Computer-based methods, systems, media, and products for determining the thermal matching parameters of cooling towers

Abstract

This application relates to a computer-based method, system, medium, and product for determining the thermal matching parameters of cooling towers. It relates to the technical field of cooling tower thermal calculation. This application corrects the enthalpy model of moist air by combining atmospheric pressure and altitude, and solves the enthalpy difference at the water-air interface point by point within the water-air ratio range. This constructs a selection condition curve characterizing the operating conditions, solving the problem of systematic deviations in the enthalpy difference at the water-air interface under non-standard air pressure and high altitude conditions in existing matching schemes. This improves the accuracy of solving cooling tower characteristic values ​​and allows the thermal calculation results to be directly converted into engineering parameters that can guide tower body processing and auxiliary equipment capacity configuration, forming an end-to-end parameter link from operating condition input to tower body manufacturing and auxiliary equipment ordering.

Description

Technical Field

[0001] This application relates to the technical field of cooling tower thermal calculation, and in particular to computer methods, systems, media and products for determining cooling tower thermal matching parameters. Background Technology

[0002] Thermodynamic matching of a cooling tower requires determining the tower's characteristic values ​​by solving the heat and mass transfer equations at the water-air interface under given parameters such as hot water temperature, cold water temperature, wet-bulb temperature, atmospheric pressure, and circulating water volume. Based on these values, a tower type and wind chamber configuration that meet the operating conditions are matched. This process involves various thermodynamic calculations, including those for humid air enthalpy, water enthalpy, and Chebikov integrals.

[0003] In related technologies, common computer-aided solutions typically use empirical formulas for the enthalpy of moist air under a single standard atmosphere to estimate the enthalpy difference at the water-air interface. Then, they numerically integrate the reciprocal of the enthalpy difference between the hot and cold water temperatures using trapezoidal or Simpson integrals to solve for the cooling tower characteristic value KaV / L. In the model matching stage, the obtained characteristic value is directly compared with the characteristic curves pre-stored in the cooling tower model characteristic database under standard operating conditions to determine whether the candidate model meets the current operating requirements. Some solutions further incorporate iterative search of the water-air ratio to improve the coverage of the solution.

[0004] However, the enthalpy model of moist air in the relevant technology is not corrected for the atmospheric pressure and altitude under actual working conditions, resulting in a systematic bias in the calculation of the enthalpy difference at the water-air interface. Furthermore, the output results of the existing solutions usually only point to the matching parameters of the cooling tower body, which is disconnected from the capacity configuration of peripheral equipment such as the supporting circulating water pump, fan frequency converter, etc. Designers need to calculate the parameters of peripheral equipment separately based on the selection results after the matching is completed. The design chain is not connected and is prone to parameter mismatch between the cooling tower body and the supporting equipment. This situation needs to be further improved. Summary of the Invention

[0005] This application provides a computer-based method, system, medium, and product for determining the thermal matching parameters of cooling towers. It generates a selection condition curve covering the complete water-to-air ratio range through pre-scanning, and calculates the water-to-air ratio of the selection condition by inversely using the ratio of the demand-side circulating water volume to the rated air volume of the candidate model, thus locating the selection condition point on the curve in one step. Simultaneously, it corrects the humid air enthalpy model by incorporating atmospheric pressure and altitude, improving the calculation accuracy of the water-to-air interface enthalpy difference under non-standard air pressure and high-altitude conditions. Furthermore, it uniformly outputs the geometric and dynamic parameters of the cooling tower body, as well as the capacity configuration parameters of the matching circulating water pump and fan frequency converter during the single matching process.

[0006] In a first aspect, this application provides a computer-based method for determining the thermal matching parameters of a cooling tower, the method comprising:

[0007] Receive the selection and design parameters of the cooling tower, which include at least the single-chamber circulating water volume, hot water temperature, cold water temperature, wet-bulb temperature, design atmospheric pressure and altitude;

[0008] The enthalpy model of moist air is corrected based on the pre-stored enthalpy models of moist air and water, combined with the atmospheric pressure and the altitude.

[0009] Based on the wet-bulb temperature, the modified wet air enthalpy model is invoked; based on the hot water temperature and the cold water temperature, the water enthalpy model is invoked; the water-air interface enthalpy difference of the cooling tower is calculated point by point within the preset water-air ratio range; and based on the hot water temperature and the cold water temperature, the characteristic values ​​of the cooling tower are solved to obtain the selection condition curve that characterizes the current selection condition requirements.

[0010] The selection condition curve is matched with the standard condition curves of each cooling tower model in the pre-stored cooling tower model characteristic database. During the matching process, the ratio of the single air chamber circulating water volume to the standard design air volume of the candidate model is used as the selection condition water-air ratio. The selection condition point is located on the selection condition curve using the selection condition water-air ratio to determine the candidate cooling tower model that meets the design parameters.

[0011] According to the preset report template, the design parameters, the selection condition curve, and the candidate cooling tower model are filled into the corresponding fields to generate a structured selection report and output it. The standard design air volume, single-chamber packing volume, and single-chamber fan shaft power of the candidate cooling tower model are output as geometric and dynamic parameters for the manufacturing of the cooling tower body, as well as the capacity configuration parameters of the matching fan frequency converter.

[0012] In the above embodiments, this application first receives design parameters including single-chamber circulating water volume, hot water temperature, cold water temperature, wet-bulb temperature, design atmospheric pressure, and altitude. It then corrects a pre-stored humid air enthalpy model using atmospheric pressure and altitude. Next, it uses the corrected enthalpy model with wet-bulb temperature to obtain the inlet enthalpy value, and uses the water enthalpy model with hot water and cold water temperatures to obtain the water-side saturation enthalpy value. Within a preset water-to-air ratio range, it solves for the water-to-air interface enthalpy difference point-by-point and obtains the cooling tower characteristic values ​​accordingly, constructing a selection condition curve characterizing the operating requirements. Finally, it uses the ratio of single-chamber circulating water volume to the standard design air volume of the candidate model as the selection condition water-to-air ratio, and positions the selected model on the selection condition curve. The model matching is completed at the working condition point, and the standard design air volume, single-chamber packing volume and single-chamber fan shaft power of the candidate model are output as geometric and dynamic parameters for tower body manufacturing, as well as capacity configuration parameters of the matching fan frequency converter. This not only solves the problem of systematic deviation in the calculation of water-air interface enthalpy difference under non-standard air pressure and high altitude conditions in the existing solution, and improves the solution accuracy of cooling tower characteristic values, but also realizes the quantitative evaluation of the processing capacity of candidate tower types under the current working conditions, and directly converts the thermal calculation results into engineering parameters that can guide tower body processing and auxiliary equipment capacity configuration, forming an end-to-end parameter link from working condition input to tower body manufacturing and supporting equipment ordering.

[0013] In some embodiments, the step of calculating the enthalpy difference at the water-air interface of the cooling tower point by point within a preset water-air ratio range, and solving for the characteristic values ​​of the cooling tower based on the hot water temperature and the cold water temperature, specifically includes:

[0014] For each water-to-gas ratio value within the water-to-gas ratio range, the first integration node, the second integration node, the third integration node, and the fourth integration node are selected between the hot water temperature and the cold water temperature according to the Chebikov four-point integration rule.

[0015] At the first integration node, the second integration node, the third integration node, and the fourth integration node, the water enthalpy model is called to obtain the water-side saturated enthalpy value, the corrected moist air enthalpy model is called and combined with the current water-to-air ratio to obtain the corresponding air enthalpy value, and the water-side saturated enthalpy value is subtracted from the air enthalpy value to obtain the first water-to-air interface enthalpy difference, the second water-to-air interface enthalpy difference, the third water-to-air interface enthalpy difference, and the fourth water-to-air interface enthalpy difference, respectively.

