A method for controlling the spraying of a concrete dam face

Abstract

The application provides a concrete dam surface spraying control method, which comprises the following steps: obtaining concrete construction parameters of a pouring bin, bin surface environment information and rated parameters of a spraying device; establishing a bin surface internal environment temperature simulation model according to the concrete construction parameters and a solar radiation temperature increment, and generating an effective simulation value of a predicted pouring temperature; determining an effective temperature difference between the inside and outside of the bin surface based on the bin surface external environment temperature, the solar radiation temperature increment and the effective simulation value; determining a target temperature difference ratio and a boundary temperature difference ratio based on a design requirement temperature difference control value, the effective temperature difference between the inside and outside of the bin surface and the rated parameters; and establishing a spraying parameter simulation model according to the target temperature difference ratio and the boundary temperature difference ratio, and generating a target simulation value of the spraying parameter. The application can solve the problem that there is a lack of systematic correlation model between the dynamic change of the temperature difference between the inside and outside of the bin surface and the spraying parameter setting, realize accurate matching of spraying control and actual temperature control requirements, and improve the concrete dam bin surface environment regulation effect.

Description

Technical Field

[0001] This application relates to the field of concrete engineering technology, and in particular to a method for spray control on the surface of a concrete dam. Background Technology

[0002] Concrete dams, as important water conservancy projects, play a crucial role in the construction of hydropower stations. During the pouring process of concrete dams, parameters such as temperature and humidity of the surface environment have a significant impact on concrete quality, thus requiring effective environmental control measures. Currently, spray cooling technology is widely used in the field of concrete dam construction to control the surface environment. This technology sprays water mist onto the surface using spray equipment, forming a mist-like heat insulation layer above the surface. This reduces direct sunlight and effectively lowers the surface temperature, significantly reducing the temperature rise of the concrete during pouring and vibration.

[0003] However, current warehouse surface spray control largely relies on traditional manual operation and independent equipment. On the one hand, environmental data (such as wind speed and temperature) needs to be measured manually on-site, resulting in large data errors and scattered storage. The lack of a unified management platform makes real-time traceability and analysis impossible. On the other hand, spray parameters (such as spray volume and spray wind speed) are set based on manual experience and cannot be dynamically adjusted according to the warehouse environment. This leads to problems such as poor spray control accuracy, unstable cooling effect (temperature fluctuations often exceeding ±5℃), and insufficient atomization range, making it difficult to cover large warehouse surfaces. This results in spray control failing to accurately match actual temperature control needs, thus limiting the effectiveness of warehouse environment regulation. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a method for controlling spray on the surface of a concrete dam, in order to solve the problems of mismatch between spray control and actual temperature control requirements and limited effect of surface environment regulation caused by manually set parameters in traditional concrete dam surface spray control.

[0005] According to one aspect of the embodiments of this application, a method for controlling spraying on the surface of a concrete dam is provided. The method includes: acquiring concrete construction parameters of the pouring dam to be sprayed, surface environmental information, and rated parameters of the spraying equipment corresponding to the pouring dam; wherein, the surface environmental information includes the external ambient temperature and solar radiation temperature increment of the pouring dam surface; the rated parameters include the rated spray volume and rated spray wind speed of the spraying equipment; establishing a simulation model of the internal ambient temperature of the pouring dam surface based on the correlation between the concrete construction parameters and the solar radiation temperature increment to generate an effective simulated value of the internal ambient temperature of the pouring dam surface; the effective simulated value is used to characterize the predicted pouring temperature of the concrete in the pouring dam surface; determining the effective temperature difference between the inside and outside of the pouring dam surface based on the external ambient temperature, solar radiation temperature increment, and effective simulated value; and determining the target temperature difference ratio of the pouring dam surface based on the internal and external temperature difference control value required by the design requirements of the pouring dam surface and the effective temperature difference between the inside and outside of the pouring dam surface; determining the boundary temperature difference ratio of the pouring dam surface based on the rated parameters; and establishing a spraying parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate target simulated values ​​of the spraying parameters; the target simulated values ​​are used to characterize the actual spray volume and actual spray wind speed of the spraying equipment.

[0006] In one optional embodiment, the boundary temperature difference ratio includes an upper boundary temperature difference ratio and a lower boundary temperature difference ratio; wherein, the upper boundary temperature difference ratio is determined based on the rated maximum spray volume and rated maximum spray wind speed of the spraying equipment, and the lower boundary temperature difference ratio is determined based on the rated maximum spray volume and rated minimum spray wind speed of the spraying equipment; based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio, a spray parameter simulation model is established to generate target simulated values ​​of the spray parameters, including: obtaining the comparison results between the target temperature difference ratio and the boundary temperature difference ratio, and establishing a spray parameter simulation model corresponding to the cooling demand level based on the comparison results to generate target simulated values.

[0007] In one optional embodiment, after establishing a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate the target simulated values ​​of the spray parameters, the method includes: obtaining the historical measured temperature difference ratio of the pouring silo and the corresponding historical spray parameters; an iterative step, obtaining the concrete pouring temperature of the pouring silo after spraying as the effective measured value, and adjusting the weighting coefficient based on the comparison result between the effective measured value and the corrected effective simulated value. Based on the adjusted weighting coefficients The effective temperature difference between the inside and outside of the storage area and the target temperature difference ratio are redefined, and the target simulated value after iteration is calculated. The target simulated value after iteration is compared with the historical spray parameters to determine whether the comparison result exceeds the preset threshold range and whether the number of iterations is less than 3. If yes, the iteration step is returned. If no, the target simulated value after iteration is output, and the actual spray volume and actual spray wind speed of the spraying equipment are represented by the target simulated value after iteration.

[0008] In an optional embodiment, after establishing a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate the target simulated value of the spray parameters, the method includes: obtaining the historical measured temperature difference ratio of the pouring silo under similar working conditions and the corresponding historical spray parameters; wherein, similar working conditions refer to the construction scheme of spray cooling implemented through engineering experience under similar silo surface conditions; calculating the optimal spray parameters corresponding to the actual achievement of the best temperature control effect under similar working conditions based on the historical measured temperature difference ratio of the pouring silo under similar working conditions and the corresponding historical spray parameters; determining a first deviation rate based on the historical spray parameters and the optimal spray parameters under similar working conditions; and determining a second deviation rate based on the target simulated value and the optimal spray parameters; comparing the first deviation rate and the second deviation rate, and if the first deviation rate is greater than the second deviation rate, then fixing the weighting coefficient. If the first deviation rate is less than or equal to the second deviation rate, the concrete pouring temperature in the pouring bin after spraying is obtained as the effective measured value, and the weighting coefficient is adjusted based on the comparison between the effective measured value and the effective simulated value. To redetermine the target simulated value, the first deviation rate is increased until it is greater than the second deviation rate; where the effective measured value is less than the effective simulated value, the weighting coefficient is increased. When the effective measured value is greater than the effective simulated value, reduce the weighting coefficient. .

