Respirator gas analysis sampling pipeline flow field simulation evaluation method and system

Abstract

The invention relates to a respirator gas analysis sampling pipeline flow field simulation evaluation method and system. The method comprises the following steps: pre-processing a geometric model of an oxygen concentration detection host; performing internal flow field extraction on the geometric model of the oxygen concentration detection host, and establishing an internal flow field sampling pipeline model; carrying out grid division; setting working conditions; selecting a physical model; setting gas physical property parameters; setting boundary conditions and simulated working conditions; carrying out solution setting and initialization; taking a cross section formed in the vertical middle position of the grid model as a monitoring surface, and taking a position, corresponding to the gas sensor, on the monitoring surface as a monitoring point; setting iterative calculation; simulating a breathing process in a preset time under the most quiet working condition and the most severe working condition, performing sampling pipeline internal flow field transient simulation on the grid model, solving the selected physical model by adopting a coupling algorithm, and sampling a monitoring surface and a monitoring point under the two working conditions in the solving process; and acquiring and displaying a simulation result, and analyzing the simulation result to evaluate the advantages and disadvantages of the designed oxygen concentration detection host.

Description

Technical Field

[0001] The present invention relates to the technical field of respirator modeling and simulation, and in particular to a respirator gas analysis sampling pipeline flow field simulation evaluation method and system. Background Art

[0002] The inventor of the present invention has searched the prior art and found that there is no technology for simulating the flow field of the respirator gas analysis sampling pipeline, and specifically, there is no technology for simulating the flow field of the oxygen concentration detection host to evaluate the quality of the oxygen concentration detection host. It is necessary to evaluate the working performance of the designed oxygen concentration detection host in the frogman respirator, and evaluate the differences between different structures to find the optimal structure. Based on this, the present invention designs a method and system for simulating the flow field of the respirator gas analysis sampling pipeline. Summary of the invention

[0003] In view of the problems and shortcomings of the prior art, the present invention provides a method and system for simulating and evaluating the flow field of a respirator gas analysis sampling pipeline.

[0004] The present invention solves the above technical problems through the following technical solutions:

[0005] The present invention provides a flow field simulation evaluation method for a respirator gas analysis sampling pipeline, which is characterized in that it comprises the following steps:

[0006] S1. Geometric preprocessing: geometric preprocessing of the geometric model of the oxygen concentration detection host in the respirator gas analysis sampling pipeline;

[0007] S2. Modeling: extracting the internal flow field of the geometric model of the oxygen concentration detection host after geometric pre-processing, and establishing the internal flow field sampling pipeline model of the oxygen concentration detection host;

[0008] S3. Meshing: Meshing the internal flow field sampling pipeline model to obtain an internal flow field sampling pipeline mesh model;

[0009] S4. Set working conditions: Set the diving depth as the simulated working environment, set the breathing flow rate of the user to follow the sinusoidal curve when breathing, and have two extreme states, namely the calmest state and the most intense state;

[0010] S5. Physical model selection: According to the working principle and working process of the oxygen concentration detection host, select the turbulence equation to describe the movement of the airflow and the generation and dissipation of turbulence, select the energy equation to calculate the temperature change, and select the component transport equation to describe the multi-component diffusion process in the gas to simulate the changes in the oxygen and carbon dioxide content in the oxygen concentration detection host;

[0011] S6. Gas physical property parameter setting: set the gas physical property parameters, including oxygen, nitrogen, carbon dioxide and water vapor;

[0012] S7, boundary conditions and simulation conditions setting: setting the inlet boundary conditions and outlet boundary conditions of the internal flow field sampling pipeline grid model, setting the simulation conditions including the calmest condition and the most violent condition;

[0013] S8, solution setting and initialization: setting the coupling algorithm to solve the selected physical model, using standard initialization, assigning values ​​to the oxygen content, carbon dioxide content, water vapor content and temperature of the initial field to simulate the initial state of the oxygen concentration detection host;

[0014] S9, construction of monitoring surface and monitoring point: the cross section formed by the vertical middle position of the internal flow field sampling pipeline grid model is used as the constructed monitoring surface to monitor the changes of physical quantities during breathing, and the position on the monitoring surface corresponding to the gas sensor is used as the constructed monitoring point;

[0015] S10, iterative calculation settings: setting the preset time and time step for each simulation condition;

[0016] S11, simulation: simulate the breathing process within a preset time under the calmest working condition and the most intense working condition, respectively perform transient simulation of the internal flow field of the sampling pipeline on the internal flow field sampling pipeline grid model, use the coupling algorithm to solve the selected physical model, and sample the pressure, velocity, temperature and oxygen concentration of the monitoring surface and monitoring points under the two working conditions during the solution process;

[0017] S12. Simulation results: obtain and display simulation results, including velocity field cloud diagrams of the monitoring surface within a preset time under the calmest working condition and the most intense working condition, velocity vector distribution diagrams during breathing, pressure cloud diagrams, temperature cloud diagrams and oxygen content distribution diagrams, velocity change curves, pressure change curves, temperature change curves and oxygen mass fraction change curves of the monitoring points within a preset time under the calmest working condition and the most intense working condition, and analyze the simulation results to evaluate the advantages and disadvantages of the designed oxygen concentration detection host.

[0018] The present invention also provides a respirator gas analysis sampling pipeline flow field simulation evaluation system, which is characterized in that it includes a pre-processing module, a modeling module, a grid division module, an operating condition setting module, a physical model selection module, a physical property parameter setting module, a condition setting module, a solution initialization setting module, a monitoring construction module, an iterative calculation setting module, a simulation module and a simulation result analysis module;

[0019] The pre-processing module is used to perform geometric pre-processing on the geometric model of the oxygen concentration detection host in the respirator gas analysis sampling pipeline;

[0020] The modeling module is used to extract the internal flow field of the geometric model of the oxygen concentration detection host after geometric pre-processing, and establish the internal flow field sampling pipeline model of the oxygen concentration detection host;

[0021] The grid division module is used to grid the internal flow field sampling pipeline model to obtain the internal flow field sampling pipeline grid model;

[0022] The working condition setting module is used to set the diving depth as the simulated working condition environment, and set the user's breathing flow rate to conform to the form of a sine curve when breathing, and has two extreme states, namely the calmest state and the most intense state;

[0023] The physical model selection module is used to select the turbulence equation to describe the movement of the airflow and the generation and dissipation of turbulence according to the working principle and working process of the oxygen concentration detection host, select the energy equation to calculate the temperature change, and select the component transport equation to describe the multi-component diffusion process in the gas, so as to simulate the changes in the oxygen and carbon dioxide content in the oxygen concentration detection host;

