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PROPTI - A Generalised Inverse Modelling Framework
by
Hehnen, Tristan
, Arnold, Lukas
, Vinayak, Ashish
, Trettin, Corinna
, Lauer, Patrick
in
Computer simulation
/ FDS
/ framework
/ HPC
/ inverse modelling
/ Mathematical models
/ Modelling
/ optimisation
/ Optimization
/ Parameters
/ Physical properties
/ Pyrolysis
/ Reaction kinetics
/ Simulation
2018
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PROPTI - A Generalised Inverse Modelling Framework
by
Hehnen, Tristan
, Arnold, Lukas
, Vinayak, Ashish
, Trettin, Corinna
, Lauer, Patrick
in
Computer simulation
/ FDS
/ framework
/ HPC
/ inverse modelling
/ Mathematical models
/ Modelling
/ optimisation
/ Optimization
/ Parameters
/ Physical properties
/ Pyrolysis
/ Reaction kinetics
/ Simulation
2018
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Do you wish to request the book?
PROPTI - A Generalised Inverse Modelling Framework
by
Hehnen, Tristan
, Arnold, Lukas
, Vinayak, Ashish
, Trettin, Corinna
, Lauer, Patrick
in
Computer simulation
/ FDS
/ framework
/ HPC
/ inverse modelling
/ Mathematical models
/ Modelling
/ optimisation
/ Optimization
/ Parameters
/ Physical properties
/ Pyrolysis
/ Reaction kinetics
/ Simulation
2018
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Journal Article
PROPTI - A Generalised Inverse Modelling Framework
2018
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Overview
Simulation of pyrolysis involves the knowledge of reaction kinetics and thermo-physical parameters, which are in general not directly measurable. Inverse modelling provides means to deduce the needed parameters from experimental data. This complex process involves the coupling of a simulation model with an optimisation method as well as the handling of a large amount of data. All of these processes are prone to errors and therefore a unified and automated implementation is beneficial for the whole community. In this contribution, a software to carry out this process is proposed. PROPTI is an open source tool written in Python, that is meant to provide a framework for inverse modelling of parameters in computer simulation, with emphasis on pyrolysis modelling in fire simulation. Its generalised formulation allows the usage of any simulation model in combination with various experimental data. The underlying optimisation library allows the utilisation of HPC systems. After presenting the concept of this framework, two examples are shown to illustrate the process and demonstrate the capabilities.
Publisher
IOP Publishing
Subject
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