[0009] In this embodiment, by acquiring the concrete construction parameters of the pouring silo requiring spraying, the external ambient temperature of the silo surface, the solar radiation temperature increment, and the rated parameters of the spraying equipment corresponding to the pouring silo, a simulation model of the internal ambient temperature of the silo surface is established based on the correlation between the concrete construction parameters and the solar radiation temperature increment. This generates an effective simulated value of the internal ambient temperature of the silo surface, which is used to characterize the predicted pouring temperature of the concrete in the pouring silo, thus comprehensively considering the thermodynamic changes of the concrete from its entry into the silo to its pouring. Based on the external ambient temperature of the silo surface, the solar radiation temperature increment, and the effective simulated value, the effective temperature difference between the inside and outside of the silo surface is determined. The temperature difference is a key indicator for determining whether spray cooling is needed and for adjusting the spray intensity. Based on the design requirements of the pouring silo, the necessary internal and external temperature difference control values, the effective temperature difference between the inside and outside of the silo surface, and the rated parameters, the target temperature difference ratio and boundary temperature difference ratio of the pouring silo are determined. This process combines design requirements with actual environmental conditions, providing a basis for subsequent spray parameter calculations. Based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio, a spray parameter simulation model is established to generate target simulated values ​​for the spray parameters. These target simulated values ​​characterize the actual spray volume and actual spray wind speed of the spray equipment, thereby achieving accurate calculation and dynamic adjustment of spray parameters. In this way, by systematically integrating multi-source environmental parameters and concrete characteristics, a complete closed loop from environmental perception to spray control is constructed. This effectively solves the problem of the lack of a systematic correlation model between the dynamic changes in the internal and external temperature difference of the silo surface and the setting of spray parameters, achieving precise matching between spray control and actual temperature control needs, and significantly improving the environmental regulation effect of the silo surface.

[0010] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0011] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating the steps of a spray control method for a concrete dam surface provided in an embodiment of this application; Figure 2 Based on Figure 1 The exemplary embodiment shown illustrates a flowchart of another method for controlling spraying on the surface of a concrete dam. Figure 3 Based on Figure 1 The exemplary embodiment shown illustrates a flowchart of another method for controlling spraying on the surface of a concrete dam. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and are not limited in number; for example, a first object can be one or more. Furthermore, the term "and / or" in the specification and claims is used to describe the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. In the embodiments of this application, the term "multiple" refers to two or more, and other quantifiers are similar.

[0014] During the construction of large-volume concrete dams, the surface temperature is affected by both the external environment (especially solar radiation) and internal hydration heat, which can easily lead to excessive temperature differences between the inside and outside of the concrete, causing quality defects such as surface cracks. In existing technologies, spray control largely relies on manual experience to set the spray volume and wind speed, without establishing a quantitative correlation between measured external environmental parameters, concrete construction parameters, and spray equipment control parameters. This makes it difficult to achieve dynamic response and precise adaptation to the temperature control requirements of the pouring dam.

[0015] In response, Figure 1 This is a flowchart illustrating the steps of a concrete dam surface spray control method provided in an embodiment of this application, as follows: Figure 1 As shown, the method may include: Step S100: Obtain the concrete construction parameters, surface environment information, and rated parameters of the spraying equipment corresponding to the pouring sump that needs to be sprayed; wherein, the surface environment information includes the external ambient temperature and solar radiation temperature increment of the pouring sump; the rated parameters include the rated spray volume and rated spray wind speed of the spraying equipment. Among them, the concrete construction parameters can be the core subset of the placement information of the pouring slab that is directly related to the thermal behavior of concrete, such as the concrete entry temperature, the hydration heat temperature rise coefficient, and the thermal conductivity coefficient of aged concrete; this parameter set is used to support the input construction of the subsequent simulation model of the internal environmental temperature of the slab surface.

[0016] The information on the placement site can refer to a set of information used to characterize the spatial location and construction status of the pouring site that needs to be sprayed, such as the dam section number, placement site number, paving layer elevation, concrete design grade, placement temperature, mixing and transportation time, vibration method, etc. This information is used to reflect the physical location of the concrete on the placement surface and its initial thermal state.

[0017] The warehouse surface environmental information refers to a set of data that characterizes the external thermal conditions of the warehouse surface in real time, such as external ambient temperature, solar radiation temperature increment, relative humidity, and wind speed. This information can be obtained by deploying climate monitoring equipment, which can consist of a small weather station at the construction site, mobile thermometers and hygrometers, anemometers, solar radiation meters, and an environmental monitoring host. The small weather station, along with the anemometer and solar radiation meter, collects data on the external ambient temperature, solar radiation intensity, relative humidity, and wind speed. The mobile thermometer and hygrometer collect data on the concrete pouring temperature and humidity inside the warehouse surface. The data is then transmitted in real time to a cloud server via wireless transmission (such as GPRS) through the environmental monitoring host to ensure data timeliness. The solar radiation temperature increment can be obtained from the measured value of solar radiation intensity, based on the formula:

[0018] The calculation yielded the following results: ΔTr is the solar radiation temperature increment (°C); k is the temperature rise coefficient, ranging from 0.002 to 0.005 (°C·m² / W), which can be taken as 0.005 here; Ra is the measured value of solar radiation (W / m²). This information is used to quantify the effect of solar radiation on the temperature rise of concrete surfaces.

[0019] Rated parameters refer to the set of inherent performance indicators specified by the manufacturer for the spraying equipment, such as rated spray volume, rated spray velocity, rated working pressure, nozzle orifice diameter, outlet diameter, and maximum allowable operating power. This set is used to define the controllable boundaries of the spraying equipment at the physical level. Among them, rated spray volume can be the amount of atomized water that the spraying equipment stably outputs per unit time under rated working pressure and standard operating conditions. This parameter is used to constrain the upper / lower limits of the target spray volume. Rated spray velocity can be the average airflow velocity measured at the center axis of the outlet when the spraying equipment is driven by rated power. This parameter is used to constrain the upper / lower limits of the target spray velocity.

[0020] Understandably, the aforementioned data can be collected through manual input, automatic import, or interface with third-party systems to achieve unified data management and analysis. For example, the DIM coding system can retrieve the silo information associated with the silo number from the database to obtain the concrete construction parameters for the silo to be sprayed; the GPRS wireless communication module can obtain the silo surface environmental information from the environmental monitoring host deployed on the corresponding silo surface; and the rated spray volume and rated spray wind speed can be read from the built-in MCU of the spraying equipment through the equipment management interface.

