Method for simulating lifeline of cells in large-scale bioreactor based on Euler-Lagrangian method
Through the Euler-Lagrangian method and multiphase flow model, the substrate and dissolved oxygen gradient in large-scale bioreactors are simulated, and the problem of difficult-to-described behavior of cells in heterogeneous environments is solved, and the cellular perspective is realized environmental change recording and reactor structure optimization.
Patent Information
- Application Number
- CN202411305638.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-19
- Publication Date
- 2024-12-17
AI Technical Summary
In large-scale bioreactors, heterogeneity causes cells to adjust physiological metabolic characteristics in environmental fluctuations, affecting yield and economic benefits. It is difficult for the existing technology to effectively simulate the behavior of cells in concentration gradient environments, especially substrates and dissolved oxygen. Joint simulation of gradients is complex and lacking.
Using the Euler-Lagrangian method, a three-dimensional geometric model of large-scale bioreactors was constructed, a kinetic model of bacterial consumption of substrate and oxygen was established, and the gradients of substrate and dissolved oxygen were obtained through numerical simulation. Distribution and cell lifeline, combined with the Euler-Euler multiphase flow model and interphase mass transfer model, simulates the gas-liquid two-phase flow field and cell movement.
Accurate simulation of substrate and dissolved oxygen gradients in large-scale bioreactors, avoiding the high cost and complexity of experimental determination, recording external environment changes from the perspective of cells, and designing Scale-down bioreactors and optimizing large Scale bioreactor structures provide support.
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Figure CN119150561A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the field of bioprocess engineering, and in particular relates to a method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrange method. Background Art
[0002] During the scale-up of bioprocesses, the increase in production scale and physical limitations lead to the inevitable heterogeneity in large-scale bioreactors. Especially in aerobic microbial fermentation, this heterogeneity is mainly manifested in the formation of substrate and dissolved oxygen concentration gradients. When strains adapted to the uniform environment of small and pilot scales are transferred to large tank environments with strong heterogeneity, cells will frequently experience environmental fluctuations due to fluid flow. This inhomogeneous environment prompts cells to adjust their physiological and metabolic characteristics to adapt to the new environment, which is usually manifested in production practice as a decrease in bacterial biomass, product output and yield, which in turn affects economic benefits and may even lead to process scale-up failure.
[0003] As the core equipment of bioprocess production, the flow field environment of bioreactor not only affects the physiological metabolism of cells, but also determines the success or failure of process amplification. Therefore, it is of vital significance to study the influence of heterogeneity in large-scale bioreactors on cells. At present, the research on concentration gradient in large-scale bioreactors mainly adopts two methods: computational fluid dynamics (CFD) simulation and experimental measurement. However, due to the high experimental cost, many limiting factors and low feasibility, most studies are based on CFD simulation. The simulation methods of concentration gradient in large-scale bioreactors are mainly divided into Euler-Euler method and Euler-Lagrange method. In the Euler-Euler method, both fluid and cells are regarded as continuous phases, and the simulation process is relatively simple, but it reflects the overall average value and cannot describe the behavior of individual cells. In contrast, the Euler-Lagrange method treats fluid as a continuous phase and cells as discrete phases. This method can simulate the trajectory of cell movement through Lagrangian particles, record the information of the environment in which the particles are located, and thus observe the changes in the external environment from the perspective of cells, which has higher research value.
[0004] At present, most studies focus on the Euler-Euler method and single substrate concentration gradient, mainly because the simulation process is relatively simple and requires less computing resources. For aerobic fermentation processes, oxygen is a key factor for cell survival, so it is crucial to study the effects of dissolved oxygen concentration gradients on cells in large-scale bioreactors. However, since the joint simulation of substrate and dissolved oxygen gradients requires not only consideration of the flow field mixing characteristics within the reactor, but also complex factors such as the interphase mass transfer between the gas and liquid phases and the uptake kinetics of substrates and oxygen by the bacteria, research in this area is relatively scarce. Summary of the invention
[0005] In order to solve the above technical problems, the present invention proposes a method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method to solve the problems existing in the above prior art.
[0006] To achieve the above object, the present invention provides a method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method, comprising the following steps:
[0007] Constructing a three-dimensional geometric model of a large-scale bioreactor and meshing the three-dimensional geometric model;
[0008] Establishing a kinetic model of substrate and oxygen consumption by bacteria, coupling the kinetic model with the three-dimensional geometric model after meshing to obtain a coupling model;
[0009] Boundary conditions and solution control parameters are set, numerical simulation is performed on the coupling model based on the boundary conditions and solution control parameters, and the numerical simulation results are processed and analyzed to obtain the gradient distribution of substrate and dissolved oxygen and the lifeline of cells.
