Three-dimensional rotary gas recovery and acoustic suspension microgravity gas-thermal environment simulation cultivation method
By using a dual closed-loop control model combining three-dimensional rotating gas recovery and acoustic levitation, plant physiological parameters are monitored in real time and sound field and environmental parameters are optimized. This solves the problem of the disconnect between physiological response and environmental regulation in microgravity environment simulation and achieves accurate simulation and optimization of physiological effects.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- INSTITUTE OF ENVIRONMENT AND SUSTAINABLE DEVELOPMENT IN AGRICULTURE CAAS
- Filing Date
- 2026-05-12
- Publication Date
- 2026-06-09
AI Technical Summary
Existing technologies show a disconnect between plant physiological responses and environmental regulation under simulated microgravity environments. The lack of a unified intelligent regulation framework makes it difficult to achieve precise synchronization between physiological effects and the physical environment.
A microgravity gas-thermal environment simulation cultivation method combining three-dimensional rotating gas recovery and acoustic levitation was adopted. A dual closed-loop control model was constructed to monitor plant physiological parameters in real time and dynamically regulate them based on gas exchange diagnosis and stomatal conductance prediction models. The sound field and environmental parameters were optimized by combining multispectral image feedback.
It has enabled precise control of microgravity physiological responses by ground-based simulation devices, improving experimental repeatability and resource utilization efficiency, and providing reliable physiological models and data support for space agriculture.
Smart Images
Figure CN122172914A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of microgravity environment simulation technology, and in particular to a three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method. Background Technology
[0002] Plant cultivation technology under microgravity is a core component in developing sustainable space life support systems. With the advancement of manned deep space exploration missions, accurately simulating the space environment on Earth and studying plant adaptability has become essential for species selection, cultivation process optimization, and the accumulation of design data. The biaxial rotation system (RPM), which uses random rotation along two axes to achieve a zero average gravity vector over time, is a mainstream ground-based method for simulating the biological effects of microgravity. However, traditional RPMs can only simulate mechanical effects and cannot reproduce the crucial thermodynamic and gas diffusion environment changes under microgravity, such as leaf heat accumulation due to the lack of natural heat convection and alterations in stomatal water vapor diffusion dynamics. These are precisely the core stress factors affecting key physiological processes like transpiration and photosynthesis in plants.
[0003] To address this deficiency, the industry has recently begun exploring the integration of acoustic levitation technology with RPM systems. Acoustic levitation generates a high-intensity acoustic standing wave field within a confined space, producing acoustic radiation forces that can counteract gravity and effectively suppress buoyancy-driven natural thermal convection caused by temperature gradients. Acoustic levitation technology utilizes the nonlinear effects under high acoustic intensity conditions generated by ultrasound; the resulting air standing wave field can levitate tiny objects by counteracting their own gravity. Simultaneously, the three-dimensional standing waves generated by acoustic levitation can, to some extent, counteract thermal convection and airflow. Acoustic levitation is one of the key technologies for containerless material handling under both terrestrial and space conditions. Compared to magnetic levitation, it is not limited by material conductivity, and levitation and heating can be controlled separately. Therefore, it is widely used in materials and biochemical research, simulating cell environments unaffected by container boundaries or small-scale microgravity environments.
[0004] The specific control of acoustic heat accumulation within the acoustic levitation device includes: **Acoustic pressure inversion node:** Here, particle velocity is zero, but the acoustic pressure amplitude is maximum. Gas molecules experience the strongest compression and stretching at this point, resulting in the strongest acoustic energy absorption and the highest temperature rise. **Acoustic pressure node:** Here, acoustic pressure is zero, but particle velocity is maximum. Molecules primarily undergo directional motion here, with relatively weak friction and compression between them, leading to a lower temperature rise. As a result, a periodic temperature distribution forms within the acoustic levitation device, creating tiny "hot spots" at the acoustic pressure inversion node, while the temperature at the node remains relatively low. The temperature difference is typically very small, possibly only a few tenths of a degree Celsius to a few degrees Celsius. Overall, the acoustic levitation process can be precisely controlled to minimize the temperature difference with the air (from a few tenths of a degree Celsius to a few degrees Celsius), and its spatial distribution is also precisely controllable. This compensates for the air heat accumulation temperature faced by plants in the microgravity environment of space: at a wind speed of 0.2 m / s for 20 seconds, the leaf temperature is 1.9°C higher than the ambient temperature.
[0005] Therefore, acoustic levitation is considered a highly promising physical method for simulating containerless conditions and unique atmospheric and thermal environments in space on Earth. Chinese invention patent CN121209635A constructs a complex multiphysics coupling hardware system. Based on traditional RPM dual-axis rotation, it further introduces random lifting and lowering disturbances from the vertical slide rail and random buoyancy disturbances generated by liquid convection in the buoyancy chamber, combined with an ultrasonic sound-generating array module integrated into the cultivation chamber (for generating acoustic standing wave fields). Its control core aims to generate random rotational speed, direction, vertical displacement, and buoyancy changes through multiple servo motors, variable frequency pumps, and other actuators, hoping to statistically approximate the complex disturbances of the space environment through the coupling of various random mechanical motions. This scheme is equipped with sensors to monitor environmental parameters such as temperature, humidity, and CO2 (carbon dioxide), and adjusts them through independent physical and environmental control subsystems. However, its control logic primarily serves preset or randomly generated environmental physical parameter targets (such as specific rotational speed curves and liquid level heights), rather than the real-time physiological state of the plants.
[0006] Existing methods aim to generate specific, stochastic physical environments (such as a certain sound pressure level or a combination of rotational speeds). However, the same physical environment can produce drastically different physiological responses (such as stomatal conductance and water use efficiency) when applied to different plant species and at different growth stages. The lack of a closed-loop pathway from real-time plant physiological feedback to environmental regulation parameters makes it difficult to ensure that the physiological stress effects produced by the simulated environment are consistent with those in real space, casting doubt on the reliability of extrapolating experimental data from ground-based simulations to space. Furthermore, multiple subsystems (rotation, buoyancy, acoustic levitation, and environmental control) often operate independently or are simply superimposed, lacking a unified, collaborative control framework based on optimizing the overall physiological state of the plant. This fragmented control struggles to address the complex coupling and trade-offs between various environmental factors in plant physiological processes.