[0016] The cooling tower characteristic value under the current water-to-air ratio is calculated by the sum of the reciprocals of the first water-to-air interface enthalpy difference, the second water-to-air interface enthalpy difference, the third water-to-air interface enthalpy difference, and the fourth water-to-air interface enthalpy difference using the following formula:

[0017] ,in, These are the characteristic values ​​of the cooling tower. The specific heat capacity of water, The temperature of the hot water is... The temperature of the cold water, The enthalpy difference at the first water-vapor interface. This is the enthalpy difference at the second water-vapor interface. The enthalpy difference at the third water-vapor interface. The fourth water-gas interface enthalpy difference.

[0018] In the above embodiments, this application selects four integration nodes between hot water temperature and cold water temperature for each water-to-air ratio value within the water-to-air ratio range, according to the Chebikov four-point integration rule. At each node, the water enthalpy model is called to obtain the water-side saturated enthalpy value, the modified humid air enthalpy model is called and combined with the current water-to-air ratio value to obtain the corresponding air enthalpy value, and then the water-side saturated enthalpy value is subtracted from the air enthalpy value to obtain the enthalpy difference of the four water-to-air interfaces. Finally, the cooling tower characteristic value is directly obtained by summing the reciprocals of the four enthalpy differences according to the prescribed analytical formula. This not only solves the problem of excessive number of nodes and difficulty in balancing computational cost and accuracy in traditional numerical integration schemes under wide water-to-air ratio scanning, but also ensures that the number of enthalpy value calls for each water-to-air ratio value is strictly converged to a known constant by the fixed four-node structure, thereby improving the computational efficiency and time predictability of the overall construction process of the selection condition curve.

[0019] In some embodiments, the air enthalpy values ​​at the first integration node, the second integration node, the third integration node, and the fourth integration node are obtained by the following formula:

[0020] ,in, Let i be the air enthalpy value at the i-th integration node, where i takes the values ​​1, 2, 3, and 4 respectively, corresponding to the first integration node, the second integration node, the third integration node, and the fourth integration node. The enthalpy value of the intake air is obtained by calling the corrected wet air enthalpy model based on the wet-bulb temperature; This is the specific heat capacity of water; The temperature of the hot water; The temperature of the cold water; This is the current water-to-air ratio value; Let be the position coefficient of the i-th integration node. , , , The values ​​were 0.1, 0.4, 0.6, and 0.9 in sequence.

[0021] In some embodiments, matching the selected operating condition curve with the characteristic curves of each cooling tower model in a pre-stored cooling tower model characteristic database specifically includes:

[0022] The selection condition point is located on the selection condition curve using the water-air ratio of the selection condition, and the water-air ratio and cooling tower characteristic value of the selection condition point are obtained.

[0023] A straight line with a slope of n is drawn through the selected operating point. The intersection of the straight line with the standard operating point is taken as the standard operating point. The water-air ratio of the standard operating point is obtained. Here, n is read from a preset type-slope database according to the type of packing. The type-slope database stores at least the slope values ​​corresponding to three types of packing: film packing, drip packing, and drip-film composite packing.

[0024] Calculate the equivalent water treatment capacity of the candidate model under the selected operating conditions using the following formula:

[0025] ,in, This represents the equivalent water treatment capacity of the candidate model under the selected operating conditions. The single-chamber water processing capacity of the candidate model under standard operating conditions; The water-to-air ratio at the selected operating point; The water-to-air ratio at the standard operating condition mapping point;

[0026] When the equivalent water treatment volume is greater than or equal to the single air chamber circulating water volume, the candidate model is determined as the candidate cooling tower model.

[0027] In the above embodiments, existing solutions often use overall curve shifting or point-by-point interpolation to convert between the selection condition and the standard condition of the tower sample test when there are differences between the two. For example, when the wet-bulb temperature or temperature difference of a certain selection condition deviates from the calibration conditions of the tower sample, simple curve shifting will ignore the difference in the sensitivity of the packing structure to the water-to-air ratio, making it difficult to give the actual processing capacity of the candidate model under the selection condition analytically. This application locates the selection condition point on the selection condition curve based on the water-to-air ratio of the selection condition, draws a packing characteristic straight line with a slope of n through this point, and takes the intersection of this line and the standard condition curve as the standard condition mapping point, where the slope n varies according to the packing type. The system reads from a pre-stored type-slope database, which stores slope values ​​for at least three types of packing materials: membrane, drip, and drip-membrane composite. The equivalent treatment capacity of the candidate model under the selected operating conditions is obtained by multiplying the single-chamber water treatment capacity of the candidate model under standard operating conditions by the ratio of the water-air ratio at the two mapping points. The selection criterion is that the equivalent treatment capacity is not less than the single-chamber circulating water volume. This not only solves the problem of distorted conversion of candidate model operating conditions due to the lack of curve mapping channels in existing solutions, but also allows differences in packing structure to be directly incorporated into the mapping calculation as slope parameters, improving the specificity and resolution of the equivalent treatment capacity solution for different packing types.

[0028] In some embodiments, the method further includes:

[0029] Calculate the single-chamber performance margin of the candidate cooling tower model under the selected operating conditions using the following formula:

[0030] ,in, This represents the single-chamber performance margin of the candidate cooling tower model under the selected operating conditions. The equivalent water treatment capacity of the candidate cooling tower model under the selected operating conditions; The circulating water volume of the single air chamber;

[0031] The single-chamber performance margin is written as a field in the selection report.

[0032] In the above embodiments, existing solutions typically only provide a binary judgment result of "satisfied" or "not satisfied" after determining the candidate cooling tower model. For example, when a project faces redundancy configuration assessment or subsequent load fluctuation assessment, the binary result is difficult to reflect the degree of surplus of the candidate model relative to the design water volume. This application directly calculates the single-chamber performance margin by using the ratio of the equivalent treatment water volume of the candidate cooling tower model to the circulating water volume of a single air chamber under the selection conditions, and writes this margin as a field into the selection report. This not only solves the problem of insufficient information in the binary judgment result, but also provides a directly readable engineering basis for subsequent redundancy configuration, load expansion, and horizontal comparison of multiple models in the form of quantitative indicators.

[0033] In some embodiments, the design parameters are N sets, where N is an integer greater than or equal to 2. The i-th set of design parameters in the N sets corresponds to the i-th selection condition curve, and i takes the values ​​1, 2, ..., N in sequence.

[0034] For the candidate models in the cooling tower model characteristic database, the equivalent water treatment capacity of the candidate model under the i-th set of design parameters is obtained on the i-th selection condition curve. The operating margin coefficient is calculated using the following formula. , ,in, The single-chamber circulating water volume in the i-th set of design parameters;

[0035] The operating condition margin coefficient to The design parameter corresponding to the smallest median value is identified as the control condition of the candidate model, and the control condition is used as the control condition. The candidate model is determined to simultaneously meet the N sets of design parameters;

[0036] The identifier of the control condition and the condition margin coefficient under the control condition are written as fields into the selection report.

[0037] In the above embodiments, since multiple sets of design parameters often coexist in actual engineering projects, such as summer operating conditions, transitional season operating conditions, and winter verification operating conditions, for example, when a circulating water system is processed by selecting each set of operating conditions independently and then manually taking the intersection, it is difficult to identify the truly decisive operating condition within a unified calculation process. This application expands the design parameters to N sets, generates corresponding selection operating condition curves for each set, calculates the equivalent treatment water volume for each candidate model on each selection operating condition curve, and defines the operating condition margin coefficient by the ratio of the equivalent treatment water volume to the single-chamber circulating water volume in the set of design parameters. The design parameter corresponding to the smallest value among the N margin coefficients is identified as the control operating condition of the candidate model, and the margin coefficient under the control operating condition is not less than 1 as a unified judgment condition for the candidate model to simultaneously meet all N sets of design parameters. This not only solves the problem of unclear identification of control operating conditions caused by independent selection and manual intersection under multiple sets of design operating conditions, but also improves the analytical and traceability of the joint judgment results of multiple operating conditions by using the minimum margin coefficient as a unified criterion.