[0021] Step S200: Based on the correlation between concrete construction parameters and solar radiation temperature increment, establish a simulation model of the internal ambient temperature of the pouring surface to generate effective simulation values ​​of the internal ambient temperature of the pouring surface; the effective simulation values ​​are used to characterize the predicted pouring temperature of the concrete in the pouring slab. The correlation between concrete construction parameters and solar radiation temperature increment can refer to the nonlinear coupling relationship formed between the two in the process of heat conduction and heat accumulation. The concrete construction parameters include at least the concrete placement temperature, the hydration heat temperature rise coefficient, and the thermal conductivity coefficient of aged concrete. The relationship is reflected as follows: the concrete placement temperature determines the initial thermal state, the hydration heat temperature rise coefficient determines the hydration heat release rate and peak value, and the thermal conductivity coefficient of aged concrete determines the influence of the thermal conduction of aged concrete on the temperature of newly poured concrete; the solar radiation temperature increment determines the additional heat input to the surface of newly poured concrete. All four factors jointly affect the temperature field evolution trend of the concrete surface in a certain period of time after pouring.

[0022] The simulation model of the internal ambient temperature of the concrete pouring site can be a mathematical expression structure used to describe the temperature distribution and time evolution of the concrete inside the pouring site. Its input is the concrete construction parameters and the solar radiation temperature increment, and the output is the effective simulated value of the internal ambient temperature of the pouring site, which is a single characteristic temperature value representing the overall thermal state of the concrete in the pouring site. This value is used to characterize the predicted pouring temperature of the concrete in the pouring site, that is, the expected peak temperature of the concrete in the pouring site before the spraying intervention. It not only directly affects the early stress development and cracking risk of the concrete, but also serves as the basis for subsequent temperature difference assessment.

[0023] In some embodiments, step S200 may be to establish an effective simulated value of the internal ambient temperature of the storage area according to Formula 4: Formula 4: ; in, This represents an effective simulated value for the internal ambient temperature of the warehouse. The concrete pouring temperature; This represents the temperature rise caused by the heat release during hydration. Correction value for thermal conductivity of aged concrete foundations; This represents the increase in temperature due to solar radiation.

[0024] Optional, concrete pouring temperature The actual temperature of the concrete upon placement can be obtained by considering the temperature increments during various stages of transportation, loading, transfer, and unloading, and can be based on the formula:

[0025] Calculated; where, It is the temperature at which the goods enter the warehouse. It is the outlet temperature. It is the first Temperature increment coefficient (°C / min) It is the first Time taken for each step (min).

[0026] Among them, outlet temperature Without adding ice or using a fan-cooled system, the following formula can be used:

[0027] Calculated; where, , , , These are the specific heats of sand, stone, cement, and water, respectively, expressed in kJ / (kg·℃). , These represent the moisture content of sand and gravel, respectively, in percentages (%). , , , These represent the weights of sand, stone, cement, and water in each cubic meter of concrete, expressed in kJ / (kg·℃). , , , These represent the temperatures of sand, stone, cement, and water, respectively, in °C. The mechanical heat generated during the mixing process is expressed in kJ / m³. 3 It can be based on the formula:

[0028] Calculated; where, The motor power of the mixer is expressed in KW (kilowatts). This refers to the stirring time, expressed in minutes (min). This refers to the mixer capacity, in meters (m). 3 (cubic meters), calculated based on the effective discharge volume.

[0029] In the absence of data, take kJ / (kg·℃) kJ / (kg·℃), at this point, the outlet temperature Based on the formula:

[0030] Calculations show that, in the absence of ice and air cooling, if some of the mixing water is replaced with ice chips, the latent heat absorbed when the ice chips melt (335 kJ / kg) can lower the concrete outlet temperature. At this point, the outlet temperature... Based on the formula:

[0031] Calculated; where, Ice addition rate (percentage of actual water added); To ensure the effectiveness of adding ice, since some of the ice chips melt during transportation before entering the mixer, therefore... The value range is usually 0.75 to 0.85; the definitions of other parameters are the same as the corresponding parameters in the aforementioned formula.

[0032] Optional, the temperature rise caused by the heat release during hydration. It can be obtained directly from experimental data; among them, the equivalent hydration heat release time Based on the formula:

[0033] Calculated; where, The initial temperature of the adiabatic temperature rise test block; The concrete pouring temperature; This refers to the equivalent hydration heat release time, i.e., the time required for the adiabatic temperature rise test. This refers to the interval between thin layer laying.

[0034] When experimental data is lacking but an adiabatic temperature rise fitting formula is available, the temperature rise caused by the heat release during hydration is... It can also be determined based on the fitting formula; where, When using exponential fitting, the temperature rise caused by the exothermic hydration reaction is... for:

[0035] In the formula, This represents the final value of the adiabatic temperature rise; a and b are both constants, determined by the properties of the adiabatic temperature rise curve.

[0036] When fitting using a hyperbolic form, the temperature rise caused by the exothermic hydration is... for:

[0037] In the formula, is the final value of the adiabatic temperature rise; n is a constant, determined by the properties of the adiabatic temperature rise curve.

[0038] Optional, correction value for thermal conductivity of aged concrete foundations Based on the formula:

[0039] Calculated; where, The base correction value (°C) is 0.5; 0.5 is an empirical coefficient. Measured temperature (°C) of the old paving layer; The concrete pouring temperature; The coefficient representing the influence of thermal conductivity is calibrated based on the thickness of the paving layer and its specific heat.

[0040] Step S300: Based on the external ambient temperature of the silo surface, the solar radiation temperature increment, and the effective simulated value, determine the effective temperature difference between the inside and outside of the silo surface; and based on the internal and external temperature difference control value required by the design requirements of the casting silo and the effective temperature difference between the inside and outside of the silo surface, determine the target temperature difference ratio of the casting silo. The effective temperature difference between the inside and outside of the storage area refers to a quantitative indicator reflecting the current degree of thermal imbalance on the storage surface. It is defined as the difference between the effective simulated value of the internal ambient temperature and the external ambient temperature, corrected for by solar radiation temperature increments. Based on the formula:

[0041] The calculation yields the following formula: The external ambient temperature of the warehouse surface (°C); This represents the effective simulated value (°C) of the internal ambient temperature of the warehouse. The solar radiation temperature increment (°C) is the value of the solar radiation temperature increment. All of the above parameters can be obtained or generated from the aforementioned content.

[0042] The required internal and external temperature difference control value for the pouring silo design can refer to the maximum allowable internal and external temperature difference limit specified in the hydraulic engineering specifications or design documents to prevent concrete cracking, such as 25℃, 22℃, or set according to the dam body section; this value serves as the temperature control target benchmark to measure whether the current thermal state exceeds the limit.

[0043] The target temperature difference ratio can be the ratio of the current effective temperature difference between the inside and outside of the storage area to the design temperature difference control value. This ratio is used to convert the absolute temperature difference into a dimensionless control index, and is used to evaluate the degree to which the actual cooling effect at the construction site achieves the design requirements. Therefore, the target temperature difference ratio... Based on the formula: ; The calculation yields the following formula: The required internal and external temperature difference control value (°C) for the design requirements of the pouring silo; The effective temperature difference between the inside and outside of the warehouse (°C) is given; the "+3.5" in the denominator of the formula is an empirical correction value (°C) used to provide a safety buffer for situations such as measurement uncertainty or local stress concentration.

