Method and device for analyzing wind resistance parameters of a target region

Abstract

The application discloses a target area wind-resistant parameter analysis method, which comprises the following steps: reference meteorological station selection, consistency correction, wind speed long time sequence construction, return period wind speed calculation, typical gale process simulation, engineering area and meteorological station gale correlation model, and engineering area wind-resistant parameter determination. The wind-resistant parameter fusion analysis method provided by the application is based on observation data and numerical simulation, fully utilizes the advantages of meteorological observation data near the engineering and numerical modes, and can realize the determination of the wind-resistant parameters in a complex terrain area with lack of data, thereby providing a reference basis for engineering wind-resistant design.

Description

Technical Field

[0001] This invention relates to the field of meteorological observation, and in particular to a method and equipment for analyzing wind resistance parameters of a target area. Background Technology

[0002] Wind resistance parameters, such as return-time wind speed, are essential for various building designs. Return-time wind speed is typically calculated based on long-term observations from meteorological stations. However, an increasing number of projects now pass through sparsely populated areas, while national meteorological stations are usually located in urban areas. The terrain features of the meteorological station locations may not be representative of the terrain features of the project site, making it difficult to determine the wind resistance parameters. Furthermore, with the increasing demands for high-quality construction and operation in modern engineering projects, differentiated and precise parameter design is becoming increasingly important. Although there are now numerous ground-based meteorological stations, national meteorological stations are still relatively few, and regional meteorological stations have short observation periods, their site environments may not meet national meteorological observation standards, and there are also questions about the representativeness of regional meteorological stations for the project.

[0003] In existing technologies, one method for determining wind resistance parameters for engineering projects is to establish on-site observation stations for long-term monitoring, establish correlations with national meteorological stations, and then calculate the wind resistance parameters. This method is time-consuming and unsuitable for many projects with short construction periods. If the project requires extensive deployment of observation equipment (such as long-distance power transmission lines or railways), the cost becomes prohibitively high, making it almost impractical. Therefore, there is an urgent need for a method that can obtain the wind resistance parameters of a target area based on existing observation data at a low cost. Summary of the Invention

[0004] The purpose of this invention is to provide a method and device for analyzing wind resistance parameters of a target area, which can calculate the return period wind speed for a target area in a complex terrain region, provide a reference for wind resistance design in the target area, and only requires existing observation data, without the need for costly long-term observation.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for analyzing wind resistance parameters of a target area, comprising:

[0007] Step 1: Determine the reference meteorological stations based on the project requirements and obtain the observation data of the reference meteorological stations, including the time series of the annual maximum wind speed of the reference meteorological stations.

[0008] Step 2: If there is a sudden change in the annual maximum wind speed time series, the ratio method is used to correct the annual maximum wind speed time series; if there is no sudden change, step 2 is skipped.

[0009] Step 3: Determine whether the recording period of the annual maximum wind speed time series is consistent with the period from the establishment of the reference meteorological station to the present. If they are inconsistent, extend the annual maximum wind speed time series; if they are consistent, skip step 3.

[0010] Step 4: Using the annual maximum wind speed time series, calculate the return period wind speed of the reference meteorological station based on the frequency corresponding to different return periods;

[0011] Step 5: Simulate a typical strong wind process in the target area to obtain the maximum wind speed distribution in the target area.

[0012] Step 6: For the distribution of maximum wind speed during the process, use interpolation to determine the maximum wind speed of the reference meteorological station and the target area, and calculate the wind speed ratio.

[0013] Step 7: Calculate the return period wind speed of the target area based on the return period wind speed and strong wind ratio of the reference meteorological stations.

[0014] Furthermore, in step one above, the reference meteorological station can be one or more meteorological stations that meet the engineering requirements.

[0015] Furthermore, in step two above, let the starting year of the abrupt change be year j, and calculate the average annual maximum wind speed of 1-j and jn (where n is the most recent year of the annual maximum wind speed record). and And based on the ratio of the two The annual maximum wind speed before the abrupt change point is corrected.

