MOSAIC a web-based modeling environment for code generation

Kuntsche, Stefan; Barz, Tilman; Kraus, R.H.; Arellano‐García, Harvey; Wozny, Günter

doi:10.1016/j.compchemeng.2011.03.022

Cited by 42 publications

(24 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both models are formulated in the web-based modeling environment MOSAIC (Kuntsche et al, 2011). MOSAIC's language specificator is used to automatically export the optimization problem to AMPL using IPOPT (W€ achter and Biegler, 2005) as a solver.…”

Section: Modelingmentioning

confidence: 99%

Optimization during the process synthesis: enabling the oxidative coupling of methane by minimizing the energy required for the carbon dioxide removal

Esche

Müller

Song

et al. 2015

Journal of Cleaner Production

View full text Add to dashboard Cite

Section: Modelingmentioning

confidence: 99%

Optimization during the process synthesis: enabling the oxidative coupling of methane by minimizing the energy required for the carbon dioxide removal

Esche

Müller

Song

et al. 2015

Journal of Cleaner Production

View full text Add to dashboard Cite

“…Further specifications on how models are entered and stored inside MOSAIC have already been presented in previous publications , , . An important remark has to be made at this point: all model elements inside MOSAIC except for the external function calls can be transcribed into sets of equations.…”

Section: Workflowmentioning

confidence: 99%

“…MOSAIC has been under development at the Process Dynamics and Operations Group at Technische Universität Berlin for several years. Its original purpose was as a modeling tool at the documentation level . Models in MOSAIC consist of collections of equations and functions, which are entered by the user in LaTeX and stored in MathML.…”

Section: Motivation and Introductionmentioning

confidence: 99%

MOSAIC – Enabling Large‐Scale Equation‐Based Flow Sheet Optimization

Esche

Hoffmann

Illner

et al. 2017

Chemie Ingenieur Technik

View full text Add to dashboard Cite

Dedicated software exists for both process simulation and optimization. Given the advantages of simultaneous optimization schemes, engineers are frequently tasked with reimplementing their simulation models in optimization languages or environments. In this contribution, a workflow is introduced to model chemical engineering models in MathML and to have an automatic code generation for both specialized simulation and optimization tools. Two examples are given to highlight the performance of this workflow implemented in the modeling, simulation, and optimization environment MOSAIC.

show abstract

“…However, the shown methods will be based on the modeling tool “MOSAICmodeling” that has been under development at the Process Dynamics and Operations Group (http://www.dbta.tu-berlin.de) of Technische Universität Berlin since 2008. Originally, it was designed as a modeling tool operating on the documentation level . Models in MOSAICmodeling are implemented fully equation‐oriented, entered by users in LaTeX, and stored in MathML .…”

Section: Motivation and Introductionmentioning

confidence: 99%

Analysis and Decomposition for Improved Convergence of Nonlinear Process Models in Chemical Engineering

Bublitz

Esche

Tolksdorf

et al. 2017

Chemie Ingenieur Technik

View full text Add to dashboard Cite

Solving nonlinear equation systems as they occur in process simulation simultaneously, often fails due to ill-conditioned models or bad initialization. To counteract these issues two methods have been implemented in the web-based platform MOSAICmodeling. The Dulmage-Mendelsohn algorithm forms a block diagonal Jacobian matrix. In addition, the bordered block transformation identifies variables that need to be carefully initialized due to their great influence on the system. Both methods are applied on two process models and their convergence and sensitivity towards initialization is analyzed. Motivation and IntroductionIn process simulation tools for chemical engineering applications, such as Aspen Plus, Aspen Hysis, ChemCAD, gPROMS, and Pro/II, the initialization and solution procedure is still mostly governed by the so-called sequential modular approach. This implies the selection of so-called tear streams, which act as entry points to flowsheets and the reconciliation of recycle streams. Starting with these tear streams, unit operations are solved sequentially and the whole flowsheet is solved repeatedly until the properties of the tear stream remain constant between iterations. Within each unit operation, similar approaches are combined with heuristic rules and algorithms on how to solve each independently, e.g., a sequential tray by tray calculation of a distillation column. These methods typically feature an internal modularization regarding property calculations, thermodynamics, etc., all of which are yet again solved with dedicated algorithms. Some of these process simulation tools have been under development for more than 35 years and major advancements have been achieved regarding the size and complexity of flow sheets, the incorporation of thermodynamic models, numerical simulation, and graphical user interfaces [1].Despite this progress, process simulation of flow sheets with many recycle streams still requires some form of manual intervention, implying a certain level of user interaction to steadily improve starting values for tear streams [2]. Such interaction typically requires detailed engineering knowledge. Mere guessing of starting values of temperatures, pressures, compositions, or flows is of course highly undesirable and should be minimized as far as possible. This becomes especially relevant in view of the increasing size of flowsheets with up to several millions of variables.If one chooses an equation-oriented approach instead of the sequential modular approach, this issue becomes even more imminent. The equation-oriented mode attempts a simultaneous solution of the whole process system, usually with some quasi-Newton-type solver. To ensure convergence, a good initial point close to the desired solution is required. In practice, equation-oriented tools, e.g., gPROMS, use sequential-modular techniques as initialization methods before switching over to the equation-oriented mode, Pantelides et al. [3].In general, the nonlinear models underlying any process simulation in chemical engineering ...

show abstract

MOSAIC a web-based modeling environment for code generation

Cited by 42 publications

References 41 publications

Optimization during the process synthesis: enabling the oxidative coupling of methane by minimizing the energy required for the carbon dioxide removal

Optimization during the process synthesis: enabling the oxidative coupling of methane by minimizing the energy required for the carbon dioxide removal

MOSAIC – Enabling Large‐Scale Equation‐Based Flow Sheet Optimization

Analysis and Decomposition for Improved Convergence of Nonlinear Process Models in Chemical Engineering

Contact Info

Product

Resources

About