[0044] Step S400: Determine the boundary temperature difference ratio of the casting chamber based on the rated parameters; Among them, the boundary temperature difference ratio can be a set of temperature difference ratio thresholds derived from the rated parameters of the spraying equipment, corresponding to its physical limit operating state; this set is used to define the safe and feasible domain for adjusting the spraying parameters.

[0045] Generally, the boundary temperature difference ratio can be adopted as the upper limit boundary temperature difference ratio. Upper limit boundary temperature difference ratio It can be determined based on the rated maximum spray volume and rated maximum spray wind speed of the spraying equipment, specifically using the formula:

[0046] Calculated; where, This is an empirical coefficient for the ratio of fan air volume to temperature difference. This is the correction factor for the fan air volume; This is the rated maximum spray volume; The wind speed-temperature difference ratio exponent coefficient; This is the rated maximum spray speed; This is the power factor of the wind speed; This refers to the diameter of the air outlet of the spray equipment; typically, It can be obtained by fitting data such as wind speed and temperature at the engineering site. In the absence of a fitting formula, empirical fixed values ​​can also be used. It is 2.5168. It is 0.04354. It is 2.4. It is 1.25.

[0047] In some embodiments, the boundary temperature difference ratio may further include the lower limit boundary temperature difference ratio. Lower limit boundary temperature difference ratio The value can be determined based on the rated maximum spray volume and rated minimum spray wind speed of the spray equipment, specifically using the following formula:

[0048] Calculated; where, The rated minimum spray velocity; other parameters are defined as the aforementioned upper limit boundary temperature difference ratio. The corresponding parameters in the calculation formula are defined in the same way.

[0049] In response, the upper limit boundary temperature difference ratio Characterized as the ratio of the maximum temperature difference that a spraying device can handle when operating at its rated maximum spray volume and rated maximum spray velocity in combination; lower limit boundary temperature difference ratio. Characterized as the minimum temperature difference ratio that a spraying device can handle when operating at its rated maximum spray volume and rated minimum spray wind speed in combination.

[0050] Step S500: Based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio, establish a spray parameter simulation model to generate target simulation values ​​of the spray parameters; the target simulation values ​​are used to characterize the actual spray volume and actual spray wind speed of the spray equipment.

[0051] The correlation between the target temperature difference ratio and the boundary temperature difference ratio can refer to the judgment relationship between the two in the spray cooling efficiency range. This relationship divides the temperature difference control demand into multiple levels (such as low demand, medium demand, and high demand), and each level corresponds to a set of differentiated spray parameter combination strategies.

[0052] The spray parameter simulation model can be a functional relationship or logical rule set used to map the temperature difference ratio range determination result to executable equipment instructions. Its output target simulation value is the combination of actual spray volume and actual spray wind speed. By obtaining the comparison result of the target temperature difference ratio and the boundary temperature difference ratio, a spray parameter simulation model corresponding to the cooling demand level can be established based on the comparison result. This can generate a better combination of spray parameters that meets the current temperature control requirements and is within the rated capacity range of the equipment, i.e., the target simulation value. Based on the target simulation value, a control signal is generated to adjust the working parameters of the spray equipment. This can avoid water waste and droplet deposition caused by excessively high parameters, and also avoid insufficient cooling caused by excessively low parameters.

[0053] For example, in this embodiment, when only the upper limit boundary temperature difference ratio is used for the boundary temperature difference ratio, the model can classify the operating condition where the target temperature difference ratio is less than the upper limit boundary temperature difference ratio as a low demand level, thereby reducing the actual spray volume and actual spray wind speed; and classify the operating condition where the target temperature difference ratio is greater than or equal to the upper limit boundary temperature difference ratio as a high demand level, thereby increasing the actual spray volume and actual spray wind speed. Of course, when both the upper and lower limit boundary temperature difference ratios are used for the boundary temperature difference ratio, the model can also: when the target temperature difference ratio is less than or equal to the lower limit boundary temperature difference ratio, determine the cooling demand level as a low demand level and adopt a low wind speed and high mist volume mode; when the target temperature difference ratio is greater than the lower limit boundary temperature difference ratio and less than the upper limit boundary temperature difference ratio, determine the cooling demand level as a medium demand level and adopt a wind speed and mist volume coordinated adjustment mode; when the target temperature difference ratio is greater than or equal to the upper limit boundary temperature difference ratio, determine the cooling demand level as a high demand level and adopt a high wind speed and high mist volume full-load operation mode.

[0054] It is understood that this application may also employ a fuzzy PID controller, using the target temperature difference ratio as the error input and the boundary temperature difference ratio as the constraint boundary, to output the continuous adjustment of the spray volume and wind speed in real time; furthermore, a three-dimensional mapping table of temperature difference ratio-spray volume-spray wind speed may be pre-constructed using a lookup table method, and the target simulated value may be obtained by interpolation during operation; this application obtains the target simulated value for characterizing the actual operating state of the spray equipment based on any of the above methods, without limitation here, and will not be elaborated further.

[0055] In summary, this embodiment of the application accurately quantifies external thermal disturbances by using measured solar radiation intensity as a key input; it constructs an internal temperature simulation model of the concrete surface by integrating concrete construction parameters and solar radiation temperature increments, comprehensively considering the thermodynamic changes of concrete from placement to pouring, thus improving the reliability of predicted pouring temperature; and it introduces the effective temperature difference between the inside and outside of the concrete surface as an intermediate variable for regulation, determining the target temperature difference ratio, and then establishing a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio, thereby achieving accurate calculation and dynamic adjustment of spray parameters. In this way, by systematically integrating multi-source environmental parameters and concrete characteristics, a complete closed loop from environmental perception to spray control is constructed, effectively solving the problem of the lack of a systematic correlation model between the dynamic changes of the temperature difference between the inside and outside of the concrete surface and the setting of spray parameters, achieving precise matching between spray control and actual temperature control needs, and significantly improving the environmental regulation effect of the concrete surface.

[0056] In some embodiments, a detailed description is provided of how to establish a spray parameter simulation model corresponding to the cooling demand level based on the comparison results between the target temperature difference ratio and the boundary temperature difference ratio, in order to generate target simulated values. This surface spray control method is applicable to situations such as... Figure 1 The S500 shown includes S510-S530, which are described in detail below: Step S510: When the target temperature difference ratio is less than or equal to the lower limit boundary temperature difference ratio, establish a spray parameter simulation model using Formula 1 to generate target simulation values; Formula 1: ; in, This represents the actual spray volume. This refers to the actual spray wind speed; The target temperature difference ratio; This is an empirical coefficient for the ratio of fan air volume to temperature difference. This is the correction factor for the fan air volume; This is the rated maximum spray volume; The wind speed-temperature difference ratio exponent coefficient; This is the rated minimum spray wind speed; This is the rated maximum spray speed; This is the power factor of the wind speed; This refers to the diameter of the air outlet of the spray equipment; typically, It can be obtained by fitting data such as wind speed and temperature at the engineering site. In the absence of a fitting formula, empirical fixed values ​​can also be used. It is 2.5168. It is 0.04354. It is 2.4. It is 1.25.