[0010] Preferably, the large-scale bioreactor comprises a reactor tank, an air inlet ring, a baffle, and a stirring paddle.
[0011] Preferably, when meshing the three-dimensional geometric model, polyhedral meshes are used for meshing, and the air intake ring, the agitator and the baffle are locally encrypted.
[0012] Preferably, the expression of the kinetic model is:
[0013]
[0014]
[0015] In the formula, q s is the rate of substrate uptake by the bacteria, q o is the oxygen uptake rate of the bacteria, C s is the substrate concentration, C o is the dissolved oxygen concentration, K s is the affinity constant of the bacteria to the substrate, K o is the affinity constant of the bacteria for oxygen.
[0016] Preferably, the method for obtaining the gradient distribution of substrate and dissolved oxygen and the lifeline of cells comprises:
[0017] Based on the Euler-Euler multiphase flow model, the gas-liquid two-phase flow is simulated. When the torque of the impeller is stable, the convergence state is reached and the steady-state gas-liquid two-phase flow field is obtained.
[0018] Open the interphase mass transfer model, calculate the interphase oxygen mass transfer based on the steady-state gas-liquid two-phase flow field, and obtain the mass transfer results;
[0019] Simulating the substrate and dissolved oxygen concentration gradients based on the mass transfer results to obtain the distribution of the substrate and oxygen concentration gradients;
[0020] Turn on the discrete phase model and simulate cell movement based on the distribution of substrate and oxygen concentration gradients to obtain the lifeline of the cell.
[0021] Preferably, when simulating the gas-liquid two-phase, the direction and magnitude of gravity are set, the direction of gravity is the negative direction of the z-axis of the coordinate system, the component transport equation is turned on to simulate the convection diffusion of the substrate and oxygen, the gas-liquid two-phase materials are set as mixtures, and the material properties are determined by the volume / mass weighted mixed power law.
[0022] Preferably, when calculating the oxygen mass transfer between phases, only the component transport related equations are opened to solve, and convergence is achieved when the changes in oxygen concentrations in the gas phase and the liquid phase are stable.
[0023] Preferably, the liquid phase material is set to be a mixture of oxygen, substrate and fermentation liquid, and the kinetic equations of substrate introduction and substrate and oxygen uptake by bacteria are compiled into FLUENT through source UDF for calculation and solution.
[0024] Preferably, when performing cell movement simulation, massless Lagrangian particles are introduced at the top of the reactor to simulate cells for movement simulation.
[0025] Compared with the prior art, the present invention has the following advantages and technical effects:
[0026] The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method described in the present invention can simulate the substrate and dissolved oxygen concentration gradients in the large-scale bioreactor, avoiding the difficulties and high costs of traditional experimental measurements, and can record changes in the external environment from the perspective of cells, providing support for designing scale-down bioreactors to explore the impact of the heterogeneous environment of large-scale bioreactors on cells and for the design optimization of large-scale bioreactor structures, filling the gap in domestic research in related fields. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:
[0028] Figure 1 A three-dimensional geometric model diagram of a large-scale bioreactor according to an embodiment of the present invention;
[0029] Figure 2The simulated substrate and dissolved oxygen concentration gradient distribution diagrams of the embodiment of the present invention, the left figure is the substrate concentration gradient distribution diagram, and the right figure is the dissolved oxygen gradient distribution diagram;
[0030] Figure 3 A schematic diagram of the substrate lifeline experienced by cells according to an embodiment of the present invention;
[0031] Figure 4 Schematic diagram of the dissolved oxygen lifeline experienced by cells according to an embodiment of the present invention. DETAILED DESCRIPTION
[0032] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.
[0033] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.
[0034] Embodiment 1
[0035] This embodiment provides a method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method, comprising the following steps:
[0036] Constructing a three-dimensional geometric model of a large-scale bioreactor and meshing the three-dimensional geometric model;
[0037] Establishing a kinetic model of substrate and oxygen consumption by bacteria, coupling the kinetic model with the three-dimensional geometric model after meshing to obtain a coupling model;
[0038] Boundary conditions and solution control parameters are set, numerical simulation is performed on the coupling model based on the boundary conditions and solution control parameters, and the numerical simulation results are processed and analyzed to obtain the gradient distribution of substrate and dissolved oxygen and the lifeline of cells.