[0024] The physical property parameter setting module is used to set the physical property parameters of the gas, which include oxygen, nitrogen, carbon dioxide and water vapor;

[0025] The condition setting module is used to set the inlet boundary conditions and outlet boundary conditions of the internal flow field sampling pipeline grid model, and the simulation conditions include the calmest condition and the most violent condition;

[0026] The solution initialization setting module is used to set the coupling algorithm to solve the selected physical model, use standard initialization, and assign values ​​to the oxygen content, carbon dioxide content, water vapor content and temperature of the initial field to simulate the initial state of the oxygen concentration detection host;

[0027] The monitoring construction module is used to use the cross section formed by the vertical middle position of the internal flow field sampling pipeline grid model as a constructed monitoring surface for monitoring the change of physical quantities during breathing, and to use the position on the monitoring surface corresponding to the gas sensor as a constructed monitoring point;

[0028] The iterative calculation setting module is used to set the preset time and time step for each simulation condition;

[0029] The simulation module is used to simulate the breathing process within a preset time under the calmest working condition and the most intense working condition, respectively perform transient simulation of the internal flow field of the sampling pipeline on the internal flow field sampling pipeline grid model, use the coupling algorithm to solve the selected physical model, and during the solution process, respectively perform pressure, velocity, temperature and oxygen concentration sampling on the monitoring surface and monitoring points under the two working conditions;

[0030] The simulation result analysis module is used to obtain and display simulation results, including velocity field cloud maps of the monitoring surface within a preset time under the calmest working conditions and the most intense working conditions, breathing velocity vector distribution maps, pressure cloud maps, temperature cloud maps and oxygen content distribution maps, and velocity change curves, pressure change curves, temperature change curves and oxygen mass fraction change curves of the monitoring points within a preset time under the calmest working conditions and the most intense working conditions. The simulation results are analyzed to evaluate the advantages and disadvantages of the designed oxygen concentration detection host.

[0031] The positive and progressive effects of the present invention are:

[0032] The present invention models an oxygen concentration detection host, establishes an internal flow field sampling pipeline model of the oxygen concentration detection host, obtains an internal flow field sampling pipeline grid model by grid division, and performs three-dimensional flow field simulations under calm conditions and severe conditions by using ANSYS simulation software according to the established internal flow field sampling pipeline grid model, obtains the distribution of velocity, pressure, oxygen concentration and temperature in the pipeline flow field under calm conditions and severe conditions and their changes with time, analyzes the advantages and disadvantages of the oxygen concentration detection host through simulation results, and obtains the optimal structural solution of the oxygen concentration detection host by comparison. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Flow chart of the flow field simulation evaluation method for the respirator gas analysis sampling pipeline.

[0034] Figure 2 This is the geometric model diagram of oxygen concentration detection hosts one, two and three.

[0035] Figure 3 This is a schematic diagram of the structure of oxygen concentration detection host three.

[0036] Figure 4 This is a model diagram of the internal flow field sampling pipeline of the oxygen concentration detection host.

[0037] Figure 5 This is the internal flow field sampling pipeline model diagram of the oxygen concentration detection host 2.

[0038] Figure 6 This is the internal flow field sampling pipeline model diagram of the oxygen concentration detection host three.

[0039] Figure 7 This is the internal flow field sampling pipeline grid model diagram of the oxygen concentration detection host.

[0040] Figure 8 This is the grid model diagram of the internal flow field sampling pipeline of the oxygen concentration detection host 2.

[0041] Fig. 9 This is the internal flow field sampling pipeline grid model diagram of the oxygen concentration detection host three.

[0042] Fig.10 This is the inlet and outlet boundary condition diagram of oxygen concentration detection host one.

[0043] Fig.11 This is the inlet and outlet boundary condition diagram of oxygen concentration detection host 2.

[0044] Fig.12 This is the inlet and outlet boundary condition diagram of oxygen concentration detection host three.

[0045] Fig.13 This is a graph of the speed changes at the entrance of the main unit during the breathing process (the calmest state).

[0046] Fig.14 This is a diagram of the speed change at the entrance of the oxygen concentration detection host during the breathing process (the most intense state).

[0047] Fig.15 This is the monitoring surface and monitoring point location map corresponding to the oxygen concentration detection host.

[0048] Fig.16 This is the monitoring surface and monitoring point location map corresponding to the oxygen concentration detection host 2.

[0049] Fig.17 This is the monitoring surface and monitoring point location map corresponding to the oxygen concentration detection host three.

[0050] Fig.18 This is a cloud diagram of the velocity field of the main engine under calm and severe working conditions for oxygen concentration detection at 30 seconds.

[0051] Fig.19 This is the velocity field cloud diagram of the main engine under calm and severe working conditions for oxygen concentration detection at 30 seconds.

[0052] Fig. 20 This is a cloud diagram of the velocity field of the main engine under three calm and severe working conditions for oxygen concentration detection at 30 seconds.

[0053] Fig.21 The oxygen concentration detection host is a speed vector diagram under calm and severe working conditions at 30 seconds.

[0054] Fig. 22 It is the speed vector diagram of the main engine under calm and severe working conditions for oxygen concentration detection at 30 seconds.

[0055] Fig.23 It is a speed vector diagram of the main engine under three calm and severe working conditions for oxygen concentration detection at 30 seconds.

[0056] Fig.24 It is a speed change curve of the sensor monitoring point under quiet working conditions from 0 to 30 seconds.

[0057] Fig.25This is a curve diagram of the speed change of the sensor monitoring point under severe working conditions from 0 to 30 seconds.

[0058] Fig.26 It is a curve diagram of pressure change at the sensor monitoring point under calm working conditions from 0 to 30 seconds.

[0059] Fig. 27 It is a curve diagram of pressure change at the sensor monitoring point under severe working conditions from 0 to 30 seconds. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0061] like Figure 1 As shown, this embodiment provides a method for simulating and evaluating the flow field of a respirator gas analysis sampling pipeline, which includes the following steps:

[0062] Step 101, geometric pre-processing: for three oxygen concentration detection hosts with different structural designs, namely oxygen concentration detection host 1, oxygen concentration detection host 2 and oxygen concentration detection host 3, see Figure 2 From left to right, the three structures are geometrically pre-processed using ANSYS SpaceClaim software to remove unnecessary lines, bolts, useless fillets, etc. that are useless to the internal flow field of each structure, and to repair interference structures such as sealing rubber rings and assembly gaps.

[0063] This embodiment includes the structure of the oxygen detection device in the invention patent with application number 2024116337235 and name of a double-chamber underwater wireless data monitoring system for a diving breathing apparatus, constituting the structure of an oxygen concentration detection host one.

