constraints
PR Chain
Testing
~2075 lines of new tests covering model construction, discretization, physics constraints, and validation against scipy baseline.