Detection method for analyzing influence of plant physiological status on comprehensive benefits of indoor restorative environment health

Abstract

The invention discloses a detection method for analyzing the influence of plant physiological status on comprehensive benefits of indoor restorative environmental health, and relates to the technical field of plant environmental health, comprising the following steps: step S1, constructing an indoor model grid for distributing plants; s2, acquiring an air sample, and detecting components and concentration of the air sample; s3, predicting the diffusion rate of air substance components; and S4, calculating the coupling diffusion effect of the substances in the indoor air. By applying a model grid mixing strategy, exponential distribution of the speed, temperature and concentration of the plant volatile substances is accurately captured, the diffusion rule of flowing substances is predicted by combining the coupling effect of the concentration gradient and turbulent diffusion of the volatile substances, the diffusion effect of the multi-component plant volatile substances is simulated, and the plant volatile substance diffusion efficiency is improved. The indoor environment with distributed plants is accurately detected, the influence of the plant physiological state on the indoor environment health is judged, and the influence of plant volatile substances on the human body physiological state is conveniently detected.

Description

Technical Field

[0001] This invention relates to the field of environmental health testing technology, and in particular to a testing method for analyzing the impact of plant physiological state on the overall health benefits of indoor restorative environments. Background Technology

[0002] Plant volatile organic compounds constitute a complex chemical communication and defense system, offering significant benefits to the plants themselves, other organisms, the entire ecosystem, and humans. They play a role in pest and disease resistance and pollination. Simultaneously, plants regulate the humidity and temperature of the surrounding environment through transpiration, especially in summer, cooling and increasing humidity to improve thermal comfort. Furthermore, plants improve air quality; some release oxygen, negative ions, and other beneficial volatile compounds, contributing to air purification. Inhaling plant volatiles has significant health benefits, primarily due to terpenes. These substances can lower salivary cortisol levels, reduce stress, decrease sympathetic nerve activity, and enhance parasympathetic nerve activity, leading to relaxation, alleviating anxiety and depression, and boosting positive emotions. Through multi-sensory passive perception and the inhalation of beneficial substances, they regulate the stress state of the nervous and physiological systems, promoting positive psycho-physiological interactions and achieving health benefits, as well as improved work and study efficiency.

[0003] Due to the beneficial effects of volatile organic compounds emitted by plants on people, greenery is commonly placed in indoor spaces such as classrooms, research facilities, offices, and homes. The substances emitted by plants improve the health support of the indoor environment. Developing a method to detect the correlation and response between plant physiological states and the health support of the indoor environment and human health in indoor spaces of specific scales and shapes is key to revealing the dynamic benefit mechanisms of plants and providing a scientific basis for the design and layout of functional indoor plant landscapes. Common detection methods often utilize contact physical sensors and non-contact optical and remote sensing technologies to monitor plant status, primarily measuring the plant's own environment. This is not suitable for measuring the overall health-enhancing effect on the indoor space, leading to large errors in the detection results and reducing the scientific validity, value, and accuracy of the human-factor matching of the detection results. Summary of the Invention

[0004] The purpose of this invention is to provide a detection method for analyzing the impact of plant physiological state on the overall health benefits of indoor restorative environments, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a detection method for analyzing the impact of plant physiological states on the overall health benefits of indoor restorative environments, comprising the following steps:

[0006] Step S1: Construct an indoor model grid for the distribution of plants, discretize the indoor space into a set of cells, and simulate indoor air flow and air quality changes;

[0007] Step S2: Based on the model grid constructed in step S1, set up an air sampling device indoors to obtain air samples, and use gas chromatograph and mass spectrometer to detect the composition and concentration of plant volatile substances in the samples, and identify beneficial plant volatile substances in the air that promote human health.

[0008] Step S3: Calculate the gas component concentration data and grid data obtained in Step S2 using a turbulence model to predict the diffusion rate of different plant volatile components in flowing air.

[0009] Step S4: Based on the composition and concentration of plant volatiles detected in Step S2, use a component transport model to process the coupled diffusion effect of different plant volatiles in indoor air, predict the spatial distribution and temporal evolution of each substance in the flow, and predict the concentration of plant volatiles.

