Red blood cell refrigeration house and optimization design method thereof

Abstract

The invention discloses a red blood cell refrigeration house optimization design method, and relates to the technical field of refrigeration equipment, and the method comprises the steps: setting constraint conditions of each factor of a red blood cell refrigeration house, each factor comprising the specific surface area of the red blood cell refrigeration house, the variable cross-section height, the air cooler position, the internal heat source position, the air cooler air supply temperature and the air supply speed; based on the level number of each factor, acquiring a factor level table, and designing an orthogonal experiment working condition; thermal performance evaluation indexes under different working conditions are calculated, and orthogonal simulation results under different working conditions are obtained; based on the orthogonal simulation result, performing range analysis on the thermal performance evaluation index under the orthogonal experiment working condition to obtain an orthogonal experiment calculation result; and an orthogonal experiment calculation result is analyzed to obtain an optimal combination working condition of each factor, so that unnecessary energy loss is reduced, temperature uniformity and velocity field distribution are optimized, and the stability of a storage environment is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of refrigeration equipment, in particular to a red blood cell cold storage and an optimization design method thereof. Background Art

[0002] Optimizing the thermal performance of red blood cell cold storage is crucial to ensuring the quality and storage safety of red blood cells. The optimal storage temperature of red blood cells should be maintained between 2°C and 6°C to inhibit cell metabolism and prolong the shelf life. Any fluctuation within this temperature range may cause damage to red blood cells, induce metabolic abnormalities or increase the risk of hemolysis. Therefore, ensuring the uniformity and stability of the temperature inside the cold storage is the key to improving the efficiency and safety of red blood cell storage;

[0003] At present, the design of traditional red blood cell cold storage is mostly focused on the research of airflow conditions, storage location layout and air curtain, and less attention is paid to the optimization of internal structures such as the specific surface area and internal variable cross-section of the cold storage. Reasonable design of the specific surface area value can effectively reduce the heat exchange between the inside of the cold storage and the external environment. The internal variable cross-section design can effectively guide the uniform distribution of airflow, reduce local airflow stagnation, and improve air flow efficiency; in addition, with the introduction of intelligent and automated technologies, cold storage is gradually equipped with sensors, robotic arms and remote monitoring systems. Although these technologies can improve operating efficiency through real-time monitoring and automatic adjustment, these devices will act as internal heat sources during operation, affecting the uniformity and stability of the temperature field in the cold storage, and increasing the energy consumption of the cold storage. Summary of the invention

[0004] In order to overcome the defects of high energy consumption, uneven and unstable temperature field of the red blood cell cold storage in the above-mentioned prior art, the present invention proposes a red blood cell cold storage and an optimization design method thereof.

[0005] To achieve the above object, the present invention adopts the following technical scheme, a method for optimizing the design of a red blood cell cold storage, comprising:

[0006] S1: Set the constraints of various factors of the red blood cell cold storage; the various factors include the specific surface area of ​​the red blood cell cold storage, the height of the variable section, the position of the air cooler, the position of the internal heat source, the air supply temperature of the air cooler, and the air supply speed;

[0007] S2: Based on the number of levels of each factor, obtain the factor level table and design orthogonal experimental conditions;

[0008] S3: Calculate the thermal performance evaluation index under different working conditions and obtain the orthogonal simulation results under different working conditions;

[0009] S4: Based on the orthogonal simulation results, the range analysis of the thermal performance evaluation index under the orthogonal experimental conditions is performed to obtain the orthogonal experimental calculation results;

[0010] S5: Analyze the calculation results of the orthogonal experiment to obtain the optimal combination of various factors.

[0011] Preferably, in step S1, the constraints of various factors of the red blood cell cold storage are set, including:

[0012] S11: Set the specific surface area S of the red blood cell cold storage A Based on the calculation formula of specific surface area, the external length L of the red blood cell cold storage is obtained. n and width W n Dimensions:

[0013]

[0014] Among them, H f is the height of the red blood cell cold storage, A is the surface area of ​​the red blood cell cold storage, and V is the volume of the red blood cell cold storage;

[0015] S12: Set the variable cross-section height H1 of the red blood cell cold storage to meet i is an integer, and i∈0,3];

[0016] S13: Set the position L1 of the cold air blower in the red blood cell cold storage to meet j is an integer, and j∈[0,2];

