Method and system for determining optimal construction window period of mass concrete in ultrahigh altitude area

Abstract

The invention belongs to the technical field of concrete construction in ultrahigh altitude areas, and particularly relates to a method and system for determining the optimal construction window period of mass concrete in ultrahigh altitude areas. Comprising the following steps: S1, acquiring high-frequency meteorological factor original data of an anemometer tower in a wind power plant per unit time in N years; identifying and eliminating abnormal values, and filling missing values by adopting a linear interpolation method; forming a high-frequency meteorological data set with unit time as an interval; s2, according to the high-frequency meteorological data set in the step S1, a hierarchical structure model of the influence of high-frequency meteorological factors on concrete construction is constructed based on an AHP method, and a standardized construction suitability index is obtained through calculation; s3, performing statistics on construction suitability index frequency distribution of each month and each day, and generating a construction suitability index frequency distribution table of each month and each day; and S4, determining an optimal construction time window period through the construction suitability index frequency distribution table of each month and each day. And the determination of the optimal construction window period of the mass concrete in the ultrahigh altitude area is more accurate.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of concrete construction in super high altitude area, and particularly relates to a method and system for determining the optimal construction window period of mass concrete in super high altitude area. BACKGROUND

[0002] When mass concrete construction is carried out in super high altitude area, the meteorological conditions in super high altitude area are complex and changeable, such as air temperature, air pressure, humidity, irradiance and wind speed, and other meteorological factors fluctuate sharply in a short time, which has a great impact on the construction quality of concrete. Specifically, low temperature will delay the hydration reaction of concrete, resulting in slow strength growth of concrete; high wind speed and low humidity will accelerate the evaporation of water on the surface of concrete, causing dry cracking; strong irradiance will affect the performance of admixture and change the setting time of concrete. When mass concrete construction is carried out, the influence of low temperature, high wind speed, low humidity and strong irradiance on concrete is more obvious. Super high altitude refers to an altitude of more than 3500m. Mass concrete refers to a large block of concrete with a minimum cross section of greater than or equal to 300cm and a single side heat dissipation size of greater than or equal to 75cm, and a double side heat dissipation size of at least 100cm. The traditional construction window period determination method mainly depends on experience judgment or low frequency (daily or hourly) single meteorological factor data, and cannot accurately capture the change rule of meteorological factors and the coupling effect of multiple meteorological factors, so it is difficult to adapt to the harsh construction environment in super high altitude area. SUMMARY

[0003] The technical problem to be solved by the application is to provide a method and system for determining the optimal construction window period of mass concrete in super high altitude area, so as to make the determination of the optimal construction window period of mass concrete in super high altitude area more accurate.

[0004] The technical solution adopted by the application to solve the technical problem is: a method for determining the optimal construction window period of mass concrete in super high altitude area, comprising the steps of: S1, collecting high-frequency meteorological factor original data of the wind field in the wind tower for N years per unit time, the high-frequency meteorological factor original data including air temperature, relative humidity, air pressure, irradiance and wind speed at a height of L; identifying and removing outliers, and filling in missing values by linear interpolation method; forming a high-frequency meteorological data set with unit time as the interval; Wherein, the unit time is less than 1h; the height L is 1-10m; S2, constructing a hierarchical structure model of the influence of high-frequency meteorological factors on concrete construction based on the AHP method according to the high-frequency meteorological data set in step S1, and calculating the standardized construction suitability index; S3, statistics of the monthly and daily construction suitability index frequency distribution, and generation of the monthly and daily construction suitability index frequency distribution table; S4, determining the optimal construction time window by the monthly and daily construction suitability index frequency distribution table.

[0005] Further, in the step S1, the abnormal values are identified and removed according to the 3σ criterion, and the missing values are filled by the linear interpolation method.

[0006] Further, the step S2 specifically comprises the following steps: S201, constructing a hierarchical structure model of the influence of high-frequency meteorological factors on the construction of mass concrete; S202, using the 1-9 scale method to compare the relative importance of air temperature, relative humidity, air pressure, irradiance and wind speed pairwise, and constructing a judgment matrix; the weights of air temperature, relative humidity, air pressure, irradiance and wind speed are obtained by calculation respectively; S203, performing consistency test on the judgment matrix; when the consistency test is qualified, the index data of each high-frequency meteorological factor is standardized according to the high-frequency meteorological element suitability standard; the construction suitability index SSI is calculated according to the standardized index data of each high-frequency meteorological factor; the standardized construction suitability index is obtained by standardizing the construction suitability index SSI .

