Dynamic humidity simulation method for multi-area clean plant based on wind pressure and humidity coupling

Abstract

The invention discloses a multi-region clean workshop dynamic humidity simulation method based on wind pressure and humidity coupling, which comprises the following specific steps: S1, establishing a basic form of a multi-region clean workshop differential pressure gradient model, performing equation matrix, and calculating multi-region room air permeability; s2, establishing a dynamic humidity migration model, and taking the room air seepage quantity as a key parameter influencing the room humidity; s3, the dynamic humidity change equation is subjected to matrix processing, so that a multi-region room model can be solved conveniently; s4, solving a dynamic humidity change equation, and dynamically simulating the room humidity; compared with the prior art, coupling calculation is carried out on the air volume, the pressure difference and the humidity of the multi-area clean workshop through MATLAB, the influence of room air seepage on the room humidity is mainly considered, and finally dynamic simulation of the room humidity of the multi-area clean workshop is achieved.

Description

Technical Field

[0001] This invention belongs to the field of humidity control in multi-zone cleanrooms, specifically involving a dynamic humidity simulation method for multi-zone cleanrooms based on wind pressure and humidity coupling. Background Technology

[0002] Humidity control in civil buildings affects the comfort and health of people, while in industrial buildings it is closely related to process standards and product quality. my country's advanced manufacturing industry is at a critical stage of transformation and upgrading. Key development areas of "Made in China," such as new energy, biomedicine, and precision manufacturing, all place high demands on humidity control. At this stage, research on the principles of humidity environment creation and optimized control is of great significance in both ensuring and improving the production process level of advanced manufacturing and reducing energy consumption.

[0003] Cleanrooms are typically divided into multiple zones based on production processes and cleanliness requirements, with varying temperature, humidity, and cleanliness standards between zones. Due to air exchange and the movement of personnel and equipment between zones, humidity diffuses and migrates, affecting the overall humidity balance. Airflow, pressure differential, and humidity within a cleanroom are interconnected. Because of airflow balance and pressure gradients between rooms, air leakage occurs through gaps in doors and other openings, leading to humidity migration and exchange. Current research, both domestically and internationally, focuses on the thermal-humidity coupling of building envelopes and the simulation of airflow and pressure differentials, with limited research on building interior models, particularly indoor humidity balance. Furthermore, while current multi-zone cleanrooms can efficiently control airflow and pressure differentials on demand, precise humidity control remains a challenge. Summary of the Invention

[0004] To address the aforementioned issues, this invention discloses a dynamic humidity simulation method for multi-zone cleanrooms based on wind pressure and humidity coupling. The method simulates different room humidity design requirements and operating conditions, and uses MATLAB to couple and calculate air volume, pressure difference, and humidity, thereby obtaining different dynamic humidity change curves. This facilitates on-demand humidity control, reduces energy consumption, and has a wide range of applications.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] A dynamic humidity simulation method for multi-zone cleanrooms based on wind pressure-humidity coupling includes the following steps:

[0007] S1. Establish the basic form of the pressure gradient model for a multi-zone cleanroom, matrix the equations, and calculate the air infiltration volume in the multi-zone rooms.

[0008] S2. Establish a dynamic humidity migration model and substitute the infiltration volume calculated in S1 into the model for coupled calculation.

[0009] S3. The dynamic humidity change equation is matrixed to facilitate the solution of multi-area room models;

[0010] S4. Solve the dynamic humidity change equation using the finite difference method in MATLAB to dynamically simulate room humidity.

[0011] As a further preferred embodiment of the present invention, step S1 includes the following specific steps:

[0012] S1-1. Establish the basic form of the pressure difference equation. For each room i, define its pressure difference balance equation as follows: Among them G zi It is the air infiltration rate of room i, c ij It is the door gap coefficient between rooms i and j. If rooms i and j are not connected, then c ij =0, P i and P j These are the pressures in room i and room j, respectively.