[0007] In summary, while current technologies combining RPM and acoustic levitation have made progress in hardware integration, their core remains a simulation and reproduction paradigm driven by the physical environment. To truly realize the goal of ground-based simulation serving space agriculture research, it is essential to explore an intelligent control paradigm focused on sensing and optimizing plant physiological states. Establishing an air-thermal coupling simulation and heat dissipation control model at the crop growth scale allows for the study of microgravity air-thermal environment simulation cultivation and methods to improve airflow heat dissipation control. Therefore, there is an urgent need for a dual-closed-loop intelligent control system capable of real-time sensing of plant physiological signals, analyzing environmental effects based on physiological mechanism models, and directly controlling physiological indicators. This would solve the problem of the disconnect between environmental simulation and physiological effects, enabling ground-based simulation devices not only to reproduce the environment but also to study and optimize physiological responses, providing direct and reliable model and data support for the design and optimization of space cultivation systems. Summary of the Invention
[0008] This application provides a three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method to solve the problems in the prior art.
[0009] On the one hand, embodiments of this application provide a method for simulating cultivation in a three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment, including: Based on acoustic levitation and gas recovery, a microgravity gas-thermal environment simulation cultivation experimental system was established on the basis of RPM. The experimental system includes a cultivation chamber, an environmental control chamber, RPM, an acoustic levitation device, and a gas recovery and monitoring unit. A dual-loop control model is constructed, with the physiological model as the core. The dual-loop control model includes a first closed-loop control and a second closed-loop control; the physiological model includes a gas exchange diagnostic model and a stomatal conductance prediction model. First closed-loop control: Real-time monitoring of environmental parameters in the cultivation chamber; online calculation of key physiological parameters of plants in the cultivation chamber based on a gas exchange diagnostic model; comparison of key physiological parameters with a first preset target to obtain a first comparison result; dynamic adjustment of sound field parameters of the acoustic levitation device and environmental parameters of the cultivation chamber based on the first comparison result. Second closed-loop control: periodically acquire multispectral images of the plants growing in the cultivation chamber, extract phenotypic data of the plants based on the multispectral images; compare the phenotypic data with the second preset target to obtain the second comparison result; based on the second comparison result, correct the parameters of the stomatal conductance prediction model and the first preset target.
[0010] Furthermore, the porosity prediction model is a porosity prediction model that incorporates the acoustic levitation effect. The calculation formula for the porosity prediction model is as follows:
[0011] in, For the stomatal conductance of the blade, For maximum porosity, , , , are the response functions for photosynthetically active radiation, vapor pressure deficit, temperature, and CO2, respectively. For photosynthetically active radiation variables, For water vapor pressure deficit variables, For temperature variables, For CO2 variables, For shear wind correction term, Low-speed airflow wind speed. For matrix water potential function, As a variable of matrix water potential, This is a comprehensive correction factor for microgravity and adiabatic environment. , The equivalent additional water vapor pressure difference generated by the sound radiation force. This is due to a normal water vapor pressure deficit.
[0012] Furthermore, the stomatal conductance prediction model uses acoustic stress factors... To quantify the direct promoting effects of sound pressure and thermal effects on stomatal opening and closing under environmental stress. ,in, This is the empirical coefficient for acoustic stress attenuation. The amplitude of the sound pressure level. The frequency of the sound.
[0013] Furthermore, key physiological parameters include: transpiration rate, net photosynthetic rate, stomatal conductance, and water use efficiency.
[0014] Furthermore, the first preset goal is the optimal curve of the key physiological parameters.
[0015] Furthermore, the second pre-defined objective includes: the empirical range of physiological data and node information that identifies the stages of plant growth and development.
[0016] Furthermore, the experimental system includes a heat balance model, a humidity balance model, and a CO2 mass balance model. The heat balance model includes the energy balance equations for the cultivation chamber and the environmental control chamber.
[0017] Furthermore, the energy balance equation for the cultivation chamber is:
[0018] in, For the quality of dry air inside the cultivation chamber, The specific heat capacity of air at constant pressure. The air temperature inside the cultivation chamber. For time, The heat generated by the LED (light-emitting diode) light source inside the cultivation chamber. To reduce net heat transfer between the cultivation chamber walls and the external environment, For net heat exchange with the ventilation of the environmental control chamber.
[0019] The energy balance equation for the environmental control chamber is:
[0020] in, To regulate the dry air quality inside the environmental control cabin, To regulate the temperature of the environmental control chamber, To provide the net heat output of the heating / cooling actuators within the environmental control cabin, This refers to the total heat loss between the environmental control chamber and the external environment through walls, ventilation, and other means.
[0021] Furthermore, the equilibrium equation of the humidity balance model is:
[0022] in, For the quality of dry air inside the cultivation chamber, The humidity ratio of the air inside the cultivation chamber. The rate at which water vapor is produced by plant transpiration. The evaporation rate of water from non-plant surfaces within the cultivation chamber. The dry air mass flow rate for ventilation in the environmental control chamber. The humidity ratio of the air exiting the environmental control cabin. The rate of active humidification or dehumidification, The rate at which water condenses and precipitates on a cold surface.
[0023] Furthermore, the equilibrium equation of the CO2 mass balance model is:
[0024] in, For the volume of the cultivation chamber, This refers to the CO2 concentration inside the cultivation chamber. To determine the rate at which CO2 is replenished to the system from the gas source, The rate at which plants absorb CO2 through photosynthesis. To regulate the CO2 concentration inside the environmental control chamber, This represents the rate at which CO2 dissolves in the water within the system.
