PROPTI - A Generalised Inverse Modelling Framework
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...
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| Veröffentlicht in: | Journal of physics. Conference series 2018-11, Vol.1107 (3), p.32016 |
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| creator | Arnold, Lukas Hehnen, Tristan Lauer, Patrick Trettin, Corinna Vinayak, Ashish |
| description | 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. |
| doi_str_mv | 10.1088/1742-6596/1107/3/032016 |
| format | Article |
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| subjects | Computer simulation FDS framework HPC inverse modelling Mathematical models Modelling optimisation Optimization Parameters Physical properties Pyrolysis Reaction kinetics Simulation |
| title | PROPTI - A Generalised Inverse Modelling Framework |
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