[0038] In some embodiments, when all candidate models in the cooling tower model characteristic database do not meet the determination criteria under a single-chamber configuration, the single-chamber circulating water volume in the i-th group of design parameters is replaced with... M increases sequentially from 2, and the calculation of the operating margin coefficient and the verification of the judgment conditions are repeated. The value of M that first appears in a candidate model that meets the judgment conditions is determined as the target number of air chambers. The corresponding candidate model was determined to be the multi-chamber target model;

[0039] The target number of air chambers The target multi-chamber model is included in the selection report as the manufacturing and ordering parameters for the target multi-chamber model.

[0040] In the above embodiments, since there may not be any candidate models in the database that can simultaneously meet all operating conditions with a single-chamber configuration under scenarios with multiple sets of stringent design parameters, it is impossible to automatically provide feasible alternatives based on multi-chamber splitting. When all candidate models fail to meet the judgment conditions under the single-chamber configuration, this application replaces the single-chamber circulating water volume in each set of design parameters with the original value divided by M, so that M increases sequentially from 2. Under each value of M, the calculation of the operating condition margin coefficient and the verification of the judgment conditions are repeated, and the value of M in which the first candidate model meets the judgment conditions is determined as the target number of chambers. and the corresponding candidate models along with The manufacturing and ordering parameters of the multi-chamber target model are included in the selection report. This not only solves the problem of interruption in the matching process when the single-chamber configuration is not feasible, but also incorporates the multi-chamber into the same calculation process by incrementing the number of chambers in integer increments, so that the manufacturing and ordering parameters can be updated synchronously with the changes in the chamber configuration.

[0041] In a second aspect, embodiments of this application provide a computer system for determining the thermal matching parameters of a cooling tower, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, and the one or more processors calling the computer instructions to cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0042] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a system, cause the system to perform the method described in the first aspect and any possible implementation thereof.

[0043] Fourthly, embodiments of this application provide a computer program product that, when run on a system, causes the system to execute the method described in any possible implementation of the first aspect.

[0044] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0045] 1. By combining atmospheric pressure and altitude to correct the enthalpy model of humid air, and solving the enthalpy difference of the water-air interface point by point within the water-air ratio range, a selection condition curve characterizing the working conditions is constructed. This solves the problem of systematic deviation of the water-air interface enthalpy difference in the existing matching scheme under non-standard air pressure and high altitude conditions, improves the solution accuracy of cooling tower characteristic values, and directly converts the thermodynamic calculation results into engineering parameters that can guide the tower body processing and auxiliary equipment capacity configuration, forming an end-to-end parameter link from working condition input to main body manufacturing and supporting equipment ordering;

[0046] 2. By selecting four integration nodes according to Chebikov's four-point integration rule for each water-to-air ratio to solve the cooling tower characteristic value, and obtaining the air enthalpy value at each node with the inlet air enthalpy value as the starting point and according to the preset position coefficient, it not only solves the problem of too many nodes and difficulty in balancing computational cost and accuracy in traditional trapezoidal or Simpson integrals under wide water-to-air ratio scanning, but also makes the number of calls to the enthalpy model strictly converge to a known constant, improving the computational efficiency and time predictability of the overall construction process of the selection condition curve;

[0047] 3. By drawing a straight line of packing characteristics with a slope that varies with the packing type through the selected operating point, and intersecting it with the standard operating condition curve, a standard operating condition mapping point is obtained. Then, the equivalent water treatment capacity of the candidate model under the selected operating condition is analytically obtained by the ratio of the water-air ratio of the two mapping points. The minimum margin coefficient is used to identify the control condition, and the integer number of air chambers is used to upgrade the level to handle the infeasibility of a single air chamber. This solves the problems of curve conversion distortion and unclear joint judgment of multiple operating conditions in the existing scheme, and improves the resolution of the matching results and the scope of engineering application under different packing types and multiple operating conditions. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating a computer-based method for determining the thermal matching parameters of a cooling tower in an embodiment of this application.

[0049] Figure 2 This is a schematic diagram of a physical device structure of a computer system for determining the thermal matching parameters of a cooling tower, as described in this application. Detailed Implementation

[0050] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0051] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0052] To facilitate understanding, the application scenarios of the embodiments of this application are described below.

[0053] In the field of cooling tower thermal matching and engineering selection, the design water volume, temperature parameters and meteorological parameters of the circulating cooling water system jointly determine the geometric dimensions of the tower, the packing volume and the fan shaft power configuration. The matching calculation results will directly affect the subsequent tower manufacturing and auxiliary equipment ordering.

[0054] In related technologies, the enthalpy formula for moist air is mostly established based on the standard atmospheric pressure at sea level, without correcting for pressure and altitude deviations under actual operating conditions. This leads to a systematic underestimation or overestimation of the enthalpy difference at the water-air interface. At the same time, in the model matching process, the conversion is mostly done by overall curve translation or simple point-by-point interpolation, lacking an analytical mapping channel between the standard operating condition curve and the selected operating condition curve with the water-air ratio as the index. This makes it difficult to reflect the true processing capability of the candidate tower type under the current operating conditions. In addition, for situations where multiple sets of design operating conditions coexist or where a single wind chamber configuration is not feasible, existing solutions generally lack a judgment and decomposition mechanism that can be incorporated into a unified calculation process.

[0055] This application is mainly applied to engineering scenarios requiring the matching of circulating cooling towers, such as thermal power generation, petrochemicals, and large-scale centralized air conditioning cold sources. These scenarios involve numerous selection and design parameter groups, a wide range of operating conditions, and high precision requirements for the capacity configuration of the tower body, supporting circulating water pumps, and fan frequency converters. In these applications, the matching results not only need to provide feasible tower type names but also need to directly output geometric and dynamic parameters that can guide tower body processing and auxiliary equipment ordering. To solve the above technical problems, this application provides a computer-based method for determining the thermal matching parameters of cooling towers. An embodiment is described below, combined with… Figure 1 The present application describes a computer-based method for determining the thermal matching parameters of a cooling tower in its embodiments:

[0056] Please see Figure 1 This application provides a computer-based method for determining the thermal matching parameters of a cooling tower, comprising the following steps:

[0057] S101. Receive the selection and design parameters of the cooling tower. The design parameters shall include at least the single-chamber circulating water volume, hot water temperature, cold water temperature, wet-bulb temperature, design atmospheric pressure, and altitude.

[0058] Among them, the circulating water volume of a single air chamber refers to the circulating water flow rate that a single air chamber of the cooling tower needs to handle under the design conditions; the hot water temperature refers to the temperature of the circulating water returning from the user side to the top of the cooling tower for cooling; the cold water temperature refers to the temperature of the circulating water flowing out of the collection pool after being cooled by the cooling tower; the wet bulb temperature refers to the wet bulb temperature under the local design meteorological conditions; the design atmospheric pressure refers to the local annual average or the atmospheric pressure value selected in the design; and the altitude refers to the height of the cooling tower installation site relative to sea level.

[0059] Specifically, the system first provides a parameter input entry point through a human-computer interaction interface or engineering data interface; then it receives the above six required parameters and optional parameters in sequence; next, it performs a validity check on the parameter value range and unit; finally, it writes the parameters that pass the check into the parameter cache of the current session, waiting for subsequent steps to call.

[0060] S102. Based on the pre-stored enthalpy model of moist air and water, and combined with atmospheric pressure and altitude, the enthalpy model of moist air is corrected.