[0025] The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method in this application has the following advantages: By employing the core concept of intelligent dual-closed-loop control targeting plant physiological states, this technology revolutionizes ground-based microgravity simulation from a traditional physical reproduction-type experimental device into an intelligent experimental scheme for physiological research. It not only resolves the core contradiction in existing technologies—the disconnect between environmental simulation and physiological effects—but also achieves significant progress in multiple dimensions, including control intelligence, depth of mechanism research, experimental repeatability, resource utilization efficiency, and technological universality. This provides an indispensable methodology and tool for precise control of space plant biology research and future space agriculture systems. Attached Figure Description
[0026] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0027] Figure 1 This is a schematic diagram of the dual closed-loop control model structure provided in the embodiments of this application.
[0028] Figure 2 The flowchart of the dual closed-loop control provided in the embodiments of this application is shown.
[0029] Figure 3 The model data flow diagram provided for the embodiments of this application.
[0030] Figure 4 This is a schematic diagram illustrating the effect of temperature and air pressure on porosity in an embodiment of this application.
[0031] Figure 5 A schematic diagram of the three-dimensional relationship of physiological indicators provided in the embodiments of this application.
[0032] Figure 6 This is a dynamic schematic diagram of airflow velocity provided for an embodiment of this application.
[0033] Figure 7 This is a schematic diagram of temperature dynamics and carbon dioxide dynamics provided for an embodiment of this application.
[0034] Figure 8 This is a schematic diagram of the dynamics of air pressure and water vapor pressure provided in the embodiments of this application.
[0035] Figure 9 This is a schematic diagram illustrating the dynamics of net photosynthetic rate, dynamics of water use efficiency, and changes in PID control signals provided in the embodiments of this application.
[0036] Figure 10 This is a schematic diagram illustrating the dynamics of transpiration rate, stomatal conductance, and carbon dioxide utilization rate provided in the embodiments of this application.
[0037] Figure 11 A schematic diagram of the main heat exchange unit provided in the embodiments of this application.
[0038] Figure 12 This is a schematic diagram of the water vapor generation and circulation path provided in the embodiments of this application.
[0039] Figure 13 The simulation effect of the acoustic levitation ultrasonic array system.
[0040] Figure 14 A schematic diagram of acoustic suspension cultivation of lettuce and sound field control. Detailed Implementation
[0041] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0042] Figure 1 This is a schematic diagram of the dual closed-loop control model structure provided in an embodiment of this application. This embodiment of the application provides a three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method, including: Based on acoustic levitation and gas recovery, a microgravity gas-thermal environment simulation cultivation experimental system was established on the basis of RPM. The experimental system includes a cultivation chamber, an environmental control chamber, RPM, an acoustic levitation device, and a gas recovery and monitoring unit.
[0043] In detail, the gaseous and thermal environment of the plant cultivation gaseous environment was simulated under ground-based microgravity to obtain data on the approximate biological effects of growth stress under relative microgravity. Based on RPM, a model of plant physiological metabolism and environmental monitoring and regulation under gas recovery and acoustic levitation was constructed.
[0044] For example, an experimental system capable of simulating the core characteristics of microgravity in space is first established on Earth. This system consists of physical environment simulation hardware and monitoring and control software. The experimental system mainly includes: a sealed cultivation chamber for holding plant samples, equipped with an LED light source, an infrared thermometer, and an acoustic levitation device; an environmental control chamber, independently connected to the cultivation chamber via sealed gas and liquid circuits, containing heating, cooling, humidification, dehumidification, CO2 replenishment, and a circulating air pump, used to precisely control the gas environment parameters (temperature, humidity, CO2 concentration, etc.) within the cultivation chamber without interfering with the operation of the main simulation device; and an RPM, serving as a mechanical motion platform, with the cultivation chamber fixed to the inner rotation axis of this frame and driven by a servo motor. Random, slow rotation along mutually perpendicular X and Y axes causes the gravity vector acting on the plant to become increasingly randomized over time in three-dimensional space, with its long-term statistical average approaching zero. This simulates the mechanical effects of microgravity. To simulate more complex spatial gravity disturbance environments, the cultivation chamber can also introduce pre-defined displacement or buoyancy disturbances in the vertical direction while rotating along both axes. An acoustic levitation device is integrated inside the cultivation chamber. Ultrasonic sound-emitting array modules are installed on opposite side walls inside the chamber, and the distance between the two arrays can be adjusted... and vocal frequency This ensures that the conditions for forming a stable acoustic standing wave are met. ,in, The wavelength of sound waves in the cabin air. It is a positive integer.
[0045] Specifically, this acoustic standing wave field has two key functions: First, simulating containerless and microgravity effects: at the sound pressure node (sound pressure is zero, particle velocity is maximum), the acoustic radiation force can balance gravity, enabling the levitation of small objects and interfering with the motion of gas molecules, simulating the containerless condition and the constrained state of matter under microgravity; Second, suppressing natural thermal convection: at the sound pressure anti-node (sound pressure amplitude is maximum, particle velocity is zero), the strongest acoustic energy absorption leads to a slight increase in local temperature. The entire sound field, through its energy distribution and acoustic radiation force field, can effectively suppress the buoyancy-driven natural thermal convection within the cultivation chamber caused by uneven temperature. Under real space microgravity, such thermal convection almost disappears, and heat transfer mainly relies on conduction and radiation. This device simulates this key thermodynamic environmental characteristic through the sound field.
[0046] In detail, the basic parameters of the sound field are as follows: Instantaneous sound pressure The calculation formula is as follows: ,in, For environmental static pressure, The amplitude of the sound pressure level. For wave number, Angular frequency, For location, For time.
[0047] The formula for calculating sound pressure amplitude is: ,in, It is air density. For the speed of sound, It is the amplitude of the sound wave.
[0048] Sound intensity The calculation formula is: .
[0049] Sound radiation force The calculation formula is: ,in, Let the radius be the object's radius. This represents the distance from the center of the object to the sound pressure node. This acoustic radiation force can be used to analyze the effect of the sound field on the water film on the blade surface or the vapor exhaled from the stomata.