[0057] In this way, Formula 1 can generate a combination of actual spray volume and actual spray wind speed suitable for mild cooling requirements, thereby ensuring the basic atomization capability and environmental coverage stability of the spray system under low load conditions, and achieving the goal of saving water resources and energy consumption.

[0058] Step S520: When the target temperature difference ratio is greater than the lower boundary temperature difference ratio and less than the upper boundary temperature difference ratio, establish a spray parameter simulation model using Formula 2 to generate target simulation values; Formula 2: ; in, This represents the actual spray volume. This refers to the actual spray wind speed; This is the rated maximum spray volume; This is the rated maximum spray speed; The diameter of the air outlet of the spray equipment; This is an empirical coefficient for the ratio of fan air volume to temperature difference. This is the correction factor for the fan air volume; The wind speed-temperature difference ratio exponent coefficient This is the power factor of wind speed; under normal circumstances, It can be obtained by fitting data such as wind speed and temperature at the engineering site. If a fitting formula is not available, empirical fixed values ​​can also be used. The specific fixed values ​​are the same as the corresponding parameters in Formula 1.

[0059] In this way, Formula 2 can generate a combination of actual spray volume and actual spray wind speed suitable for medium cooling demand levels, thereby ensuring the uniformity of atomization coverage while taking into account both cooling efficiency and energy consumption.

[0060] Step S530: When the target temperature difference ratio is greater than or equal to the upper limit boundary temperature difference ratio, establish a spray parameter simulation model using Formula 3 to generate target simulation values; Formula 3: ; in, This represents the actual spray volume. This refers to the actual spray wind speed; This is the rated maximum spray volume; This is the rated maximum spray speed.

[0061] In this way, Formula 3 can generate a combination of actual spray volume and actual spray wind speed suitable for high cooling requirements, thereby ensuring that the temperature inside the silo can be reduced quickly under extreme temperature control pressure, meeting the cooling requirements of special working conditions such as extreme high temperature and strong sunlight, and ensuring the quality of concrete.

[0062] In some embodiments, due to the correction value for the thermal conductivity foundation of aged concrete in Formula 4 The baseline values ​​obtained from fixed empirical coefficients may lead to underestimating thermal resistance during thick-layer pouring and overestimating thermal resistance during thin-layer pouring. Therefore, to accurately reflect actual site conditions, an effective simulated value for the internal ambient temperature of the pouring surface is needed. A second correction is performed. This embodiment details how to obtain the corrected effective simulation value based on the precise correction value optimized from multi-condition measured data. This surface spray control method is applicable in situations such as... Figure 1 S200 shown includes S210, which is described in detail below: Step S210: Correct the effective simulation values ​​using Formula 5; Formula 5: ; in, These are the corrected, valid simulated values; This is the valid simulated value before correction, which was explained in the previous embodiments and is used here as a known input in the correction calculation; For a linear interpolation model based on the pavement thickness, in the formula... The lower limit of the baseline heat conduction correction value is 0.08℃, and the preferred value for engineering applications is 0.08℃. The upper limit reference thermal conductivity correction value is 0.12℃, and the preferred engineering value is 0.12℃; The minimum reference paving layer thickness is 0.3m, with the preferred value for the project being 0.3m. The upper limit of the reference paving layer thickness is 0.3m, and the preferred value for the project is 0.3m; The actual paving layer thickness is measured on-site; in this embodiment, the value used is 0.4m, representing a typical engineering example. This is the weighting coefficient, with a value range of [0.8, 1.2] and a default value of 1.

[0063] It is understood that in this embodiment, It is a heat conduction temperature rise compensation amount obtained by fitting historical measured data or calibrating based on engineering experience under typical thin-layer pouring conditions. It is used to characterize the temperature correction range caused by the heat conduction from aged concrete to newly poured concrete under minimum paving thickness conditions. It is the amount of thermal conduction temperature rise compensation obtained by fitting historical measured data or calibrating based on engineering experience under typical thick-layer pouring conditions. It is used to characterize the additional temperature correction required due to the decrease in thermal conductivity of aged concrete caused by the increase in thermal resistance under the maximum paving thickness. This is a preset thin-layer reference thickness used to anchor the left endpoint of the linear interpolation model, ensuring that the correction term converges to this value as the paving thickness approaches it. . This is a preset reference thickness used to anchor the right endpoint of the linear interpolation model, ensuring that the correction term converges to this value as the paving thickness approaches it. . The actual paving thickness data of the current pouring sump can be obtained through laser rangefinder, ultrasonic thickness gauge, or manual ruler measurement. The measurement locations cover a representative area of ​​the sump surface (e.g., five points including the four corners and the center), and the average value is used in the calculation. This parameter serves as an interpolation variable, driving the correction term in... and The transitions are linear and proportional, thus achieving continuous adaptation to different thickness conditions. The weighting coefficients... This is an adjustable parameter used to adjust the overall scaling of the heat conduction correction term. This parameter does not change the interpolation structure, but only globally weights the interpolation results to accommodate systematic biases caused by differences in the thermal conductivity of different dam materials, the insulation performance of the formwork, or seasonal environmental variations; simultaneously, the weighting coefficients... In this embodiment, adjustable degrees of freedom can be provided for subsequent model iteration and optimization, but its initial settings do not depend on any subsequent implementation methods.

[0064] Thus, according to Formula 5, the simulated value of the internal ambient temperature of the warehouse can be obtained. Thickness adaptive correction results This allows it to more accurately reflect the influence of heat conduction of aged concrete on the temperature of freshly poured concrete under actual pouring conditions, thereby solving the problem of temperature difference calculation deviation caused by the inability of fixed heat conduction correction values ​​to adapt to varying paving thicknesses, and providing more reliable temperature boundary conditions for subsequent spraying parameters.

[0065] It is also understandable that, after correcting the effective simulated value using Formula 5, the effective temperature difference between the inside and outside of the storage area in step S300 should be determined based on the external ambient temperature of the storage area, the solar radiation temperature increment, and the corrected effective simulated value; therefore, the effective temperature difference between the inside and outside of the storage area... Based on the formula:

[0066] The calculation yields the following formula: The external ambient temperature of the warehouse surface (°C); The corrected effective simulation value (°C); The solar radiation temperature increment (°C) is the value of the solar radiation temperature increment. All of the above parameters can be obtained or generated from the aforementioned content.

[0067] In some embodiments, a detailed description is provided of how to optimize spray parameters by iteratively reducing the deviation between the model-calculated values ​​and the optimal values ​​measured in the field. Please refer to [link to relevant documentation] for details. Figure 2 , Figure 2 Based on Figure 1 The exemplary embodiment shown illustrates a flowchart of another method for spray control on the surface of a concrete dam. This surface spray control method, as in... Figure 1 Following step S500, and building upon step S210 included in step S200, the details are as follows: Following step S500, which establishes a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate target simulated values ​​of the spray parameters, the following steps are included: Step S610: Obtain the historical measured temperature difference ratio of the pouring chamber and the corresponding historical spray parameters; Among them, the historical measured temperature difference ratio can refer to the ratio of the temperature difference between the inside and outside of the warehouse surface obtained by actual measurement after spraying operation under the same or similar warehouse surface construction conditions to the temperature difference control value required by the design; historical spraying parameters can include the actual spraying volume and actual spraying wind speed used in this spraying operation.