[0064] This embodiment includes the structure of the oxygen detection host in the invention patent with application number 202410559489X and name of a closed respirator breathing gas oxygen concentration monitoring system, constituting the structure of oxygen concentration detection host two.

[0065] The structure of the oxygen concentration detection host 3 in this embodiment is shown in Figure 3 , Figure 3 Mark 1 is the differential pressure sensor, mark 2 is the oxygen sensor, mark 3 is the control circuit board, mark 4 is the battery, and mark 5 is the communication module.

[0066] Step 102, modeling: extracting the internal flow field of each oxygen concentration detection host structure after geometric pre-processing, and establishing the internal flow field sampling pipeline model of each oxygen concentration detection host.

[0067] in, Figure 4 This is the internal flow field sampling pipeline model of the oxygen concentration detection host. Figure 5 This is the internal flow field sampling pipeline model of the oxygen concentration detection host 2. Figure 6 This is the internal flow field sampling pipeline model of the oxygen concentration detection host three.

[0068] Step 103, meshing: Ansys FluentMeshing meshing tool is used to mesh each internal flow field sampling pipeline model to obtain the corresponding internal flow field sampling pipeline mesh model. This step of meshing realizes the spatial discretization of the fluid domain, preparing for the subsequent fluid flow solution.

[0069] Among them, for the internal flow field sampling pipeline model of the oxygen concentration detection host one, a quadrilateral surface mesh is generated, a smooth-transition method is used to generate the boundary layer, and a polyhedral mesh (Poly-Hexcore mesh) with a hexahedron core is selected as the volume mesh to fill the internal mesh of the flow field. The number of meshes is 277,000, and the minimum orthogonal quality of the mesh is 0.28, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host one (see Figure 7 ). The criterion for the minimum orthogonal quality of a grid is usually greater than 0.1, and the grid can be used for flow field simulation analysis.

[0070] For the internal flow field sampling pipeline model of the oxygen concentration detection host II, a quadrilateral surface mesh is generated, a smooth conversion method is used to generate the boundary layer, and a polyhedral mesh is selected as the volume mesh to fill the internal mesh of the flow field. The number of meshes is 180,000, and the minimum orthogonal quality of the mesh is 0.32, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host II (see Figure 8 ). The criterion for the minimum orthogonal quality of a grid is usually greater than 0.1, and the grid can be used for flow field simulation analysis.

[0071] For the internal flow field sampling pipeline model of the oxygen concentration detection host three, a quadrilateral surface mesh is generated, a smooth conversion method is used to generate the boundary layer, and a polyhedral mesh is selected as the volume mesh to fill the internal mesh of the flow field. The number of meshes is 417,700, and the minimum orthogonal quality of the mesh is 0.25, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host three (see Fig. 9 ). The criterion for the minimum orthogonal quality of a grid is usually greater than 0.1, and the grid can be used for flow field simulation analysis.

[0072] Step 104, working condition calculation: Taking the diving depth of 0 to 40m as the simulated working environment, according to the design requirements, when the user breathes, the change of the breathing flow rate conforms to the form of a sine curve. In actual use, the user has two extreme states, namely the calmest state and the most intense state. The peak inhalation volume in the calmest state is 600ml, and the breathing frequency is 13 times / min. The peak inhalation volume in the most intense state is 5000ml, and the frequency is 21 times / min. The two extreme working conditions are analyzed below.

[0073] The calmest working condition: The peak inspiratory volume in the calmest state is 600ml, the respiratory rate is 13 times / minute, the cycle is 60 / 13 seconds, and the function of the respiratory flow curve is Where t is the time in seconds.

[0074] The most intense working condition: The peak inspiratory volume in the most intense state is 5000ml, the respiratory rate is 21 times / minute, the cycle is 60 / 21 seconds, and the function of the respiratory flow curve is Where t is the time in seconds.

[0075] Step 105, physical model selection: According to the working principle and working process of the oxygen concentration detection host, a mathematical model is used to describe its physical process. During the working process of the oxygen concentration detection host, when the human body inhales, the gas in the inhalation bag of the respirator will flow through the internal flow field area of ​​the oxygen concentration detection host and then enter the human body from the outlet through the connecting pipe and the one-way breathing valve. The turbulence equation (SST k-omega equation) is used to describe the movement of the airflow and the generation and dissipation of turbulence; in order to calculate the temperature change, the energy equation is used to describe it; in order to simulate the changes in the oxygen and carbon dioxide content in the oxygen concentration detection host, the Species transport component transport equation is used to describe the multi-component diffusion process in the gas; the simulation equation settings of the three internal flow field sampling pipeline grid models are the same.

[0076] Among them, the SST k-omega turbulence model is a two-equation model, and k and omega are solved by the following equations respectively:

[0077]

[0078] Among them, G k represents the generation of turbulent kinetic energy due to the mean velocity gradient, G w represents the generation of w, τ k and τ w denote the effective diffusion of k and w, respectively, and Y k and Y w They represent the dissipation of k and w due to turbulence respectively.

[0079] The component transport equation solved by Ansys Fluent is as follows:

[0080]

[0081] ρ is the density of the mixture; i is each component; v is the velocity of the diffusing component; Ri is the net generation rate of component i; Si is the generation rate of component i due to the source term. By solving this equation, the local mass fraction of each component is predicted to obtain the distribution of concentration.

[0082] The energy equation solved by Ansys Fluent is as follows:

[0083]

[0084] where k eff is the effective thermal conductivity (k+k t ), k t is the turbulent heat transfer coefficient, which is used according to the turbulence model; Jj is the diffusion flow rate of component j. The three terms in the brackets on the right side of the equation represent heat conduction, component diffusion, and turbulent heat diffusion from left to right; S h is the volume heat source term; h is the enthalpy in the system.

[0085] Step 106, material property parameter setting: select the physical property parameters in the built-in fluid model material database, and the mixed gas parameters corresponding to the three oxygen concentration detection hosts are the same.

[0086] Table 1

[0087]

[0088] Step 107, boundary conditions and simulation working condition settings: The working conditions are that the human body is in the calmest state and the most intense state. When inhaling, the gas in the inhalation bag flows into the inlet of the oxygen concentration detection host and flows out from its outlet. The exhaled gas does not flow into the oxygen concentration detection host. The transient numerical simulation of this process within half a minute is performed. The initial boundary conditions are shown in Table 2 below.

[0089] Table 2

[0090]

[0091] The inlet of the oxygen concentration detection host is connected to the air bag, so the gas composition entering is the gas composition in the air bag, that is, 32% oxygen and 68% nitrogen.