[0010] Step S5: Combine the turbulence model in Step S3 and the component transport model in Step S4 to construct an indoor simulation model and perform three-dimensional numerical simulation of the diffusion law of volatile substances from plants in the indoor environment.

[0011] Preferably, the indoor model mesh creation in step S1 includes the following steps:

[0012] Step S11: By using prismatic layer meshes on the plant surface and near the vents, structured and semi-structured meshes that capture the flow within the boundary layer are generated to produce multi-layered, highly anisotropic prismatic layer meshes for boundary layer refinement.

[0013] Step S12: Fill the space formed by complex geometry by using unstructured tetrahedral meshes in the mainstream area;

[0014] Step S13: Generate a pyramid mesh and a polyhedral mesh as a buffer in the connection area between the prism layer mesh and the outer tetrahedral mesh.

[0015] Preferably, the prism layer mesh establishment in step S11 includes the following steps:

[0016] Step S111: By setting the height of the first layer mesh and determining the number of layers, where the height of the first layer mesh is the distance from the center of the first layer mesh to the wall, the product of the height and the number of layers is calculated to obtain the total thickness, so that the total thickness covers the boundary layer;

[0017] Step S112: Transition between multiple prism layer meshes is performed by setting the growth rate, i.e. the thickness ratio of two adjacent mesh layers.

[0018] Preferably, the indoor air sampling in step S2 includes the following steps:

[0019] Step S21: By distributing foliage plants and flowering plants in the indoor environment, and setting up gas samplers in the corresponding grids of the model grid during the flowering period and non-flowering period of the flowering plants, respectively, air samples are obtained at different grid locations.

[0020] Step S22: By introducing the collected air sample into a gas chromatograph, different plant volatiles in the gas are separated in the chromatographic column, and different substances elute at different times;

[0021] Step S23: Use a mass spectrometer to ionize and fragment the different substances separated by the gas chromatograph, and identify the composition and content of the substances by detecting the mass-to-charge ratio of the fragments, and detect the volatile plant substances that promote human health.

[0022] Preferably, the setting of the turbulence model in step S3 includes the following steps:

[0023] Step S31: Obtain the turbulent viscosity equation through the mean strain rate tensor and the rotation rate tensor, constrain the positive definiteness of the turbulent viscosity, and generate a new turbulent kinetic energy equation based on the standard turbulence model;

[0024] Step S32: Derive the dissipation rate equation based on the precise transport equation of vorticity fluctuations, substitute it into the turbulent kinetic energy equation in step S31, generate a new turbulence model, and correct the turbulence model.

[0025] Preferably, the component transport model construction in step S4 includes the following steps:

[0026] Step S41: By setting the plant surface as a constant mass source, the volatilization rate of foliage and flowering plants is classified according to flowering period and non-flowering period, and boundary conditions are set.

[0027] Step S42: Set the indoor temperature to a constant 26.85℃. The change in gas density is only caused by the mixing of components, eliminating the influence of thermal expansion and the influence of real-time changes in light intensity and temperature on the evaporation rate.

[0028] Step S43: The Maxwell-Stefan equation is used to handle the mutual coupling effect between the diffusion of volatile substances in different plants, and the diffusion of volatile substances in plants is predicted.

[0029] Preferably, the processing of the Maxwell-Stefan equations in step S43 includes the following steps:

[0030] Step S431: Calculate the average velocity between different substances based on the diffusion rates of different plant volatiles.

[0031] Step S432: Calculate the mole fraction of different components based on the obtained plant volatile substance composition;

[0032] Step S433: Combining the average velocity and mole fraction of different plant volatiles from the above steps, the diffusion driving force of the corresponding components is calculated using the Maxwell-Stefan diffusion coefficient. Based on the diffusion driving force of different plant volatiles, the diffusion changes are predicted, and the diffusion state of plant volatiles in the room and the concentration of their distribution in different areas are predicted.

[0033] Preferably, the establishment of the indoor simulation model in step S5 includes the following steps:

[0034] Step S51: By importing the 3D model and repairing minor features of the mesh, the obtained data on the composition and concentration of plant volatiles are processed in combination with the set model mesh and turbulence model.

[0035] Step S52: Perform iterative calculations according to the settings in step S51 until the solution converges, and then perform the solution calculation.