[0013] S1-2. Construct the pressure difference matrix equation and convert the pressure difference equation into matrix form, i.e., A·P=B, where matrix A is an n×n square matrix representing the connection relationship between each room, P is an n-dimensional column vector representing the pressure in each room, and B is an n-dimensional column vector representing the air infiltration volume in each room.

[0014] S1-3, Construct matrix A and source term vector B, and the diagonal elements of matrix A are A ii Let represent the total door gap coefficient of room i, which is equal to the sum of the door gap coefficients of room i and all its adjacent rooms, i.e. off-diagonal element A ij , i≠j, represents the connection relationship between room i and room j, and takes the value A. ij =c ij The air infiltration volume G in each room i in the source term vector B zi The i-th term B in vector B i =G zi ;

[0015] S1-4. Solve the pressure difference equation. By solving the matrix equation A·P=B, the pressure P of each room can be obtained.

[0016] As a further preferred embodiment of the present invention, step S2 includes the following specific steps:

[0017] S2-1. Considering the influence of supply air humidity input, the supply air system provides a specific humidity W s,iAir enters room i, with a supply air volume of G. s,i Therefore, the moisture flow rate entering room i is G. s,i ·W s,i The change in net humidity caused by the air supply is written as G. s,i ·(W s,i -W i ), where W i The specific humidity of room i is used to convert this humidity change into the rate of change of specific humidity. The room volume V also needs to be considered. i Given the air density ρ, the rate of change of the supply air term is:

[0018] S2-2. Considering the influence of humidity input from the moisture source, the moisture source in the room will directly release water vapor, and the dehumidification rate is... Due to moisture dissipation rate This is the increase in water vapor mass. To convert it to an increase in specific humidity, you need to divide it by the room volume V. i Given the air density ρ, the contribution term from the moisture source is obtained as follows:

[0019] S2-3. Considering the humidity exchange caused by air infiltration, if there is an air infiltration volume G between room j and room i. ij This will result in humidity exchange, with the flow rate of moisture entering room i from room j being G. ij ·W j The moisture flow rate output from room i to room j is G. ij ·W i Therefore, the change in net humidity caused by air infiltration is G. ij (W j -W i In the room humidity change rate, it is necessary to sum for each connected room. Therefore, the effect of air seepage on room i is:

[0020] S2-4. Based on the law of conservation of mass and the fluid flow equation, combining S2-1, S2-2, and S2-3, we obtain the dynamic equation for the change in room humidity as follows:

[0021] As a further preferred embodiment of the present invention, step S3 includes the following specific steps:

[0022] S3-1. Establish the basic form of the humidity dynamic change equation. For room i, the humidity change considers the supply air, return air, and humidity balance of each room. The humidity dynamic change equation is: Among them W i It is the specific humidity of room i, G s,i V is the air volume supplied to room i. i W is the volume of room i.s,i The specific humidity of the room's air supply is G. ij It is the air infiltration rate between room i and room j;

[0023] S3-2. Construct a dynamic humidity change matrix equation and convert the dynamic humidity change equation into matrix form. Where matrix A is an n×n square matrix representing the influence of room supply air volume and air infiltration between adjacent rooms, W is an n-dimensional column vector representing the specific humidity of each room, and B is an n-dimensional column vector representing the influence of moisture source and supply air specific humidity of each room.

[0024] S3-3. Construct matrix A and source term vector B, with the diagonal elements of matrix A being A... ii , representing the coefficient of variation of the humidity of room i itself, i.e. off-diagonal element A ij , i≠j, represents the humidity transfer coefficient between room i and room j, with a value of The source term vector B represents the source term B for each room. i Includes room humidity and supply air specific humidity.

[0025] S3-4 Solve the humidity equation and use the finite difference method based on MATLAB to dynamically simulate the humidity changes in each room.

[0026] As a further preferred embodiment of the present invention, step S4 includes the following specific steps:

[0027] S4-1. Determine the initialization conditions. First, set the initial humidity of each room (usually set to the supply air specific humidity value), and then set the simulation step size dt and the total time T to determine the total number of iteration steps.