[0092] The outlet of the oxygen concentration detection host is connected to the intake pipe and the one-way breathing valve. The initial state is the state filled with air when the product is installed. The mixed gas components are the atmospheric gas components, with oxygen O2 accounting for 20.946%, carbon dioxide CO2 accounting for 0.037%, water vapor H2O accounting for 0.25%, and the remaining gas is nitrogen N2.

[0093] The inlet and outlet boundary conditions of the oxygen concentration detection host are shown in Fig.10 , the import and export boundary conditions of oxygen concentration detection host 2 are shown in Fig.11 , the import and export boundary conditions of oxygen concentration detection host 3 are shown in Fig.12 .

[0094] During the exhalation cycle, the exhaled gas enters the exhalation bag through the one-way breathing valve, and then enters the CO2 absorption tank or is discharged through the exhaust pipe. During the inhalation cycle, the gas in the inhalation bag flows into the oxygen concentration detection host from the inlet on one side of the inhalation bag. The function form of the inlet gas velocity of the oxygen concentration detection host in half a minute under different human body conditions is as follows: Fig.13 and Fig.14 .

[0095] Step 108, solution setting and initialization: The selected physical model is solved using the Coupled coupling algorithm. The gradient discretization format in the coupling algorithm is the least squares method. The pressure, momentum, turbulence, components and energy discretization all use the second-order upwind format to improve the solution accuracy. Using standard initialization, the initial field is assigned an oxygen O2 content of 20.946%, a carbon dioxide CO2 content of 0.037%, a water vapor H2O content of 0.25%, and a temperature of 20°C to simulate the initial state of the oxygen concentration detection host. The solution settings and initialization of the three internal flow field sampling pipeline grid models are the same.

[0096] Step 109, constructing the monitoring surface and monitoring points: The cross section formed by the vertical middle position of the internal flow field sampling pipeline grid model is used as the constructed monitoring surface to monitor the physical quantity changes during the breathing process, and the position on the monitoring surface corresponding to the gas sensor is used as the constructed monitoring point. During the calculation process, the monitoring surface and the monitoring point are sampled for physical quantity data, including pressure, velocity, O2 concentration, and temperature.

[0097] Among them, the monitoring surface and monitoring point positions corresponding to the oxygen concentration detection host are shown in Fig.15 , the monitoring surface and monitoring point positions corresponding to the oxygen concentration detection host 2 are shown in Fig.16 , the monitoring surface and monitoring point positions corresponding to the oxygen concentration detection host are shown in Fig.17 .

[0098] Step 110, iterative calculation settings: the preset time for each model and working condition simulation is 30 seconds, the simulation time step is 0.02 seconds, and 20 iterations are performed in each time step to ensure convergence in each time step and ensure simulation accuracy. The preset time is 30 seconds, and the number of time steps is 30 / 0.02=1500 steps.

[0099] Step 111, simulation: simulate the breathing process within a preset time (30 seconds) under the calmest working condition and the most intense working condition, perform transient simulation of the internal flow field of the sampling pipeline for each internal flow field sampling pipeline grid model under the two working conditions, use the coupling algorithm to solve the selected physical model, and sample the pressure, velocity, temperature and oxygen concentration of the monitoring surface and monitoring point under the two working conditions during the solution process. The simulation process of the three internal flow field sampling pipeline grid models is the same, and each model and working condition simulates the actual breathing process of 30 seconds.

[0100] Step 112, simulation results: obtain and display the simulation results of each internal flow field sampling pipeline grid model, including the velocity field cloud map of the monitoring surface within the preset time under the calmest working condition and the most intense working condition, the velocity vector distribution map during breathing, the pressure cloud map, the temperature cloud map and the oxygen content distribution map, the velocity change curve, the pressure change curve, the temperature change curve and the oxygen mass fraction change curve of the monitoring point within the preset time under the calmest working condition and the most intense working condition, compare the velocity field cloud maps of the last second under the two working conditions in the three internal flow field sampling pipeline grid models, compare the velocity vector distribution maps of the last second during breathing in the two working conditions in the three grid models, and compare the velocity field cloud maps of the last second under the three grid models. The pressure cloud maps of the last second under the two working conditions are compared, the temperature cloud maps of the last second under the two working conditions in the three grid models are compared, the oxygen content distribution maps of the last second under the two working conditions in the three grid models are compared, the speed change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, the pressure change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, the temperature change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, and the oxygen mass fraction change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, and the advantages and disadvantages of the three oxygen concentration detection hosts are compared and evaluated.

[0101] For example: 1. Velocity field comparison

[0102] (1) Speed ​​cloud map

[0103] The velocity field cloud diagrams of various internal flow field sampling pipeline grid models under different working conditions at 30 seconds are compared (see Figure 18-20). By comparison, it can be seen that the maximum speed of the model corresponding to the oxygen concentration detection host 1 is 0.23m / s in the calmest state and 1.25m / s in the most violent state; the maximum speed of the model corresponding to the oxygen concentration detection host 2 is 0.18m / s in the calmest state and 0.88m / s in the most violent state. The minimum speed of the models corresponding to these two oxygen concentration detection hosts is 0m / s. This shows that the gas circulation in the model corresponding to the oxygen concentration detection host 1 is faster, and the gas replacement in the main channel is faster.

[0104] In addition, there is a small curved gap channel between the bottom space of the model corresponding to the oxygen concentration detection host 1 and the main channel, and part of the gas will flow into this area. The gas in this area cannot or is difficult to be updated, which is a dead zone. The airflow of the model corresponding to the oxygen concentration detection host 2 will basically fill all areas and update the gas at all times, and there is basically no large dead zone.

[0105] According to the flow field simulation results of the model corresponding to the oxygen concentration detection host three, it can be seen that the maximum speed is 0.21m / s in the calmest state and 1.48m / s in the most violent state, both of which are greater than the first two models, indicating that the gas flow rate inside the structure of the oxygen concentration detection host three is fast, and when a person inhales, the oxygen in the air bag is more easily transported to the human body.

[0106] (2) Comparison of velocity vector during breathing

[0107] The velocity vector diagrams of various internal flow field sampling pipeline grid models under different working conditions at 30 seconds are compared (see Figure 21-23 ). By comparing the velocity vector diagrams, it can be seen that each model has a certain reflux area. The reflux area of ​​the model corresponding to the oxygen concentration detection host one is mainly located above the main channel, between the main channel differential pressure sensor and the oxygen sensor, and in the large space below the differential pressure sensor (in the rectangular box in the figure). The reflux area of ​​the model corresponding to the oxygen concentration detection host two is mainly located in the differential pressure sensor and each circular corner area (in the rectangular box in the figure). The reflux area of ​​the model corresponding to the oxygen concentration detection host three is mainly located in the differential pressure sensor and the bottom structure area (in the rectangular box in the figure).