[0007] Further, the step S203 comprises the following steps: S2031, calculating the maximum eigenvalue λ max : ; Wherein, A is the judgment matrix; W is the approximate eigenvector of the judgment matrix A; W i is the normalized vector; n is the order of the judgment matrix A; Calculate the consistency index CI: ; Wherein, n is the order of the judgment matrix A; According to the consistency index CI and the random consistency index RI, the consistency ratio CR is calculated: ; Wherein, the random consistency index RI is obtained according to the order of the matrix; The threshold value of the consistency ratio CR is set to 0.1, when CR < 0.1, the consistency test of the judgment matrix is qualified, and the weight distribution is reasonable; S2032, the index data of each high-frequency meteorological factor is standardized according to the high-frequency meteorological element suitability standard; Standardization of air temperature index data: ; wherein, T is the average temperature data per unit time; is the standardized temperature index data; Standardization of relative humidity index data: ; wherein, H is the average relative humidity data per unit time; is the standardized relative humidity index data; Standardization of air pressure index data: ; wherein, P is the average air pressure data per unit time; is the standardized air pressure index data; Standardization of irradiance index data: ; wherein, I is the average irradiance data per unit time; is the standardized irradiance index data; Standardization of wind speed index data: ; wherein, W is the average wind speed data per unit time; is the standardized wind speed index data; S2033, using the weighted average method to calculate the construction suitability index SSI: ; wherein, is the weight of the ith high-frequency meteorological factor index; is the standardized data of the ith high-frequency meteorological factor index; S2034, using the range standardization formula to standardize the construction suitability index SSI to obtain the standardized construction suitability index ; The range standardization formula is: ; The calculation formula of the standardized construction suitability index is: ; wherein, SSI is any construction suitability index in the statistical period; SSI MIN is the minimum value of the construction suitability index per unit time in the statistical period; SSI MAXThis represents the maximum value of the construction suitability index per unit time within the statistical period.

[0008] Furthermore, step S3 includes the following steps: S301, Settings The threshold is 0.6, calculated through iteration. Sequence, marked ≥0.6 time points; S302, using months and days as time periods, calculates the conditions that are met within each period. For a continuous time period of a threshold condition, calculate its duration and the number of occurrences. S303, Based on the statistical results, calculate the frequency of the construction suitability index distribution for each month and day, and generate a frequency distribution table of the construction suitability index for each month and day; The formula for calculating frequency is: ; Where N is the number of times the time period that meets the condition occurs; T represents the total number of unit time periods within this time period.

[0009] Furthermore, step S4 includes the following steps: S401. From the frequency distribution table of construction suitability index for each month and day, select the time period with the highest frequency and a continuous duration of not less than 4 hours as the preliminary recommended best construction time window. S402: Obtain short-term weather forecast data for the next 3 to 7 days from the local meteorological department, dynamically adjust the construction window, and obtain the final optimal construction time window.

[0010] Furthermore, step S4 also includes step S403, which pushes the optimal construction time window information to the construction management terminal and provides early warnings for unsuitable construction periods.

[0011] Furthermore, the unit time in step S1 is 10 minutes.

[0012] The system for determining the optimal construction window for large-volume concrete in ultra-high altitude areas adopts a method for determining the optimal construction window for large-volume concrete in ultra-high altitude areas. It includes a module for acquiring and preprocessing high-frequency meteorological factor raw data, a module for constructing a construction suitability index, a module for statistically analyzing the frequency of the construction suitability index, and a module for determining the optimal construction time window. The high-frequency meteorological factor raw data acquisition and preprocessing module is used to collect high-frequency meteorological factor raw data from the wind farm's meteorological towers over N years at unit time intervals. The high-frequency meteorological factor raw data includes air temperature, relative humidity, air pressure, irradiance, and wind speed at a height of L; identify and remove outliers, and fill in missing values ​​using linear interpolation; and form a high-frequency meteorological dataset at unit time intervals. The construction suitability index construction module is configured to construct a hierarchical structure model of the influence of high-frequency meteorological factors on concrete construction based on the AHP method according to the high-frequency meteorological data set in step S1, and obtain a standardized construction suitability index by calculation; The construction suitability index frequency statistics module is configured to statistically analyze the monthly and daily construction suitability index frequency distribution, and generate a monthly and daily construction suitability index frequency distribution table; The optimal construction time window period determination module is configured to determine the optimal construction time window period through the monthly and daily construction suitability index frequency distribution table.

