Simulation Best Practices for Mixing Equipment Webinar

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Hello everyone, welcome to the Simulation Best Practices for Mixing Equipment webinar. My name is Jesus Ramirez and I am part of the technical team of Ozen Engineering. Today, we are going to present an overview of mixing processes using ANSYS CFD and Rocky-DEM.

In this presentation, we will discuss the challenges in the mixing industry, the quantified impact of simulation on efficient use of mixing equipment, and provide examples of how simulation is used in this field. We will divide this presentation into sections.

First, we will talk about mixing equipment that involve fluids and later, we will talk about solid powder mixing. Mixing is a common upstream process among different industries, such as chemical, pharma, consumer products, food, among others.

While the product is different, the objectives are similar, namely increasing the yield while ensuring the required mixing behavior and hence the final product quality. In the past, mixers seemed like boxes where processes were improved mostly by trial and error.

However, the science and technology involved in the design, functionality, and application of the mixers indicate otherwise.

Generally, some of the aspects to consider in the mixer design processes are the temperature, the need for aeration, the agitation level required, and the flow dynamics behavior.

Due to the lack of adequate sensors, it is impossible to perform a complete characterization of the flow inside the mixing tanks. Also, the costs associated with experimentation in mixing tanks, particularly for business and industrialization, are high.

A turbine impeller is a powerful tool contributing to a very fast and efficient mixing process that allows for the creation of complex flow patterns. This, in turn, enables the processing of various materials.

The same principles apply to the design of mixers for different industries, such as the food, chemical, and pharmaceutical industries. The design requirements for mixers include efficient and cost-effective mixing processes for bringing quality products to the market in less time.

These requirements can be summarized as follows: doing a scale-up of various units of operation from the lab to the plant scale, adapting the system mix equipment to a new formulation or operating conditions to ensure efficient plant operations and meet government regulations, and ensuring batch quality consistency through digitalization.

Engineers, process engineers, and other stakeholders use these considerations when they want to improve or design mixing equipment. For this conclusion, thank you. Now, let's talk about how simulation has helped some industries improve their operations and increase their revenue.

One customer developed an improved design for a mixing tank that provides a 5 times better mixing for solid suspensions using 12% less power. Simulation helps engineering teams make design decisions that balance mixing performance and power draw.

Another customer was able to decrease the time required for cell culture growth by 30%. This means several days of time savings. According to discussions with different pharma companies, the use of simulations allows them to have an increase in their revenues of around 1%.

This means millions of dollars of revenues per batch. Now, let's talk about some applications for mixing equipment that involve fluids. In the pharmaceutical industry, the most common application is a mixing machine.

Companies are interested in mixing stand characterizations with the following goals: identifying potential scale-up issues for risk analysis, impact of geometry on the product quality, impact of operating conditions that affect the unit operation, and retrofitting the new process in the system equipment.

For doing this, it is common to use a single-phase mixing system. Then, with that in mind, using CFD allows for a complete characterization of the flow behavior in both simple and complex geometry.

It is also possible to determine the influence of tank and impeller geometry over the fluid dynamic behavior inside the mixing tank.

The most frequent properties and characteristics extracted from CFD simulation for mixing tanks are velocity fields, shear stress fields, reconnection of recirculation zones, streamlines, and power consumption. This is a very common application.

Only one application is mentioned here, but there are many more. To summarize, artists often use a sample with another sample as a normal modification tool to fully understand how an interesting circuit can be created using correct frequency at ideal degrees.

By doing this, there is a reduction of the required computational time for solving the model, which makes it easier to do parametric studies or design of experiments to get adequate operating conditions or for scaling purposes.

As we previously mentioned, doing a scale-up represents a significant challenge, both in time and money, for sentient processes.

By doing your own CFD analysis or by doing a consulting project with us, your company can gain the necessary process understanding and accurate scale-up conditions for your mixing tanks to go from lab scale to plant scale.

With CFD, it is possible to get valuable insights into the physics of scale-up and the risks involved. Basically, CFD simulation helps companies in decision-making on equipment sizing and cutting down on expensive raw material usage.