[0108] 2. Pressure field comparison

[0109] The pressure cloud diagrams of various internal flow field sampling pipeline grid models under different working conditions at 30 seconds are compared. From the comparison, it can be seen that the maximum pressure of the model corresponding to the oxygen concentration detection host one is 0.38Pa in the calmest state and 2.75Pa in the most intense state, both located at the one-way breathing valve connection port, the minimum pressure is -0.09Pa in the calmest state and -0.54Pa in the most intense state, and the pressure difference is 0.47Pa in the calmest state and 3.29Pa in the most intense state; while the maximum pressure of the model corresponding to the oxygen concentration detection host two is 0.17Pa in the calmest state and 0.998Pa in the most intense state, and the position is the same as the model corresponding to the oxygen concentration detection host one, the minimum pressure is -0.157Pa in the calmest state and -1.11Pa in the most intense state, and the pressure difference is 0.327Pa in the calmest state and 2.11Pa in the most intense state. By comparison, it can be seen that the overall pressure fluctuation in the sampling pipeline of the model corresponding to the oxygen concentration detection host one is greater.

[0110] From the flow field analysis of the model corresponding to the oxygen concentration detection host three, it can be seen that the maximum pressure is 0.196Pa in the calmest state and 0.951Pa in the most violent state, the minimum pressure is -0.111Pa in the calmest state and -0.882Pa in the most violent state, and the pressure difference is 0.307Pa and 1.833Pa in the calmest and most violent states respectively. The overall pressure fluctuation is smaller than that of the model corresponding to the oxygen concentration detection host one and the model corresponding to the oxygen concentration detection host two. Therefore, the overall structure has the smallest flow resistance to the gas and the fastest flow rate, which is conducive to faster acquisition of oxygen during inhalation.

[0111] In addition, the maximum pressure of the three corresponding models of the oxygen concentration detection host is located near the differential pressure sensor, which is more sensitive to the fluctuation of flow field pressure and can detect the pressure fluctuation of gas more easily and clearly.

[0112] 3. Temperature comparison

[0113] The temperature cloud diagrams of various internal flow field sampling pipeline grid models under different working conditions at 30 seconds are compared. From the comparison, it can be seen that since only 20℃ gas in the air bag enters each oxygen concentration monitoring host, the internal temperature is 20℃ at 30 seconds.

[0114] 4. Comparison of Oxygen O2 Mass Concentration

[0115] The oxygen content distribution diagrams of various internal flow field sampling pipeline grid models under different working conditions at 30 seconds are compared. Through the comparison, it can be seen that the oxygen mass fraction in the main channel of the model corresponding to the oxygen concentration detection host 1 is 32%, while in the large space below the differential pressure sensor, the oxygen mass fraction is around 24%, indicating that the gas has not been updated in time, and there is still residual oxygen in the initial state of the air component. The main reason is that the curved channel between the main channel and the space hinders the exchange of new and old air. The overall oxygen mass fraction of the model corresponding to the oxygen concentration detection host 2 is 32%, indicating that the oxygen is updated relatively timely.

[0116] The flow field analysis of the model corresponding to the oxygen concentration detection host three was carried out. At 30 seconds, the oxygen concentration was 32% regardless of whether it was in a calm state or an intense state. This also indirectly proved that the airflow entered the oxygen concentration detection host three from the air bag and took away all the initial air.

[0117] 5. Comparison of sensor monitoring point data

[0118] (1) Speed ​​curve of sensor monitoring point during 30s breathing process

[0119] The velocity change curves of the sensor monitoring points during 30 seconds of breathing under different working conditions of various internal flow field sampling pipeline grid models are compared (see Figure 24-25 ). From the curve comparison, it can be seen that the maximum speed of the model corresponding to the oxygen concentration detection host 1 is significantly greater than the model corresponding to the oxygen concentration detection host 2 and the model corresponding to the oxygen concentration detection host 3, indicating that the speed fluctuation of the sensor position of the model corresponding to the oxygen concentration detection host 1 is greater than that of the model corresponding to the oxygen concentration detection host 2. This is because the internal airflow of the oxygen concentration detection host 1 is a straight-through structure. During inhalation, the gas can quickly pass through the internal space after entering from the inhalation bag, while the airflow of the oxygen concentration detection host 2 and the oxygen concentration detection host 3 is a bypass structure, resulting in a smaller fluctuation of the airflow speed at the sensor position.

[0120] (2) Pressure curve of the sensor monitoring point during 30s breathing

[0121] The pressure change curves of the sensor monitoring points during 30 seconds of breathing under different working conditions of various internal flow field sampling pipeline grid models are compared (see Figure 26-27 ). From the curve comparison, it can be seen that the pressure fluctuation of the model corresponding to the oxygen concentration detection host 1 is significantly smaller than that of the model corresponding to the oxygen concentration detection host 2 and the model corresponding to the oxygen concentration detection host 3. The pressure fluctuation of the model corresponding to the oxygen concentration detection host 3 is the largest, indicating that under the structure of the model corresponding to the oxygen concentration detection host 3, the pressure difference sensor is most sensitive to the change of pressure fluctuation and can best detect the pressure change.

[0122] The oxygen concentration detection host 1 has a straight-through structure, with a fast airflow velocity, which causes a small air pressure on the sensor. The oxygen concentration detection host 2 and the oxygen concentration detection host 3 have internal airflows that flow around, especially in the narrow space near the sensor, which causes a large pressure on the sensor, resulting in large pressure fluctuations. In addition, the differential pressure sensor of the oxygen concentration detection host 3 is perpendicular to the airflow direction, so the pressure fluctuation is the largest.

[0123] (3) Temperature curve of the sensor monitoring point during 30s breathing process

[0124] The temperature change curves of the sensor monitoring points during 30 seconds of breathing under different working conditions of various internal flow field sampling pipeline grid models are compared. From the curve, it can be seen that since the exhaled gas does not enter the oxygen concentration detection host, the temperature remains consistent with the temperature inside the inhalation bag, that is, 20°C.

[0125] (4) Oxygen O2 mass fraction curve at the sensor monitoring point during 30s breathing

[0126] The oxygen mass fraction change curves of the sensor monitoring point during 30 seconds of breathing under different working conditions of various internal flow field sampling pipeline grid models are compared. Through the curve comparison, it can be seen that the time for the model corresponding to the oxygen concentration detection host 1 and the model corresponding to the oxygen concentration detection host 2 to reach oxygen concentration equilibrium (32%) is significantly longer than that of the model corresponding to the oxygen concentration detection host 3. This is because the oxygen concentration detection host 3 is located on the side connected to the inhalation bag, and the gas will be detected immediately as soon as it enters the oxygen concentration detection host, while the oxygen concentration detection host 1 and the oxygen concentration detection host 2 are located inside the sampling pipeline, and it takes a certain amount of time for the internal gas to be updated, which has a certain lag.