[0013] Compared with the prior art, the method and system for determining the optimal construction window period of mass concrete in an ultrahigh-altitude region provided by the present application make the determination of the optimal construction window period of mass concrete in an ultrahigh-altitude region more accurate.

[0014] First, the short-period variation characteristics of high-frequency meteorological factors in a high-altitude region are comprehensively and accurately captured by using 10-min high-frequency meteorological data, which greatly improves the support accuracy of meteorological data for construction time decision-making compared with low-frequency data in the background technology.

[0015] Second, the influence of multiple high-frequency meteorological factors on concrete construction is comprehensively considered by using the AHP method to determine the weight of each high-frequency meteorological factor, so that the construction suitability index is more scientific and reasonable, and the suitability of meteorological conditions for construction is effectively quantified.

[0016] Third, the monthly and daily construction suitability index frequency distribution is statistically analyzed, which can mine the rules of suitable construction under different time scales and provide long-term and short-term time window references for construction plan development.

[0017] Fourth, the recommended window is dynamically adjusted in combination with short-term meteorological forecast data, which enhances the flexibility and adaptability of construction time decision-making and reduces the risk of weather changes to construction quality. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a flowchart of the present application. DETAILED DESCRIPTION

[0019] The present application will be further described below in combination with the accompanying drawings Figure 1 and examples.

[0020] The method for determining the optimal construction window period of mass concrete in an ultrahigh-altitude region comprises the following steps: S1, collect the high-frequency meteorological factor original data of the wind farm in each unit time for N years, the high-frequency meteorological factor original data includes the temperature, relative humidity, air pressure, irradiance and wind speed at a height of L; identify and eliminate outliers, and use linear interpolation method to fill in the missing values; form a high-frequency meteorological data set with unit time as the interval; wherein, 1≤N≤3, preferably, N=1; The unit time is less than 1h, preferably 10min; The height L is 1-10m, preferably L=10m.

[0021] Specifically, 2024.5.1-2025.4.30 is selected as a period of one year. The high-frequency meteorological data set includes 52560 groups of effective data, and is stored in a time series database, as shown in Figure 1 .

[0022] Specifically, in the step S1, the outliers are identified and eliminated according to the 3σ criterion, and the missing values are filled in by using the linear interpolation method.

[0023] S2, according to the high-frequency meteorological data set in step S1, a hierarchical structure model of the influence of high-frequency meteorological factors on concrete construction is constructed based on the AHP method, and a standardized construction suitability index is obtained by calculation.

[0024] Specifically, the AHP method is the analytic hierarchy process.

[0025] Specifically, the step S2 specifically includes the following steps: S201, constructing a hierarchical structure model of the influence of high-frequency meteorological factors on mass concrete construction; For the foundation concrete construction of the wind farm in the super-high altitude area, the high-frequency meteorological factors affecting the mass concrete construction are listed in two levels, and a two-level structure including a target layer and a criterion layer is constructed, as shown in Table 1.

[0026] Table 1

[0027] S202, using the 1-9 scale method to compare the relative importance of temperature, relative humidity, air pressure, irradiance and wind speed two by two, and constructing a judgment matrix, as shown in Table 2; by calculation, the weights of temperature, relative humidity, air pressure, irradiance and wind speed are 0.495, 0.247, 0.033, 0.121 and 0.105, respectively; Table 2

[0028] S203, performing consistency check on the judgment matrix; when the consistency check is qualified, performing standardization on each high-frequency meteorological factor index data according to the high-frequency meteorological element suitability standard; calculating a construction suitability index SSI according to the standardized high-frequency meteorological factor index data; performing standardization on the construction suitability index SSI to obtain a standardized construction suitability index .