[0016] Furthermore, in step three above, the sequence extension of the annual maximum wind speed time series specifically refers to: calculating the annual maximum wind speed V based on the 2-minute wind speed records. i2minmax (i = 1, ..., n), take the annual maximum wind speed V for the same period. imax Using ratio The annual maximum wind speed is calculated from the 2-minute wind speed record, and then combined with the existing annual maximum wind speed records to form a longer time series of annual maximum wind speeds.

[0017] Furthermore, in step five above, the simulation of typical strong wind processes includes: selection of typical strong wind processes, debugging of numerical models, simulation of strong wind processes, and verification and correction of simulation results.

[0018] Furthermore, step six above also includes determining the maximum wind speed V of the reference meteorological station and the target area based on the maximum wind speed distribution of the process. i参证站 and V i目标 The maximum value is used to determine the wind ratio p = V between the reference meteorological station and the target area. 目标max / V参证站max .

[0019] Furthermore, step seven above also includes determining the return period wind speed V based on the reference meteorological station. p参证站 Calculate the return period wind speed V of the target area using the wind ratio p. p =V p参证站 ×p.

[0020] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements any of the methods described above in the embodiments of the present invention.

[0021] Invention Function and Effect

[0022] This invention primarily addresses the problem of determining wind resistance parameters for certain engineering projects, a problem present in existing technologies. Considering that an increasing number of engineering projects pass through sparsely populated areas, while national meteorological stations are typically located in urban areas, the terrain features of the meteorological station locations may not be representative of the project site's terrain features, leading to difficulties in determining wind resistance parameters. Furthermore, with the increasing demands for high-quality construction and operation in modern engineering projects, differentiated and precise parameter design is becoming increasingly important. Some meteorological stations have short observation periods, and their site environments may not meet national meteorological observation standards. This invention utilizes existing observation data combined with numerical simulation analysis methods. Leveraging the advantage of numerical models in effectively characterizing the impact of terrain on wind fields, it establishes a strong wind correlation between reference meteorological stations and the project location, thereby calculating the wind resistance parameters for the project location and enabling more efficient determination of these parameters.

[0023] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0024] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0025] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below.

[0026] Figure 1 A flowchart illustrating an analysis method provided in an embodiment of the present invention;

[0027] Figure 2 This invention provides a wind speed consistency correction analysis for the Thirteen Rooms Station in an embodiment of the invention.

[0028] Figure 3 A hardware structure diagram of a computer device provided in an embodiment of the present invention; Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or apparatus.

[0031] <Example>

[0032] Figure 1 This is a schematic flowchart illustrating an analysis method provided in an embodiment of the present invention. (Reference) Figure 1 The present invention provides a method for analyzing wind resistance parameters of a target area, which specifically includes the following steps:

[0033] Step 1: Determine the reference meteorological stations based on the project requirements and obtain the observation data of the reference meteorological stations, including the time series of the annual maximum wind speed of the reference meteorological stations.

[0034] The selection of reference meteorological stations generally considers national meteorological stations within a 100km radius of the target area. If meteorological stations are sparse, a wider range can be considered. The historical development of the meteorological station and the stability and magnitude of its annual average wind speed are analyzed. Meteorological stations with a high number of years with an annual average wind speed less than 2m / s are generally not selected as reference stations. Meteorological stations with a clear decreasing trend in wind speed year by year indicate changes in the surrounding environment and are also unsuitable as reference stations. Meteorological stations with obvious abrupt changes in their annual average wind speed sequences can be considered as reference stations if the sequences before and after the abrupt change are relatively stable. Reference meteorological stations are generally selected from those located upwind of the target area.

[0035] For target areas with meteorological observations, reference meteorological stations are determined by analyzing the correlation between meteorological stations and concurrently observed wind speeds in the target area. The correlation analysis includes the correlation coefficients of all concurrent wind speeds and the consistency of wind speed fluctuations during periods of high wind. Meteorological stations with high correlation coefficients and good consistency of wind speed fluctuations during periods of high wind are selected as reference meteorological stations.