[0068] Understandably, there is a correlation between historical measured temperature difference ratios and historical spray parameters through timestamps, storage location codes, and operating condition identifiers, all of which are stored in a historical database on a cloud server. The historical database supports retrieval by dam section number, storage location DIM code, construction date (year, month, day, hour), etc., and can provide an accurate and effective reference benchmark for the current iteration.

[0069] Step S620: Iterative step, obtain the concrete pouring temperature in the pouring bin after spraying as the effective measured value, and adjust the weighting coefficient based on the comparison between the effective measured value and the corrected effective simulated value. Based on the adjusted weighting coefficients The effective temperature difference between the inside and outside of the warehouse and the target temperature difference ratio were redefined, and the target simulated value after iteration was calculated. The effective measured value can refer to the average temperature value collected simultaneously at five measuring points (center and four corners) on the surface by a mobile thermometer after the spraying operation and before the concrete is laid, vibrated, and initially set; the corrected effective simulated value can refer to the value calculated according to Formula 5 in the aforementioned embodiment. In this embodiment, the weighting coefficient is adjusted. The action can be to update the scaling ratio of the linear interpolation part in the heat conduction correction model online based on the direction and amplitude of the temperature deviation between the measured and simulated temperatures. This compensates for systematic deviations caused by unmodeled factors such as errors in paving layer thickness measurement, the dispersion of thermal conductivity of aged concrete, and changes in boundary heat exchange conditions. This allows the calculated effective temperature difference between the inside and outside of the paving surface to more closely approximate the real physical response, thereby improving the accuracy of subsequent target temperature difference ratios and simulated spray parameters.

[0070] Step S630: Compare the iterated target simulation value with the historical spray parameters, and determine whether the comparison result exceeds the preset threshold range and whether the number of iterations is less than 3; if yes, return to the iteration step S620; if no, output the iterated target simulation value, and use the iterated target simulation value to represent the actual spray volume and actual spray wind speed of the spraying equipment.

[0071] The preset threshold range can refer to the relative deviation threshold between the iterated target simulated value and the corresponding parameter in the historical spray parameters. In this embodiment, the relative deviation threshold can be set to ±0.05 m³ / h for the actual spray volume and ±0.5 m / s for the actual spray wind speed. The number of iterations is recorded by an internal system counter, with an initial value of 0, incremented by 1 each time the return to iteration step S620 is executed. In this embodiment, the key criterion for determining the action constitutes the closed-loop convergence control logic is that when the iterated target simulated value falls within the preset threshold range (simultaneously satisfying spray volume ≤ ±0.05 m³ / h and wind speed ≤ ±0.5 m / s), and the number of iterations reaches 3 or more, the system terminates the iteration and locks the final output.

[0072] In this way, an initial reference system is constructed by obtaining historical measured temperature difference ratios and historical spraying parameters, and the weighting coefficient is driven by the deviation between the effective measured value and the corrected simulated value of the concrete pouring temperature after spraying. The system dynamically adjusts and then reconstructs the effective temperature difference between the inside and outside of the container, the target temperature difference ratio, and the target simulated values ​​of the spray parameters in a closed loop. Based on this, the model converges through a dual constraint process of a preset threshold range and a lower limit for the number of iterations, ensuring that the model outputs stable and executable spray control parameters through at least three feedback adjustments, thus avoiding random factors.

[0073] In some embodiments, step S620 adjusts the weighting coefficients based on the comparison result between the effective measured values ​​and the corrected effective simulated values. The steps include: When the effective measured value is less than the corrected effective simulated value, increase the weighting coefficient. ; When the effective measured value is less than the corrected effective simulated value, it indicates that the current model's prediction of the internal ambient temperature of the sump is too high, meaning that the heat conduction correction has excessively weakened the effective simulated value, resulting in the simulated temperature being lower than the actual pouring temperature; in this case, increasing... This can reduce the overall weakening effect of the correction, thereby increasing... This makes the corrected effective simulated values ​​closer to the effective measured values. Conversely, If the effective measured value is greater than the corrected effective simulated value, reduce the weighting coefficient. .

[0074] When the effective measured value is greater than the corrected effective simulated value, it indicates that the current model's prediction of the internal ambient temperature of the sump is too low, meaning the heat conduction correction is insufficient, resulting in the simulated temperature being higher than the actual pouring temperature; in this case, reduce... This could enhance the weakening effect of the correction, thereby further reducing the price. This makes the corrected effective simulated value closer to the effective measured value.

[0075] It is understandable that the above weighting coefficients The increase / decrease operation can be performed in the current... Increase / decrease by 0.05 based on the base, always constrained within the range of [0.8, 1.2]; or, use a proportional increase / decrease method to make... New value = ×(1±0.05), and always constrained within the range of [0.8, 1.2]; no restrictions are imposed here, nor will they be elaborated further.

[0076] In some embodiments, the calibration of the spray parameter simulation model is described in detail. See [link to documentation]. Figure 3 , Figure 3 Based on Figure 1 The exemplary embodiment shown illustrates a flowchart of another method for spray control of a concrete dam surface. This surface spray control method, as in... Figure 1 Following step S500, and building upon step S210 included in step S200, the details are as follows: Following step S500, which establishes a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate target simulated values ​​of the spray parameters, the following steps are included: Step S710: Obtain the historical measured temperature difference ratio of the pouring silo under similar working conditions and the corresponding historical spray parameters; where similar working conditions refer to the construction plan for spray cooling implemented based on engineering experience under similar silo surface conditions. Similar operating conditions refer to historical construction scenarios where, within the same or similar dam sections, similar embankment elevations, similar paving layer thicknesses, similar concrete mix proportions, and similar ambient temperatures and solar radiation intensity ranges, spray cooling was implemented using manual experience or conservative methods to set spray parameters and successfully achieve temperature control targets. The historical measured temperature difference ratio under similar operating conditions refers to the value calculated based on the ratio of the measured temperature difference between the inside and outside of the embankment surface to the required internal and external temperature difference control value under those similar operating conditions; it characterizes the degree to which the actual temperature control effect under those conditions is achieved relative to the design target. Historical spray parameters can be the actual operating parameters of the spray equipment executed under those similar operating conditions, including the actual spray volume and the actual spray wind speed.