[0029] Specifically, step S203 includes the following steps: S2031, calculating the maximum eigenvalue λ of the judgment matrix max : ; Wherein, A is the judgment matrix; W is an approximate eigenvector of the judgment matrix A; W i is a normalized vector; n is the order of the judgment matrix A; Calculate the consistency index CI: ; Wherein, n is the order of the judgment matrix A; According to the consistency index CI and the random consistency index RI, the consistency ratio CR is calculated: ; Wherein, the random consistency index RI is obtained according to the order of the matrix; The threshold of the consistency ratio CR is set to 0.1, when CR < 0.1, the judgment matrix consistency check is qualified, and the weight distribution is reasonable; S2032, performing standardization on each high-frequency meteorological factor index data according to the high-frequency meteorological element suitability standard; Standardization of temperature index data: ; Wherein, T is the average temperature data per unit time; is the standardized temperature index data; Standardization of relative humidity index data: ; Wherein, H is the average relative humidity data per unit time; is the standardized relative humidity index data; Standardization of air pressure index data: ; Wherein, P is the average air pressure data per unit time; is the standardized air pressure index data; Irradiance index data standardization: ; wherein I is the average irradiance data per unit time; is the normalized irradiance index data; Wind speed index data standardization: ; wherein W is the average wind speed data per unit time; is the normalized wind speed index data; S2033, using the weighted average method to calculate the construction suitability index SSI: ; wherein, is the weight of the i-th high-frequency meteorological factor index; is the normalized i-th high-frequency meteorological factor index data; ; S2034, using the range standardization formula to standardize the construction suitability index SSI to obtain the normalized construction suitability index ; The range standardization formula is: ; The calculation formula of the normalized construction suitability index is: ; wherein SSI is any construction suitability index in the statistical period; SSI MIN is the minimum value of the construction suitability index per unit time in the statistical period; SSI MAX is the maximum value of the construction suitability index per unit time in the statistical period.

[0030] S3, statistics of the construction suitability index frequency distribution in each month and day, and generate the construction suitability index frequency distribution table in each month and day.

[0031] Specifically, the step S3 includes the following steps: S301, setting the threshold value to 0.6, traversing the calculation results, and marking out the time points of ≥0.6; S302, taking month and day as the time period, statistics of the continuous time period in each period that meets the threshold condition, calculating its duration and occurrence times; S303, according to the statistical result, calculating the frequency of the construction suitability index distribution in each month and day, and generating a frequency distribution table of the construction suitability index in each month and day; The frequency calculation formula is: ; Wherein, N is the number of time periods meeting the condition; T is the total number of unit time periods in the time period.

[0032] The unit time in step S303 is 10 min, that is, T is the total number of 10 min time periods in the time period.

[0033] Table 3 shows the classification of the standardized construction suitability index .

[0034] Table 3

[0035] Table 4 shows the frequency distribution of the construction suitability index in each month.

[0036] Table 4

[0037] Table 5 shows the frequency distribution of the construction suitability index in 24 hours in a day throughout the year.

[0038] Table 5

[0039] Table 6 shows the frequency distribution of the construction suitability index in 24 hours in a day in July.

[0040] Table 6

[0041] S4, determine the best construction time window period through the frequency distribution table of the construction suitability index in each month and day.

[0042] Specifically, the step S4 includes the following steps: S401, select the time period with the highest frequency and continuous duration not less than 4h from the frequency distribution table of the construction suitability index in each month and day as the preliminary recommended best construction time window period; S402, obtain the short-term weather forecast data provided by the local meteorological department for the next 3-7 days, dynamically adjust the construction time, and obtain the final best construction time window period.

[0043] Specifically, when each day in the short-term weather forecast data for the next 3-7 days is sunny, the final best construction time window period is obtained.

[0044] S403, push the best construction time window information to the construction management terminal, and prewarn and prompt the inappropriate construction period.