[0017] S14: Set the position L2 of the internal heat source in the red blood cell cold storage to meet m is an integer, and m∈1,4];

[0018] S15: Setting the air supply temperature Tf of the red blood cell cold storage to satisfy Ta≤Tf≤Tb; wherein the air supply temperature refers to the air temperature at the air supply outlet of the air cooler; Ta and Tb are the set minimum air supply temperature and maximum air supply temperature, respectively;

[0019] S16: Set the air supply speed Vf of the red blood cell cold storage to satisfy Va≤Vf≤Vb; wherein the air supply speed refers to the air speed at the air supply outlet of the air cooler; Va and Vb are the set minimum air supply speed and maximum air supply speed, respectively.

[0020] Preferably, in step S2, the number of levels of each factor refers to the sum of the number of selectable values ​​of each factor.

[0021] Preferably, in step S3, the thermal performance evaluation index includes the average temperature Temperature extreme difference R, temperature non-uniformity coefficient σ t , velocity non-uniformity coefficient σ v , the calculation formula is as follows:

[0022]

[0023] Among them, x is the XY section cloud map number inside the red blood cell cold storage, n is the number of sections, Tx is the average temperature of the xth section, T max is the maximum temperature of the cold storage, T min is the minimum value of the cold storage temperature, v x is the average wind speed at the x-th section, It is the average wind speed of the cold storage as a whole.

[0024] Preferably, in step S4, based on the orthogonal simulation results, the range analysis is performed on the thermal performance evaluation index under the orthogonal experimental working conditions to obtain the orthogonal experimental calculation results, wherein Kp represents the sum of the corresponding thermal performance evaluation indexes under all working conditions at the pth level, m is the total number of levels corresponding to each factor; the range S is k p The difference between the maximum and minimum values ​​in the experiment indicates the influence of each factor on the experimental results. The importance is ranked according to the size of S, and the optimal level is k. p The factor level corresponding to the minimum value in .

[0025] Preferably, in step S5, the orthogonal experimental calculation results are analyzed to obtain the optimal combination conditions of each factor. The priority of selecting the optimal level of each factor should first consider the average temperature, which must meet the blood red blood cell storage condition of 2 to 6°C, followed by the temperature non-uniformity coefficient and the temperature extreme difference, and finally the speed non-uniformity coefficient.

[0026] A red blood cell cold storage, as a design basis for a red blood cell cold storage optimization design method, comprises: a storage body 1 and a door 2, a plurality of shelves 3 are arranged on both sides of the storage body, an adjustable position air cooler is arranged inside the storage body along the length direction of the storage body, an air supply port 4 and an air return port 5 are arranged on both sides of the air cooler, a variable cross-section 6 with adjustable height is arranged on one side of the storage body, an illuminating lamp 7 is arranged at the center of the top of the storage body, an adjustable position internal heat source is also arranged inside the storage body along the length direction of the storage body, the internal heat source comprises a sensor 8, a mechanical arm and a fully automatic device 9 and a monitor 10, the mechanical arm and the fully automatic device 9 are fixed within the measurement range of the sensor 8 matrix, and the sensor 8, the mechanical arm and the fully automatic device 9 and the monitor 10 are in the same side plane.

[0027] A readable storage medium stores a computer program, which implements a method for optimizing the design of a red blood cell cold storage when executed.

[0028] A computer program product includes a computer program / instruction, which implements a method for optimizing the design of a red blood cell cold storage when executed by a processor.

[0029] The advantages of the present invention are:

[0030] (1) When optimizing the design of the red blood cell cold storage, the present invention comprehensively considers six key factors and their constraints, including specific surface area, variable cross-section height, air cooler position, internal heat source position, air supply temperature and speed. This multi-factor optimization can cover the main variables that affect the performance of the red blood cell cold storage, ensuring the comprehensiveness and scientificity of the cold storage performance from the design stage.

[0031] (2) The present invention uses orthogonal experimental design to optimize multiple factors. By reasonably selecting the factor level table, the actual number of experiments is reduced, the representativeness of the experimental results is ensured, and at the same time, the research cost can be effectively reduced, and the experimental efficiency and optimization accuracy of the red blood cell cold storage design can be improved.