[0050] For example, the basis of closed-loop control is a sensor network. High-precision sensor arrays are deployed in both the cultivation chamber and the environmental control chamber to monitor environmental data in real time. These sensors include: environmental sensors: temperature sensor, humidity sensor, CO2 sensor, O2 sensor, and air pressure sensor; and physiological monitoring sensors: CO2 sensors are installed on the inlet and outlet air ducts connecting the cultivation chamber and the control chamber to measure the concentration at the air inlet. and outlet concentration The airflow sensor is used to monitor the dry air molar flow rate at the air inlet. Infrared thermography cameras are used for non-contact measurement of blade temperature. Multispectral imaging cameras are used to periodically acquire images of plant canopies in order to analyze phenotypic data such as chlorophyll content, canopy water content, and leaf area index (LAI).
[0051] A dual-loop control model is constructed, with the physiological model as the core, including a first-loop control and a second-loop control; the physiological model includes a gas exchange diagnostic model and a stomatal conductance prediction model.
[0052] First closed-loop control: Real-time monitoring of environmental parameters in the cultivation chamber; online calculation of key physiological parameters of plants in the cultivation chamber based on a gas exchange diagnostic model; comparison of key physiological parameters with a first preset target to obtain a first comparison result; dynamic adjustment of acoustic field parameters of acoustic levitation and environmental parameters of the cultivation chamber based on the first comparison result; Second closed-loop control: Periodically acquiring multispectral images of plants growing in the cultivation chamber; extracting phenotypic data of plants based on multispectral images; comparison of phenotypic data with a second preset target to obtain a second comparison result; correction of stomatal conductance prediction model parameters and the first preset target based on the second comparison result.
[0053] In detail, traditional simulation devices mainly focus on the reproduction of physical environmental parameters, while this application uses plant physiological signals as the core input and control target of the system through a dual closed loop. The system can not only simulate the microgravity environment, but also actively study and optimize the physiological response of plants in this environment, solving the problem of the disconnect between gas environment and physiological effects in ground simulation. This model upgrades environmental simulation from open-loop reproduction to closed-loop optimization.
[0054] The core of this application lies in a dual-closed-loop control system that directly regulates plant physiological state. The physiological model is constructed based on two layers: a gas exchange diagnostic model for online inversion of real-time plant physiological state; and a stomatal conductance prediction model incorporating acoustic levitation effects, serving as the system's intelligent core to understand and predict the regulatory mechanisms of the environment on plant physiology. Dual-closed-loop control is achieved through the interaction of these two models.
[0055] For example, such as Figure 1 As shown in the schematic diagram of the dual closed-loop control model, the controller receives short-term metabolic and physiological data from the closed air path recovery and longer-term characterization data from the multispectral camera. After processing by the dual closed-loop model, it outputs environmental adjustment commands to the environmental control chamber, which ultimately affect the physiological state of the plant. Figure 2 The dual closed-loop control flowchart illustrates the multispectral and gas cycle crop physiological dual closed-loop adaptive environmental control process with gas exchange monitoring as the core. It includes the first closed-loop control, which involves acoustic suspension adjustment, environmental parameter correction and PID control, and the collaborative working logic between it and the second closed-loop control, which is based on multispectral imaging.
[0056] Specifically, the first closed-loop control is based on real-time physiological monitoring and environmental regulation using a gas exchange diagnostic model. As a fast-response loop, it calculates key plant physiological parameters online by monitoring real-time changes in environmental parameters such as gas composition at the inlet and outlet, and immediately adjusts the acoustic field parameters and environmental parameters to approach the first preset target. The online calculation model for key physiological parameters is based on the law of conservation of mass, and inversely determines plant physiological activities by measuring changes in the gas composition flowing through the cultivation chamber.
[0057] In one possible implementation, the first preset goal is the optimal curve of the key physiological parameters.
[0058] In one possible implementation, the porosity prediction model is a porosity prediction model that incorporates the acoustic levitation effect. Based on the classic Jarvis-type model, it innovatively introduces a quantitative correction for the acoustic levitation effect. The porosity prediction model provides setpoints and feedforward predictions for optimized control and model self-learning. The porosity prediction model serves a dual purpose: first, its output predictions act as the optimization reference target for the first closed loop; second, its internal parameters are the objects of calibration and learning for the second closed loop.
[0059] The calculation formula for the stomatal conductance prediction model is as follows:
[0060] in, For the stomatal conductance of the blade, For maximum porosity, , , , , respectively, are the response functions for photosynthetically active radiation, vapor pressure deficit, temperature, and CO2. For photosynthetically active radiation variables, For water vapor pressure deficit variables, The temperature variable is the air temperature. For CO2 variables, For shear wind correction term, Low-speed airflow wind speed. This is the shear wind correction factor. The substrate water potential function reflects the regulation of stomata by root water uptake and is part of the classical stomatal model. In this system, it is determined by the state of the water supply control system of the cultivation chamber (such as substrate humidity). It is an independent input parameter and is not directly coupled with acoustic levitation. Therefore, it is often treated as a constant or background condition when analyzing the specific effects of acoustic levitation. As a variable of matrix water potential, This is a comprehensive correction factor for microgravity and adiabatic environment, which integrates the microgravity biological effects simulated by RPM. Furthermore, the thermal insulation properties of the sealed chamber can serve as an empirical correction factor in long-term simulations. This factor can be calibrated by comparing the experimental results of ground-based control experiments with those of the system of this invention. Its purpose is to make the basic model more adaptable to the special scenario of system-level microgravity simulation. ,in, The equivalent additional water vapor pressure difference generated by the sound radiation force. This is due to a normal water vapor pressure deficit.
[0061] In one possible implementation, the stomatal conductance prediction model uses the acoustic stress factor. To quantify the promoting effect of sound pressure and thermal effects on stomatal opening and closing under environmental stress compensatory imbalance. ,in, This is the empirical coefficient for acoustic stress attenuation. The frequency of the sound.
[0062] In detail, acoustic levitation affects water vapor transport at the blade air interface through two mechanisms: Sound pressure and thermal effects directly stress: Localized heating and sound pressure oscillations caused by sound field energy can directly affect stomatal opening and closing. This effect can be assessed using factors... describe, .