[0045] The system for determining the best construction window period of mass concrete in an ultrahigh-altitude area adopts the method for determining the best construction window period of mass concrete in an ultrahigh-altitude area, and comprises a high-frequency meteorological factor original data acquisition and preprocessing module, a construction suitability index construction module, a construction suitability index frequency statistical module, and a best construction time window period determination module. The high-frequency meteorological factor original data acquisition and preprocessing module is used to acquire the high-frequency meteorological factor original data of the wind measurement tower in the wind farm in N years per unit time, and the high-frequency meteorological factor original data includes the temperature, relative humidity, air pressure, irradiance and wind speed at a height of L; abnormal values are identified and removed, and the missing values are filled by using a linear interpolation method; and a high-frequency meteorological data set with a unit time interval is formed. The construction suitability index construction module is used to construct a hierarchical structure model of the influence of high-frequency meteorological factors on concrete construction based on the AHP method according to the high-frequency meteorological data set in step S1, and the standardized construction suitability index is obtained by calculation. The construction suitability index frequency statistical module is used to statistically analyze the construction suitability index frequency distribution in each month and day, and generate a construction suitability index frequency distribution table in each month and day. The best construction time window period determination module is used to determine the best construction time window period through the construction suitability index frequency distribution table in each month and day.

[0046] The embodiments of the specific embodiments are the preferred embodiments of the present application, and are not limited to the protection scope of the present application. Any equivalent changes made according to the structure, shape and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A method for determining the optimal construction window for large-volume concrete in ultra-high altitude areas, characterized in that... Including the following steps: S1. Collect raw high-frequency meteorological factor data from the wind farm's meteorological towers over N years at unit time intervals. The raw high-frequency meteorological factor data includes air temperature, relative humidity, air pressure, irradiance, and wind speed at a height of L. Identify and remove outliers, and fill in missing values ​​using linear interpolation. Form a high-frequency meteorological dataset at unit time intervals. Among them, the unit time is less than 1 hour; the height L is 1 to 10 meters. S2. Based on the high-frequency meteorological dataset in step S1, construct a hierarchical model of the influence of high-frequency meteorological factors on concrete construction using the AHP method, and calculate the standardized construction suitability index. S3, Calculate the frequency distribution of the construction suitability index for each month and day, and generate a table of the frequency distribution of the construction suitability index for each month and day; S4. The optimal construction time window is determined by the frequency distribution table of the construction suitability index for each month and day.

2. The method for determining the optimal construction window period for large-volume concrete in ultra-high altitude areas as described in claim 1, characterized in that, In step S1, outliers are identified and removed according to the 3σ criterion, and missing values ​​are filled in using linear interpolation.

3. The method for determining the optimal construction window period for large-volume concrete in ultra-high altitude areas as described in claim 1, characterized in that, Step S2 specifically includes the following steps: S201, Construct a hierarchical model of the impact of high-frequency meteorological factors on the construction of large-volume concrete. S202 uses a 1-9 scale to compare the relative importance of temperature, relative humidity, air pressure, irradiance, and wind speed pairwise to construct a judgment matrix; the weights of temperature, relative humidity, air pressure, irradiance, and wind speed are calculated respectively. S203, perform a consistency check on the judgment matrix; if the consistency check is successful, standardize the data of each high-frequency meteorological factor index according to the suitability standard of high-frequency meteorological elements; calculate the construction suitability index SSI based on the standardized data of each high-frequency meteorological factor index; standardize the construction suitability index SSI to obtain the standardized construction suitability index. .

4. The method for determining the optimal construction window period for large-volume concrete in ultra-high altitude areas as described in claim 3, characterized in that, Step S203 includes the following steps: S2031, Calculate the largest eigenvalue λ of the judgment matrix. max : ； Where A is the judgment matrix; W is an approximate eigenvector of the judgment matrix A; W i A normalized vector; n is the order of the judgment matrix A; Calculate the consistency index (CI): ； Where n is the order of the judgment matrix A; The consistency ratio CR is calculated based on the consistency index CI and the random consistency index RI: ； Among them, the random consistency index RI is obtained by looking up a table based on the matrix order; The threshold for the consistency ratio (CR) is set to 0.