[0061] Among them, the moist air enthalpy model refers to the analytical relationship that takes temperature and atmospheric pressure as input and outputs the moist air enthalpy value corresponding to a unit mass of dry air. The water enthalpy model refers to the analytical relationship that takes water temperature as input and outputs the water-side saturated enthalpy value. Enthalpy model correction refers to replacing the saturated water vapor partial pressure and moisture content terms related to air pressure in the moist air enthalpy model according to the atmospheric pressure and altitude under the current operating conditions, so that the output enthalpy value corresponds to the actual air pressure conditions under the current operating conditions.

[0062] Specifically, the system first retrieves the analytical expressions of the moist air enthalpy model and the water enthalpy model based on the standard atmospheric pressure at sea level from the model library; then, it substitutes the design atmospheric pressure and the local atmospheric pressure converted from altitude into the pressure-related terms in the moist air enthalpy model to obtain the correction coefficient under the current operating conditions; next, it replaces the original standard atmospheric pressure-related terms in the moist air enthalpy model with the correction coefficient to obtain the corrected moist air enthalpy model; finally, it loads the corrected moist air enthalpy model and the water enthalpy model together into the enthalpy calculation engine, waiting for subsequent steps to call them point by point.

[0063] It should be noted that the enthalpy model of moist air in this embodiment is based on a unit mass of dry air, denoted as . ,in, The temperature of the moist air (unit: °C) The local atmospheric pressure (unit: kPa); the water enthalpy model is denoted as ,in, This is the saturated enthalpy value on the water side (unit: kJ / kg). When the user inputs the design atmospheric pressure... At an altitude of 1000m, the system follows... The input value is used directly, or, if the input value is missing, P is calculated backwards from the altitude-pressure conversion relationship. This P value is then substituted into the calculation steps for saturated water vapor partial pressure and moisture content in the humid air enthalpy model, switching the enthalpy output from the original standard pressure reference to the current operating condition reference. The input to the corrected humid air enthalpy model is the humid air temperature, and the output is the corrected humid air enthalpy value, which serves as the air-side source of the enthalpy difference at the water-air interface in S103.

[0064] In one embodiment, when the design atmospheric pressure value is missing or significantly inconsistent with altitude, the system will deduce the local atmospheric pressure from altitude using a preset pressure-altitude relationship. That is, during the parameter verification phase, the system will determine whether the design atmospheric pressure field is missing or whether the deviation from the theoretical pressure corresponding to altitude exceeds a preset threshold. If the determination result is yes, the local atmospheric pressure will be deduced from altitude using the following formula, and the deduced value will replace the original value and be substituted into the enthalpy model of moist air. Where P is the local atmospheric pressure (unit: kPa). The standard atmospheric pressure at sea level is 101.325 kPa, and H is the altitude of the cooling tower installation site (in meters).

[0065] Among them, the pressure-height relationship formula refers to the analytical conversion formula with altitude as input and local atmospheric pressure as output, and the consistency threshold refers to the preset upper limit of deviation for judging whether the input value of the design atmospheric pressure is consistent with the theoretical air pressure corresponding to the altitude.

[0066] Specifically, the system first determines whether the design atmospheric pressure field is missing. If it is missing, it directly calculates P from the altitude using the pressure-height relationship described above. Then, if the design atmospheric pressure field is not missing, it calculates the theoretical atmospheric pressure corresponding to the altitude using the pressure-height relationship described above. And obtain the entered value and The absolute deviation is then compared with a preset consistency threshold (e.g., 2 kPa). If the deviation does not exceed the threshold, the entered value is used; if the deviation exceeds the threshold, the entered value is used. Replace the entered value and send a pressure-altitude consistency alarm to the user; finally, substitute the final P value into the saturated water vapor partial pressure term and moisture content term of the humid air enthalpy model to complete the enthalpy model correction.

[0067] S103. Based on the wet-bulb temperature, call the corrected wet air enthalpy model; based on the hot water temperature and cold water temperature, call the water enthalpy model; calculate the water-air interface enthalpy difference of the cooling tower point by point within the preset water-air ratio range; and solve the cooling tower characteristic values ​​based on the hot water temperature and cold water temperature to obtain the selection condition curve that characterizes the current selection condition requirements.

[0068] The water-to-air ratio refers to the ratio of the mass flow rate of circulating water to the mass flow rate of dry air within the cooling tower, denoted as . The enthalpy difference at the water-air interface refers to the difference between the saturated enthalpy of the water side and the enthalpy of the air at the corresponding location at a specified water temperature; the characteristic value of a cooling tower refers to a dimensionless quantity characterizing the cooling capacity of the tower, denoted as . ,in, The mass transfer coefficient is . The contact area per unit packing volume. For the packing volume, The circulating water volume is denoted as 'circulating water volume'. The selection condition curve refers to the curve showing how the required characteristic values ​​of the tower body change with the water-air ratio under the current selection design parameters.

[0069] Specifically, the system first obtains several discrete points of water-to-air ratio within a preset step size range (e.g., 0.5 to 2.0); then, for each discrete point of water-to-air ratio, it solves the characteristic value of the cooling tower according to Chebikov's four-point integration rule; next, it uses the wet-bulb temperature, hot water temperature, and cold water temperature in the selection design parameters as inputs to construct a selection condition curve that characterizes the current selection condition requirements, and writes the curve into the condition curve cache.

[0070] It should be noted that the enthalpy difference at the water-vapor interface is calculated according to... We obtain, where, From the water enthalpy model, The enthalpy values ​​are derived from the modified humid air enthalpy model and recursively derived from the inlet air enthalpy through energy balance. The cooling tower characteristic values ​​are solved by using the hot water temperature and cold water temperature as the upper and lower limits of integration, and the reciprocal of the enthalpy difference as the integrand, obtained through numerical integration. On the selected operating condition curve, the horizontal axis represents the water-to-air ratio. The vertical axis represents the characteristic values ​​at this water-to-air ratio. This curve represents the mass transfer capacity of the packing required for the tower to complete the cooling task under current operating conditions.

[0071] In one embodiment, the enthalpy difference at the water-air interface of the cooling tower is calculated point by point within a preset water-air ratio range, and the characteristic values ​​of the cooling tower are solved based on the hot water temperature and the cold water temperature. Specifically, this includes: for each water-air ratio value within the water-air ratio range, selecting a first integration node, a second integration node, a third integration node, and a fourth integration node between the hot water temperature and the cold water temperature according to Chebikov's four-point integration rule; and adjusting the values ​​at the first integration node, the second integration node, the third integration node, and the fourth integration node respectively. The water-side saturation enthalpy is obtained using the water enthalpy model. The corrected humid air enthalpy model is then called, and the corresponding air enthalpy is obtained by combining it with the current water-to-air ratio. The air enthalpy is subtracted from the water-side saturation enthalpy to obtain the first, second, third, and fourth water-to-air interface enthalpy differences. The cooling tower characteristic values ​​under the current water-to-air ratio are then calculated using a preset formula by summing the reciprocals of the first, second, third, and fourth water-to-air interface enthalpy differences.

[0072] Among them, Chebikov's four-point integration rule refers to a numerical integration method that determines four integration nodes between the upper and lower limits of integration using position coefficients of 0.1, 0.4, 0.6, and 0.9, and then multiplies the approximate value of the integral by taking the weighted average of the integrands at the four nodes and multiplying it by the length of the integration interval. The water-side saturated enthalpy value refers to the saturated enthalpy value corresponding to the water temperature at the node obtained by calling the water enthalpy model. The air enthalpy value refers to the saturated enthalpy value corresponding to the node position obtained by calling the modified moist air enthalpy model and combining it with the current water-to-air ratio through energy balance recursion.