[0077] Step S720: Based on the historical measured temperature difference ratio of the casting silo under similar working conditions and the corresponding historical spray parameters, calculate the optimal spray parameters corresponding to the best temperature control effect under similar working conditions. The optimal spray parameters include the optimal spray volume and the optimal spray velocity. The optimal spray volume can refer to the actual spray volume that makes the measured value of the concrete pouring temperature closest to the design target temperature under similar working conditions. The optimal spray velocity can refer to the actual spray velocity that makes the atomization coverage uniformity and cooling efficiency optimal under similar working conditions. In this embodiment, the best temperature control effect is judged by the minimum absolute value of the deviation between the measured value of the concrete pouring temperature and the target temperature, and the target temperature can be specified by the design documents. In this way, the optimal spray parameters can be derived from the historical measured temperature difference ratio and the corresponding historical spray parameters to determine the spray volume and wind speed corresponding to the best temperature control effect (such as minimum temperature difference and uniform cooling) under specific weather, material, and warehouse surface conditions. Specifically, a two-dimensional scatter plot can be constructed based on multiple sets of historical spray parameters and corresponding measured pouring temperatures under similar working conditions. A local weighted regression can be used to fit the spray volume-temperature response curve, and the extreme point of spray volume that minimizes the temperature deviation can be searched on the curve and taken as the optimal spray volume. Based on the Pearson correlation coefficient analysis of the measured pouring temperature and spray wind speed in historical data, the median wind speed in the interval with the strongest correlation can be selected as the optimal spray wind speed.

[0078] Step S730: Determine the first deviation rate based on historical spray parameters and optimal spray parameters under similar operating conditions; and determine the second deviation rate based on the target simulated value and optimal spray parameters; The first deviation rate can be a quantitative indicator of the degree to which historical spray parameters deviate from the optimal spray volume and optimal spray wind speed, used to characterize the control accuracy level based on existing engineering experience. In this embodiment, the first deviation rate includes the first spray volume deviation rate and the first spray wind speed deviation rate, wherein... First spray volume deviation rate = , First spray wind speed deviation rate = ; The first deviation rate can be obtained by taking the arithmetic mean of the two.

[0079] The target simulated value can refer to the simulated spray volume and simulated spray wind speed that the current spraying equipment should execute, generated by combining the spray parameter simulation model established according to the aforementioned embodiments with input variables such as concrete construction parameters, effective temperature difference inside and outside the slab, and boundary temperature difference ratio under similar working conditions. The second deviation rate can be a quantitative indicator of the degree to which the target simulated value deviates from the optimal spray volume and optimal spray wind speed. It is used to characterize the degree to which the target simulated value output by the spray parameter simulation model of this application approximates the historical best practice. In this embodiment, the second deviation rate includes the second spray volume deviation rate and the second spray wind speed deviation rate, wherein... Second spray volume deviation rate = , Second spray wind speed deviation rate = ; The second deviation rate can be obtained by taking the arithmetic mean of the two.

[0080] Step S740: Compare the first deviation rate with the second deviation rate. If the first deviation rate is greater than the second deviation rate, then fix the weighting coefficient. If the first deviation rate is less than or equal to the second deviation rate, the concrete pouring temperature in the pouring bin after spraying is obtained as the effective measured value, and the weighting coefficient is adjusted based on the comparison between the effective measured value and the effective simulated value. To redetermine the target simulated value, the first deviation rate is increased until it is greater than the second deviation rate; where the effective measured value is less than the effective simulated value, the weighting coefficient is increased. When the effective measured value is greater than the effective simulated value, reduce the weighting coefficient. .

[0081] Specifically, the first bias rate is directly compared with the second bias rate. If the former is larger, it indicates that the current model output is better than historical experience, and the current model is locked in. No further updates will be made; conversely, if the first bias rate is less than or equal to the second bias rate, it indicates that the current model output accuracy is insufficient and the weight coefficients need to be adjusted. To calibrate the model. At this point, adjust the weight coefficients. The operational logic can follow the directional rules defined in step S620 of the aforementioned embodiments, and adjust the weighting coefficients based on the comparison results between the effective measured value and the effective simulated value of the concrete pouring temperature after spraying. This is done to redetermine the target simulation value and update the second deviation rate until the first deviation rate is greater than the second deviation rate.

[0082] Furthermore, if the first deviation rate is greater than the second deviation rate, a precision threshold can be set. The deviation of the ratio of the first deviation rate to the second deviation rate is compared with this precision threshold. If the deviation is greater than or equal to the precision threshold, it indicates that the precision meets the standard, and the current weighting coefficient can be fixed. For example, if a precision threshold is set to 15%, then... If the weighting is ≥15%, it means that the current model output is more than 15% better than historical experience. In this case, the current weighting coefficients can be fixed. Conversely, if the deviation of this ratio is less than the accuracy threshold, it indicates that the current model output accuracy is insufficient, and the weight coefficients should be further adjusted. The target simulation value is then redefined until the accuracy is achieved.

[0083] Thus, by introducing historically optimal spray parameters under similar operating conditions as an external reference benchmark, a horizontal comparison mechanism between the first and second deviation rates is constructed. Using this mechanism, when the model output is better than historical experience, the current weight coefficients are promptly solidified to avoid redundant iterations; when the model output is worse than historical experience, the weight coefficients are adjusted in a targeted manner based on the relative relationship between effective measured values ​​and effective simulated values. The target simulation value is then regenerated, driving continuous model optimization and calibration until it surpasses the historical best performance under similar operating conditions, thus achieving a precise match between spray control and actual temperature control requirements.

[0084] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0085] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for controlling spraying on the surface of a concrete dam, characterized in that, The method includes: The concrete construction parameters, surface environment information, and rated parameters of the spraying equipment corresponding to the pouring silo to be sprayed are obtained; wherein, the surface environment information includes the external ambient temperature and solar radiation temperature increment of the pouring silo surface; the rated parameters include the rated spray volume and rated spray wind speed of the spraying equipment; Based on the correlation between the concrete construction parameters and the solar radiation temperature increment, a simulation model of the internal ambient temperature of the pouring slab is established to generate an effective simulation value of the internal ambient temperature of the pouring slab; the effective simulation value is used to characterize the predicted pouring temperature of the concrete in the pouring slab. Based on the external ambient temperature of the silo surface, the solar radiation temperature increment, and the effective simulated value, the effective temperature difference between the inside and outside of the silo surface is determined; and based on the internal and external temperature difference control value required by the design requirements of the casting silo and the effective temperature difference between the inside and outside of the silo surface, the target temperature difference ratio of the casting silo is determined. Based on the rated parameters, determine the boundary temperature difference ratio of the casting chamber; Based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio, a spray parameter simulation model is established to generate target simulation values ​​for the spray parameters; the target simulation values ​​are used to characterize the actual spray volume and actual spray wind speed of the spray equipment.

2. The method for controlling spraying on the surface of a concrete dam according to claim 1, characterized in that, The boundary temperature difference ratio includes an upper boundary temperature difference ratio and a lower boundary temperature difference ratio; wherein, the upper boundary temperature difference ratio is determined based on the rated maximum spray volume and rated maximum spray wind speed of the spraying equipment, and the lower boundary temperature difference ratio is determined based on the rated maximum spray volume and rated minimum spray wind speed of the spraying equipment; the step of establishing a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate target simulated values ​​of the spray parameters includes: Obtain the comparison result between the target temperature difference ratio and the boundary temperature difference ratio, and establish a spray parameter simulation model corresponding to the cooling demand level based on the comparison result to generate the target simulation value.