[0032] (3) The present invention introduces average temperature Temperature range R, temperature non-uniformity coefficient σ t and velocity non-uniformity coefficient σ v As a thermal performance evaluation index, the distribution characteristics of temperature and airflow in the cold storage are comprehensively quantified and evaluated; priority is given to meeting the strict temperature requirements for red blood cell storage (2-6°C), and secondly, temperature uniformity and velocity field distribution are optimized to ensure the stability of the storage environment.

[0033] (4) The present invention utilizes range analysis to quantify the impact of each factor on the thermal performance index and to clarify the importance ranking and priority of each factor. The method is intuitive and scientific, ensuring that the optimal combination of the final design solution is based on reliable statistical analysis.

[0034] (5) The present invention significantly improves the thermal performance utilization efficiency and reduces unnecessary energy loss by optimizing the specific surface area, internal variable cross-section height, and position layout of the red blood cell cold storage. At the same time, by scientifically controlling the air supply temperature, equipment overload operation is avoided, the system energy consumption is further reduced, the equipment life is extended, and the economy and reliability of the cold storage operation are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a diagram of the red blood cell cold storage model;

[0036] Figure 2 Flowchart of the design method for optimizing the cold storage of red blood cells. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Example 1

[0039] like Figure 1 As shown, the present invention proposes a red blood cell cold storage, comprising: a storage body 1 and a door 2, a plurality of shelves 3 are arranged on both sides of the storage body, an adjustable position air cooler is arranged inside the storage body, the position of the air cooler is adjusted along the length direction of the storage body, air supply ports 4 and return ports 5 are arranged on both sides of the air cooler, and a variable cross-section 6 with adjustable height is arranged on one side of the storage body to effectively guide the uniform distribution of the air flow inside the red blood cell cold storage, and an illuminating lamp 7 is arranged at the center of the top of the storage body to provide light for convenience of operation. An adjustable position internal heat source is also arranged inside the storage body along the length direction of the storage body, and the internal heat source includes a sensor 8, a mechanical arm and a fully automatic device 9 and a monitor 10. The sensor 8 is responsible for monitoring the environment, warning faults and recording data, and assisting the mechanical arm in precise movement. The mechanical arm and the fully automatic device 9 are used to achieve efficient handling and reduce labor costs; the monitor 10 is used to monitor the cold storage situation in real time to ensure storage, and the safety mechanical arm and the fully automatic device 9 are fixed within the measurement range of the sensor 8 matrix, and the sensor 8, the mechanical arm and the fully automatic device 9 and the monitor 10 are in the same side plane.

[0040] From the perspective of fluid dynamics, the interior of the red blood cell cold storage adopts a variable cross-section design. When the airflow passes through the variable cross-section area, the airflow velocity and pressure will produce adaptive changes according to the continuity equation and Bernoulli's principle, thereby effectively guiding the airflow to be evenly distributed, stabilizing the temperature in the storage and ensuring a good storage environment for red blood cells.

[0041] Example 2

[0042] like Figure 2 As shown, the present invention proposes a red blood cell cold storage optimization design method, comprising:

[0043] Step 1: Set the specific surface area S of the red blood cell cold storage A Based on the calculation formula of specific surface area, the external length L of the red blood cell cold storage is obtained. n and width W n Dimensions:

[0044]

[0045] Among them, H f is the height of the red blood cell cold storage, A is the external surface area of ​​the red blood cell cold storage, and V is the volume of the red blood cell cold storage.

[0046] The specific surface area of ​​the red blood cell cold storage is the ratio of the surface area of ​​the external structure of the red blood cell cold storage to its volume. The effect of the variable cross-section design on the volume is ignored here.

[0047] In this embodiment, the high H f Take 2m; the volume V of the red blood cell cold storage is 25m 3; Under the condition of fixed height and fixed volume, obtain the external length L of the red blood cell cold storage n and width W n The size of the sample point, n is the sample point number, n = 1, 2, ... N; in this example, N is 4, a total of 4 sample points, that is, 4 specific surface area values. Studies have shown that a smaller specific surface area can reduce heat exchange and energy loss, thereby improving thermal insulation performance, helping to reduce the energy consumption of cold storage and improve overall operating efficiency. Therefore, the specific surface area should be as small as possible. In this example, 2.1m -1 , 2.2m -1 , 2.3m -1 (initial value), 2.4m -1 .

[0048] Step 2: Set the variable cross-section height H1 of the red blood cell cold storage to meet i is an integer, i∈[0,3]; the variable cross-section height of the red blood cell cold storage is the distance from the top of the red blood cell cold storage along the vertical direction downward of the red blood cell cold storage.