[0036] Step S53: Analyze the calculation structure of step S52 and transform the calculated data into intuitive graphics.

[0037] Preferably, the solution calculation in step S52 includes the following steps:

[0038] Step S521: First, a pressure field is preset, and under this pressure field, the momentum equation is solved to obtain the preset velocity field;

[0039] Step S522: Based on the error that the velocity field does not satisfy the continuity, construct a pressure correction equation to correct the set pressure field, and update the velocity field through the corrected pressure field to make it satisfy the continuity equation;

[0040] Step S523: Repeat the above process by using the corrected pressure field and velocity field as new preset values ​​until the solution converges.

[0041] Preferably, the construction of the intuitive graphic in step S53 includes the following steps:

[0042] Step S531: Using the acquired data on the composition, concentration, and diffusion rate of volatile substances in plants, select bar charts and line graphs to convey information, and display the data within the grid in conjunction with the established model grid;

[0043] Step S532: Render the model according to the design principles, and use accent colors to highlight the main data points and areas.

[0044] The technical effects and advantages of this invention are as follows:

[0045] By applying a model-mesh hybrid strategy, the boundary layer of the model mesh uses a prismatic layer mesh, while the remaining areas use a tetrahedral mesh. Leveraging the high precision of the boundary layer and the flexibility of unstructured meshes in handling complex geometry, the exponential distribution of velocity, temperature, and concentration of plant volatiles is accurately captured. Furthermore, a gas sampling device is set up according to the model mesh to detect the composition and concentration of plant volatiles. Combining the coupling effect of volatile concentration gradients and turbulent diffusion, the diffusion law of flowing substances is predicted, simulating the diffusion effect of multi-component plant volatiles. This facilitates accurate detection of indoor air quality in environments with distributed plants, makes it easier to assess the impact of plant physiological states on indoor health, and facilitates the detection of beneficial effects of plant volatiles on human physiological states. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the detection method of the present invention.

[0047] Figure 2 This is a schematic diagram of the process for creating the indoor model mesh according to the present invention.

[0048] Figure 3 This is a schematic diagram of the indoor air sampling process of the present invention.

[0049] Figure 4 This is a schematic diagram of the process for setting up the turbulence model of the present invention.

[0050] Figure 5 This is a schematic diagram of the component transport model construction process of the present invention.

[0051] Figure 6 This is a schematic diagram of the equation processing flow of the present invention.

[0052] Figure 7 This is a schematic diagram illustrating the process of establishing the indoor simulation model of this invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] This invention provides, for example Figures 1-7 The method shown here for analyzing the impact of plant physiological states on the overall health benefits of indoor restorative environments includes the following steps:

[0055] Step S1: Construct an indoor model grid for the distribution of plants, discretize the indoor space into a set of cells, and simulate indoor air flow and air quality changes;

[0056] Step S2: Based on the model grid constructed in step S1, set up an air sampling device indoors to obtain air samples, and use gas chromatograph and mass spectrometer to detect the composition and concentration of plant volatile substances in the samples, and identify beneficial plant volatile substances in the air that promote human health.

[0057] Step S3: Calculate the gas component concentration data and grid data obtained in Step S2 using a turbulence model to predict the diffusion rate of different plant volatile components in flowing air.

[0058] Step S4: Based on the composition and concentration of plant volatiles detected in Step S2, use a component transport model to process the coupled diffusion effect of different plant volatiles in indoor air, predict the spatial distribution and temporal evolution of each substance in the flow, and predict the concentration of plant volatiles.

[0059] Step S5: Combine the turbulence model in Step S3 and the component transport model in Step S4 to construct an indoor simulation model and perform three-dimensional numerical simulation of the diffusion law of volatile substances from plants in the indoor environment.

[0060] Step S1, the creation of the indoor model mesh, includes the following steps:

[0061] Step S11: By using prismatic layer meshes on the plant surface and near the vents, structured and semi-structured meshes that capture the flow within the boundary layer are generated to produce multi-layered, highly anisotropic prismatic layer meshes for boundary layer refinement.

[0062] Step S12: Fill the space formed by complex geometry by using unstructured tetrahedral meshes in the mainstream area;

[0063] Step S13: Generate a pyramid mesh and a polyhedral mesh as a buffer in the connection area between the prism layer mesh and the outer tetrahedral mesh.