[0039] The specific implementation steps are as follows:
[0040] The 3D geometric model of a large-scale bioreactor was constructed based on Creo software, and the impeller area and the reactor body area were drawn separately. Figure 1 shown.
[0041] The drawn geometric model is converted into stp format and imported into Design Modeler for boundary conditions and fluid domain naming. It is saved as an agdb format file and then imported into FLUENT MESHING for mesh drawing. The Watertight Geometry workflow is used for meshing. The overall mesh uses polyhedral meshes, and the impeller, intake ring and baffle areas are locally encrypted, with the number of meshes being approximately 1.5 million.
[0042] The equations for the uptake of substrate and oxygen by bacteria use an unstructured kinetic model, and the uptake rates of the two by the bacteria are coupled together. The kinetic parameters are determined through small-scale experiments.
[0043]
[0044] In the formula, q s is the rate of substrate uptake by the bacteria, q o is the oxygen uptake rate of the bacteria, C s is the substrate concentration, C o is the dissolved oxygen concentration, K s is the affinity constant of the bacteria to the substrate, K o is the affinity constant of the bacteria for oxygen.
[0045] Import the generated grid file into FLUENT to set the initial calculation conditions, and then perform the calculation and solution until the calculation process reaches convergence.
[0046] The entire calculation process is divided into four steps. The initial calculation condition setting includes the selection of solution type and operating conditions, physical model, material properties, boundary conditions, initialization, solution method, determination of control equations and compilation of UDF.
[0047] The first step is to calculate the steady-state gas-liquid two-phase flow field. First, set the gravity direction to the negative direction of the coordinate system z-axis and the gravity magnitude to 9.8m / s 2The Euler-Euler multiphase flow model is used to simulate the gas-liquid two-phase flow. The surface tension is set to 0.073N / m, the drag model is set to the Grace model, and other interphase forces are ignored. The size of the gas phase is controlled by the PBM model, and the range is set to 0.2mm-6.4mm. The component transport equation is turned on to simulate the convection and diffusion of the substrate and oxygen. The gas and liquid phase materials are set to mixtures. The gas phase material composition is oxygen and nitrogen, and the liquid phase material composition is oxygen and fermentation liquid. The material properties are determined by the volume / mass weighted mixed power law. The turbulence model is set to the standard k-ε model. The impeller area simulates the rotation of the impeller through a multiple reference frame (MRF). The interface is set to interface, the gas inlet surface is set to velocity-inlet, the gas outlet surface is set to degassing, and the remaining boundary conditions are set to wall. The value of velocity-inlet is used as a reference for initialization, and the volume fraction of the gas phase is set to 0, and the component patch of oxygen in the liquid phase is 0. The solution method uses the PhaseCoupled SIMPLE algorithm, and the residual is set to 10 -5 The impeller torque is monitored during the solution process and is considered converged when stability is reached.
[0048] The second step is to calculate the oxygen mass transfer between phases. Based on the calculation results of the first step, the interphase mass transfer model is enabled, and the transfer of oxygen from the gas phase to the liquid phase is set. The mass transfer rate is calculated using the Higbie permeation model and written into FLUENT through a user-defined function (UDF). The solution type is changed to transient solution, and only the component transport-related solution equations are enabled. The solution time step is set to 0.02s, and the calculation residual is set to 10 -4 During the solution process, monitoring points are set to monitor the changes in oxygen concentration in the gas phase and liquid phase, and convergence is considered when it is stable.
[0049] The third step is to simulate the concentration gradient of substrate and dissolved oxygen. Based on the results of oxygen mass transfer in the second step, the liquid phase material is set to a mixture of oxygen, substrate and fermentation liquid. The introduction of substrate and the kinetic equations of the bacterial cell's uptake of substrate and oxygen are compiled into FLUENT through the source UDF. Then continue to calculate and solve, and the calculation residual is set to 10 -4 , the solution process monitors the changes in oxygen concentration in the two phases and the changes in substrate concentration in the liquid phase, and is considered to have converged when stability is reached.
[0050] The fourth step is the simulation of cell movement. After simulating the distribution of substrate and oxygen concentration gradients, the discrete phase model is turned on. A certain number of massless Lagrangian particles are introduced at the top of the reactor to simulate cells. The DRW random walk model is enabled to simulate cell movement. The substrate and dissolved oxygen concentration gradients are frozen during particle movement. Only the particle motion equations are solved. The simulation time step is set to 0.02s. At the same time, UDF is written to record the substrate and dissolved oxygen concentrations in the grid where each particle is located at each time point and output to the file to complete the recording of the cell lifeline.