[0049] In this example, the variable cross-section height takes 4 values: when i=0, H1=0; when i=1, (initial value); when i=2, When i=3,

[0050] Step 3: Set the position L1 of the cold air blower in the red blood cell cold storage to meet j is an integer, j∈[0,2]; the position of the air cooler in the red blood cell cold storage refers to the distance between the side of the red blood cell cold storage far away from the variable cross-section and the air cooler.

[0051] Step 4: Set the position L2 of the internal heat source in the red blood cell cold storage to meet m is an integer, m∈1,4]. In this example, the internal heat source includes a sensor, a mechanical arm, a fully automatic device and a monitor. The position of the internal heat source in the red blood cell cold storage refers to the distance between the side of the red blood cell cold storage away from the variable cross section and the internal heat source.

[0052] Step 5: Set the air supply temperature T of the red blood cell cold storage f Meet 0℃≤T f ≤1.5℃; the supply air temperature refers to the air temperature at the air outlet 4 of the air cooler.

[0053] Step 6: Set the air supply speed Vf of the red blood cell cold storage to satisfy 2.6m / s≤Vf≤3.2m / s; wherein the air supply speed refers to the air speed at the air supply port 4 of the air cooler.

[0054] Step 7: According to the number of levels of each factor in the red blood cell cold storage, obtain the factor level table and design the orthogonal experimental conditions. The commonly used method for designing orthogonal experimental conditions is to perform permutation analysis on the level combinations that are representative of each factor to represent the comprehensive level test. n (p m ), where L represents the orthogonal array, n represents the number of trials and the number of rows in the orthogonal array, p represents the number of levels of each factor, and m represents the number of factors, that is, the number of columns in the orthogonal array.

[0055] The factors include specific surface area (A), variable cross-section height (B), layout position of air cooler (C), layout position of internal heat source (D), air supply temperature (E) and air supply speed (F), all of which affect the uniformity of temperature field and velocity field of red blood cell cold storage; the number of levels of each factor refers to the sum of the number of selectable values ​​of each factor, and the factor level table is shown in Table 1. According to the factor level table, the mixed level orthogonal L n (4 5 ·3 1 ), the quasi-horizontal orthogonal method is used, that is, the low-level factors are converted into virtual levels to meet the requirements of the standard orthogonal table, and a relatively close standard orthogonal table L is selected. 25 (4 6 ) to simulate orthogonality.

[0056] Table 1 Factor level table

[0057]

[0058] Step 8: Calculate the thermal performance evaluation index under different working conditions and obtain the orthogonal simulation results under different working conditions. The thermal performance evaluation index includes the average temperature Temperature extreme difference R, temperature non-uniformity coefficient σ t , velocity non-uniformity coefficient σ v The formula is as follows:

[0059]

[0060] Among them, x is Figure 1 XY cross-section cloud diagram inside the red blood cell cold storage (divided by the simulation software Ansys) number, n is the number of sections, Tx is the average temperature of the xth XY section, T max is the maximum temperature of the cold storage, T min is the minimum value of the cold storage temperature, v x is the average wind speed at the x-th section, is the average wind speed of the entire cold storage, the average temperature of the cross section, the maximum and minimum temperatures of the cold storage, the average wind speed of all cross sections and the average wind speed of the entire cold storage are automatically generated by the simulation software Ansys.

[0061] The three-dimensional model of the red blood cell cold storage under the combined working conditions of each level of each factor was established, and then the numerical model was established using computational fluid dynamics (CFD) simulation software. After the CFD calculation converged, the data was exported, and the arithmetic mean temperature, temperature range, temperature non-uniformity coefficient and velocity non-uniformity coefficient were calculated according to the formula with reference to the temperature cloud map of different sections in the red blood cell cold storage. The orthogonal simulation results are shown in Table 2.

[0062] Table 2 Orthogonal simulation results

[0063]

[0064] Step 9: Based on the orthogonal simulation results, perform range analysis on the thermal performance evaluation index under the orthogonal experimental conditions to obtain the orthogonal experimental calculation results. The orthogonal experimental calculation results are shown in Table 3. Kp represents the sum of the corresponding thermal performance evaluation indexes under all conditions at the pth level. m is the total number of levels corresponding to each factor. The range S is k p The difference between the maximum and minimum values ​​in the equation indicates the influence of each factor on the experimental results. The larger the S, the more significant the influence of the factor on the results. The importance is ranked according to the size of S, and the optimal level is k. p The factor level corresponding to the minimum value in . It can be seen from Table 3 that different thermal properties are different.