[0073] Specifically, the system first uses position coefficients. , , , exist to The water temperature at four integration nodes is determined within the interval; then, at each node, the water enthalpy model is called to obtain the water-side saturation enthalpy value. The corresponding air enthalpy value is obtained by taking the current water-to-air ratio and the location coefficient. Next, subtract the corresponding air enthalpy from the water-side saturation enthalpy at each node to obtain the results. , , , Finally, the cooling tower characteristic values ​​under the current water-to-air ratio are obtained using the following formula: .in, These are the characteristic values ​​of the cooling tower (dimensionless). Specific heat capacity of water (unit: kJ / (kg·℃)) The temperature of the hot water is expressed in °C. The temperature is the cold water temperature (unit: °C). , , , These are the enthalpy differences at the first, second, third, and fourth water-air interfaces (unit: kJ / kg).

[0074] It should be noted that this numerical integration rule ensures that the number of enthalpy value calls for each water-to-air ratio is strictly converged to four calls to the water enthalpy model and one humid air enthalpy recursion. This results in the solution cost of the entire selection condition curve increasing linearly with the number of discrete points for the water-to-air ratio, instead of increasing quadratically with the number of integration nodes; position coefficient The values ​​0.1, 0.4, 0.6, and 0.9 are engineering simplifications of the Chebikov integral at the four integration nodes, thus achieving an accuracy comparable to that of higher-order Simpson integrals while maintaining four enthalpy values.

[0075] Furthermore, the air enthalpy values ​​at the first integration node, the second integration node, the third integration node, and the fourth integration node are calculated according to the preset recursive formula. The recursive formula takes the intake air enthalpy value obtained by calling the corrected wet air enthalpy model based on the wet-bulb temperature as the starting point of the recursion, and uses the current water-to-air ratio, hot water temperature, cold water temperature, and the position coefficient of each integration node as the recursive parameters.

[0076] The starting point of the recursion refers to the enthalpy value of the intake air obtained by calling the corrected wet-bulb temperature enthalpy model. The position coefficient refers to the preset dimensionless coefficient corresponding to the position of each integration node.

[0077] Specifically, the system first uses the wet-bulb temperature to call the corrected enthalpy model of moist air to obtain the enthalpy value of the intake air. As the starting point for recursion; then, based on the current water-to-air ratio and the specific heat capacity of water, calculate the enthalpy increment corresponding to each unit of position coefficient; then, based on the position coefficient... , , , The air enthalpy at each integration node is calculated. Finally, the four air enthalpy values ​​are returned and subtracted from the corresponding water-side saturation enthalpy to obtain the four water-air interface enthalpy differences. The recursive formula used is as follows: ,in, Let be the air enthalpy value at node i (unit: kJ / kg), where i takes the values ​​1, 2, 3, and 4 respectively. The enthalpy of the incoming air (unit: kJ / kg). Specific heat capacity of water (unit: kJ / (kg·℃)) The temperature of the hot water is expressed in °C. The temperature is the cold water temperature (unit: °C). This is the current water-to-air ratio value (dimensionless). Let be the position coefficient of the i-th integration node.

[0078] It should be noted that this recursive relationship originates from the gas-liquid two-phase energy balance of the cooling tower. Its relative position from the temperature of the cold water By directly integrating, the above linear recursive formula can be obtained; therefore, regardless of the value of the position coefficient, the air enthalpy value at each integration node can be analytically obtained from the air intake enthalpy value and the position coefficient, without having to repeatedly call the modified humid air enthalpy model, thus reducing the number of times the humid air enthalpy model is called at each water-to-air ratio discrete point from four to one.

[0079] S104. Match the selection condition curve with the characteristic curves of each cooling tower model in the pre-stored cooling tower model characteristic database. During the matching process, the ratio of the circulating water volume of a single air chamber to the standard design air volume of the candidate model is used as the water-air ratio of the selection condition. The selection condition point is located on the selection condition curve using the water-air ratio of the selection condition to determine the candidate cooling tower model that meets the design parameters.

[0080] Among them, the cooling tower model characteristic database refers to a database that pre-stores the characteristic curves, standard design air volume, single air chamber water handling volume, single air chamber packing volume, and single air chamber fan shaft power of each cooling tower model under calibration conditions. The water-air ratio of the selection condition refers to the water-air ratio value obtained by dividing the single air chamber circulating water volume by the standard design air volume of the candidate model under the selection condition. The selection condition point refers to the characteristic value point of the water-air ratio of the selection condition on the selection condition curve.

[0081] Specifically, the system first reads candidate models and their standard design air volumes from the cooling tower model characteristic database; then, it divides the circulating water volume of a single air chamber by the standard design air volume of the candidate model to obtain the water-air ratio under the selection condition; next, it locates the selection condition point on the selection condition curve using this water-air ratio to obtain the characteristic value requirement under the selection condition, and establishes an analytical mapping between this selection condition point and the standard condition curve of the candidate model; finally, it determines whether the candidate model meets the selection design parameters based on the analytical mapping result, and writes the candidate models that meet the conditions into the candidate model list.

[0082] It should be noted that the determination of whether a candidate model meets the requirements is no longer based on whether a single point falls above the curve. Instead, an analytical mapping is established between the selected operating point and the standard operating curve to obtain the equivalent water treatment capacity of the candidate model under the selected operating condition. The comparison between the equivalent water treatment capacity and the circulating water volume of a single air chamber is used as the final determination criterion. The input to the cooling tower model characteristic database is the model number, and the output is the standard design air volume, single air chamber water treatment capacity, single air chamber packing volume, and single air chamber fan shaft power of that model. Each parameter and the matching module are intrinsically linked through a unified field index.

[0083] S105. According to the preset report template, fill in the design parameters, selection condition curves and candidate cooling tower models into the corresponding fields, generate a structured selection report and output it, and output the standard design air volume, single air chamber packing volume and single air chamber fan shaft power of the candidate cooling tower models as geometric and dynamic parameters for the manufacturing of the cooling tower body, as well as the capacity configuration parameters of the matching fan frequency converter.

[0084] Among them, the report template refers to a structured document template with predefined field names, field order, and field format, while the geometric and dynamic parameters refer to dimensional and power parameters used to guide tower body processing and main body manufacturing.

[0085] Specifically, the system first retrieves a preset report template; then it fills in the design parameters into the parameter field, renders the selection condition curve as a chart and fills it into the curve field, and fills in the candidate cooling tower model into the model field; next, it reads the standard design air volume, single-chamber packing volume, and single-chamber fan shaft power of the candidate cooling tower model, and fills them into the geometric and dynamic parameter fields of the tower body manufacturing and the capacity configuration parameter field of the matching fan frequency converter, respectively; finally, it exports the selection report and outputs it synchronously to the downstream manufacturing and procurement system through the engineering data interface.

[0086] In the above embodiments, by employing techniques such as correcting the enthalpy model of moist air based on atmospheric pressure and altitude, using Chebikov's four-point integral rule and recursive air enthalpy calculation, obtaining the mapping point on the standard operating condition curve by plotting the packing characteristic line through the selected operating point to solve for the equivalent water treatment capacity and the analytical output of the single-chamber performance margin, this approach not only solves the problem of systematic deviations in the calculation of water-air interface enthalpy difference under non-standard air pressure and high altitude conditions in existing solutions, thus improving the accuracy of solving cooling tower characteristic values, but also enables a quantifiable evaluation of the processing capacity of candidate tower types under current operating conditions through a hyperbolic matching channel. Furthermore, it allows the thermal calculation results to be directly converted into engineering parameters that can guide tower body processing and auxiliary equipment capacity configuration, forming an end-to-end parameter link from operating condition input to main body manufacturing and auxiliary equipment ordering.

[0087] However, since simple curve translation ignores the differences in the sensitivity of the packing structure to the water-air ratio, it is difficult to give the actual processing capacity of the candidate model under the selection conditions in an analytical manner.

