Flow pattern visualization in a mimic anaerobic digester: experimental and computational studies

Abstract

Advanced non-invasive experiments like computer automated radioactive particle tracking and computed tomography along with computational fluid dynamics (CFD) simulations were performed in mimic anaerobic digesters to visualize their flow pattern and obtain hydrodynamic parameters. The mixing in the digester was provided by sparging gas at three different flow rates. The simulation results in terms of overall flow pattern, location of circulation cells and stagnant regions, trends of liquid velocity profiles, and volume of dead zones agree reasonably well with the experimental data. CFD simulations were also performed on different digester configurations. The effects of changing draft tube size, clearance, and shape of the tank bottoms were calculated to evaluate the effect of digester design on its flow pattern. Changing the draft tube clearance and height had no influence on the flow pattern or dead regions volume. However increasing the draft tube diameter or incorporating a conical bottom design helped in reducing the volume of the dead zones as compared to a flat bottom digester. The simulations showed that the gas flow rate sparged by a single point (0.5 cm diameter) sparger does not have appreciable effect on the flow pattern of the digesters.

Effect of substrate pretreatment on particle size distribution in a full-scale research biogas plant

“…A core factor of this obstacle is that the properties, e.g. rheology, of the fermenting substrate cannot be sufficiently described as it is an opaque and multiphase system (Vesvikar et al, 2005). Multiphase describes the fact that the fermenting substrate contains temperatures ranging from 40°C to 53°C, liquids, solids, diluted minerals, fibrous material of different lengths and biogas Wu and Chen, 2008).…”

Impact of mixing intensity and duration on biogas production in an anaerobic digester: a review

“…A digester with a 60 bottom hopper showed better settling of solids, which resulted in significantly lower VS reduction than other digesters. Similarly, Vesvikar et al [83] compared two configurations of conical bottom digesters. The first digester had a slope of 25 and the other a slope of 60 .…”

The Research on Optimization of the Multiphase Flow Field of Biogas Plant by Using CFD Software

“…distribution of the secondary phase (straw) [9] in the flow field. According to the experiment, after 30 days of full fermentation, the TS (total solid) concentration is 12.45%, density 967.56 kg/m 3 , kinematic viscosity coefficient 0.013 m 2 /s.…”

“…About the three major mixing techniques involving mechanical, hydraulic and pneumatic [3][4][5]; It remains in dispute over whether technique is the best or how to assess the mixing effect [6]. CFD (computational fluid dynamics) software can be used to calculate and visualize the field change in the digesters caused by mixing (Vesvikar and Al-Dahhan) [7]; Karim [8] tested that the flow field matches the fact simulated using CFD by CARPT (computer automated radioactive particle tracking) and CT (computed tomography); Vesvikar [9] made further experimental verification on the flow field parameters such as velocity distribution calculated by CFD simulation. Wu [10] stated that the physical characteristics of bio-slurry is similar to that of the fluid whose flow field during mixing is a two phase process of feedstock and water, and simulation calculation was done on the two phase flow of the non-Newton fluid in the digester with CFD software.…”