[0065] Table 3 Orthogonal experimental calculation results

[0066]

[0067] Step 10: Analyze the calculation results of the orthogonal experiment to obtain the optimal combination of each factor.

[0068] According to the storage characteristics of red blood cells, the k1, k2, k3 and k4 values ​​of each factor are compared to analyze the optimal combination of each factor. The priority of selecting the optimal level of each factor should first consider the average temperature, which must meet the storage conditions of red blood cells of 2 to 6 ° C, followed by the temperature non-uniformity coefficient and the temperature range. The smaller the temperature non-uniformity coefficient and the temperature range, the better to ensure the stability of the temperature field, and finally the speed non-uniformity coefficient. For example, for the selection of the level of factor A, first consider whether the average temperature meets the conditions of 2 to 6 ° C. Since only k1 does not meet the conditions from Table 3, the selection of A can be selected from the 2-4 levels. Secondly, consider the selection of a relatively small temperature non-uniformity coefficient and temperature range. As can be seen from Table 3, for the temperature non-uniformity coefficient, the value of k2 is 0.28, which is the smallest, and for the temperature range, the values ​​of k1-k3 are basically the same, so the level of A is selected as 2, and the selection of other factors is similar. At the same time, when the temperature non-uniformity coefficient and the temperature range cannot be determined, consider selecting a smaller speed non-uniformity coefficient.

[0069] According to the above thermal performance evaluation priorities, it is found that the optimal level combination of the six factors of the red blood cell cold storage is A2B3C1D4E3F4, corresponding to a specific surface area of ​​2.2m -1 , variable section height is 2 / 6H f (2 / 6 position in the height direction of the red blood cell cold storage), the air cooler position is 0 (the leftmost in the length direction of the red blood cell cold storage), and the internal heat source position is 4 / 6 Ln (4 / 6 position in the length direction of the red blood cell cold storage), the air supply temperature is 1°C and the air supply speed is 3.2m / s.

[0070] Based on the above design scheme, the thermal performance and energy consumption of the red blood cell cold storage before and after optimization were analyzed and compared.

[0071] The comparison results of thermal performance evaluation index and energy consumption of red blood cell cold storage before and after optimization are shown in Table 4. It can be seen that after optimization, the overall average temperature of the red blood cell cold storage decreased by 1.01℃, the temperature range decreased by 1.39℃, the temperature non-uniformity coefficient decreased by 57.14%, the speed non-uniformity coefficient decreased by 16.22%, and the energy consumption E decreased by 2.31%. This result shows that the optimized geometric structure, equipment layout and air supply conditions have achieved remarkable results in improving the temperature uniformity and air flow efficiency of the cold storage.

[0072] Table 4 Comparison of thermal performance evaluation indicators and energy consumption before and after optimization

[0073]

[0074] For those skilled in the art, the present invention is not limited to the details of the exemplary embodiments described above, but also includes the same or similar structures that can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, from all points of view, the embodiments should be regarded as exemplary and non-limiting, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claim involved.

[0075] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

[0076] The techniques, shapes, and structural parts not described in detail in the present invention are all well-known techniques.

Claims

1. A method for optimizing the design of a red blood cell cold storage, characterized in that: include: S1: Set the constraints of various factors of the red blood cell cold storage; the various factors include the specific surface area, variable section height, air cooler position, internal heat source position, air cooler air supply temperature and air supply speed of the red blood cell cold storage; S2: Based on the number of levels of each factor, obtain the factor level table and design orthogonal experimental conditions; S3: Calculate the thermal performance evaluation index under different working conditions and obtain the orthogonal simulation results under different working conditions; S4: Based on the orthogonal simulation results, the range analysis of the thermal performance evaluation index under the orthogonal experimental conditions is performed to obtain the orthogonal experimental calculation results; S5: Analyze the calculation results of the orthogonal experiment to obtain the optimal combination of various factors.

