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Case study

How Biosimo Increased Understanding of their Trickle-Bed Reactor and Optimized it for Better Reaction Efficiency.

Trickle-bed Reactor Optimization by means of Computational Fluid Dynamics (CFD)
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The Challenge

Biosimo engineers observed that the reactor efficiency greatly depended on the fluid dynamics during their tests. Both the yield and product quality varied significantly. They realized that it was essential to understand the fluid dynamics thoroughly. Continuing the process development without this understanding would create too much risk for future development stages. This lack of knowledge could potentially lead to technological and economic risks when scaling up to pilot and industrial scales.

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The Solution

Biosimo tackled this typical R&D issue by modeling their trickle-bed reactor using Computational Fluid Dynamics (CFD). The CFD model can replicate the conditions under which the reactor operated during the experiments, providing additional data. Biosimo understood that the CFD model would fill in the gaps, helping them gain a much deeper understanding of the physics affecting reaction efficiency, yield, and product quality. Considering this, Biosimo chose to work with Novalabs to create a CFD model representing their trickle-bed reactor to gain deeper insights.

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The Company

Biosimo manufactures renewable chemicals by oxidizing bioethanol, providing a sustainable alternative to fossil-based chemicals. Their production process depends on a trickle bed reactor technology, which operates continuously. This reactor was developed in-house at Biosimo, specifically tailored to meet their process and product requirements. Determining the optimal operating conditions for high product yield and quality, coupled with low energy consumption, requires a series of experimental campaigns.

The Challenge

Understanding the Fluid Dynamics was Challenging and Key for Achieving our Business Goals.

Biosimo manufactures renewable chemicals through bioethanol oxidation, using continuous flow trickle bed reactor technology.

Max, CTO of Biosimo: “We saw a significant effect of the varied operation parameters on the yield and the product quality, but we were not able to observe the fluid dynamics within the reactor to understand where this could originate from. Also, the process operates at considerable elevated pressure and temperature, which would have made it very expensive to build a transparent version of the reactor to study the fluid dynamics experimentally. But still, even with a window close to the catalyst it would be impossible to observe the fluid dynamics within the trickle bed where the reaction takes place”.

Antonio, Founder and Engineer at Novalabs: "Such difficulties are common in R&D, and we see this across all industries we serve. At Novalabs, we have decades of experience in addressing complex real-world modeling problems. This experience helped us provide a solution to Biosimo by selecting the appropriate CFD simulation strategy and modeling approach."

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Maximilian Moser
Biosimo Maximilian Moser

"From the very beginning, the onboarding process was smooth and efficient. The demand assessment was thorough and helped us to identify crucial aspects of our system that needed to be simulated. The pivot to more meaningful demands was also highly appreciated, showing how the care for the best outcome was common ground. We highly recommend Novalabs for achieving business goals."

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The Approach

Biosimo intended to simulate their trickle bed reactor to gain a detailed understanding of fluid dynamics in the catalytic bed. Trickle bed reactors are complex and composed of various subsystems, which can influence each other and affect the reactor's overall performance. To precisely capture the main process features within the catalytic bed, Novalabs suggested splitting the entire system into subsystems. The first subsystem was simulated to generate accurate input parameters for the second one. This approach yielded unexpected results that challenged Biosimo's assumptions, providing even greater system understanding before the actual analysis of the trickle bed reactor had begun. It became clear that the first system's simulation was crucial to getting realistic input parameters for the trickle bed reactor simulation.

Novalabs used an isothermal, turbulent, and incompressible Volume of Fluid (VOF) approach for the first simulation to capture the system's multiphase nature. Custom Python scripts were created to extract essential information from the simulation and generate input parameters for the trickle bed simulation. The trickle bed simulation used a fully coupled thermal, turbulent, and compressible, multiphase Eulerian approach to account for the complex energy and momentum exchange between the fluids and the catalytic bed. Here too, tailored Python scripts were coded to extract quantitative data from the simulation. To aid fluid dynamic understanding and for qualitative considerations, high-resolution flow animations were provided over time.

Project Workflow

The project began with a detailed demand assessment and preparatory phase, in which Biosimo supplied key information. The virtual project kick-off allowed us to confirm data completeness and outline the upcoming steps. Our labs then determined the simulation strategies and modeling approaches, taking into account the systems' physical conditions and the flow features that needed capturing.

Biosimo aimed to understand the fluid dynamics' impact on the reactor's performance. To accomplish this, we selected key experimental configurations to simulate, characterized by notably high and low product yields. The simulations were created and run concurrently in a High-Performance Computing (HPC) environment to ensure we could deliver results within Biosimo's specified project timelines.

We carried out validation studies by comparing our computational findings with Biosimo's experimental data, which allowed us to establish confidence in our simulation methodology. We facilitated virtual updates every two weeks and encouraged technical and scientific discussion to draw conclusions from the results. Based on the simulation findings and established engineering principles, we suggested ways to fine-tune certain reactor characteristics by adjusting geometrical and operational parameters.

At the end of the project, Biosimo received presentation slides and a ready-to-run computational model for future use.

Summary

For Biosimo, understanding fluid dynamics was a crucial step in designing an efficient reactor. Attempting to design an efficient lab-scale reactor purely based on experiments introduces potential risks when scaling up, due to the possible 'black-box' nature of these experiments. Many times, it leads to a need for parameter reengineering in the large-scale reactor, which can be both expensive and time-consuming, posing a significant risk to the business. Thus, it is highly recommended to adopt a hybrid approach, combining experimentation and simulations. This approach not only proves more cost-effective but also enhances system understanding, enabling quicker achievement of engineering and business goals.

The engineers at Biosimo demonstrated great innovation in adopting this modern, hybrid approach that effectively combines experimentation with simulation. At Novalabs, we're dedicated to helping our clients reach their business objectives with confidence. We strive to make our simulation services quickly accessible and easy to use.

Emily Lupparelli

"Novalabs' CFD services identified crucial system aspects of our trickle bed reactor and provided a game-changing simulation that optimized our reaction efficiency early on. Their modelling and engineering expertise gave us confidence to scale up and maximize yield and quality. Highly recommend for gaining deep system understanding."

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