[0051] After the solution is completed, the calculation results are imported into CFD-POST software for post-processing, and the gradient distribution of substrate and dissolved oxygen in the large-scale reactor can be obtained, such as Figure 2 By visualizing the files recording the particle lifeline, we can see the changes in the environmental gradient experienced by the cells in the large-scale reactor, such as Figure 3 , 4 Statistical analysis of the distribution of switching and residence time of all particles between different environmental gradients can be used to design scale-down bioreactors and optimize the structure of large-scale bioreactors to achieve two-way adaptation of strains and environments.
[0052] In summary, the present invention applies CFD numerical calculation technology to the field of bioprocess engineering, and uses FLUENT software to numerically simulate the gradients of substrates and dissolved oxygen in large-scale bioreactors, avoiding the high cost and implementation difficulties of experimental technology in gradient research in large-scale bioreactors. It can also record changes in the external environment from the perspective of cells, providing support for designing scale-down bioreactors to explore the impact of the heterogeneous environment of large-scale bioreactors on cells and for the design optimization of large-scale bioreactor structures.
[0053] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
Claims
1. A method for simulating the lifeline of cells in large-scale bioreactors based on the Euler-Lagrangian method, It is characterized in that The following steps are involved: Constructing a three-dimensional geometric model of a large-scale bioreactor and meshing the three-dimensional geometric model; Establishing a kinetic model of substrate and oxygen consumption by bacteria, coupling the kinetic model with the three-dimensional geometric model after meshing to obtain a coupling model; Boundary conditions and solution control parameters are set, numerical simulation is performed on the coupling model based on the boundary conditions and solution control parameters, and the numerical simulation results are processed and analyzed to obtain the gradient distribution of substrate and dissolved oxygen and the lifeline of cells.
2. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 1, It is characterized in that The large-scale bioreactor comprises a reactor tank, an air inlet ring, a baffle and a stirring paddle.
3. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 1, It is characterized in that When meshing the three-dimensional geometric model, polyhedral meshes are used for meshing, and the air inlet ring, the stirring paddle and the baffle are locally encrypted.
4. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 1, It is characterized in that The expression of the kinetic model is: In the formula, q s is the rate of substrate uptake by the bacteria, q o is the oxygen uptake rate of the bacteria, C s is the substrate concentration, C o is the dissolved oxygen concentration, K s is the affinity constant of the bacteria to the substrate, K o is the affinity constant of the bacteria for oxygen.
5. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 1, It is characterized in that Methods for obtaining gradient distribution of substrate and dissolved oxygen and the lifeline of cells include: Based on the Euler-Euler multiphase flow model, the gas-liquid two-phase flow is simulated. When the torque of the impeller is stable, the convergence state is reached and the steady-state gas-liquid two-phase flow field is obtained. Open the interphase mass transfer model, calculate the interphase oxygen mass transfer based on the steady-state gas-liquid two-phase flow field, and obtain the mass transfer results; Simulating the substrate and dissolved oxygen concentration gradients based on the mass transfer results to obtain the distribution of the substrate and oxygen concentration gradients; Turn on the discrete phase model and simulate cell movement based on the distribution of substrate and oxygen concentration gradients to obtain the lifeline of the cell.
6. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 5, It is characterized in that When simulating the gas-liquid two-phase, set the direction and magnitude of gravity. The direction of gravity is the negative direction of the z-axis of the coordinate system. Enable the component transport equation to simulate the convection and diffusion of substrate and oxygen. Set the gas-liquid two-phase materials as mixtures. The material properties are determined by the volume / mass weighted mixed power law.
7. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 5, It is characterized in that When calculating the oxygen mass transfer between phases, only the component transport related equations are opened for solution, and convergence is achieved when the changes in oxygen concentrations in the gas and liquid phases are stable.
8. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 5, It is characterized in that The liquid phase material is set as a mixture of oxygen, substrate and fermentation liquid. The kinetic equations of substrate introduction and bacterial uptake of substrate and oxygen are compiled into FLUENT through source UDF for calculation and solution.
9. The method for simulating the lifeline of cells in a large-scale bioreactor based on the Euler-Lagrangian method according to claim 5, It is characterized in that When simulating cell movement, massless Lagrangian particles are introduced at the top of the reactor to simulate the cells for motion simulation.