2. A red blood cell cold storage optimization design method as claimed in claim 1, characterized in that: In step S1, the constraints of various factors of the red blood cell cold storage are set, including: S11: Set the specific surface area S of the red blood cell cold storage A Based on the calculation formula of specific surface area, the external length L of the red blood cell cold storage is obtained. n and width W n Dimensions: Among them, H f is the height of the red blood cell cold storage, A is the surface area of ​​the red blood cell cold storage, and V is the volume of the red blood cell cold storage; S12: Set the variable cross-section height H1 of the red blood cell cold storage to meet i is an integer, and i∈0,3]; S13: Set the position L1 of the cold air blower in the red blood cell cold storage to meet j is an integer, and j∈[0,2]; S14: Set the position L2 of the internal heat source in the red blood cell cold storage to meet m is an integer, and m∈1,4]; S15: Setting the air supply temperature Tf of the red blood cell cold storage to satisfy Ta≤Tf≤Tb; wherein the air supply temperature refers to the air temperature at the air supply outlet of the air cooler; Ta and Tb are the set minimum air supply temperature and maximum air supply temperature, respectively; S16: Set the air supply speed Vf of the red blood cell cold storage to satisfy Va≤Vf≤Vb; wherein the air supply speed refers to the air speed at the air supply outlet of the air cooler; Va and Vb are the set minimum air supply speed and maximum air supply speed, respectively.

3. A red blood cell cold storage optimization design method as claimed in claim 1, characterized in that: In step S2, the number of levels of each factor refers to the sum of the number of selectable values ​​of each factor.

4. A method for optimizing the design of a red blood cell cold storage as claimed in claim 1, characterized in that: In step S3, the thermal performance evaluation index includes the average temperature Temperature extreme difference R, temperature non-uniformity coefficient σ t , velocity non-uniformity coefficient σ v , the calculation formula is as follows: Among them, x is the XY section cloud map number inside the red blood cell cold storage, n is the number of sections, Tx is the average temperature of the xth section, T max is the maximum temperature of the cold storage, T min is the minimum value of the cold storage temperature, v x is the average wind speed at the x-th section, It is the average wind speed of the cold storage as a whole.

5. A method for optimizing the design of a red blood cell cold storage as claimed in claim 1, characterized in that: In step S4, based on the orthogonal simulation results, the range analysis of the thermal performance evaluation index under the orthogonal experimental working conditions is performed to obtain the orthogonal experimental calculation results, where Kp represents the sum of the corresponding thermal performance evaluation indexes under all working conditions at the pth level. m is the total number of levels corresponding to each factor; the range S is k p The difference between the maximum and minimum values ​​in the experiment indicates the influence of each factor on the experimental results. The importance is ranked according to the size of S, and the optimal level is k. p The factor level corresponding to the minimum value in .

6. A method for optimizing the design of a red blood cell cold storage as claimed in claim 1, characterized in that: In step S5, the orthogonal experimental calculation results are analyzed to obtain the optimal combination conditions of each factor. The priority of selecting the optimal level of each factor should first consider the average temperature, which must meet the blood red blood cell storage condition of 2 to 6°C, followed by the temperature non-uniformity coefficient and the temperature extreme difference, and finally the speed non-uniformity coefficient.

7. A red blood cell cold storage, as a design basis for a red blood cell cold storage optimization design method as claimed in any one of claims 1 to 6, characterized in that: include: A warehouse body (1) and a door (2), a plurality of shelves (3) are arranged on both sides of the warehouse body, an adjustable air cooler is arranged inside the warehouse body along the length direction of the warehouse body, an air supply port (4) and an air return port (5) are arranged on both sides of the air cooler, a variable cross-section (6) with adjustable height is arranged on one side of the warehouse body, a lighting lamp (7) is arranged at the center of the top of the warehouse body, and an adjustable internal heat source is also arranged inside the warehouse body along the length direction of the warehouse body, the internal heat source comprises a sensor (8), a mechanical arm and a fully automatic device (9) and a monitor (10), the mechanical arm and the fully automatic device (9) are fixed within the measurement range of the sensor (8) matrix, and the sensor (8), the mechanical arm and the fully automatic device (9) and the monitor (10) are in the same side plane.

8. A readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method for optimizing the design of a red blood cell cold storage as described in any one of claims 1 to 6 is implemented.

9. A computer program product, characterized in that It includes a computer program / instruction, which, when executed by a processor, implements a red blood cell cold storage optimization design method as described in any one of claims 1 to 6.

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