[0088] To further improve the accuracy of model selection, in some embodiments, the system performs analytical mapping between two curves by drawing a straight line of packing characteristics through the selection condition point and obtaining a mapping point on the standard condition curve. That is, the system locates the selection condition point on the selection condition curve based on the water-air ratio of the selection condition, and obtains the water-air ratio and cooling tower characteristic value of the selection condition point; draws a straight line of packing characteristics with a slope of n through the selection condition point, and takes the intersection of the packing characteristic line and the standard condition curve as the standard condition mapping point, and obtains the water-air ratio of the standard condition mapping point. Here, n is read from a preset type-slope database according to the packing type. The type-slope database stores at least the slope values ​​corresponding to three types of packing: film packing, drip packing, and drip-film composite packing; calculates the equivalent water volume of the candidate model under the selection condition according to the following formula; when the equivalent water volume is greater than or equal to the single-chamber circulating water volume, the candidate model is determined as the candidate cooling tower model.

[0089] Among them, the packing characteristic line refers to the approximate straight line that characterizes the trend of characteristic value change of the same packing structure under different water-air ratios in the operating condition curve coordinate system; the type-slope database refers to the pre-stored data structure with the packing type as the index and the slope of the packing characteristic line as the value; the standard operating condition mapping point refers to the intersection point obtained by the packing characteristic line and the standard operating condition curve of the candidate model; and the equivalent treatment capacity refers to the equivalent circulating water volume that the candidate model can treat under the selected operating condition.

[0090] Specifically, the system first locates the selection condition point on the selection condition curve based on the water-air ratio, and obtains the water-air ratio at that point. The characteristic value is then determined; next, the corresponding slope n is read from the type-slope database according to the packing type of the candidate model. A straight line with slope n is plotted through the selected operating point. Slope n is the slope of the straight line in the operating curve coordinate system with L / G as the horizontal axis and KaV / L as the vertical axis. Then, the intersection point of this packing characteristic line and the standard operating curve of the candidate model is obtained, i.e., the standard operating condition mapping point, and its water-air ratio is recorded as . Finally, the equivalent water treatment capacity of the candidate model under the selection conditions is calculated using the following formula, and whether the equivalent water treatment capacity is greater than or equal to the circulating water volume of a single air chamber is used as the criterion for whether the candidate model is selected: ,in, The equivalent water treatment capacity of the candidate model under the selected operating conditions (unit: m³ / h). The single-chamber water treatment capacity of the candidate model under standard operating conditions (unit: m³ / h). The water-air ratio (dimensionless) is the selected operating condition point. The water-air ratio (dimensionless) is the mapping point for standard operating conditions.

[0091] It should be noted that the slope values ​​pre-stored in the type-slope database are obtained based on regression analysis of test data from packing manufacturers. Thin-film packings, due to their thinner water film and more stable mass transfer area, have smaller absolute slope values; droplet packings, because their water droplet contact area varies significantly with the water-to-air ratio, have larger absolute slope values; and the slope values ​​of droplet-film composite packings fall between the two. The physical meaning of this analytical mapping is that the packing characteristic line represents the approximate trend of the packing's characteristic values ​​under different water-to-air ratios. Plotting this line through the selection operating point reconstructs the capability trajectory of the candidate packing model under the selection operating condition within the operating condition curve coordinate system. The intersection point of this line with the standard operating condition curve... This characterizes the equivalent water-air ratio required for a candidate model to achieve the desired characteristic value under the selected operating conditions. This is equivalent to adjusting the water treatment capacity of the candidate model under standard operating conditions according to... The actual treatable water volume is obtained after analytical conversion.

[0092] Furthermore, in some embodiments, the type-slope database no longer uses the packing type as a single index, but instead uses the packing type and the water-air ratio segment as dual indexes to store and retrieve the slope n. That is, before the system draws the packing characteristic straight line at the selection point, it first calculates the slope n based on the water-air ratio at the selection point. Locate the water-air ratio segment to which it belongs, and then use the packing type and the segment as dual indexes to read the corresponding slope from the type-slope database. .

[0093] Among them, water-air ratio segmentation refers to dividing the water-air ratio range (e.g., 0.5 to 2.0) into several sub-intervals according to preset breakpoints. The segmentation breakpoints must include at least two values: 0.8 and 1.2, dividing the water-air ratio range into three segments: low water-air ratio segment (L / G < 0.8), medium water-air ratio segment (0.8 ≤ L / G ≤ 1.2), and high water-air ratio segment (L / G > 1.2). Dual indexing refers to using the packing type index i and the water-air ratio segmentation index j to jointly determine the slope value. The data reading method.

[0094] Specifically, the system first selects the water-to-air ratio under the operating conditions. As input, determine the water-air ratio segment to which it belongs, and obtain the segment index j; then obtain the packing type index i according to the packing type of the candidate model, and read the corresponding slope from the type-slope database with (i, j) as the double index. Then, draw a slope with the selected operating point as the slope. The filler characteristic straight line is used to find the intersection point between this straight line and the standard operating condition curve of the candidate model, which is then used as the standard operating condition mapping point. Finally press Calculate the equivalent water treatment capacity of the candidate model under the selected operating conditions.

[0095] It should be noted that the characteristic values ​​of the same packing material do not exhibit a strictly linear trend across different water-to-air ratio ranges. In the low water-to-air ratio range, the water film on the packing surface is thinner, and mass transfer is dominated by gas film resistance, resulting in a relatively small absolute value of the slope. In the high water-to-air ratio range, the water film on the packing surface is thicker, and mass transfer is dominated by liquid film resistance, resulting in a relatively large absolute value of the slope. The medium water-to-air ratio range is a transitional zone between these two resistance-dominated mechanisms. Using dual-index segmented reading allows the packing material characteristic line to more closely reflect the actual characteristic trend of the packing material near the selection operating point. This avoids the mapping point offset and equivalent treatment capacity deviation caused by a uniform slope across the entire range when it deviates from the medium water-to-air ratio range, further improving the accuracy of the treatment capacity assessment of candidate models under the selection operating conditions.

[0096] In some embodiments, the system will further calculate the single-chamber performance margin of the candidate cooling tower model under the selection conditions and write it into the selection report. That is, the system will calculate the single-chamber performance margin of the candidate cooling tower model under the selection conditions according to the ratio of equivalent treatment water volume to single-chamber circulating water volume, and write the single-chamber performance margin as a field into the selection report.

[0097] Among them, the single-chamber performance margin refers to the percentage of the equivalent water treatment capacity of the candidate cooling tower model relative to the circulating water volume of the single-chamber under the selected operating conditions.

[0098] Specifically, the system first retrieves the equivalent water treatment capacity of the candidate cooling tower models under the selected operating conditions. With single air chamber circulating water volume Then press Calculate the performance margin of a single air chamber; then enter the margin value according to the reserved fields in the report template; finally, output it to the downstream manufacturing and procurement system along with the selection report.

[0099] Furthermore, the system will fill in the design parameters, standard operating condition curves, selection operating condition curves, candidate cooling tower models, and single-chamber performance margins into the selection report according to the preset report template. It will also output the standard design air volume, single-chamber packing volume, and single-chamber fan shaft power of the candidate cooling tower models as geometric and dynamic parameters for the manufacturing of the cooling tower body, as well as the capacity configuration parameters of the matching circulating water pump and fan frequency converter.

[0100] In one embodiment, when multiple sets of design parameters coexist, the system identifies the control condition with the smallest operating margin coefficient. That is, the system receives N sets of design parameters, where N is an integer greater than or equal to 2. The i-th set of design parameters in the N sets corresponds to the i-th selection condition curve, where i takes values ​​of 1, 2, ..., N. For candidate models in the cooling tower model characteristic database, the equivalent water treatment capacity of the candidate model under the i-th set of design parameters is obtained from the i-th selection condition curve. The operating margin coefficient is calculated using the following formula. ; the operating margin factor to The design parameter corresponding to the smallest median value is identified as the control condition of the candidate model, and the control condition is used as the basis for this identification. As a candidate model, it must simultaneously meet the criteria of N sets of design parameters; the identification of the control condition and the condition margin coefficient under the control condition are written as fields into the selection report.