[0036] Furthermore, in step one above, the reference meteorological station can be one or more meteorological stations that meet the engineering requirements. When selecting multiple reference meteorological stations, representative reference meteorological stations from different directions can be selected, and the wind resistance parameters of the target area can be comprehensively calculated by combining the observation data of all reference meteorological stations.

[0037] Continue to refer to Figure 1 Step two: If there are abrupt changes in the annual maximum wind speed time series, the ratio method is used to correct the annual maximum wind speed time series; if there are no abrupt changes, step two is skipped.

[0038] For abrupt changes in the annual maximum wind speed time series, the causes of these changes are determined to be related to the relocation of the meteorological station or the replacement of instruments, based on the historical information of the meteorological station. Therefore, the ratio method is used to correct the wind speed series.

[0039] In this embodiment of the invention, let the starting year of the mutation point be year j, and calculate the average annual maximum wind speed of 1-j and jn (where n is the most recent year of the annual maximum wind speed record). and And based on the ratio of the two The annual maximum wind speed before the abrupt change point is corrected.

[0040] Step 3: Determine whether the recording period of the annual maximum wind speed time series is consistent with the period from the establishment of the reference meteorological station to the present. If they are inconsistent, extend the annual maximum wind speed time series; if they are consistent, skip step 3.

[0041] First, determine if the recorded period of the annual maximum wind speed sequence is the same as the period since the station was established. If they are the same, there is no need to further extend the wind speed time series. If they are different, then the wind speed time series needs to be extended.

[0042] Furthermore, in step three above, the sequence extension of the annual maximum wind speed time series specifically refers to: calculating the annual maximum wind speed V based on the 2-minute wind speed records. i2minmax (i = 1, ..., n), take the annual maximum wind speed V for the same period. imax Using ratio The annual maximum wind speed is calculated from the 2-minute wind speed record, and then combined with the existing annual maximum wind speed records to form a longer time series of annual maximum wind speeds.

[0043] Step 4: Using the annual maximum wind speed time series, calculate the return period wind speed of the reference meteorological station based on the frequency corresponding to different return periods;

[0044] The annual maximum wind speed sequence is generally considered to conform to an extreme value type I distribution. Using the long-term annual maximum wind speed sequence constructed in step three, the parameters of the extreme value type I distribution function are obtained according to the Gumbel method. Based on the frequencies corresponding to different return periods, the return period wind speeds at the meteorological station locations are calculated to obtain the required return period wind speed V for the target area (e.g., 30-year, 50-year, 100-year, etc.). p参证站 .

[0045] Step 5: Simulate a typical strong wind process in the target area to obtain the maximum wind speed distribution in the target area.

[0046] The simulation of typical gale processes includes the selection of typical gale processes, the debugging of numerical models, the simulation of gale processes, and the verification and correction of simulation results.

[0047] Typical gale events are selected primarily based on gale records from meteorological stations near the target area, or based on gale events observed in the target area. The selected gale events should be representative of the dominant gale characteristics of the region.

[0048] Numerical model debugging includes setting up the simulation region and testing different parameterization schemes, with the aim of determining the appropriate mesh settings and parameterization schemes for the target region.

[0049] A detailed numerical simulation back-calculation of the strong wind process was carried out for the target area to obtain three-dimensional atmospheric wind field data with high spatiotemporal resolution.

[0050] The simulation results were verified and analyzed using meteorological station observation data and target area observation data. Because numerical simulation results for complex terrain may have significant errors, planar corrections were performed using meteorological station observation data and target area observation data.

[0051] Step 6: For the distribution of maximum wind speed during the process, use interpolation to determine the maximum wind speed of the reference meteorological station and the target area, and calculate the wind speed ratio.

[0052] Based on the simulation results of several typical strong wind processes, the distribution of maximum wind speed within the simulated area was obtained. According to the verification and correction analysis results, several cases with good simulation performance were selected, and interpolation was used to determine the maximum wind speed of the reference meteorological station and the target area. Generally, inverse distance squared interpolation is used to obtain the maximum wind speed of the reference meteorological station and the target area from the gridded wind field data. If the terrain is very complex, and the actual elevation difference within a grid is large, it is necessary to first perform height correction on the wind speed on the grid before interpolation.