Therefore, CFD simulation can save hundreds of thousands of dollars, providing characterizations of scale-ups that apply to the overall scalability process, reducing the need for building and testing prototypes.

One straightforward way for doing a scale-up using ANSYS CFD is by using parametric analysis and the design of experiments. For example, in ANSYS Configuration Tools, you can define key simulation properties to berites, key larger parameters, and such.

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Also, you can then manipulate the parameters at the project level in Workbench to investigate the design alternative. A set of parameter values representing one design alternative is called a design point.

You can create a set of design points, in tabular form, and run them automatically to perform a what-if study. On the other hand, a design of experiment is a scientific way to reduce the number of experiments while still gathering enough data to understand the relationship.

ANSYS, through the Design Explorer, proposed many design of experiment schemes to help engineers achieve the best results. For example, here you can see how the velocity distribution inside a mixing tank changes depending on the tank scale.

The same procedure can be done for different flow fields, and the changes can be correlated and shown in a response surface manner for making decisions. Now, let's talk about another way of modeling these mixing tanks, let's say applications where gas and liquids are involved.

It is common to observe that in many systems the mixing process occurs simultaneously during filling. This historically has been a challenging problem, and while it could have been accomplished, it used to take a long time to simulate with high fidelity.

Recent advances in software technology have reduced the turnaround time for this simulation by an order of magnitude. One of computational simulation's key features is to observe how the flow behaves inside a mixing tank.

For example, we can watch how the mixture process evolves qualitatively and quantitatively, and we can see how the flow is in a mixing tank with an immersed mixing device.

We can check it here, and we see how this will evolve inside the mixing tank when we are filling, we are injecting mass, and when we are using the immersed mixers. Also, you can see how the quantitative analysis is also linked to the qualitative analysis.

Then we can visualize what's happening inside the mixer tank, but also we can check the numerical information that is also important for making decisions. This is a good feature of ANSYS's tools for engineers that work in this kind of application.

Also, in this other video, we can check another application. For example, here we were interested in looking at the mixing and the free surface evolution as the mass was injected.

In this part, we're interested in the on the burden prediction for those cases where, for example, we want to check how is the turbulence behavior, how is the free surface behavior if you have a body of information, in those cases that body information is not good for the process, then to recognize where at this body of firm and how they are distributed.

Also, we can extract information about the shear stress or the Volkswagen application of these elements and also use this information, leave water in the blocks of the gestation.少iff field just like his flows.

We cannot take advantage of this information about the shear stress for those cases where the shear stress is important.

Then if you can see, we can check that with using CFD and how how the free surface how turbulence starts to act over the over the fluid inside the tank and also if we have this kind of bubble formations and flow behavior that we want to avoid or just for having a knowledge or a deeper knowledge of what's happening inside the tank.

Also, another application can be the prediction or the validation of the border depth when we have a stirring tank. Then, for example, in this case, we compare our simulation with experiment from Ciofallo et al.

Basically, we use two different approaches: we use a steady-state simulation and a transient simulation using the hybrid neta, which is one of the last numerical approaches that ANSYS has developed and that has given engineers a faster solution for transient simulation.

Then you can see here what is the comparison from the simulation results and experiment result; they are pretty close, and this is good news. Then we can see here how it looks like, and this is something that we can see using computational simulation.

We can have an idea of how is the flow behavior inside the mixing tank but also extract numerical data to compare with experimentation or with previous analysis to validate the model or to generate new new operating conditions or changes or new designs for improving the process.

Another application for gas-liquid systems is bioreactors, which are basically any manufactured device or system that supports a biologically active environment.

One type of bioreactor is the stirred-tank bioreactor, which is a reactor for large-scale aerobic cultures where gas is inserted via an airlift pump.

This kind of system has some operating problems that must be solved or avoided, such as exotic strains of cells that grow in large-scale bioreactors, which can result in therapies that easily exceed one hundred thousand dollars per gram of API.

Ensuring sufficient respiration is critical to ensure that the goals are met. High yields mean more life-saving therapies will be produced per batch. The E to predicting the gas holdup and interfacial area are met with advanced ANSYS multiphase models.