[0101] Among them, the operating margin coefficient refers to the ratio of the equivalent treatment water volume of the candidate model under a certain set of design parameters to the circulating water volume of a single air chamber in that set of design parameters. The control condition refers to the set of design parameters with the smallest operating margin coefficient among the N sets of design parameters, which plays a decisive role in the matching of candidate models.

[0102] Specifically, the system first constructs a corresponding selection condition curve for each set of design parameters, and then calculates the equivalent water treatment capacity of the candidate model on each curve. Then, the operating margin coefficient for each set of design parameters is calculated using the following formula: ,in, Let be the dimensionless operating margin factor under the i-th set of design parameters. Let m³ / h be the equivalent water treatment capacity of the candidate model under the i-th group of design parameters. The single-chamber circulating water volume (unit: m³ / h) in the i-th group of design parameters; then... to The design parameter corresponding to the smallest median value is identified as the control condition for that candidate model; finally, the control condition is used as the basis for the control condition. As a criterion for determining whether the candidate model simultaneously meets all N sets of design parameters, the identifier of the control condition and the condition margin coefficient under the control condition are written as fields into the selection report.

[0103] It should be noted that this determination method stems from the non-monotonicity of the equivalent water treatment capacity of candidate models under different design parameters. Operating conditions with high wet-bulb temperature, large temperature difference, or large circulating water volume typically correspond to smaller operating margin coefficients. Therefore, the design parameters corresponding to the minimum margin coefficient are the operating conditions that actually constrain the candidate model. Determination criteria. This is equivalent to ensuring that the equivalent water treatment capacity of the candidate model under the most stringent operating conditions is not less than the single-chamber circulating water volume under that condition, thus guaranteeing that it is not lower than the design requirements under all N sets of design parameters. For example, in a matching calculation for three sets of operating conditions (summer condition, transitional season condition, and winter verification condition), the operating margin coefficients of a certain candidate model are respectively... =1.016、 =1.20、 =1.35, because Minimum and The system will then identify the summer operating condition as the control operating condition for this candidate model, and... =1.016 is output as the operating margin coefficient under the control condition along with the selection report.

[0104] In one embodiment, when a single-chamber configuration is not feasible, the system will escalate the multi-chamber splitting process by incrementing the number of chambers to an integer level. That is, when all candidate models in the cooling tower model characteristic database fail to meet the judgment criteria under a single-chamber configuration, the system will replace the single-chamber circulating water volume in the i-th group of design parameters with... M increases sequentially from 2, and the calculation of the operating margin coefficient and the verification of the judgment conditions are repeated. The value of M that first appears when a candidate model meets the judgment conditions is determined as the target number of air chambers. The corresponding candidate model was determined as the multi-chamber target model; the target number of chambers was determined. The target multi-chamber model should be included in the selection report as a manufacturing and ordering parameter for the target multi-chamber model.

[0105] Among them, the number of target air chambers This refers to the integer value of the number of chambers that first makes a candidate model meet the judgment criteria during the multi-chamber splitting process. The target multi-chamber model refers to the model in this process. The candidate model determined under the given value.

[0106] Specifically, the system first sets M=2, replacing the single-chamber circulating water volume in each set of design parameters with... All other parameters remain unchanged. Then, the operating margin coefficient of each candidate model under the new single-chamber circulating water volume is recalculated according to the process, and the minimum margin coefficient of not less than 1 is used as the judgment condition for verification. If the judgment result is still negative, M is incremented by 1 and the above calculation and verification are repeated. Finally, the value of M that first appears to meet the judgment condition is determined as the target number of air chambers. And the corresponding candidate models were identified as the target models for multi-chamber systems. The manufacturing and ordering parameters of the multi-chamber target model should be included in the selection report along with those of the multi-chamber target model.

[0107] It should be noted that the air chamber circulating water volume is replaced with The physical meaning is that the circulating water volume originally handled by a single air chamber is evenly distributed to M parallel air chambers. Therefore, the equivalent design water volume of each air chamber decreases as M increases, and the operating margin coefficient of the candidate model increases accordingly until the judgment condition is met for the first time. Integer escalation is used instead of continuous search because the number of air chambers can only be an integer in engineering implementation.

[0108] Furthermore, in some embodiments, an upper limit protection is provided for the increase of the number of air chambers M. That is, the system will simultaneously check whether M exceeds the limit as M is incremented sequentially from 2. When M reaches If no candidate model meets the judgment criteria, the system exits the current multi-chamber splitting process of the tower pool and enters the tower pool expansion branch.

[0109] in, This refers to the maximum number of air chambers allowed under the current engineering installation conditions, which is calculated by back-calculating the available floor area of ​​the engineering installation site and the available head of the supporting circulating water pump. The tower-type pool expansion branch refers to the processing branch that expands the candidate set of the cooling tower model characteristic database to the next level of specifications according to the preset specification increment rules and then re-enters the multi-air chamber splitting process.

[0110] Specifically, the system first calculates the maximum number of air chambers for candidate models under the current engineering installation conditions using the following formula: ,in, The maximum number of ventilation chambers allowed by the available floor space, according to calculate; The maximum number of air chambers allowed by the available head of the circulating water pump, according to calculate; Available floor space for the installation site (unit: m²). The floor area of ​​a single air chamber for the candidate model (unit: m²). Available head (unit: m) for matching circulating water pumps. The required circulating water head (in meters) for the candidate model in a single-chamber configuration is given. INT() is the floor function, which rounds the value within the parentheses down to the largest integer not greater than that value. MIN() is the minimum function, which takes the smallest value among the values ​​within the parentheses. Then, after each increment of M, it is synchronously checked whether M is not greater than... When M is not greater than Continue calculating the operating margin coefficient and verifying the judgment conditions; then, when M reaches... If no candidate model meets the judgment criteria, the system retrieves the next level of candidate model set from the cooling tower model characteristic database according to the preset specification increment rule, and re-executes the multi-chamber splitting process starting from M=2; finally, the final target number of chambers is determined. The target model of the multi-chamber and the identifier of the triggered tower-type pool expansion level should be written as fields in the selection report.

[0111] It should be noted that the upper limit protection of M stems from the rigid physical constraints of the land area and circulating water pump head during project implementation: an unlimited increase in the number of air chambers would lead to a significant increase in the total length of parallel water circuits and the scale of inlet and outlet water networks, resulting in insufficient circulating water pump head redundancy and exceeding the land area limit within the project boundary. By adopting a combined judgment method of upper limit protection and tower-type pool expansion branch, the multi-air chamber splitting process can automatically switch to the next level of tower type specification when the candidate tower type specification is too small, avoiding a dead loop of infinitely increasing air chamber numbers that can never converge. This ensures that the multi-condition matching process can return feasible matching results within a finite number of steps under any design parameter input.

[0112] The following describes the computer-based system for determining the thermal matching parameters of the cooling tower in the embodiments of this application from a hardware processing perspective. Please refer to [link to relevant documentation]. Figure 2 This is a schematic diagram of a physical device structure of a computer system for determining the thermal matching parameters of a cooling tower in an embodiment of this application.

[0113] It should be noted that, Figure 2 The structure of the computer system for determining the thermal matching parameters of the cooling tower shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0114] like Figure 2 As shown, the system includes a CPU, which can perform various appropriate actions and processes based on a program stored in the ROM or a program loaded into the RAM from a storage portion, such as executing the methods described in the above embodiments. The RAM also stores various programs and data required for system operation. The CPU, ROM, and RAM are interconnected via a bus. I / O interfaces are also connected to the bus.