[0053] Furthermore, step six above also includes determining the maximum wind speed V of the reference meteorological station and the target area based on the maximum wind speed distribution of the process. i参证站 and V i目标 The maximum value is used to determine the wind ratio p = V between the reference meteorological station and the target area. 目标max / V 参证站max .

[0054] Step 7: Calculate the return period wind speed of the target area based on the return period wind speed and strong wind ratio of the reference meteorological stations.

[0055] Specifically, based on the return period wind speed V of the aforementioned reference meteorological station p参证站 Calculate the return period wind speed V of the target area using the wind ratio p. p =V p参证站 ×p.

[0056] Continue to refer to Figure 1 The working principle of the present invention will be explained in detail below using the ±1100kV ultra-high voltage direct current transmission line from Zhundong to Hami as an example, with reference to specific embodiments.

[0057] The ±1100kV ultra-high voltage direct current transmission line from Zhundong to Hami crosses the Tianshan Mountains and passes through a hundred-mile wind zone. National meteorological observation stations are scarce along the route, and the terrain is complex. This unique topography results in consistently high wind speeds, making it impossible to determine wind resistance parameters using conventional methods. Therefore, a method combining meteorological observation data and numerical simulation was adopted to determine the wind resistance parameters.

[0058] A method for fusion analysis of wind resistance parameters based on observational data and numerical simulation includes the following:

[0059] 1. Selection of reference meteorological stations

[0060] Eleven national meteorological stations along the Zhundong-Hami transmission line collected data. Through analysis of the stations' annual average wind speed, historical information, prevailing wind direction, number of days with strong winds, correlation analysis with concurrent data from meteorological stations and anemometer towers along the line, and wind consistency analysis, the reference meteorological stations were identified as Beitashan Station and Shisanjianfang Station. Beitashan Station was designated as the representative station for the northwest section of the line, and Shisanjianfang Station as the representative station for the southeast section.

[0061] 2. Consistency Analysis

[0062] Because the Shisanjianfang Station was relocated in 1999, and there were significant differences in wind speed before and after the relocation, a consistency correction was performed on the annual maximum wind speed sequence, such as... Figure 2 As shown.

[0063] 3. Construction of long-term series

[0064] The annual maximum wind speeds of the two reference meteorological stations have been recorded since the stations were built (in the 1950s and 1960s). Therefore, there is no need to perform time conversion, and the existing annual maximum wind speed series can be used as the series for the return period calculation.

[0065] 4. Calculation of wind speed during the return period

[0066] The return period wind speeds at Beitashan and Shisanjianfang stations were calculated using the Günbel method, and the results are shown in Table 1.

[0067] Table 1 Wind speeds at Beitashan and Shisanjianfang stations during the recurrence period

[0068]

[0069] 5. Simulation of typical strong wind processes

[0070] The region through which the railway line passes is dominated by cold air-driven strong winds; therefore, the selection of strong wind events primarily considered cold air-driven winds. Based on data from meteorological stations near the railway line, on-site observation data, and atmospheric circulation patterns, eight strong wind events were selected.

[0071] The model used is the mesoscale meteorological model WRF (Weather Research Forecast). Testing showed that the simulation employed a four-layer nesting structure with horizontal resolutions of 27 km, 9 km, 3 km, and 1 km. The number of horizontal grid points for the four nesting layers were 151×151, 181×151, 301×211, and 601×451, respectively, with 37 vertical layers. Initial and boundary conditions were based on NCEP reanalysis data. Topographic data were obtained from USGS data at a horizontal resolution of 30″ and SRTM3 3″, and surface vegetation type data were obtained from USGS data at a horizontal resolution of 30″. Model physical process parameter settings were as follows: microphysical processes used the Ferrier (new Eta) microphysics scheme; longwave radiation used the Rrtm scheme; shortwave radiation used the Dudhia scheme; near-surface processes used the Monin-Obukhov scheme; land surface processes used the Unified Noah land-surface model scheme; and boundary layer processes used the YSU scheme. The model output time interval was 10 minutes.

[0072] The simulation results were corrected using meteorological station and field observation data.