[0028] S4-2. Establish the discretization equations. For each room i, use the explicit Euler method to discretize the differential equations. The humidity value W at the previous time t i (t) is used to calculate the rate of change in humidity. Thus, the humidity W at the next moment can be obtained. i (t+dt);

[0029] S4-3. Iterative calculation: First, at each time step, calculate the humidity change rate of all rooms. And update the humidity value W i Then repeat the process until the total time T is reached;

[0030] S4-4. Steady-state determination: If the rate of change of humidity is less than 5% after a certain time step, the system is considered to have reached steady state, and the iteration is terminated.

[0031] The advantages of this invention are:

[0032] This invention uses MATLAB to couple and calculate air volume, pressure difference, and humidity, and performs dynamic humidity simulation in multi-zone cleanrooms. It can obtain the humidity change patterns in different rooms and analyze the humidity stabilization process, thus facilitating precise humidity control under different room design parameters and operating conditions. This invention is applicable to different multi-zone cleanrooms and can be adjusted according to the specific design conditions of the room. By optimizing the humidity control system, unnecessary humidification or dehumidification operations are reduced, energy consumption is lowered, and its application range is wide. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating the present invention;

[0034] Figure 2 This is a detailed flowchart illustrating the matrix transformation of the differential pressure gradient equation in a multi-zone cleanroom.

[0035] Figure 3 This is a detailed flowchart illustrating the matrix transformation of the dynamic humidity change equation;

[0036] Figure 4 This is a flowchart illustrating a dynamic humidity simulation algorithm based on the finite difference method.

[0037] Figure 5 This is a dynamic humidity change curve of multiple rooms based on a certain project. Detailed Implementation

[0038] The present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0039] As shown in the figure, the dynamic humidity simulation method for multi-zone cleanrooms based on wind pressure and humidity coupling described in this invention includes the following specific steps:

[0040] S1. Establish the basic form of the pressure gradient model for a multi-zone cleanroom, matrix the equations, and calculate the air infiltration volume in the multi-zone rooms.

[0041] Specifically, the following steps are included:

[0042] S1-1. Establishing the basic form of the pressure difference equation:

[0043] For each room i, its pressure balance equation can be defined as follows:

[0044]

[0045] in:

[0046] G zi This is the air infiltration rate in room i;

[0047] c ij It is the door gap coefficient between rooms i and j. If rooms i and j are not connected, then c ij =0;

[0048] P i and P j These are the pressures in room i and room j, respectively.

[0049] S1-2, Construct the pressure difference matrix equation:

[0050] The pressure difference equation can be converted into matrix form:

[0051] A·P=B

[0052] in:

[0053] Matrix A is an n×n square matrix that represents the connection relationships between the rooms;

[0054] P is an n-dimensional column vector representing the pressure in each room;

[0055] B is an n-dimensional column vector representing the air infiltration volume of each room;

[0056] S1-3, Construct matrix A and source term vector B:

[0057] Matrix A:

[0058] Diagonal element A ii It represents the total door gap coefficient of room i, which is equal to the sum of the door gap coefficients of room i and all its adjacent rooms, that is:

[0059]

[0060] For the off-diagonal element A ij , i≠j, it represents the connection relationship between room i and room j, and its value is:

[0061] A ij =c ij

[0062]

[0063] Source term vector B:

[0064] The air infiltration rate G in each room i zi The i-th term in vector B:

[0065] B i =G zi

[0066]

[0067] S1-4, Solve the pressure difference equation:

[0068] By solving the matrix equation A·P=B, the pressure P in each room can be obtained.

[0069] S2. Establish a dynamic humidity migration model and substitute the infiltration volume calculated in S1 into the model for coupled calculation.

[0070] The specific steps include the following:

[0071] S2-1. Consider the impact of supply air humidity input:

[0072] The air supply system provides specific humidity W s,i Air enters room i, with a supply air volume of G. s,i Therefore, the moisture flow rate entering room i is:

[0073] G s,i ·W s,i

[0074] The change in net humidity caused by air supply can be described as:

[0075] G s,i ·(W s,i -W i )

[0076] Among them W i It is the specific humidity of room i.