[0115] The following components are connected to the I / O interface: input sections including cameras, infrared sensors, etc.; output sections including liquid crystal displays (LCDs) and speakers, etc.; storage sections including hard drives, etc.; and communication sections including network interface cards such as LAN (Local Area Network) cards and modems, etc. The communication section performs communication processing via a network such as the Internet. Drives are also connected to the I / O interface as needed. Removable media, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on the drive as needed so that computer programs read from them can be installed into the storage section as needed.

[0116] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by the CPU, it performs the various functions defined in this application.

[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0118] Specifically, the system in this embodiment includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements the method provided in the above embodiment.

[0119] In another aspect, this application also provides a computer-readable storage medium, which may be included in the system described in the above embodiments; or it may exist independently and not assembled into the system. The storage medium carries one or more computer programs that, when executed by a processor of the system, cause the system to implement the methods provided in the above embodiments.

[0120] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0121] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

Claims

1. A computer-based method for determining the thermal matching parameters of a cooling tower, characterized in that, The method includes: Receive the selection and design parameters of the cooling tower, which include at least the single-chamber circulating water volume, hot water temperature, cold water temperature, wet-bulb temperature, design atmospheric pressure and altitude; The enthalpy model of moist air is corrected based on the pre-stored enthalpy models of moist air and water, combined with the atmospheric pressure and the altitude. Based on the wet-bulb temperature, the modified wet air enthalpy model is invoked; based on the hot water temperature and the cold water temperature, the water enthalpy model is invoked; the water-air interface enthalpy difference of the cooling tower is calculated point by point within the preset water-air ratio range; and based on the hot water temperature and the cold water temperature, the characteristic values ​​of the cooling tower are solved to obtain the selection condition curve that characterizes the current selection condition requirements. The selection condition curve is matched with the standard condition curves of each cooling tower model in the pre-stored cooling tower model characteristic database. During the matching process, the ratio of the single air chamber circulating water volume to the standard design air volume of the candidate model is used as the selection condition water-air ratio. The selection condition point is located on the selection condition curve using the selection condition water-air ratio to determine the candidate cooling tower model that meets the design parameters. According to the preset report template, the design parameters, the selection condition curve, and the candidate cooling tower model are filled into the corresponding fields to generate a structured selection report and output it. The standard design air volume, single-chamber packing volume, and single-chamber fan shaft power of the candidate cooling tower model are output as geometric and dynamic parameters for the manufacturing of the cooling tower body, as well as the capacity configuration parameters of the matching fan frequency converter.

2. The method according to claim 1, characterized in that, The step of calculating the enthalpy difference at the water-air interface of the cooling tower point by point within a preset water-air ratio range, and solving for the characteristic values ​​of the cooling tower based on the hot water temperature and the cold water temperature, specifically includes: For each water-to-gas ratio value within the water-to-gas ratio range, the first integration node, the second integration node, the third integration node, and the fourth integration node are selected between the hot water temperature and the cold water temperature according to the Chebikov four-point integration rule. At the first integration node, the second integration node, the third integration node, and the fourth integration node, the water enthalpy model is called to obtain the water-side saturated enthalpy value, the corrected moist air enthalpy model is called and combined with the current water-to-air ratio to obtain the corresponding air enthalpy value, and the water-side saturated enthalpy value is subtracted from the air enthalpy value to obtain the first water-to-air interface enthalpy difference, the second water-to-air interface enthalpy difference, the third water-to-air interface enthalpy difference, and the fourth water-to-air interface enthalpy difference, respectively. The cooling tower characteristic value under the current water-to-air ratio is calculated by the sum of the reciprocals of the first water-to-air interface enthalpy difference, the second water-to-air interface enthalpy difference, the third water-to-air interface enthalpy difference, and the fourth water-to-air interface enthalpy difference using the following formula: ,in, These are the characteristic values ​​of the cooling tower. The specific heat capacity of water, The temperature of the hot water is... The temperature of the cold water, The enthalpy difference at the first water-vapor interface. This is the enthalpy difference at the second water-vapor interface. The enthalpy difference at the third water-vapor interface. The fourth water-gas interface enthalpy difference.

3. The method according to claim 2, characterized in that, The air enthalpy values ​​at the first integration node, the second integration node, the third integration node, and the fourth integration node are obtained by the following formula: ,in, Let i be the air enthalpy value at the i-th integration node, where i takes the values ​​1, 2, 3, and 4 respectively, corresponding to the first integration node, the second integration node, the third integration node, and the fourth integration node. The enthalpy value of the intake air is obtained by calling the corrected wet air enthalpy model based on the wet-bulb temperature; This is the specific heat capacity of water; The temperature of the hot water; The temperature of the cold water; This is the current water-to-air ratio value; Let be the position coefficient of the i-th integration node. , , , The values ​​were 0.1, 0.4, 0.6, and 0.9 in sequence.

4. The method according to claim 1, characterized in that, The selected operating condition curve is matched with the characteristic curves of each cooling tower model in the pre-stored cooling tower model characteristic database, specifically including: The selection condition point is located on the selection condition curve using the water-air ratio of the selection condition, and the water-air ratio and cooling tower characteristic value of the selection condition point are obtained. A straight line with a slope of n is drawn through the selected operating point. The intersection of the straight line with the standard operating point is taken as the standard operating point. The water-air ratio of the standard operating point is obtained. Here, n is read from a preset type-slope database according to the type of packing. The type-slope database stores at least the slope values ​​corresponding to three types of packing: film packing, drip packing, and drip-film composite packing. Calculate the equivalent water treatment capacity of the candidate model under the selected operating conditions using the following formula: ,in, This represents the equivalent water treatment capacity of the candidate model under the selected operating conditions. The single-chamber water processing capacity of the candidate model under standard operating conditions; The water-to-air ratio at the selected operating point; The water-to-air ratio at the standard operating condition mapping point; When the equivalent water treatment volume is greater than or equal to the single air chamber circulating water volume, the candidate model is determined as the candidate cooling tower model.

5. The method according to claim 4, characterized in that, The method further includes: Calculate the single-chamber performance margin of the candidate cooling tower model under the selected operating conditions using the following formula: ,in, This refers to the single-chamber performance margin of the candidate cooling tower model under the selected operating conditions; The equivalent water treatment capacity of the candidate cooling tower model under the selected operating conditions; The circulating water volume of the single air chamber; The single-chamber performance margin is written as a field in the selection report.

6. The method according to claim 1, characterized in that, The design parameters are in N sets, where N is an integer greater than or equal to 2. The i-th set of design parameters in the N sets corresponds to the i-th selection condition curve, and i takes the values ​​1, 2, ..., N in sequence. For the candidate models in the cooling tower model characteristic database, the equivalent water treatment capacity of the candidate model under the i-th set of design parameters is obtained on the i-th selection condition curve. The operating margin coefficient is calculated using the following formula. , ,in, The single-chamber circulating water volume in the i-th set of design parameters; The operating condition margin coefficient to The design parameter corresponding to the smallest median value is identified as the control condition of the candidate model, and the control condition is used as the control condition. The candidate model is determined to simultaneously meet the N sets of design parameters; The identifier of the control condition and the condition margin coefficient under the control condition are written as fields into the selection report.

7. The method according to claim 6, characterized in that, When all candidate models in the cooling tower model characteristic database do not meet the judgment condition under the single-chamber configuration, the single-chamber circulating water volume in the i-th group of design parameters is replaced with... M increases sequentially from 2, and the calculation of the operating margin coefficient and the verification of the judgment conditions are repeated. The value of M that first appears in a candidate model that meets the judgment conditions is determined as the target number of air chambers. The corresponding candidate model was determined to be the multi-chamber target model; The target number of air chambers The target multi-chamber model is included in the selection report as the manufacturing and ordering parameters for the target multi-chamber model.

8. A computer-based system for determining the thermal matching parameters of a cooling tower, characterized in that, include: One or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the system, the system performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the system, the system performs the method as described in any one of claims 1-7.

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