[0127] In summary, the structural design of the oxygen concentration detection host 3 is the most reasonable and the best solution. The oxygen concentration detection host 3 can detect pressure fluctuations most quickly and capture changes in oxygen concentration. The internal structure makes the flow rate the fastest, which is conducive to the human body to inhale the required oxygen.

[0128] The present embodiment also provides a respirator gas analysis sampling pipeline flow field simulation evaluation system, which includes a pre-processing module, a modeling module, a grid division module, an operating condition setting module, a physical model selection module, a physical property parameter setting module, a condition setting module, a solution initialization setting module, a monitoring construction module, an iterative calculation setting module, a simulation module and a simulation result analysis module.

[0129] The pre-processing module is used to perform geometric pre-processing on the geometric model of the oxygen concentration detection host in the respirator gas analysis sampling pipeline.

[0130] The modeling module is used to extract the internal flow field of the geometric model of the oxygen concentration detection host after geometric pre-processing, and to establish the internal flow field sampling pipeline model of the oxygen concentration detection host.

[0131] The grid division module is used to perform grid division on the internal flow field sampling pipeline model to obtain the internal flow field sampling pipeline grid model.

[0132] The working condition setting module is used to set the diving depth as the simulated working environment, and set the user's breathing flow rate to conform to the form of a sine curve when breathing, and has two extreme states, namely the calmest state and the most intense state.

[0133] The physical model selection module is used to select the turbulence equation to describe the movement of the airflow and the generation and dissipation of turbulence according to the working principle and working process of the oxygen concentration detection host, select the energy equation to calculate the temperature change, and select the component transport equation to describe the multi-component diffusion process in the gas, so as to simulate the changes in the oxygen and carbon dioxide content in the oxygen concentration detection host.

[0134] The physical property parameter setting module is used to set the physical property parameters of the gas, which include oxygen, nitrogen, carbon dioxide and water vapor.

[0135] The condition setting module is used to set the inlet boundary conditions and outlet boundary conditions of the internal flow field sampling pipeline grid model, and to set the simulation conditions including the calmest condition and the most violent condition.

[0136] The solution initialization setting module is used to set the coupling algorithm to solve the selected physical model. Standard initialization is used to assign values ​​to the oxygen content, carbon dioxide content, water vapor content and temperature of the initial field to simulate the initial state of the oxygen concentration detection host.

[0137] The monitoring construction module is used to use the cross section formed by the vertical middle position of the internal flow field sampling pipeline grid model as a constructed monitoring surface for monitoring the changes in physical quantities during the breathing process, and to use the position of the corresponding gas sensor on the monitoring surface as a constructed monitoring point.

[0138] The iterative calculation setting module is used to set the preset time and time step for each simulation condition.

[0139] The simulation module is used to simulate the breathing process within a preset time under the calmest and most intense working conditions. The internal flow field sampling pipeline grid model is used for transient simulation of the internal flow field of the sampling pipeline. The selected physical model is solved by a coupling algorithm. During the solution process, pressure, velocity, temperature and oxygen concentration are sampled on the monitoring surface and monitoring points under the two working conditions.

[0140] The simulation result analysis module is used to obtain and display the simulation results, including the velocity field cloud map of the monitoring surface within the preset time under the calmest working conditions and the most intense working conditions, the velocity vector distribution map during breathing, the pressure cloud map, the temperature cloud map and the oxygen content distribution map, the velocity change curve, the pressure change curve, the temperature change curve and the oxygen mass fraction change curve of the monitoring point within the preset time under the calmest working conditions and the most intense working conditions. The simulation results are analyzed to evaluate the advantages and disadvantages of the designed oxygen concentration detection host.

[0141] Although the specific embodiments of the present invention are described above, those skilled in the art should understand that these are only examples, and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A method for simulating and evaluating the flow field of a respirator gas analysis sampling pipeline, characterized in that: It includes the following steps: S1. Geometric preprocessing: geometric preprocessing of the geometric model of the oxygen concentration detection host in the respirator gas analysis sampling pipeline; S2. Modeling: extracting the internal flow field of the geometric model of the oxygen concentration detection host after geometric pre-processing, and establishing the internal flow field sampling pipeline model of the oxygen concentration detection host; S3. Meshing: Meshing the internal flow field sampling pipeline model to obtain an internal flow field sampling pipeline mesh model; S4. Set working conditions: Set the diving depth as the simulated working environment, set the breathing flow rate of the user to follow the sinusoidal curve when breathing, and have two extreme states, namely the calmest state and the most intense state; S5. Physical model selection: According to the working principle and working process of the oxygen concentration detection host, select the turbulence equation to describe the movement of the airflow and the generation and dissipation of turbulence, select the energy equation to calculate the temperature change, and select the component transport equation to describe the multi-component diffusion process in the gas to simulate the changes in the oxygen and carbon dioxide content in the oxygen concentration detection host; S6. Gas physical property parameter setting: set the gas physical property parameters, including oxygen, nitrogen, carbon dioxide and water vapor; S7, boundary conditions and simulation conditions setting: setting the inlet boundary conditions and outlet boundary conditions of the internal flow field sampling pipeline grid model, setting the simulation conditions including the calmest condition and the most violent condition; S8, solution setting and initialization: setting the coupling algorithm to solve the selected physical model, using standard initialization, assigning values ​​to the oxygen content, carbon dioxide content, water vapor content and temperature of the initial field to simulate the initial state of the oxygen concentration detection host; S9, construction of monitoring surface and monitoring point: the cross section formed by the vertical middle position of the internal flow field sampling pipeline grid model is used as the constructed monitoring surface to monitor the changes of physical quantities during breathing, and the position on the monitoring surface corresponding to the gas sensor is used as the constructed monitoring point; S10, iterative calculation settings: setting the preset time and time step for each simulation condition; S11, simulation: simulate the breathing process within a preset time under the calmest working condition and the most intense working condition, respectively perform transient simulation of the internal flow field of the sampling pipeline on the internal flow field sampling pipeline grid model, use the coupling algorithm to solve the selected physical model, and sample the pressure, velocity, temperature and oxygen concentration of the monitoring surface and monitoring points under the two working conditions during the solution process; S12. Simulation results: obtain and display simulation results, including velocity field cloud diagrams of the monitoring surface within a preset time under the calmest working condition and the most intense working condition, velocity vector distribution diagrams during breathing, pressure cloud diagrams, temperature cloud diagrams and oxygen content distribution diagrams, velocity change curves, pressure change curves, temperature change curves and oxygen mass fraction change curves of the monitoring points within a preset time under the calmest working condition and the most intense working condition, and analyze the simulation results to evaluate the advantages and disadvantages of the designed oxygen concentration detection host.