[0077] To convert this humidity change into the rate of change of specific humidity, the room volume V also needs to be considered. i And air density ρ. Therefore, the rate of change of the supply air term is:

[0078]

[0079] S2-2. Consider the influence of humidity input from the moisture source:

[0080] The moisture source in the room will directly release water vapor, and the dehumidification rate is... Due to moisture dissipation rate This is the increase in water vapor mass. To convert it to an increase in specific humidity, you need to divide it by the room volume V. i Based on the air density ρ, the contribution term of the moisture source is obtained as follows:

[0081]

[0082] S2-3, Considering humidity exchange caused by air infiltration

[0083] If there is an air infiltration flow rate G between room j and room i ij This will result in humidity exchange. The flow rate of moisture entering room i from room j is G. ij ·W j The moisture flow rate output from room i to room j is G. ij ·W i Therefore, the change in net humidity caused by air infiltration is as follows:

[0084] G ij (W j -W i )

[0085] In the room humidity change rate calculation, it is necessary to sum for each connected room. Therefore, the effect of air infiltration on room i is:

[0086]

[0087] S2-4. Based on the law of conservation of mass and the fluid flow equation, combining the three terms S2-1, S2-2, and S2-3, we obtain the dynamic equation for the change in room humidity:

[0088]

[0089] S3. The dynamic humidity change equation is matrixed to facilitate the solution of multi-area room models;

[0090] The specific steps include the following:

[0091] S3-1. Establishing the basic form of the equation for dynamic humidity change:

[0092] For room i, the humidity change takes into account the supply air, return air, and humidity balance of each room. The dynamic humidity change equation is:

[0093]

[0094] in:

[0095] W i It is the specific humidity of room i;

[0096] G s,i This is the air volume supplied to room i;

[0097] V i It is the volume of room i;

[0098] W s,i The specific humidity is the air supply volume of room i;

[0099] G ij It is the air infiltration rate between room i and room j;

[0100] S3-2. Constructing the dynamic humidity change matrix equation:

[0101] Convert the dynamic humidity change equation into matrix form:

[0102]

[0103] in:

[0104] Matrix A is an n×n square matrix that represents the influence of room air supply volume and air infiltration between adjacent rooms;

[0105] W is an n-dimensional column vector representing the specific humidity of each room;

[0106] B is an n-dimensional column vector representing the influence of moisture source and supply air specific humidity in each room;

[0107] S3-3, Construct matrix A and source term vector B:

[0108] Matrix A:

[0109] For diagonal element A ii It represents the coefficient of variation of the humidity of room i itself:

[0110]

[0111] For the off-diagonal element A ij , i≠j, represents the humidity transfer coefficient between room i and room j:

[0112] Source term vector B:

[0113] Source item B for each room i Includes room humidity and supply air specific humidity:

[0114]

[0115] S3-4. Solve the humidity equation:

[0116] The humidity changes in each room were dynamically simulated using the finite difference method based on MATLAB.

[0117] S4. Solve the dynamic humidity change equation using the finite difference method in MATLAB to dynamically simulate room humidity; including the following specific steps:

[0118] S4-1, Initialization conditions:

[0119] 1. Set the initial humidity for each room (usually set to the supply air specific humidity value).

[0120] 2. Set the simulation step size dt and the total time T to determine the total number of iterations.

[0121] S4-2 Discretization Equations:

[0122] For each room i, the differential equation is discretized using the explicit Euler method:

[0123]

[0124] The humidity value W at the previous time t i (t) is used to calculate the rate of change in humidity. Thus, the humidity W at the next moment can be obtained. i (t+dt).

[0125] S4-3, Iterative Calculation:

[0126] 1. At each time step, calculate the humidity change rate for all rooms. And update the humidity value W i .

[0127] 2. Repeat this process until the total time T is reached.

[0128] S4-4, Steady-state determination:

[0129] If the rate of change in humidity is less than 5% after a certain time step, the system is considered to have reached a steady state, and the iteration terminates.