[0064] The model mesh exhibits a large velocity gradient within the boundary layer, while the prismatic layer mesh is densely refined along the wall direction, accurately capturing the exponential distribution of velocity, temperature, and concentration of volatile substances in plants. The anisotropic mesh matches the anisotropic flow characteristics within the boundary layer, resulting in minimal numerical diffusion. The mainstream region is well-suited for generating tetrahedral meshes using CFD software's automatic mesh generators, such as Fluent and Star-CCM+, significantly simplifying the mesh generation workflow. It can automatically and quickly fill extremely complex spaces composed of plant leaves, stems, etc., without requiring complex decomposition logic. The hybrid strategy of prismatic layer meshes and tetrahedral meshes, combined with the high precision of structured meshes in the boundary layer and the flexibility of unstructured meshes in handling complex geometries, achieves the optimal balance between accuracy and efficiency.

[0065] Step S11, the creation of the prism layer mesh, includes the following steps:

[0066] Step S111: By setting the height of the first layer mesh and determining the number of layers, where the height of the first layer mesh is the distance from the center of the first layer mesh to the wall, the product of the height and the number of layers is calculated to obtain the total thickness, so that the total thickness covers the boundary layer;

[0067] Step S112: Transition between multiple prism layer meshes is performed by setting the growth rate, i.e. the thickness ratio of two adjacent mesh layers.

[0068] Indoor air sampling in step S2 includes the following steps:

[0069] Step S21: By distributing foliage plants and flowering plants in the indoor environment, and setting up gas samplers in the corresponding grids of the model grid during the flowering period and non-flowering period of the flowering plants, respectively, air samples are obtained at different grid locations.

[0070] Step S22: By introducing the collected air sample into a gas chromatograph, different plant volatiles in the gas are separated in the chromatographic column, and different substances elute at different times;

[0071] Step S23: Use a mass spectrometer to ionize and fragment the different substances separated by the gas chromatograph, and identify the composition and content of the substances by detecting the mass-to-charge ratio of the fragments, and detect the volatile plant substances that promote human health.

[0072] By detecting the types of volatile substances emitted by plants in the indoor environment, we can obtain the components of substances in the air that are beneficial to the human body, such as myrcene, L-pinene, ocimene, nerol, and nerol acetate. These substances can have effects on the human body such as calming the mind and promoting sleep, relieving stress, refreshing the mind, and relieving cough and asthma.

[0073] Setting up the turbulence model in step S3 includes the following steps:

[0074] Step S31: Obtain the turbulent viscosity equation through the mean strain rate tensor and the rotation rate tensor, constrain the positive definiteness of the turbulent viscosity, and generate a new turbulent kinetic energy equation based on the standard turbulence model;

[0075] Step S32: Derive the dissipation rate equation based on the precise transport equation of vorticity fluctuations, substitute it into the turbulent kinetic energy equation in step S31, generate a new turbulence model, and correct the turbulence model.

[0076] By adopting the Realizable k-ε model for the turbulence model, the mathematical description of turbulence is made more consistent with physical reality. This ensures that the turbulent normal stress is always positive and satisfies the mathematical constraints on Reynolds stress. It accurately predicts the expansion rate of the jet and the mixing layer, and derives the dissipation rate equation from the precise transport equation of vorticity fluctuations, thus improving the rigor of the calculation.

[0077] The component transport model construction in step S4 includes the following steps:

[0078] Step S41: By setting the plant surface as a constant mass source, the volatilization rate of foliage and flowering plants is classified according to flowering period and non-flowering period, and boundary conditions are set.

[0079] Step S42: Set the indoor temperature to a constant 26.85℃. The change in gas density is only caused by the mixing of components, eliminating the influence of thermal expansion and the influence of real-time changes in light intensity and temperature on the evaporation rate.

[0080] Step S43: The Maxwell-Stefan equation is used to handle the mutual coupling effect between the diffusion of volatile substances in different plants, and the diffusion of volatile substances in plants is predicted.