1. When CR < 0.1, the consistency check of the judgment matrix is ​​considered to be successful and the weight allocation is reasonable. S2032, based on the suitability standards for high-frequency meteorological elements, standardize the data of each high-frequency meteorological factor index. Standardization of temperature index data: ； Where T represents the average temperature data per unit time; Standardized temperature index data; Standardization of relative humidity index data: ; Where H represents the average relative humidity data per unit time; This refers to the standardized relative humidity data. Standardization of air pressure index data: ; Where P represents the average air pressure data per unit time; This refers to standardized air pressure data. Standardization of irradiance index data: ; Where I represents the average irradiance data per unit time; The data represents the standardized irradiance index. Standardization of wind speed data: ; Where W represents the average wind speed data per unit time; This refers to standardized wind speed data. S2033, Calculate the Construction Suitability Index (SSI) using the weighted average method: ； in, The weight of the i-th high-frequency meteorological factor indicator; This refers to the standardized data of the i-th high-frequency meteorological factor index. S2034, the construction suitability index (SSI) is standardized using the range standardization formula to obtain the standardized construction suitability index. ; The standardization formula for the range is: ; Standardized construction suitability index The calculation formula is: ； Wherein, SSI is any construction suitability index within the statistical period; SSI MIN It represents the minimum value of the construction suitability index per unit time within the statistical period; SSI MAX This represents the maximum value of the construction suitability index per unit time within the statistical period.

5. The method for determining the optimal construction window period for large-volume concrete in ultra-high altitude areas as described in claim 1, characterized in that, Step S3 includes the following steps: S301, Settings The threshold is 0.6, calculated through iteration. Sequence, marked ≥0.6 time points; S302, using months and days as time periods, calculates the conditions that are met within each period. For a continuous time period of a threshold condition, calculate its duration and the number of occurrences. S303, Based on the statistical results, calculate the frequency of the construction suitability index distribution for each month and day, and generate a frequency distribution table of the construction suitability index for each month and day; The formula for calculating frequency is: ; Where N is the number of times the time period that meets the condition occurs; T represents the total number of unit time periods within this time period.

6. The method for determining the optimal construction window period for large-volume concrete in ultra-high altitude areas as described in claim 1, characterized in that, Step S4 includes the following steps: S401. From the frequency distribution table of construction suitability index for each month and day, select the time period with the highest frequency and a continuous duration of not less than 4 hours as the preliminary recommended best construction time window. S402: Obtain short-term weather forecast data for the next 3 to 7 days from the local meteorological department, dynamically adjust the construction window, and obtain the final optimal construction time window.

7. The method for determining the optimal construction window period for large-volume concrete in ultra-high altitude areas as described in claim 6, characterized in that, Step S4 also includes step S403, which pushes the optimal construction time window information to the construction management terminal and provides early warnings for unsuitable construction periods.

8. The method for determining the optimal construction window period for large-volume concrete in ultra-high altitude areas as described in claim 1, characterized in that, The unit time in step S1 is 10 minutes.

9. A system for determining the optimal construction window for large-volume concrete in ultra-high altitude areas, employing the method for determining the optimal construction window for large-volume concrete in ultra-high altitude areas as described in any one of claims 1-8, characterized in that... It includes modules for acquiring and preprocessing raw data of high-frequency meteorological factors, constructing a construction suitability index, statistically analyzing the frequency of the construction suitability index, and determining the optimal construction time window. The high-frequency meteorological factor raw data acquisition and preprocessing module is used to collect high-frequency meteorological factor raw data from the wind farm's meteorological towers over N years at unit time intervals. The high-frequency meteorological factor raw data includes air temperature, relative humidity, air pressure, irradiance, and wind speed at a height of L; identify and remove outliers, and fill in missing values ​​using linear interpolation; and form a high-frequency meteorological dataset at unit time intervals. The construction suitability index construction module is used to construct a hierarchical model of the influence of high-frequency meteorological factors on concrete construction based on the high-frequency meteorological dataset in step S1 and the AHP method, and to calculate the standardized construction suitability index. The construction suitability index frequency statistics module is used to statistically analyze the frequency distribution of the construction suitability index for each month and day, and generate a table of the frequency distribution of the construction suitability index for each month and day. The optimal construction time window determination module is used to determine the optimal construction time window by using the frequency distribution table of construction suitability index for each month and day.

Images