[0063] The effect of acoustic radiation on leaf water film: The acoustic radiation force acting on the water film at the stomatal opening or leaf surface may alter the morphology of the water film and evaporation kinetics, equivalent to generating an additional driving barrier or thrust. This can be conceptualized as... , , For standing wave acoustic radiation force, For the density of water, This is the acceleration due to gravity.
[0064] The combined effect of these two mechanisms alters the driving force of water vapor diffusion in the blade microenvironment. In the stomatal conductance prediction model, they are uniformly integrated into the water vapor pressure deficit response function. input variables middle: As an additional item, directly with Add; As a stress factor, the modulation of pores affects a given... The response sensitivity, in the specific implementation of the model, is used as... A correction coefficient inside the function.
[0065] The porosity prediction model can also incorporate thermal convection corrections, using the response function. To quantify, ,in, The thermal convection coefficient, This represents the intensity of thermal convection.
[0066] To further improve the accuracy of acoustic levitation effect parameters in the stomatal conductance prediction model, an offline calibration process based on a photosynthesis instrument can be performed: Using a portable photosynthesis instrument (such as the LI-6800), in vitro measurements are conducted on sample leaves to obtain high-precision baseline values for stomatal conductance, net photosynthetic rate, and transpiration rate; these baseline values are then fused and compared with the corresponding parameters estimated online by the system concurrently based on a gas exchange diagnostic model. Specific optimization and correction are then performed on parameters directly related to the acoustic levitation effect in the stomatal conductance prediction model, particularly the coefficients related to acoustic stress. and calculation The proportionality coefficient. This calibration process enables the system to more accurately quantify the core mechanism by which acoustic levitation affects plants, thereby indirectly generating better sound field control commands in daily closed-loop control.
[0067] Based on the aforementioned stomatal conductance prediction model incorporating the acoustic levitation effect, the impacts of acoustic levitation and airflow on key plant physiological processes can be further quantified. For example, the actual transpiration rate changes under the influence of acoustic levitation. It can be represented as: ,in, This refers to the equivalent buoyancy parameter, which is the quantification of the equivalent upward buoyancy effect caused by the acoustic radiation field. Low-speed airflow wind speed. This is the saturated water vapor pressure in the pore cavities inside the blade. It is the air vapor pressure. The combined correction factor for acoustic levitation and airflow on transpiration, and the change in the true net photosynthetic rate under the influence of acoustic levitation. (The predicted net photosynthetic rate based on the stomatal conductance prediction model) can be expressed as: ,in, For the maximum carboxylation rate, It is a comprehensive correction factor for the effects of acoustic levitation and airflow on photosynthesis. This is the CO2 compensation point. , These are the Michaelis constants for oxygen and carbon dioxide, respectively. Oxygen concentration, This represents the intercellular CO2 concentration. These model parameters will be calibrated using a second closed-loop circuit.
[0068] In one possible implementation, key physiological parameters include: transpiration rate, net photosynthetic rate, stomatal conductance, and water use efficiency.
[0069] For example, Figure 3 The model data flow diagram details the flow of data, materials, and computational resources between the cultivation chamber and the environmental control chamber in the first closed-loop control, including the complete transfer and conversion relationships from basic quantities, detected quantities, computational quantities to control quantities. The following is the calculation process for key physiological parameters: (1) Instantaneous transpiration rate per unit time and per unit leaf area The calculation, in which the leaf area change is estimated, can be performed by using the infrared channels of a multispectral camera to estimate the three-dimensional depth of the leaf:
[0070] in, The water vapor mole fraction at the air inlet. The water vapor mole fraction at the outlet. The dry air molar flow rate entering the cultivation chamber. This represents the total leaf area of the plant.
[0071] (2) Instantaneous net photosynthetic rate per unit time and per unit leaf area Calculation of the diagnostic net photosynthetic rate based on real-time inversion of gas exchange:
[0072] in, The CO2 mole fraction at the air inlet. The CO2 mole fraction at the outlet is the fractional term. This is a correction factor for the water vapor dilution effect of water vapor carried out by transpiration on the CO2 concentration at the outlet (i.e., It was measured in air containing more water vapor.
[0073] (3) Calculation of water use efficiency.
[0074] Water use efficiency It is a key indicator for measuring the trade-off between plant carbon fixation and water consumption, and is directly calculated from the two core parameters mentioned above:
[0075] This comprehensive indicator characterizes the trade-off between plant carbon fixation and water consumption, serving as a key link between physiological state and environmental regulation. It can be used as one of the primary preset targets, allowing for the setting of optimal values based on the physiological characteristics of the target crop at different growth and development stages. The controller will calculate the target curve that changes over time in real time. By comparing with the target curve, the sound pressure amplitude and frequency of the acoustic suspension device, as well as the CO2 concentration, temperature, and humidity of the environmental control chamber, are dynamically adjusted through PID and other control algorithms to make the actual physiological state of the plant approach the preset target.
[0076] (4) Calculation model of porosity conductance.
[0077] Stomatal conductance is a core physiological parameter that connects the gas exchange between the plant's interior and the external environment.
[0078] Total water vapor conductance The calculation formula is:
[0079] in, The molar fraction of water vapor within the stomata inside the blade can be determined by the blade temperature. It is obtained by calculating its saturated water vapor pressure and then converting it.
[0080] Water vapor porosity This refers to the conductivity of the stomata for water vapor after the boundary layer resistance has been removed. It is also a core parameter reflecting the active regulation ability of plants, and the calculation formula is:
[0081] in, For blade boundary layer conductance, This is the asymmetry coefficient of stomatal conductance on both sides of the blade. , This represents the ratio of stomatal conductance on the upper and lower surfaces of the blade. Under ideal conditions, the predicted value obtained from the stomatal conductance prediction model is... It should equal That is, the actual stomatal conductance obtained from this diagnosis. This will be used as the predicted value in the calibration and correction of the stomatal conductance prediction model in the second closed loop. The benchmark target.