[0081]

[0082] Note: The concentration of substances released by plants is affected by various factors such as light and temperature. The data in the table are the average values ​​under normal planting conditions, indoor temperature of 20-28℃, and sunny days from 10 to 12 o'clock.

[0083] Table 3. Details of Major Organic Matter and Negative Ion Parameters Released by Plants

[0084]

[0085] According to the data in Tables 1-3, the distribution of volatile organic compounds (VOCs) released by indoor plants in the room shows a relatively obvious regularity. First, the VOC concentration diffuses outward from the plant itself, and the concentration decreases with distance from the plant, reflecting the natural diffusion and dilution process of volatiles from the source. Second, in the vertical direction, the VOC concentration is not uniformly distributed, but shows that the concentration near the ground is significantly higher than that near the ceiling. This phenomenon is mainly because the density of some VOC molecules released by plants is greater than that of air. Under the influence of gravity, they tend to settle downward and accumulate in the area near the ground when air flow is weak.

[0086] The concentration of volatiles varies among plants during different flowering periods. The overall trend is that the concentration of volatiles in flowering plants is significantly higher than that in non-flowering plants. The VOCs source release rate of flowering plants is generally higher than that in non-flowering plants. This is highly consistent with the physiological mechanism of plants. Flowering plants need to attract pollinators or resist pathogens through volatile substances, which leads to enhanced metabolic activity.

[0087] In a closed indoor environment of approximately 40-50 square meters, equipping it with 3-6 small to medium-sized aromatic plants can improve concentration by about 25%-50% and significantly improve the user's psychological mood by 25%-60% at moderate to low scent intensity. At the same time, the plants can increase the indoor relative humidity by about 10%-35% through transpiration, which helps to alleviate discomfort caused by dryness. Combined with the antibacterial and air-purifying functions of their volatile substances, they together create a healthy indoor fragrance environment that is both refreshing, soothing, and regulates the microclimate.

[0088] The treatment of the Maxwell-Stefan equations in step S43 includes the following steps:

[0089] Step S431: Calculate the average velocity between different substances based on the diffusion rates of different plant volatiles.

[0090] Step S432: Calculate the mole fraction of different components based on the obtained plant volatile substance composition;

[0091] Step S433: Combining the average velocity and mole fraction of different plant volatiles from the above steps, the diffusion driving force of the corresponding components is calculated using the Maxwell-Stefan diffusion coefficient. Based on the diffusion driving force of different plant volatiles, the diffusion changes are predicted, and the diffusion state of plant volatiles in the room and the concentration of their distribution in different areas are predicted.

[0092] The Maxwell-Stefan equations are shown below:

[0093]

[0094] This represents the diffusion driving force of component i;

[0095] It represents the product of the gas constant and temperature;

[0096] Indicates the mole fraction of component j;

[0097] This represents the average velocity of components i and j;

[0098] This represents the Maxwell-Stefan diffusion coefficient.

[0099] When component i moves at a rate different from that of component j ( During motion, it will experience resistance from component j. The more components j there are, the greater the resistance. The greater the velocity difference, the greater the resistance, and the higher the diffusion coefficient. This reflects the ease with which ij molecules interdiffusion occurs. The larger the value, the lower the resistance.

[0100] Simultaneously, based on the diffusion changes of plant volatile substances, the concentration of volatile substances in the indoor environment is predicted. Combined with the data on the concentration of main released organic substances and negative ions from foliage plants and flowering plants in Tables 1 and 2, and by monitoring the physical condition of people in indoor air environments with different concentrations of plant volatile substances, the beneficial effects of plant volatile substance concentrations on the human body are observed, and the impact of different concentrations of plant volatile substances on the human body is assessed.

[0101] Step S5, establishing the indoor simulation model, includes the following steps:

[0102] Step S51: By importing the 3D model and repairing minor features of the mesh, the obtained data on the composition and concentration of plant volatiles are processed in combination with the set model mesh and turbulence model.

[0103] Step S52: Perform iterative calculations according to the settings in step S51 until the solution converges, and then perform the solution calculation.

[0104] Step S53: Analyze the calculation structure of step S52 and transform the calculated data into intuitive graphics.

