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Title: Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

Journal Article · · Biotechnology and Bioengineering
DOI: https://doi.org/10.1002/bit.28906 · OSTI ID:2483772
ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [3];  [3]; ORCiD logo [4]; ORCiD logo [1]; ORCiD logo [5]
  1. Department of Civil and Environmental Engineering University of Michigan Ann Arbor Michigan USA
  2. Department of Mathematical and Statistical Sciences University of Colorado Denver Denver Colorado USA
  3. Computational Earth Science Group Los Alamos National Laboratory New Mexico USA
  4. Applied Materials Division Argonne National Laboratory Lemont Illinois USA
  5. Department of Civil and Environmental Engineering University of Michigan Ann Arbor Michigan USA, Department of Mechanical Engineering University of Michigan Ann Arbor Michigan USA

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.

Sponsoring Organization:
USDOE
OSTI ID:
2483772
Journal Information:
Biotechnology and Bioengineering, Journal Name: Biotechnology and Bioengineering Journal Issue: 4 Vol. 122; ISSN 0006-3592
Publisher:
Wiley Blackwell (John Wiley & Sons)Copyright Statement
Country of Publication:
United States
Language:
English

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