Computational fluid dynamics study on mixing mode and power consumption in anaerobic mono- and co-digestion

Zhang, Yuan; Yu, Guangren; Yu, Liang; Siddhu, Muhammad Abdul Hanan; Gao, Mengjiao; Abdeltawab, Ahmed A.; Al-Deyab, Salem S.; Chen, Xiaochun

doi:10.1016/j.biortech.2015.12.023

Cited by 68 publications

(23 citation statements)

References 31 publications

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“…The k-ε model is known to be suitable for mixing and swirl flows, and is one of the most commonly used turbulence models for industrial applications. According to Zhang et al (2016) [21] this model could best predict the mixing in reactors compared to other turbulence models. The near wall flow is modelled through the wall function approach which allows for analytical expressions to compute the near wall flow region with relatively lower computational cost compared to low Re number approaches.…”

Section: Computational Fluid Dynamicsmentioning

confidence: 98%

“…Through CFD investigations, Ameur (2016) [20] has shown that among different vessel shapes, spherical ones provide uniform flow in the entire vessel and lead to lowest energy consumption. Zhang et al (2016) [21] did a comparison between the power number obtained from experimental data and the results of different turbulence models for the digestion of cattle manure and corn stover, considering the fluid as incompressible and pseudoplastic. Results showed that higher accuracy was obtained by using the standard k-ε model.…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Study of Biogas Reactor Fluid Rheology—Implications for Mixing Profile and Power Demand

et al. 2019

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Anaerobic digestion (AD) is an established process for integrating waste management with renewable energy and nutrient recovery. Much of the research in this field focuses on the utilisation of new substrates, yet their effects on operational aspects such as fluid behaviour and power requirement for mixing are commonly overlooked, despite their importance for process optimisation. This study analysed rheological characteristics of samples from 21 laboratory-scale continuous stirred-tank biogas reactors (CSTBRs) digesting a range of substrates, in order to evaluate substrate effect on mixing efficiency and power demand through computational fluid dynamics (CFD). The results show that substrate and process parameters, such as solids content and organic loading, all have a significant effect on CSTBR fluid rheology. The correlation levels between rheological and process parameters were different across substrates, while no specific fluid behaviour patterns could be associated with substrate choice. Substrate should thus be considered an equally important rheology effector as process parameters. Additional substrate-related parameters should be identified to explain the differences in correlations between rheological and process parameters across substrate groups. The CFD modelling revealed that the rheology differences among the AD processes have significant implications for mixing efficiency and power demand of the CSTBRs, highlighting the importance of considering the substrate-induced effects on CSTBR rheology before including a new substrate.

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Section: Computational Fluid Dynamicsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Biogas Reactor Fluid Rheology—Implications for Mixing Profile and Power Demand

et al. 2019

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“…The study proves that the issue of evaluating the mixing efficiency of fermenters is very complicated, and there is no clear criterion [69]. Due to large variability of fixed and operational parameters that affect mixing, Computational Fluid Dynamics (CFD) modeling is massively used, but it is very difficult to fully validate the results [70,71]. Table 5.…”

Section: Mixing Of Anaerobic Digestermentioning

confidence: 99%

A Novel Check-List Strategy to Evaluate the Potential of Operational Improvements in Wastewater Treatment Plants

et al. 2020

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With increasing demands for cleaning and purification of water, wastewater treatment plants (WWTP) require their most efficient operation. The operators are thus obliged to constantly review the efficiency of the processing units and technological equipment of WWTPs and seek opportunities for improvements. To increase the efficiency of particular equipment, the important parameters to be used for the intensification must be correctly selected. A common WWTP consists of different types of processing units, where the basic parameters can be changed to achieve the highest efficiency (i.e., maximum output with minimum energy consumption) in the WWTP. However, due to many possible technologies in the wastewater treatment process, the combinations of processing units can be complex. In such cases, the efficiency assessment can be misleading if only basic parameters were accessed. Moreover, single-unit intensification can potentially improve the efficiency of the unit itself but cannot guarantee full process improvement. This can be due to negative causal effects in the downstream due to that unit intensification. This work reviews of key parameters at five selected pieces of WWTP equipment (inlet pump station, airlift pump, primary sedimentation tank, aeration chamber, and mixing of anaerobic digester) to demonstrate the correct selection of all affected parameters for the efficiency assessment. In the context of the whole WWTP process, it is necessary to take into account several other parameters to evaluate the efficiency of the equipment. Finally, a methodology for assessing the significance of the identified parameters is proposed. This methodology is effectively applied and demonstrated in the WWTP case study.

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“…4 for an example of CFD employed at full-scale). This is reflected by the increasing number of studies and software platforms that use CFD for AD research, including the performance of gas-mixing [161], physical mixing [162,163], process design and optimisation [164].…”

Section: Computational Fluid Dynamicsmentioning

confidence: 99%

Not Just Numbers: Mathematical Modelling and its Contribution to Anaerobic Digestion Processes

Wade¹

2020

Preprint

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Mathematical modelling of bioprocesses has a long and notable history, with eminent contributions from fields including microbiology, ecology, biophysics, chemistry, statistics, control theory and mathematical theory. This richness of ideas and breadth of concepts provide great motivation for inquisitive engineers and intrepid scientists to try their hand at modelling, and this collaboration of disciplines has also delivered significant milestones in the quality and application of models for both theoretical and practical interrogation of engineered biological systems. The focus of this review is the anaerobic digestion process, which, as a technology that has come in and out of fashion, still remains a fundamental process for addressing the global climate emergency. Whether with conventional anaerobic digestion systems, biorefineries, or other anaerobic technologies, mathematical models are important tools that are used to design, monitor, control and optimise the process. Both highly structured, mechanistic models and data-driven approaches have been used extensively over half a decade, but recent advances in computational capacity, scientific understanding and diversity and quality of process data, presents an opportunity for the development of new modelling paradigms, augmentation of existing methods, or even incorporation of tools from other disciplines, to ensure that anaerobic digestion research can remain resilient and relevant in the face of emerging and future challenges.

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Computational fluid dynamics study on mixing mode and power consumption in anaerobic mono- and co-digestion

Cited by 68 publications

References 31 publications

A Comparative Study of Biogas Reactor Fluid Rheology—Implications for Mixing Profile and Power Demand

A Comparative Study of Biogas Reactor Fluid Rheology—Implications for Mixing Profile and Power Demand

A Novel Check-List Strategy to Evaluate the Potential of Operational Improvements in Wastewater Treatment Plants

Not Just Numbers: Mathematical Modelling and its Contribution to Anaerobic Digestion Processes

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