[0130] Example 2:

[0131] Given the known supply air volume, return air volume, exhaust air volume, supply air specific humidity, moisture source velocity, and pressure of the multi-zone cleanroom, the method for simulating and calculating the dynamic humidity of the room is as follows:

[0132] S001: Collect data on air supply volume, return air volume, exhaust air volume, supply air specific humidity, relevant moisture source intensity, pressure, and volume of 15 rooms in a cleanroom of a certain project in Taizhou. First, substitute the data into a multi-zone pressure gradient model to determine the direction of air leakage between the 15 rooms and calculate the specific amount of air leakage.

[0133] S002: Based on the connection relationship between the 15 rooms, establish a dynamic humidity change matrix, and substitute the air infiltration volume between the 15 rooms calculated in S001 into the dynamic humidity change matrix for coupled calculation.

[0134] S003: Input known data such as room air volume, supply air specific humidity (9.5 g / kg dry), moisture source rate (1 g / s), pressure, and volume. Then, discretize the humidity dynamic change equation for each room and perform iterative calculations to obtain humidity dynamic change curves for 15 rooms. The initial humidity on the curves is the room supply air specific humidity (9.5 g / kg dry). Among them, the humidity change of the room directly affected by the moisture source is the largest, with a steady-state humidity of 10.45 g / kg dry. The humidity change of the related rooms directly affected by air infiltration in the room is the second largest, with a steady-state humidity of 10.02 g / kg dry. The steady-state humidity of the remaining rooms does not exceed 9.68 g / kg dry, and the humidity of all rooms reaches a stable state within 4000s.

[0135] This invention uses MATLAB to couple and calculate air volume, pressure difference, and humidity, and performs dynamic humidity simulation in multi-zone cleanrooms. It can obtain the humidity change patterns in different rooms and analyze the humidity stabilization process, thus facilitating precise humidity control under different room design parameters and operating conditions. This invention is applicable to different multi-zone cleanrooms and can be adjusted according to the specific design conditions of the room. By optimizing the humidity control system, unnecessary humidification or dehumidification operations are reduced, energy consumption is lowered, and its application range is wide.

[0136] It should be noted that the above content merely illustrates the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. For those skilled in the art, various improvements and modifications can be made without departing from the principle of the present invention, and all such improvements and modifications fall within the scope of protection of the claims of the present invention.

Claims

1. A dynamic humidity simulation method for multi-zone cleanrooms based on wind pressure and humidity coupling, characterized in that, The specific steps include the following: S1. Establish the basic form of the pressure gradient model for a multi-zone cleanroom, matrix the equations, and calculate the air infiltration volume in the multi-zone rooms. S2. Establish a dynamic humidity migration model and substitute the infiltration volume calculated in S1 into the model for coupled calculation. S3. The dynamic humidity change equation is matrixed to facilitate the solution of multi-area room models; S4. Solve the dynamic humidity change equation using the finite difference method in MATLAB to dynamically simulate room humidity.

2. The method for dynamic humidity simulation of multi-zone cleanrooms based on wind pressure and humidity coupling according to claim 1, characterized in that, The specific steps include the following: S1-1. Establishing the basic form of the pressure difference equation: For each room i, its pressure balance equation is defined as follows: in: G zi This is the air infiltration rate in room i; c ij It is the door gap coefficient between rooms i and j. If rooms i and j are not connected, then c ij =0; P i and P j These are the pressures in room i and room j, respectively. S1-2, Construct the pressure difference matrix equation: Convert the pressure difference equation into matrix form: A·P=B in: Matrix A is an n×n square matrix that represents the connection relationships between the rooms; P is an n-dimensional column vector representing the pressure in each room; B is an n-dimensional column vector representing the air infiltration volume of each room; S1-3, Construct matrix A and source term vector B: Matrix A: For diagonal element A ii It represents the total door gap coefficient of room i, which is equal to the sum of the door gap coefficients of room i and all its adjacent rooms, that is: For the off-diagonal element A ij , i≠j, it represents the connection relationship between room i and room j, and its value is: Source term vector B: The air infiltration rate G in each room i zi The i-th term in vector B: B i =G zi S1-4, Solve the pressure difference equation: The pressure P in each room is obtained by solving the matrix equation A·P=B.