[0082] CO2 total conductivity It has a fixed proportional relationship with the pore conductance of water vapor, mainly due to the difference in diffusion coefficient, and its calculation formula is:
[0083] Figure 4 This diagram illustrates the effect of temperature and pressure on stomatal conductance, showing the three-dimensional response of stomatal conductance to changes in ambient temperature and pressure. This relationship is an important basis for constructing the stomatal conductance prediction model that incorporates environmental factors as described above in this application, demonstrating the necessity of accurately controlling temperature and pressure parameters in microgravity simulations to reproduce correct physiological responses. Figure 5 The three-dimensional relationship diagram of physiological indicators shows the interrelationship between the three core physiological indicators of net photosynthetic rate, transpiration rate and stomatal conductance, reflecting the complex constraints and synergy of multiple parameters as regulatory targets.
[0084] For example, based on the above model, more auxiliary physiological parameters can be calculated. These auxiliary physiological parameters are used to supplement the judgment on whether plant physiology and air environment tend to be similar to the microgravity environment of aviation, based on the dimensions of key physiological parameters.
[0085] Specifically, the calculation of auxiliary physiological parameters includes: (1) CO2 utilization efficiency Calculation:
[0086] in, CO2 utilization rate, , The density of CO2 under standard conditions. The number of air exchanges per unit time in the experimental cultivation chamber. For the volume of the cultivation chamber, For cultivation area, , These are the CO2 concentrations at the air inlet and outlet of the cultivation chamber, respectively. The rate of change of CO2 concentration inside the cultivation chamber. , , They are respectively CO2 concentration in the cultivation chamber obtained over time and CO2 concentration in the cultivation chamber obtained over time. For CO2 replenishment rate, The carbon dioxide rate coefficient for entering plant leaves when acoustic levitation blocks air from entering.
[0087] (2) Changes in total evapotranspiration level (total water consumption) Calculation:
[0088] in, The water vapor condensation recovery rate is calculated by determining the amount of condensate recovered from the heat pump using the dehumidified condensate water level. To improve the water vapor exchange rate between the inside and outside of the cultivation chamber, , The density of water vapor under standard conditions. , These represent the air humidity inside and outside the cultivation chamber, respectively. The rate of change of water vapor inside the cultivation chamber. , , They are respectively The humidity of the air inside the cultivation chamber was obtained over time and The humidity level of the air inside the cultivation chamber was obtained over time.
[0089] (3) Net photosynthetic rate of the canopy .
[0090] During system operation, to verify the above... To ensure accuracy, or when the flow rate method is not readily available, cross-calculation can be performed by monitoring changes in CO2 concentration within the cultivation chamber. The principle is that the reduction in CO2 within the chamber equals the amount absorbed by the plants.
[0091] Net photosynthetic rate of the canopy The calculation formula is:
[0092] (4) Blade energy balance calculation (used to quantify acoustic suspension thermal effect).
[0093] Sensible heat exchange, according to Newton's law of cooling, involves the blades dissipating sensible heat through convection. for:
[0094] in, For air temperature, For the leaf temperature, The average convective heat transfer coefficient, , is the thermal conductivity of air, a function of temperature. , For boundary layer temperature, , The Nusselt number represents the intensity of convection, especially for forced convection (such as when there is forced ventilation in the system). , It is the Prandtl number (approximately 0.7 for air). The Reynolds number is... , For air speed, The kinematic viscosity of air. , This represents the characteristic length of the blade in the wind direction.
[0095] The significance of this calculation lies in the fact that acoustic levitation directly reduces [the risk of convection]. This leads to the same Under temperature difference, the heat dissipation capacity of the blades The descent. This is the core physical mechanism for simulating the heat accumulation phenomenon in microgravity blades.
[0096] Latent heat exchange, also known as evaporation heat loss, is the exchange of heat through evaporation. The calculation formula is:
[0097] in, It is the transpiration rate in units of mass. It is the latent heat of vaporization of water.
[0098] Simplified energy balance formula: The total energy balance of the leaf (ignoring radiation and metabolic heat) is simplified to the absorbed photosynthetically active radiation. Through this relationship, the measured data can be combined. and Reverse reasoning or verification and This quantifies the suppression of convection caused by acoustic levitation, leading to heat accumulation in the blades. The degree of physical effect (increase).
[0099] The system compares the physiological parameters calculated in real time with the first preset target (expected optimal curve, threshold, etc.) to generate the first comparison result.
[0100] For example, adjusting the sound field parameters means adjusting the ultrasonic array. and For example, when the calculated stomatal conductance is too high, indicating that transpiration may be too strong, the sound pressure can be increased to further suppress convection and exacerbate the heat accumulation effect in the leaves, thereby studying the thermal stress feedback mechanism of the stomata; environmental parameter regulation involves adjusting the gases input into the cultivation chamber by controlling the environmental control chamber, and the controlled parameters include: CO2 concentration and air temperature. With humidity Low-speed airflow wind speed (used to study the effect of weak forced ventilation on mitigating the local thermal effect caused by acoustic levitation). Figure 6 , Figure 7 These are dynamic diagrams of airflow velocity, temperature, and carbon dioxide, demonstrating the system's ability to control airflow velocity, temperature, and CO2 concentration in real time. Figure 8 This demonstrates the dynamic changes in the environmental parameter of air pressure, as well as the changes in water vapor pressure determined by temperature and humidity, serving as an example of the stability of environmental control. Figure 9 This demonstrates how the net photosynthetic rate and water use efficiency of plants dynamically approach and remain near the preset optimal curves under the adjustment of external PID control signals, intuitively reflecting the effectiveness of closed-loop control targeting physiological parameters. Figure 10 The diagrams show the dynamic changes in transpiration rate, stomatal conductance, and carbon dioxide use efficiency, demonstrating the synergistic dynamic changes of transpiration rate, stomatal conductance, and CO2 use efficiency under system regulation, further verifying the comprehensive regulatory effect of the system on the overall physiological state of plants.
[0101] The second closed-loop control is a slow-response loop that uses multispectral images to acquire phenotypic information of long-term plant growth. The extracted phenotypic data is compared with a second preset target. Based on the comparison results, the internal parameters of the stomatal conductance prediction model incorporating acoustic levitation effects are calibrated and corrected to ensure the accuracy of long-term simulation and regulation.
