Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)
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| Format: | Artículo Open Access |
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Wiley
2024
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| _version_ | 1867004378085326848 |
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| author | Kuang Zhu Wenjuan Zhang Elchin Jafarov Satish Karra Kurt Solander Meltem Urgun Demirtas Lutgarde Raskin Steven Skerlos |
| author_facet | Kuang Zhu Wenjuan Zhang Elchin Jafarov Satish Karra Kurt Solander Meltem Urgun Demirtas Lutgarde Raskin Steven Skerlos Kuang Zhu Wenjuan Zhang Elchin Jafarov Satish Karra Kurt Solander Meltem Urgun Demirtas Lutgarde Raskin Steven Skerlos |
| collection | Wiley Open Access |
| contents | Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F) Kuang Zhu Wenjuan Zhang Elchin Jafarov Satish Karra Kurt Solander Meltem Urgun Demirtas Lutgarde Raskin Steven Skerlos Biotechnology and Bioengineering ABSTRACT An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature. 10.1002/bit.28906 http://creativecommons.org/licenses/by-nc/4.0/ |
| doi_str_mv | 10.1002/bit.28906 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_bit_28906 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by-nc/4.0/ |
| publishDate | 2024 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F) Kuang Zhu Wenjuan Zhang Elchin Jafarov Satish Karra Kurt Solander Meltem Urgun Demirtas Lutgarde Raskin Steven Skerlos Biotechnology and Bioengineering Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F) Kuang Zhu Wenjuan Zhang Elchin Jafarov Satish Karra Kurt Solander Meltem Urgun Demirtas Lutgarde Raskin Steven Skerlos Biotechnology and Bioengineering ABSTRACT An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature. 10.1002/bit.28906 http://creativecommons.org/licenses/by-nc/4.0/ |
| title | Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F) |
| topic | Biotechnology and Bioengineering |
| url | https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/bit.28906 |