3. The method for controlling spraying on the surface of a concrete dam according to claim 2, characterized in that, The step of obtaining the comparison result between the target temperature difference ratio and the boundary temperature difference ratio, and establishing a spray parameter simulation model corresponding to the cooling demand level based on the comparison result to generate the target simulation value, includes: When the target temperature difference ratio is less than or equal to the lower limit boundary temperature difference ratio, the spray parameter simulation model is established using Formula 1 to generate the target simulation value; Official 1: ; in, This represents the actual spray volume. This refers to the actual spray wind speed; The target temperature difference ratio; This is an empirical coefficient for the ratio of fan air volume to temperature difference. This is the correction factor for the fan air volume; This is the rated maximum spray volume; The wind speed-temperature difference ratio exponent coefficient; This is the rated minimum spray wind speed; This is the rated maximum spray speed; This is the power factor of the wind speed; The diameter of the air outlet of the spraying equipment.

4. The method for controlling spraying on the surface of a concrete dam according to claim 2, characterized in that, The step of obtaining the comparison result between the target temperature difference ratio and the boundary temperature difference ratio, and establishing a spray parameter simulation model corresponding to the cooling demand level based on the comparison result to generate the target simulation value, further includes: When the target temperature difference ratio is greater than the lower boundary temperature difference ratio and less than the upper boundary temperature difference ratio, the spray parameter simulation model is established using Formula 2 to generate the target simulation value; Official 2: ; in, This represents the actual spray volume. This refers to the actual spray wind speed; This is an empirical coefficient for the ratio of fan air volume to temperature difference. This is the correction factor for the fan air volume; This is the rated maximum spray volume; The wind speed-temperature difference ratio exponent coefficient; This is the rated maximum spray speed; This is the power factor of the wind speed; The diameter of the air outlet of the spraying equipment.

5. The method for controlling spraying on the surface of a concrete dam according to claim 2, characterized in that, The step of obtaining the comparison result between the target temperature difference ratio and the boundary temperature difference ratio, and establishing a spray parameter simulation model corresponding to the cooling demand level based on the comparison result to generate the target simulation value, further includes: When the target temperature difference ratio is greater than or equal to the upper limit boundary temperature difference ratio, the spray parameter simulation model is established using Formula 3 to generate the target simulation value; Official 3: ; in, This represents the actual spray volume. This refers to the actual spray wind speed; This is the rated maximum spray volume; This refers to the rated maximum spray speed.

6. The method for controlling spraying on the surface of a concrete dam according to any one of claims 1-5, characterized in that, The step of establishing a simulation model of the internal environmental temperature of the storage surface based on the correlation between the concrete construction parameters and the solar radiation temperature increment, in order to generate effective simulated values ​​of the internal environmental temperature of the storage surface, includes: An effective simulated value of the internal ambient temperature of the warehouse surface is established using Formula 4. Official 4: ; in, This represents an effective simulated value for the internal ambient temperature of the warehouse. The concrete pouring temperature; This represents the temperature rise caused by the heat release during hydration. Correction value for thermal conductivity of aged concrete foundations; This represents the increase in temperature due to solar radiation.

7. The method for controlling spraying on the surface of a concrete dam according to claim 6, characterized in that, The step of establishing a simulation model of the internal environmental temperature of the storage surface based on the correlation between the concrete construction parameters and the solar radiation temperature increment, in order to generate effective simulated values ​​of the internal environmental temperature of the storage surface, further includes: The effective simulation value is corrected using Formula 5; Official 5: ; in, These are the corrected, valid simulated values; These are the valid simulated values ​​before correction; This is the lower limit of the baseline thermal conductivity correction value; This is the upper limit reference thermal conductivity correction value; The lower limit of the reference paving layer thickness; The upper limit of the reference paving layer thickness, The actual thickness of the paving layer was measured on-site. This is the weighting coefficient, with a value range of [0.8, 1.2] and a default value of 1.

8. The method for controlling spraying on the surface of a concrete dam according to claim 7, characterized in that, After the step of establishing a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate target simulated values ​​of the spray parameters, the following steps are included: Obtain the historical measured temperature difference ratio and corresponding historical spray parameters of the pouring chamber; In the iterative steps, the concrete pouring temperature of the pouring bin after spraying is obtained as a valid measured value. Based on the comparison between the valid measured value and the corrected valid simulated value, the weighting coefficient is adjusted. Based on the adjusted weighting coefficients The effective temperature difference between the inside and outside of the warehouse and the target temperature difference ratio are redefined, and the target simulated value after iteration is calculated. The iterated target simulation value is compared with the historical spray parameters to determine whether the comparison result exceeds a preset threshold range and whether the number of iterations is less than 3. If yes, the iteration step is returned; if no, the iterated target simulation value is output, and the iterated target simulation value is used to characterize the actual spray volume and actual spray wind speed of the spraying device.

9. The method for controlling spraying on the surface of a concrete dam according to claim 8, characterized in that, The concrete pouring temperature of the pouring hopper after spraying is obtained as a valid measured value. Based on the comparison between the valid measured value and the corrected valid simulated value, the weighting coefficient is adjusted. ,include: If the effective measured value is less than the corrected effective simulated value, increase the weighting coefficient. ; If the effective measured value is greater than the corrected effective simulated value, reduce the weighting coefficient. .

10. The method for controlling spraying on the surface of a concrete dam according to claim 7, characterized in that, After the step of establishing a spray parameter simulation model based on the correlation between the target temperature difference ratio and the boundary temperature difference ratio to generate target simulated values ​​of the spray parameters, the following steps are included: Obtain the historical measured temperature difference ratio of the pouring silo under similar working conditions and the corresponding historical spray parameters; wherein, the similar working conditions refer to the construction scheme of spray cooling implemented based on engineering experience under similar silo surface conditions; Based on the historical measured temperature difference ratio of the pouring hopper under similar working conditions and the corresponding historical spray parameters, the optimal spray parameters corresponding to the actual achievement of the best temperature control effect under similar working conditions are calculated. Based on the historical spray parameters under similar operating conditions and the optimal spray parameters, a first deviation rate is determined; and based on the target simulated value and the optimal spray parameters, a second deviation rate is determined. The first deviation rate is compared with the second deviation rate. If the first deviation rate is greater than the second deviation rate, the weighting coefficient is fixed. If the first deviation rate is less than or equal to the second deviation rate, the concrete pouring temperature of the pouring hopper after spraying is obtained as a valid measured value, and the weighting coefficient is adjusted based on the comparison between the valid measured value and the valid simulated value. To redetermine the target simulated value until the first deviation rate is greater than the second deviation rate; wherein, If the effective measured value is less than the effective simulated value, increase the weighting coefficient. ; If the effective measured value is greater than the effective simulated value, decrease the weighting coefficient. .

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