3. The method for simulating dynamic humidity in a multi-zone cleanroom based on wind pressure and humidity coupling according to claim 1, characterized in that, The specific steps include the following: S2-1. Consider the impact of supply air humidity input: The air supply system provides specific humidity W s,i Air enters room i, with a supply air volume of G. s,i Therefore, the moisture flow rate entering room i is: G s,i ·W s,i The change in net humidity caused by air supply can be described as follows: G s,i ·(W s,i -W i ) To convert this humidity change into the rate of change of specific humidity, the room volume V also needs to be considered. i And the air density ρ; therefore, the rate of change of the supply air term is: S2-2. Consider the influence of humidity input from the moisture source: The moisture source in the room will directly release water vapor, and the dehumidification rate is... Due to moisture dissipation rate This is the increase in water vapor mass. To convert it to an increase in specific humidity, you need to divide it by the room volume V. i Based on the air density ρ, the contribution term of the moisture source is obtained as follows: S2-3, Considering humidity exchange caused by air infiltration If there is an air infiltration flow rate G between room j and room i ij This will result in humidity exchange; the flow rate of moisture input from room j to room i is G. ij ·W j The moisture flow rate output from room i to room j is G. ij ·W i Therefore, the change in net humidity caused by air infiltration is as follows: G ij (W j -W i ) In the room humidity change rate calculation, it is necessary to sum for each connected room. Therefore, the effect of air infiltration on room i is: S2-4. Based on the law of conservation of mass and the fluid flow equation, combining the three terms S2-1, S2-2, and S2-3, we obtain the dynamic equation for the change in room humidity:

4. The method for simulating dynamic humidity in a multi-zone cleanroom based on wind pressure and humidity coupling according to claim 1, characterized in that, Includes the following steps: S3-1. Establishing the basic form of the equation for dynamic humidity change: For room i, the humidity change takes into account the supply air, return air, and humidity balance of each room. The dynamic humidity change equation is: in: W i It is the specific humidity of room i; G s,i This is the air volume supplied to room i; V i It is the volume of room i; W s,i The specific humidity is the air supply volume of room i; G ij It is the air infiltration rate between room i and room j; S3-2. Constructing the dynamic humidity change matrix equation: Convert the dynamic humidity change equation into matrix form: in: Matrix A is an n×n square matrix that represents the influence of room air supply volume and air infiltration between adjacent rooms; W is an n-dimensional column vector representing the specific humidity of each room; B is an n-dimensional column vector representing the influence of moisture source and supply air specific humidity in each room; S3-3, Construct matrix A and source term vector B: Matrix A: For diagonal element A ii It represents the coefficient of variation of the humidity of room i itself: For the off-diagonal element A ij , i≠j, represents the humidity transfer coefficient between room i and room j: Source term vector B: Source item B for each room i Includes room humidity and supply air specific humidity: S3-4. Solve the humidity equation: The humidity changes in each room were dynamically simulated using the finite difference method based on MATLAB.

5. The method for dynamic humidity simulation of multi-zone cleanrooms based on wind pressure and humidity coupling according to claim 1, characterized in that, Includes the following steps: S4-1, Initialization conditions:

1. Set the initial humidity for each room; 2. Set the simulation step size dt and the total time T to determine the total number of iterations; S4-2 Discretization Equations: For each room i, the differential equation is discretized using the explicit Euler method: The humidity value W at the previous time t i (t) is used to calculate the rate of change in humidity. Thus, the humidity W at the next moment can be obtained. i (t+dt); S4-3, Iterative Calculation:

1. At each time step, calculate the humidity change rate for all rooms. And update the humidity value W i ; 2. Repeat this process until the total time T is reached; S4-4, Steady-state determination: If the rate of change in humidity is less than 5% after a certain time step, the system is considered to have reached a steady state, and the iteration terminates.

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