These models track the gas and liquid interaction, even predicting the bubble size and shape. This allows ANSYS to help your biology and process engineering specialists predict with confidence the mass transfer, dissolved oxygen, the carbon dioxide and other gases.

For example, let's talk about these pictures. You can see how the oxygen or the gas is entered or injected into the mixing tank by the sparger. You can see how is the injection and how with the impellers the oxygen or the gas is distributed inside the tank.

The idea is to have a good behavior of this distribution for having an improvement on the process. This can be easily done using CFD. Also, we can extract how is the normalized concentration at a desired point, such as a proof point, like a sensor.

Then we can test how is the concentration at that point in CFD. We can have multiple points, infinite number of points, to track and compare this the data obtained from that point with experimental data for validation purposes and for starting like a virtual prototyping for a validated module.

Also, we can see here how a trace agent is injected in a random part of the mixing tank and how it is distributed and it becomes uniform and mixed with the with the solvent inside the mixing tank.

It is very easy to observe this using CFD and to have insights of what's happening with the gases and with the mixing processes we are interested in. Another application for mixing tanks is the analysis of solid suspension. In this case, the customer goal is different.

For example, the customer wants to ensure that equates solid suspension in the tank, also wants to analyze the dissolution or crystallization sequence of the solid suspension.

For example, the customer wants to analyze the system or to minimize the power requirements to have a longer impeller life and also a longer vessel life. For this, we have different solutions. For example, we can predict the flow patterns and turbulence in an accurate way.

Also, ANSYS has advanced modeling approaches for solid-liquid mixing along with reactions. For example, we can use the liquid mixing method to measure the flow patterns and flow patterns.

For example, we can use the liquid mixing method to measure the flow patterns or different drag models that accurately predict the particle behavior. Also, as a big part of this, we can create a design of experiments to find the optimal operating conditions.

With this, the customer receives some benefits. For example, it allows them to understand the mixing characteristics as flow patterns, solid distribution, and cloud height. Also, they can predict the shear rate and shear history and also minimize batch failures.

We can see, for example, in the picture in the left bottom corner, how is the effect of using one or two impellers on the cloud height and the volume fraction of solid inside the mixing tank. Also, we can see that this behavior is very similar to the previous example.

For example, we can see that this behavior is very similar to the previous example. For example, we can see that this behavior is very similar to the previous example. So we can see that this behavior is very similar to the previous example.

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At the same time, a minimum velocity, also called the just-suspended speed, is required to be maintained. As you can see, in the left bottom animation, you can observe how the cloud head prediction visualization can be obtained from a CFD animation or a CFD simulation.

On the other hand, the top right images are coming from a comprehensive analysis of a conical bottom reactor. In this case, water is used as a liquid, and solids are with 180 microns in diameter in size. The reactor was subdivided into several sections.

Yet, two different agitation rates were studied. You can see in the image that the solid distribution is compared for the three different rotational speeds. It was observed that the speeds of 100 rpm and 150 rpm were not adequate to suspend the solids.

For instance, the velocity of 220 rpm predicted that this speed was good enough to suspend the solids. You can see here how the solids tend to settle at the bottom of the reactor for the 100 and 150 rpm, and in this case, it seems that they are well suspended or well mixed inside the reactor.

As you can see, using computational simulation can give you a detailed information of the flow field. For example, you can obtain the general flow of the reactor. This is a very simple and detailed simulation. The objective is to determine the flow of the reactor.

You can obtain the shear rate characteristics for checking if some of your solids will be damaged by exposure to regions with high shear. Also, you can predict just the suspension velocity, just to know if your solids will settle or not.

Or also, you can predict the solid concentration profile throughout the vessel. Another type of mixer equipment is the static mixer. Static mixers are common in the reactor. They are used in the process industry, such as chemical, consumer products, food, among others.

They have the advantage of being part of a continuous process rather than a batch discontinuous, which makes them attractive to high-yield processes. As always, the goal is to ensure proper mixes on the two or more ingredients.

The challenge comes when the properties of these fluids are quite different. Static mixers improve the quality of the liquid. They are also used in the process of making the liquid.

Static mixers impose a considerable pressure drop and hence accurate system sizing is of remarkable importance since it will directly influence the operation. At the same time, they also impose significant shear onto the system, which may result in material degradation, depending on the application.

