Elsevier

Bioresource Technology

Volume 203, March 2016, Pages 166-172
Bioresource Technology

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

https://doi.org/10.1016/j.biortech.2015.12.023Get rights and content

Highlights

  • CFD models were developed for anaerobic mono-digestion and co-digestion.

  • Continuous and intermittent mixing was compared in anaerobic co-digestion.

  • New index of net power production was proposed to optimize feedstock ratio.

  • Optimum feedstock ratios were determined for different mixing modes.

Abstract

Computational fluid dynamics (CFD) was applied to investigate mixing mode and power consumption in anaerobic mono- and co-digestion. Cattle manure (CM) and corn stover (CS) were used as feedstock and stirred tank reactor (STR) was used as digester. Power numbers obtained by the CFD simulation were compared with those from the experimental correlation. Results showed that the standard kε model was more appropriate than other turbulence models. A new index, net power production instead of gas production, was proposed to optimize feedstock ratio for anaerobic co-digestion. Results showed that flow field and power consumption were significantly changed in co-digestion of CM and CS compared with those in mono-digestion of either CM or CS. For different mixing modes, the optimum feedstock ratio for co-digestion changed with net power production. The best option of CM/CS ratio for continuous mixing, intermittent mixing I, and intermittent mixing II were 1:1, 1:1 and 1:3, respectively.

Introduction

Anaerobic digestion (AD) is a biological treatment process for different organic wastes to alleviate the energy and environmental issues of society. Due to depletion of non-renewable energy resources and deterioration of global environment, AD is becoming more attractive and popular in society. Anaerobic digestion can be classified as, (1) mono-digestion (i.e., digestion of single substrate) and (2) co-digestion (i.e., simultaneous digestion of two or more substrates).

Anaerobic mono-digestion of agriculture waste is yet a problem due to diverse nature and nutrients imbalance of each substrate for anaerobic micro-organisms. Corn stover (CS) is a lignocellulosic biomass with high organic carbon, whereas cattle manure (CM) contains more nitrogen. Thus anaerobic co-digestion of CM and CS can balance the nutrients for micro-organism (Yue et al., 2013), improve the buffer capacity and enhance the methane content and process stability (Belle et al., 2015, Li et al., 2009, Wu et al., 2010, Mata-Alvarez et al., 2011). Co-digestion has higher biogas production and stable performance, e.g., methane production in co-digestion of CM with radish is 39% higher than that in mono-digestion of CM (Belle et al., 2015); biogas production in co-digestion of CM with CS is 24% higher than that in mono-digestion of CM (Yue et al., 2013). Currently, many studies are focused on the anaerobic co-digestion of animal manure and agro-industrial waste (e.g., CM with CS) (Yue et al., 2013, Li et al., 2009, Li et al., 2014).

China is one of the largest agricultural countries and produces different type of wastes such as crop residuals and animal manure. Almost half of the agricultural waste is abandoned or burnt in the open field, while manure is also not utilized and treated fully. This would cause serious environmental and safety problems such as haze weather, fire disaster, and traffic accidents, etc. Converting lignocellulosic biomass to biomethane through anaerobic digestion is an important way to reuse agricultural and animal waste such as CM and CS. Therefore, AD has received increasing attention for treating CM and CS (Li et al., 2009, Li et al., 2014, Yue et al., 2013). Several biogas plants that use CM and CS as feedstock have been constructed in China.

For a co-digestion system, the digestion performance is not only influenced by substrates type, feedstock ratio, organic loading rate, and hydraulic retention time but also mixing mode and mixing conditions (Lehtomäki et al., 2007, Li et al., 2014, Wu et al., 2010, Xie et al., 2011b). Mixing is an important operation for distributing nutrients, supplying nutrients to micro-organisms, reducing the inhibitory effect, and adjusting pH in the anaerobic digester. Higher mixing intensity demands more power input and reduces the digester performance. However, there are considerable potential energy savings from lowering mixing intensity and mixing time. It is possible to reduce the power consumption of a biogas plant by using intermittent mixing modes. Intermittent mixing has been shown to be able to produce the same amount of biogas compared to continuous mixing, while decreasing the maintenance and energy demand of the process (Bridgeman, 2012, Karim et al., 2005, Kowalczyk et al., 2013, Lindmark et al., 2014, Ong et al., 2002). Another issue worthy of concerning in mixing of digester is power consumption, which is consumed in motor driven. The power consumption of mixing can vary from 14% to 54% of the total energy demand in a plant (Kowalczyk et al., 2013). With the aim of generating more power in AD process, it is necessary to balance power consumption for AD and energy production from AD. Therefore, it is of great interest to efficiently perform mixing with minimum power consumption and maximum energy production. Thus a new index, net power production is proposed to optimize AD process in this study.