2. The method for simulating and evaluating the flow field of a respirator gas analysis sampling pipeline according to claim 1, characterized in that: In step S1, for three oxygen concentration detection hosts with different structural designs, namely oxygen concentration detection host 1, oxygen concentration detection host 2 and oxygen concentration detection host 3, geometric pre-processing is performed on the geometric models of the three structures respectively, and redundant lines, bolts and useless fillets that are useless to the internal flow field of each structure are removed, and the interference structure and assembly gap are repaired; In step S2, the internal flow field is extracted from the geometric model of each oxygen concentration detection host after geometric pre-processing, and the internal flow field sampling pipeline model of each oxygen concentration detection host is established; In step S3, each internal flow field sampling pipeline model is meshed to obtain a corresponding internal flow field sampling pipeline mesh model; In step S4, the operating conditions of the three internal flow field sampling pipeline grid models are set to be the same; In step S5, the physical model selection of the three internal flow field sampling pipeline grid models is set to be the same; In step S6, the gas property parameters of the three internal flow field sampling pipeline grid models are set to be the same; In step S7, the boundary conditions and simulation conditions of the three internal flow field sampling pipeline grid models are set to be the same, wherein the type of the inlet boundary condition is the velocity inlet, including velocity, relative pressure, turbulence intensity, hydraulic diameter, nitrogen gas volume fraction, water vapor volume fraction, oxygen volume fraction and carbon dioxide volume fraction, and the type of the outlet boundary condition is the free outflow boundary; In step S8, the solution settings and initialization of the three internal flow field sampling pipeline grid models are set to be the same; In step S9, the monitoring surfaces and monitoring points of the three internal flow field sampling pipeline grid models are set to be the same; In step S10, iterative calculation settings of three internal flow field sampling pipeline grid models are set to be the same; In step S11, the simulation processes of the three internal flow field sampling pipeline grid models are set to be the same; In step S12, the simulation results are compared: the simulation results of each internal flow field sampling pipeline grid model are obtained and displayed, including the velocity field cloud map of the monitoring surface within the preset time under the calmest working condition and the most intense working condition, the velocity vector distribution map during breathing, the pressure cloud map, the temperature cloud map and the oxygen content distribution map, the velocity change curve, the pressure change curve, the temperature change curve and the oxygen mass fraction change curve of the monitoring point within the preset time under the calmest working condition and the most intense working condition, the velocity field cloud map of the last second under the two working conditions in the three internal flow field sampling pipeline grid models are compared, the velocity vector distribution map of the last second under the two working conditions in the three grid models are compared, and the three grid models are compared. The pressure cloud maps of the last second under the two working conditions in the three grid models are compared, the temperature cloud maps of the last second under the two working conditions in the three grid models are compared, the oxygen content distribution maps of the last second under the two working conditions in the three grid models are compared, the speed change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, the pressure change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, the temperature change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, and the oxygen mass fraction change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared to evaluate the advantages and disadvantages of the three oxygen concentration detection hosts.

3. The method for simulating and evaluating the flow field of a respirator gas analysis sampling pipeline according to claim 2, characterized in that: In step S3, for the internal flow field sampling pipeline model of the oxygen concentration detection host 1, a quadrilateral surface mesh is generated, a boundary layer is generated by a smooth conversion method, and a polyhedral mesh of a hexahedral core is selected as a volume mesh to fill the internal mesh of the flow field, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host 1; For the internal flow field sampling pipeline model of the oxygen concentration detection host 2, a quadrilateral surface mesh is generated, a boundary layer is generated by a smooth conversion method, and a polyhedral mesh is selected as a volume mesh to fill the internal mesh of the flow field, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host 2; For the internal flow field sampling pipeline model of the oxygen concentration detection host three, a quadrilateral surface mesh is generated, the boundary layer is generated by smooth conversion, and the polyhedron mesh is selected as the volume mesh to fill the internal mesh of the flow field, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host three.

4. The method for simulating and evaluating the flow field of a respirator gas analysis sampling pipeline according to claim 1 or 2, characterized in that: In step S4, the peak inspiratory volume in the calmest state is set to 600 ml, the respiratory rate is set to 13 times / min, and the peak inspiratory volume in the most intense state is set to 5000 ml, the frequency is set to 21 times / min; The calmest working condition: The function of the breathing flow curve is The most severe working condition: The function of the breathing flow curve is Where t is time in seconds.

5. The method for simulating and evaluating the flow field of a respirator gas analysis sampling pipeline according to claim 1 or 2, characterized in that: In step S8, the gradient discretization format in the coupling algorithm is the least squares method, and the pressure, momentum, turbulence, components and energy discretization all adopt the second-order upwind format to improve the solution accuracy.