Different configurations of static mixers exist. For example, the SMX, that is the one that is used for the liquid. The SMX is the one that is used for the liquid. The SMX is the one that is used for the liquid. The SMX is the one that is used for the liquid.

The SMX is the one that is used for the liquid. The SMX is the one that is used for the liquid. The SMX is the one that is used for the liquid. The CSK, that is the one that we are showing here. And the knix mixers are the most common.

However, in recent years there has been a development of new static mixers and new designs to improve the efficiency of mixing and also to reduce the pressure drop.

For doing this, a virtual prototyping procedure using computational simulation is a good approach to prove concepts, develop ideas, and get the best result or the best design in a shorter time.

In the pictures, you can see a typical SMX mixer, that is the one that is shown in the top right part of the slide. In the bottom part, you can see a contour that shows the concentration variation of a tracer that was fed from the side inlet.

It is obvious that the operating conditions need to be adjusted to ensure complete mixing. And this is the kind of things that we can see and we can observe using CFD or computational simulations to get the proper behavior of the flow.

In this case, it is obvious that the designers need to do changes in the geometry of the static mixers to get a good result for mixing. Finally, another application for this kind of mixing equipment that works with fluids is clean-in-place (CIP) systems.

In this case, the customer goal is basically to sufficiently mix the fluid in the system and also have a sufficient and consistent cleaning of the process. Of course, doing a sizing of the systems across the different plants and to minimize and also predict the cleaning time material.

For that, for doing that, we can do single and multi-phase simulations. Basically, we can predict the free surface behavior, the droplet formation, and also the flow rate. We can estimate what is the jet behavior and how is the liquid film formation inside the tank.

With this kind of models, you can analyze the effect of the nozzle and the spray for new designs for head selections also to estimate the time for having a complete cleaning compared to the one you are considering, which one will shift the fluid and so on.

As you know, these types of models are used installed in many systems, such as IndexTank for processing hot yards, RedG Account for 24 hours passing the left Christ iy show up the code wereely in the KOF template.

For example, the green to go left arrow, want to stop the process or you need to stop the process for cleaning the tanks; you can't estimate how much time does that it will take, and this is a pretty interesting application for this kind of computational modeling.

Now, let's talk about powder and solid mixing. Powder and solid mixing is achieved using a mechanical device that rotates, a stationary vessel with agitators, a vibration unit, a gravity motionless device, and other ways that we are not going to discuss.

Most mixers split and recombine the powders to create new interfaces and to remove segregation and stratification. However, these same devices also can induce segregation of powders based on difference in particle size, particle shape, or density.

Therefore, understanding how this equipment works is of vital importance for engineers. Three types of particle motion are generally responsible for mixing of powders: convective mixing, shear mixing, and diffusive mixing.

In the diffusive mixing, we have some equipment, such as the blenders, the double comb blenders, and the drums blenders. For the convective mixing, we have the ribbon blenders, the screw blenders, and the paddle mixers.

Finally, for the shear mixing, we can find the rotating drum and the plug shear mixer. These are equipments that are used to transform any type of granular material from coarse grain to very fine powders. They are used in almost all industries where granular material needs to be transported.

These equipments can be seen in a wide range of industries. It is common to see that they have many different types and shapes. However, they have the same main engineering objectives, that is to ensure the material flow.

Also, as the mixing equipment that involves fluids, their goal is to allow for reduction in operational costs and increase processor reliability. We can model this kind of mixers using one of our newer products, such as Rocky-DEM.

With Rocky-DEM, we can apply the discrete element method for modeling particles with real shapes occupying real volumes inside the model.

As you can see in these pictures, these particles can be spherical or can be with any shape that you need, that you want, with the properties of the real material particles and with the motion that they will have inside the device.

Then, with this kind of solver that analyzes the particles, we can determine if the mixing of powder and solids is good enough or if we need to do changes on the designs or on the concept we are testing before moving to a manufacturing stage.

We can also use the same method to do the same with the other products. And that's it. Thank you for watching. Please subscribe to our channel and give us a thumbs up. Thank you. See you next time. Bye. Bye. Bye. Bye.