Computational fluid dynamics (CFD) is an efficient tool and widely used to study complex phenomena in many disciplines (chemical process, power plants, aeromechanics of vehicles etc) at very low cost, which are not understandable in relatively expensive experimental studies. CFD has been successfully used to study flow field and mixing in anaerobic digester. Some researchers employed CFD to improve impeller efficiency and enhance AD process (Shen et al., 2013, Wu, 2012a, Yu et al., 2011). The effect of other parameters such as substrate loading (Bridgeman, 2012), shear stress (Hoffmann et al., 2008) and mixing rate (Terashima et al., 2009) etc. was also simulated by CFD models. Wu (2011) evaluated six RANS-based (Reynolds-averaged Navier–Stokes) turbulent models in AD mixing simulation, and recommended the standard k–ω and the realizable k–ε models to predict mechanical agitation of non-Newtonian fluids at six total solid (TS) levels. Furthermore, Wu (2012b) suggested that large eddy simulation (LES) performed better than RANS simulation in predicting turbulent flow in anaerobic digester; however, its industrial application was limited due to high computing costs. In previous studies, major efforts have been made on mono-digestion. To our best information, there is no report on the relationship between appropriate substrates ratio of co-digestion and power consumption/production of STR.

Therefore, the main objectives of this study were to: (1) develop an appropriate numerical model of CFD for AD in our research; (2) investigate the flow field and power consumption in mono- and co-digestion of CM and CS in STR; (3) determine the effective feedstock ratio of co-digestion and synergistic effect on power production.

Section snippets

Substrates and AD process

In this study, CM and CS were selected as substrates for AD process. Both CM and CS were collected from Shunyi County of Beijing City, China. The CM was diluted with tap water to approximately 12%TS, and then long manure fiber was separated using a sieve with a 1 cm diameter screen. After that, the CM slurry was stored in a freezer (at −20 °C). When used as feedstock for anaerobic digestion, the CM slurry was further diluted to 5.4%TS. The CS was chopped into 1.0–1.5 cm in length after being

Experimental correlation and numerical simulation of power number

Power number is an important parameter for the assessment of agitator mixing performance and it is greatly affected by the slurry’s rheological properties (Chudacek, 1985). In this study, two methods were used to calculate power number of agitator. One is empirical correlation derived from experimental data. Another is numerical simulation derived from theoretical equations. The power number of agitator from empirical correlation was calculated by the following equations (Nagata, 1975).NP-exp=A

Model validation

Table 2 shows the validation of the different turbulence models by comparing the predicted power number with the experimentally correlated one (Nagata, 1975). Reynolds stress with an appropriate turbulence model is critical to characterize the flow field in a constrained vessel with rotating elements. Five turbulence models were assessed by predicting the power number. In an unbaffled STR, the power number was empirically correlated from the experimental data (Nagata, 1975). Empirical

Conclusions

Through comparing power numbers obtained from CFD simulation with those from experimental correlation, standard kε turbulence model was selected to evaluate the flow fields and power consumption in STR. Mixing uniformity of mono- and co-digestion were decreased in the following trend: CM > co-digestion > CS. Net power production was proposed to optimize the feedstock ratio of anaerobic co-digestion, and the index indicated that 1:1, 1:1, and 1:3 were proper for continuous mixing, INTER I, and

Acknowledgements

The authors are grateful for the financial support from National Natural Science Foundation of China (21176021, 21276020), Fundamental Research Funds for the Central Universities (YS1401) and the Ministry of Science and Technology (863 Program, 2012AA101803). We extend our appreciation to the Deanship of Scientific Research at King Saud University for funding the work, through Research Group Project No. RG-1436-026.

References (33)

Cited by (67)

View all citing articles on Scopus
View full text