[0102] In one possible implementation, the second pre-defined objective includes: the empirical range of physiological data and node information that identifies the stages of plant growth and development.
[0103] (1) Multispectral image processing and phenotypic data extraction.
[0104] Phenotypic data extraction: By processing periodically acquired multispectral images, key phenotypic data such as chlorophyll content, canopy water content, nitrogen content, and leaf area index (LAI) can be extracted.
[0105] These data reflect the nutritional status, biomass accumulation, and water stress of plants over longer timescales, and are an important supplement to transient gas exchange data.
[0106] (2) Calibration and correction of model parameters.
[0107] The extracted phenotypic data is compared with the second preset target to generate a second comparison result.
[0108] Based on this result, the system does not directly regulate the environment, but instead corrects the parameters of the stomatal conductance prediction model used in the first closed loop. For example, using the inverted chlorophyll content, the maximum carboxylation rate related to photosynthetic capacity can be calibrated. The estimated value; using canopy water content data, the matrix water potential function in the stomatal conductance prediction model was corrected. The parameters; using continuously measured LAI, the calculation is updated. and Total leaf area used at that time .
[0109] (3) Dynamic updates of preset targets.
[0110] The second closed loop can also dynamically update the first preset target in the first closed loop based on the plant's growth and development stage. For example, the system can automatically switch between different optimal targets during the seedling stage, rapid growth stage, and maturity stage. or The target curve enables adaptive cultivation management that matches plant phenology.
[0111] Through the continuous operation of the second closed loop, the system forms an intelligent system with the capabilities of execution, evaluation, learning, and optimization, which transcends static environmental simulation.
[0112] As can be seen from the above dual-loop control model, by simultaneously acquiring the instantaneous physiological metabolic rate of the fast-response loop and the long-term developmental phenotypic information of the slow-response loop, the data fusion strategy of gas exchange combined with multispectral imaging provides a unique dataset for constructing an accurate physiological model of space plants.
[0113] In this application, in order to achieve the aforementioned stable and precise environmental control, a dynamic heat and mass balance model was established for the cultivation chamber and environmental control chamber system as the theoretical basis for closed-loop control. Figure 11 This is a schematic diagram of the main heat exchange units involved in the heat balance model of this application. It includes the experimental chamber (cultivation chamber), the air chamber (environmental control chamber), and components that realize heating (PTC), cooling (semiconductor, chiller) and constant temperature heating of water, showing the path of heat transfer and regulation within the system. Figure 12 This is a schematic diagram of the water vapor generation and circulation path in the humidity balance model, showing the dynamic balance path of water in the system through processes such as evaporation, atomization, condensation, and ventilation. Figure 13 To simulate the effect of the acoustic levitation ultrasonic array system, the environmental data and physiological data feedback obtained from the model can be used to further regulate the sound field in the acoustic levitation cultivation system. This method can adjust the spatial position of the acoustic levitation and the output sound pressure and sound intensity of each ultrasonic module, thereby controlling the small-scale control of the crop heat accumulation area and heat accumulation to achieve the optimal goal. Figure 14A schematic diagram illustrating acoustic suspension cultivation of lettuce and sound field control.
[0114] In one possible implementation, the experimental system includes a heat balance model, a humidity balance model, and a CO2 mass balance model, wherein the heat balance model includes an energy balance equation for the cultivation chamber and an energy balance equation for the environmental control chamber.
[0115] (1) Heat balance model.
[0116] The system's heat transfer mainly includes heat generation from LED light sources inside the cultivation chamber, heat exchange between the chamber walls and the external water bath, ventilation heat exchange between the cultivation chamber and the environmental control chamber, and heating / cooling heat exchange within the environmental control chamber itself.
[0117] In one possible implementation, the energy balance equation for the cultivation chamber includes: The rate of change of the internal energy of the air inside the cultivation chamber is equal to its net heat gain rate, which can be expressed as:
[0118] in, For the quality of dry air inside the cultivation chamber, The specific heat capacity of air at constant pressure. The air temperature inside the cultivation chamber. For time, The heat generated by the LED light source inside the cultivation chamber As the net heat transfer between the cultivation chamber walls and the external environment is positive, the outflow is positive. For the net heat exchange with the ventilation of the environmental control chamber, the inflow is positive.
[0119] Bulkhead heat transfer It can be calculated using the following formula:
[0120] in, The overall heat transfer coefficient of the cultivation chamber walls, This represents the effective heat exchange area between the cultivation chamber and the external water bath. The temperature of the external water bath.
[0121] Ventilation and heat exchange Determined by the enthalpy difference between the incoming and outgoing air:
[0122] in, The dry air mass flow rate through the cultivation chamber. The temperature of the environmental control chamber (air source).
[0123] As a thermal hub, the environmental control chamber has the following energy balance:
[0124] in, To regulate the dry air quality inside the environmental control cabin, The net heat output of the heating / cooling actuators (such as PTC and semiconductor cooling chips) in the environmental control cabin (positive for heating and negative for cooling). This refers to the total heat loss between the environmental control chamber and the external environment through walls, ventilation, and other means.
[0125] After considering heat loss in the piping, the effective ventilation heat exchange needs to be multiplied by an efficiency factor. The heat loss can be estimated as follows:
[0126] in, It can be estimated from its heat transfer characteristics:
[0127] in, The characteristic length of the ventilation duct. This refers to the thermal resistance per unit length of the ventilation duct.
[0128] (2) Humidity balance model.
[0129] The changes in water vapor content within the system are mainly determined by plant transpiration, surface evaporation, active humidification / dehumidification, ventilation, and condensation.
[0130] In one possible implementation, the humidity balance equation is:
[0131] in, For the quality of dry air inside the cultivation chamber, The humidity ratio (water vapor mass / dry air mass) of the air inside the cultivation chamber. This represents the rate at which water vapor is produced through plant transpiration. It is calculated from the transpiration rate derived from the gas exchange diagnostic model. This refers to the rate of water evaporation from non-plant surfaces (such as nutrient solution) within the cultivation chamber. The dry air mass flow rate for ventilation in the environmental control chamber. The humidity ratio of the air exiting the environmental control cabin. The rate of active humidification (positive) or dehumidification (negative). The rate at which moisture condenses and precipitates on a cold surface (such as a refrigerator).