6. A respirator gas analysis sampling pipeline flow field simulation evaluation system, characterized in that: It includes a pre-processing module, a modeling module, a meshing module, a working condition setting module, a physical model selection module, a physical property parameter setting module, a condition setting module, a solution initialization setting module, a monitoring construction module, an iterative calculation setting module, a simulation module and a simulation result analysis module; The pre-processing module is used to perform geometric pre-processing on the geometric model of the oxygen concentration detection host in the respirator gas analysis sampling pipeline; The modeling module is used to extract the internal flow field of the geometric model of the oxygen concentration detection host after geometric pre-processing, and establish the internal flow field sampling pipeline model of the oxygen concentration detection host; The grid division module is used to grid the internal flow field sampling pipeline model to obtain the internal flow field sampling pipeline grid model; The working condition setting module is used to set the diving depth as the simulated working condition environment, and set the user's breathing flow rate to conform to the form of a sine curve when breathing, and has two extreme states, namely the calmest state and the most intense state; The physical model selection module is used to select the turbulence equation to describe the movement of the airflow and the generation and dissipation of turbulence according to the working principle and working process of the oxygen concentration detection host, select the energy equation to calculate the temperature change, and select the component transport equation to describe the multi-component diffusion process in the gas, so as to simulate the changes in the oxygen and carbon dioxide content in the oxygen concentration detection host; The physical property parameter setting module is used to set the physical property parameters of the gas, which include oxygen, nitrogen, carbon dioxide and water vapor; The condition setting module is used to set the inlet boundary conditions and outlet boundary conditions of the internal flow field sampling pipeline grid model, and the simulation conditions include the calmest condition and the most violent condition; The solution initialization setting module is used to set the coupling algorithm to solve the selected physical model, use standard initialization, and assign values ​​to the oxygen content, carbon dioxide content, water vapor content and temperature of the initial field to simulate the initial state of the oxygen concentration detection host; The monitoring construction module is used to use the cross section formed by the vertical middle position of the internal flow field sampling pipeline grid model as a constructed monitoring surface for monitoring the change of physical quantities during breathing, and to use the position on the monitoring surface corresponding to the gas sensor as a constructed monitoring point; The iterative calculation setting module is used to set the preset time and time step for each simulation condition; The simulation module is used to simulate the breathing process within a preset time under the calmest working condition and the most intense working condition, respectively perform transient simulation of the internal flow field of the sampling pipeline on the internal flow field sampling pipeline grid model, use the coupling algorithm to solve the selected physical model, and during the solution process, respectively perform pressure, velocity, temperature and oxygen concentration sampling on the monitoring surface and monitoring points under the two working conditions; The simulation result analysis module is used to obtain and display simulation results, including velocity field cloud maps of the monitoring surface within a preset time under the calmest working conditions and the most intense working conditions, breathing velocity vector distribution maps, pressure cloud maps, temperature cloud maps and oxygen content distribution maps, and velocity change curves, pressure change curves, temperature change curves and oxygen mass fraction change curves of the monitoring points within a preset time under the calmest working conditions and the most intense working conditions. The simulation results are analyzed to evaluate the advantages and disadvantages of the designed oxygen concentration detection host.

7. The respirator gas analysis sampling pipeline flow field simulation evaluation system according to claim 6, characterized in that: The pre-processing module is used for three oxygen concentration detection hosts with different structural designs, namely oxygen concentration detection host 1, oxygen concentration detection host 2 and oxygen concentration detection host 3, to perform geometric pre-processing on the geometric models of the three structures respectively, remove unnecessary lines, bolts and useless fillets that are useless to the internal flow field of each structure, and repair the interference structure and assembly gap; The modeling module is used to extract the internal flow field of each oxygen concentration detection host geometry model after geometric pre-processing, and establish the internal flow field sampling pipeline model of each oxygen concentration detection host; The grid division module is used to grid each internal flow field sampling pipeline model to obtain a corresponding internal flow field sampling pipeline grid model; The working condition setting module is used to set the working conditions of three internal flow field sampling pipeline grid models to be the same; The physical model selection module is used to set the physical model selection of three internal flow field sampling pipeline grid models to be the same; The physical property parameter setting module is used to set the same gas physical property parameters for three internal flow field sampling pipeline grid models; The condition setting module is used to set the boundary conditions and simulation conditions of the three internal flow field sampling pipeline grid models to be the same, wherein the type of the inlet boundary condition is the velocity inlet, including velocity, relative pressure, turbulence intensity, hydraulic diameter, nitrogen gas volume fraction, water vapor volume fraction, oxygen volume fraction and carbon dioxide volume fraction, and the type of the outlet boundary condition is the free outflow boundary; The solution initialization setting module is used to set the solution settings and initialization of three internal flow field sampling pipeline grid models to be the same; The monitoring construction module is used to set the monitoring surfaces and monitoring points of the three internal flow field sampling pipeline grid models to be the same; The iterative calculation setting module is used to set the iterative calculation settings of three internal flow field sampling pipeline grid models to be the same; The simulation module is used to set the simulation process of three internal flow field sampling pipeline grid models in the same way; The simulation result analysis module is used to obtain and display the simulation results of each internal flow field sampling pipeline grid model, including the velocity field cloud map of the monitoring surface within the preset time under the calmest working condition and the most intense working condition, the velocity vector distribution map during breathing, the pressure cloud map, the temperature cloud map and the oxygen content distribution map, the velocity change curve, the pressure change curve, the temperature change curve and the oxygen mass fraction change curve of the monitoring point within the preset time under the calmest working condition and the most intense working condition, compare the velocity field cloud maps of the last second under the two working conditions in the three internal flow field sampling pipeline grid models, compare the velocity vector distribution maps of the last second under the two working conditions in the three grid models, and compare the velocity field cloud maps of the last second under the three grid models. The pressure cloud maps of the last second under the two working conditions are compared, the temperature cloud maps of the last second under the two working conditions in the three grid models are compared, the oxygen content distribution maps of the last second under the two working conditions in the three grid models are compared, the speed change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, the pressure change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, the temperature change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, and the oxygen mass fraction change curves of the monitoring points within the preset time under the two working conditions in the three grid models are compared, and the advantages and disadvantages of the three oxygen concentration detection hosts are compared and evaluated.

8. The respirator gas analysis sampling pipeline flow field simulation evaluation system as claimed in claim 7, characterized in that: The grid division module is used to generate a quadrilateral surface grid for the internal flow field sampling pipeline model of the oxygen concentration detection host one, generate a boundary layer by smooth conversion, and select a polyhedral grid with a hexahedral core as a volume grid to fill the internal grid of the flow field, thereby obtaining the internal flow field sampling pipeline grid model of the oxygen concentration detection host one; For the internal flow field sampling pipeline model of the oxygen concentration detection host 2, a quadrilateral surface mesh is generated, a boundary layer is generated by a smooth conversion method, and a polyhedral mesh is selected as a volume mesh to fill the internal mesh of the flow field, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host 2; For the internal flow field sampling pipeline model of the oxygen concentration detection host three, a quadrilateral surface mesh is generated, the boundary layer is generated by smooth conversion, and the polyhedron mesh is selected as the volume mesh to fill the internal mesh of the flow field, thereby obtaining the internal flow field sampling pipeline mesh model of the oxygen concentration detection host three.

9. The respirator gas analysis sampling pipeline flow field simulation evaluation system according to claim 6 or 7, characterized in that: The working condition setting module is used to set the peak inspiratory volume in the calmest state to 600 ml and the respiratory rate to 13 times / min, and the peak inspiratory volume in the most intense state to 5000 ml and the frequency to 21 times / min; The calmest working condition: The function of the breathing flow curve is The most severe working condition: The function of the breathing flow curve is Where t is time in seconds.

10. The respirator gas analysis sampling pipeline flow field simulation evaluation system according to claim 6 or 7, characterized in that: The solution initialization setting module is used in the coupling algorithm, and the gradient discretization format is the least square method. The pressure, momentum, turbulence, component and energy discretization all adopt the second-order upwind format to improve the solution accuracy.

Images