Kuang Zhu, Wenjuan Zhang, Elchin Jafarov, Satish Karra, Kurt Solander, Meltem Urgun Demirtas, Lutgarde Raskin, Steven Skerlos
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引用次数: 0
摘要
为了实现厌氧消化过程的快速和数值稳定的模拟,引入了一个开源建模平台,称为厌氧消化模型1 Fast (ADM1F)。ADM1F与iPython接口兼容,以方便模型配置、仿真、数据分析和可视化。通过实现称为便携式科学计算扩展工具包(PETSc)的先进开源数值方法库来求解ADM1方程组,可以实现更快的模拟和更稳定的结果。利用PETSc, ADM1F可以在0.2 s内稳定地完成稳态仿真,比用MATLAB实现的基准ADM1模型快99%以上,同时模型输出与基准模型输出的一致性在1%以内。然而,对于动态模拟,只有当进水特性更新频率高于每4小时时,ADM1F才具有计算速度优势。ADM1F作为研究厌氧消化系统的工具的能力通过ADM1F的两个实例实现来证明:(1)两相共消化方案评估有机负荷率和底物组成对反应器性能和稳定性的影响,以及(2)传统消化方案评估导致不稳定的中断后恢复策略的有效性。这些例子展示了高仿真速度和iPython接口的便利性如何允许ADM1F在几分钟内完成复杂的分析,比目前文献中报道的计算策略快得多。
Open-Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)
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.
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