[0105] The solution calculation in step S52 includes the following steps:

[0106] Step S521: First, a pressure field is preset, and under this pressure field, the momentum equation is solved to obtain the preset velocity field;

[0107] Step S522: Based on the error that the velocity field does not satisfy the continuity, construct a pressure correction equation to correct the set pressure field, and update the velocity field through the corrected pressure field to make it satisfy the continuity equation;

[0108] Step S523: Repeat the above process by using the corrected pressure field and velocity field as new preset values ​​until the solution converges.

[0109] By pre-setting an initial pressure field and velocity field Discretize and solve the momentum equation as follows:

[0110]

[0111] in( A represents the force generated by the pressure gradient term, which can be obtained by solving the problem. .

[0112] Pressure correction value p= + ;

[0113] Speed ​​correction value v= + ;

[0114] Substituting into the momentum equation and the continuity equation, we can obtain the following about... Poisson-type equations:

[0115]

[0116] Among them, source terms It is based on The unbalanced residual of the calculated mass flow rate.

[0117] The corrected pressure formula is as follows:

[0118]

[0119] in It is the stress under-relaxation factor, which is usually less than 1.

[0120] Using the obtained The velocity field is updated directly based on the derived relation to obtain the velocity v that satisfies continuity.

[0121] The construction of the intuitive graphic in step S53 includes the following steps:

[0122] Step S531: Using the acquired data on the composition, concentration, and diffusion rate of volatile substances in plants, select bar charts and line graphs to convey information, and display the data within the grid in conjunction with the established model grid;

[0123] Step S532: Render the model according to the design principles, and use accent colors to highlight the main data points and areas.

[0124] Principle of this invention:

[0125] By applying a model-mesh hybrid strategy, the boundary layer of the model mesh uses a prismatic layer mesh, while the remaining areas use a tetrahedral mesh. Leveraging the high precision of the boundary layer and the flexibility of unstructured meshes in handling complex geometry, the exponential distribution of velocity, temperature, and concentration of plant volatiles is accurately captured. Furthermore, a gas sampling device is set up according to the model mesh to detect the composition and concentration of plant volatiles. Combining the coupling effect of volatile concentration gradients and turbulent diffusion, the diffusion law of flowing substances is predicted, simulating the diffusion effect of multi-component plant volatiles. This allows for accurate detection of indoor air quality in environments with distributed plants, determining the impact of plant physiological states on indoor health, and assessing the beneficial effects of plant volatiles on human physiological states.

[0126] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A detection method for analyzing the impact of plant physiological states on the overall health benefits of indoor restorative environments, characterized in that, Includes the following steps: Step S1: Construct an indoor model grid for the distribution of plants, discretize the indoor space into a set of cells, and simulate indoor air flow and air quality changes; Step S2: Based on the model grid constructed in step S1, set up an air sampling device indoors to obtain air samples, and use gas chromatograph and mass spectrometer to detect the composition and concentration of plant volatile substances in the samples, and identify beneficial plant volatile substances in the air that promote human health. Step S3: Calculate the gas component concentration data and grid data obtained in Step S2 using a turbulence model to predict the diffusion rate of different plant volatile components in flowing air. Step S4: Based on the composition and concentration of plant volatiles detected in Step S2, use a component transport model to process the coupled diffusion effect of different plant volatiles in indoor air, predict the spatial distribution and temporal evolution of each substance in the flow, and predict the concentration of plant volatiles. Step S5: Combine the turbulence model in Step S3 and the component transport model in Step S4 to construct an indoor simulation model and perform three-dimensional numerical simulation of the diffusion law of volatile substances from plants in the indoor environment.

2. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 1, characterized in that, The indoor model mesh creation in step S1 includes the following steps: Step S11: By using prismatic layer meshes on the plant surface and near the vents, structured and semi-structured meshes that capture the flow within the boundary layer are generated to produce multi-layered, highly anisotropic prismatic layer meshes for boundary layer refinement. Step S12: Fill the space formed by complex geometry by using unstructured tetrahedral meshes in the mainstream area; Step S13: Generate a pyramid mesh and a polyhedral mesh as a buffer in the connection area between the prism layer mesh and the outer tetrahedral mesh.

3. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 1, characterized in that, The establishment of the prism layer mesh in step S11 includes the following steps: Step S111: By setting the height of the first layer mesh and determining the number of layers, where the height of the first layer mesh is the distance from the center of the first layer mesh to the wall, the product of the height and the number of layers is calculated to obtain the total thickness, so that the total thickness covers the boundary layer; Step S112: Transition between multiple prism layer meshes is performed by setting the growth rate, i.e. the thickness ratio of two adjacent mesh layers.

4. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 1, characterized in that, The indoor air sampling in step S2 includes the following steps: Step S21: By distributing foliage plants and flowering plants in the indoor environment, and setting up gas samplers in the corresponding grids of the model grid during the flowering period and non-flowering period of the flowering plants, respectively, air samples are obtained at different grid locations. Step S22: By introducing the collected air sample into a gas chromatograph, different plant volatiles in the gas are separated in the chromatographic column, and different substances elute at different times; Step S23: Use a mass spectrometer to ionize and fragment the different substances separated by the gas chromatograph, and identify the composition and content of the substances by detecting the mass-to-charge ratio of the fragments, and detect the volatile plant substances that promote human health.

5. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 1, characterized in that, Setting up the turbulence model in step S3 includes the following steps: Step S31: Obtain the turbulent viscosity equation through the mean strain rate tensor and the rotation rate tensor, constrain the positive definiteness of the turbulent viscosity, and generate a new turbulent kinetic energy equation based on the standard turbulence model; Step S32: Derive the dissipation rate equation based on the precise transport equation of vorticity fluctuations, substitute it into the turbulent kinetic energy equation in step S31, generate a new turbulence model, and correct the turbulence model.

6. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 1, characterized in that, The component transport model construction in step S4 includes the following steps: Step S41: By setting the plant surface as a constant mass source, the volatilization rate of foliage and flowering plants is classified according to flowering period and non-flowering period, and boundary conditions are set. Step S42: Set the indoor temperature to a constant 26.85℃. The change in gas density is only caused by the mixing of components, eliminating the influence of thermal expansion and the influence of real-time changes in light intensity and temperature on the evaporation rate. Step S43: The Maxwell-Stefan equation is used to handle the mutual coupling effect between the diffusion of volatile substances in different plants, and the diffusion of volatile substances in plants is predicted.

7. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 6, characterized in that, The processing of the Maxwell-Stefan equations in step S43 includes the following steps: Step S431: Calculate the average velocity between different substances based on the diffusion rates of different plant volatiles. Step S432: Calculate the mole fraction of different components based on the obtained plant volatile substance composition; Step S433: Combining the average velocity and mole fraction of different plant volatiles from the above steps, the diffusion driving force of the corresponding components is calculated using the Maxwell-Stefan diffusion coefficient. Based on the diffusion driving force of different plant volatiles, the diffusion changes are predicted, and the diffusion state of plant volatiles in the room and the concentration of their distribution in different areas are predicted.

8. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 1, characterized in that, The establishment of the indoor simulation model in step S5 includes the following steps: Step S51: By importing the 3D model and repairing minor features of the mesh, the obtained data on the composition and concentration of plant volatiles are processed in combination with the set model mesh and turbulence model. Step S52: Perform iterative calculations according to the settings in step S51 until the solution converges, and then perform the solution calculation. Step S53: Analyze the calculation structure of step S52 and transform the calculated data into intuitive graphics.

9. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 8, characterized in that, The solution calculation in step S52 includes the following steps: Step S521: First, a pressure field is preset, and under this pressure field, the momentum equation is solved to obtain the preset velocity field; Step S522: Based on the error that the velocity field does not satisfy the continuity, construct a pressure correction equation to correct the set pressure field, and update the velocity field through the corrected pressure field to make it satisfy the continuity equation; Step S523: Repeat the above process by using the corrected pressure field and velocity field as new preset values ​​until the solution converges.

10. The detection method for analyzing the impact of plant physiological state on the comprehensive health benefits of indoor restorative environments according to claim 8, characterized in that, The construction of the intuitive graphic in step S53 includes the following steps: Step S531: Using the acquired data on the composition, concentration, and diffusion rate of volatile substances in plants, select bar charts and line graphs to convey information, and display the data within the grid in conjunction with the established model grid; Step S532: Render the model according to the design principles, and use accent colors to highlight the main data points and areas.

Images