 Hi, I'm Binxing Wu, computational fluid dynamical engineer from Philadelphia Missing Solutions. In this video, I'm going to give you a brief introduction to large-edit simulation of mechanical missing in anaerobic digesters. Anaerobic fermentation can convert biomass into biomethane, which is a biorenewable energy. Effective digestion is highly dependent on efficient mixing. Mixing can not only prevent the settling of solids, but also enhance the nutrient delivered from the substrate to anaerobic bacteria. The primary goal of mixing is to create an optimal physical environment that favors the bacteria grow up. Generally speaking, mixing can be studied using practical image velocity, which is an optical method of flow visualization. Here I show you the PIV set up in our company lab. My co-work, Jason Dragonberry, is in charge of all the PIV test tests. And there are three major components for this PIV test. Laser uses to light up the solid particles inside the tank. The camera takes the picture and the computer shows you how the particle moves. The PIV test is good for small mixing tankers. However, it is unsuitable to the medium mixing tank and large mixing tankers. Here is the large mixing tanker with 750,000 calories. Let's take a look. We have a large scale mixing tankers for different imperial titles. We can observe highly turbulent flow inside the tank. Alternatively, mixing can be simulated using computational fluid dynamics techniques. Basically, the turbulence simulation method includes direct numerical simulation, large eddy simulation, and renal's average Navier-Stokes simulation methods. In this study, the following three sub-grade scale models were used in the LES simulations. In terms of characterization of imperial rotation, we can use multiple reference frame method and the sliding mesh method. CFD simulation was conducted in a mixing tank. In this tank, the imperial has only three blades and no bubbles were used. So one third of the mixing tank was used to the computational domain. In the pre-processing, how to generate a high-quality mesh is the key. The flow patterns in the LES simulations are very complex. They change with the time, even at the same location. These patterns are supposed to be identical for a regular simulation. In the LES simulation, for monitors, were instantaneous velocity, mean velocity, imperial torque, and imperial flow rate. Especially, the imperial torque exhibits a high-frequency oscillation. The simulation results show that the sub-grade scale models produce almost the same flow patterns. Validation of LES simulations was performed using mechanical agitation, both Newtonian and non-Newtonian fluids in the mixing tanks. Additionally, SIGS range models were used to compare with the LES model. In addition to the flow patterns, the imperial power and flow numbers are two important parameters used to evaluate the LES performance. Comparations of nine results indicate that the LES with kinetic energy transport model performed the best, but it took the longest time to obtain one solution. In conclusion, LES is an excellent turbulence modeling method, but it still has limitations for industrial applications due to its high computing costs. Using the embedded LES, which combines the LES and the range model, we are able to simulate the mixing in large and aerobic digesters. Thank you for watching, and I hope this video enhances your understanding of the paper published in biotechnology and bioengineering.