[0132] Water evaporation rate It can be modeled as: ,in, The water vapor mass transfer coefficient is... The effective area of the water surface for evaporation. To be at temperature The saturation humidity ratio of the air below.
[0133] (3) CO2 mass balance model.
[0134] In one possible implementation, the CO2 concentration change in the cultivation chamber is controlled by replenishment, plant absorption, ventilation exchange, and dissolution processes.
[0135]
[0136] in, For the volume of the cultivation chamber, This refers to the CO2 concentration inside the cultivation chamber. To determine the rate at which CO2 is replenished to the system from the gas source, The rate at which plants absorb CO2 through photosynthesis is calculated from the net photosynthetic rate derived from a gas exchange diagnostic model. To regulate the CO2 concentration inside the environmental control chamber, This represents the rate at which CO2 dissolves in the water within the system.
[0137] The standardized dynamic equilibrium equations, combined with the gas exchange diagnostic model and the dual closed-loop controller, constitute a complete predictive control theoretical framework. The controller utilizes these equations for feedforward compensation and optimization calculations to achieve rapid, stable, and precise regulation of environmental parameters such as temperature, humidity, and CO2 concentration, laying a solid theoretical foundation for intelligent control targeting physiological states.
[0138] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.
[0139] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.
Claims
1. A three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method, characterized in that, include: A microgravity gas-thermal environment simulation cultivation experimental system was established based on acoustic levitation and gas recovery, using RPM as the foundation. The experimental system includes a cultivation chamber, an environmental control chamber, RPM, an acoustic levitation device, and a gas recovery and monitoring unit. A dual-closed-loop control model is constructed, which is based on a physiological model and includes a first closed-loop control and a second closed-loop control. The physiological model includes a gas exchange diagnostic model and a stomatal conductance prediction model. First closed-loop control: Real-time monitoring of environmental parameters of the cultivation chamber; online calculation of key physiological parameters of the plants in the cultivation chamber based on the gas exchange diagnostic model; comparison of the key physiological parameters with a first preset target to obtain a first comparison result; dynamic adjustment of the sound field parameters of the acoustic levitation device and the environmental parameters of the cultivation chamber based on the first comparison result. Second closed-loop control: periodically acquire multispectral images of plants in the cultivation chamber, extract phenotypic data of plants based on the multispectral images; compare the phenotypic data with a second preset target to obtain a second comparison result; based on the second comparison result, correct the parameters of the stomatal conductance prediction model and the first preset target.
2. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 1, characterized in that, The porosity prediction model is a porosity prediction model that incorporates the acoustic levitation effect; the formula for the porosity prediction model is as follows: in, For the stomatal conductance of the blade, For maximum porosity, , , , are the response functions for photosynthetically active radiation, vapor pressure deficit, temperature, and CO2, respectively. For photosynthetically active radiation variables, For water vapor pressure deficit variables, For temperature variables, For CO2 variables, For shear wind correction term, Low-speed airflow wind speed. For matrix water potential function, As a variable of matrix water potential, This is a comprehensive correction factor for microgravity and adiabatic environment. , The equivalent additional water vapor pressure difference generated by the sound radiation force. This is due to a normal water vapor pressure deficit.
3. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 1 or 2, characterized in that, The porosity prediction model uses acoustic stress factor To quantify the direct promoting effects of sound pressure and thermal effects on stomatal opening and closing under environmental stress. ,in, This is the empirical coefficient for acoustic stress attenuation. The amplitude of the sound pressure level. The frequency of the sound.
4. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 1, characterized in that, The key physiological parameters include: transpiration rate, net photosynthetic rate, stomatal conductance, and water use efficiency.
5. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 1, characterized in that, The first preset target is the optimal curve of the key physiological parameter.
6. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 1, characterized in that, The second preset objective includes: the empirical range of physiological data and node information that identifies the stages of plant growth and development.
7. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 1, characterized in that, The experimental system includes a heat balance model, a humidity balance model, and a CO2 mass balance model. The heat balance model includes the energy balance equations for the cultivation chamber and the environmental control chamber.
8. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 7, characterized in that, The energy balance equation for the cultivation chamber is: in, For the quality of dry air inside the cultivation chamber, The specific heat capacity of air at constant pressure. The air temperature inside the cultivation chamber. For time, The heat generated by the LED light source inside the cultivation chamber To reduce net heat transfer between the cultivation chamber walls and the external environment, For net heat exchange with the ventilation of the environmental control chamber; The energy balance equation for the environmental control chamber is: in, To regulate the dry air quality inside the environmental control cabin, To regulate the temperature of the environmental control chamber, To provide the net heat output of the heating / cooling actuators within the environmental control cabin, This refers to the total heat loss between the environmental control chamber and the external environment through walls, ventilation, and other means.
9. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 7, characterized in that, The equilibrium equation of the humidity balance model is: in, For the quality of dry air inside the cultivation chamber, The humidity ratio of the air inside the cultivation chamber is given by t, where t is time. The rate at which water vapor is produced by plant transpiration. The evaporation rate of water from non-plant surfaces within the cultivation chamber. The dry air mass flow rate for ventilation in the environmental control chamber. The humidity ratio of the air exiting the environmental control cabin. The rate of active humidification or dehumidification, The rate at which water condenses and precipitates on a cold surface.
10. The three-dimensional rotating gas recovery and acoustic levitation microgravity gas-thermal environment simulation cultivation method according to claim 7, characterized in that, The equilibrium equation of the CO2 mass balance model is: in, Let t be the volume of the cultivation chamber and t be the time. This refers to the CO2 concentration inside the cultivation chamber. To determine the rate at which CO2 is replenished to the system from the gas source, The rate at which plants absorb CO2 through photosynthesis. The dry air mass flow rate for ventilation in the environmental control chamber. To regulate the CO2 concentration inside the environmental control chamber, This represents the rate at which CO2 dissolves in the water within the system.