[0073] 6. Correlation model between engineering area and meteorological station winds

[0074] For the simulation results of the eight gale events, the maximum wind speed at each grid point of each gale event was first extracted, and the maximum wind speed along the route and at the reference meteorological stations and field observation points was calculated by the inverse distance squaring method.

[0075] The maximum wind speeds along the route and at reference meteorological stations and field observation points during eight strong wind events were selected, and the wind ratio p = V at each point along the route was calculated. 工程max / V 参证站max .

[0076] 7. Determination of wind resistance parameters for the project area

[0077] Based on the return period wind speeds of the two reference meteorological stations (Table 1) and the wind speed ratio p of each point along the route to the reference meteorological stations, the return period wind speeds of each point along the route are calculated.

[0078] The wind resistance parameter fusion analysis method based on the combination of observation data and numerical simulation provided by this invention makes full use of the advantages of meteorological observation data and numerical models near the project, and can determine the wind resistance parameters in areas with complex terrain and lack of data, providing a reference for the wind resistance design of the project.

[0079] This invention also provides a computer device, including a memory and a processor. The memory stores executable code, and when the processor executes the executable code, it implements the method described in any of the above embodiments. Specifically, refer to... Figure 3 .

[0080] The computer device of this invention may include: a processor, a memory, an input / output interface, a communication interface, and a bus. The processor, memory, input / output interface, and communication interface are interconnected internally via the bus. The processor executes executable modules stored in the memory, such as... Figure 1 The computer program corresponding to the method embodiment shown.

[0081] The processor can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0082] The memory can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage devices, dynamic storage devices, etc. The memory can store the operating system and other applications. When the technical solutions provided in the embodiments of this application are implemented through software or firmware, the relevant program code is stored in the memory and called and executed by the processor.

[0083] Input / output interfaces are used to connect input / output modules to enable information input and output. Input / output modules can be configured as components within the device (not shown in the diagram) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0084] The communication interface is used to connect the communication module (not shown in the figure) to enable communication and interaction between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0085] A bus is a pathway that transmits information between various components of a device, such as processors, memory, input / output interfaces, and communication interfaces.

[0086] It should be noted that although the above-described device only shows the processor, memory, input / output interface, communication interface, and bus, in actual implementation, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this application, and not necessarily all the components shown in the figures.

[0087] Functions and effects of the embodiments

[0088] This invention provides a method for analyzing wind resistance parameters in a target area, solving the problem of difficulty in determining wind resistance parameters for certain engineering areas in existing technologies. Considering that more and more engineering projects now pass through sparsely populated areas, while national meteorological stations are usually located in urban areas, the terrain features of the meteorological station locations cannot represent the terrain features of the engineering project locations, leading to difficulties in determining the wind resistance parameters. Simultaneously, with the increasing demands for high-quality construction and operation in modern engineering projects, differentiated and precise parameter design is becoming increasingly important. Some meteorological stations have short observation periods, and their site environments cannot guarantee compliance with national meteorological observation standards. This invention utilizes existing observation data and a numerical simulation-based analysis method. Leveraging the advantage of numerical models in effectively characterizing the impact of terrain on wind fields, it establishes a strong wind correlation between reference meteorological stations and the engineering project location, thereby calculating the wind resistance parameters for the engineering project location, enabling more efficient determination of these parameters.

[0089] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for analyzing wind resistance parameters of a target area, characterized in that, The method includes: Step 1: Determine the reference meteorological stations according to the project requirements and obtain the observation data of the reference meteorological stations, including the time series of the annual maximum wind speed of the reference meteorological stations; Step 2: If there is a sudden change in the annual maximum wind speed time series, the ratio method is used to correct the annual maximum wind speed time series; if there is no sudden change, step 2 is skipped. Step 3: Determine whether the recording period of the annual maximum wind speed time series is consistent with the period from the establishment of the reference meteorological station to the present. If they are inconsistent, extend the annual maximum wind speed time series. If they are consistent, skip step 3. Step 4: Using the annual maximum wind speed time series, calculate the return period wind speed of the reference meteorological station based on the frequency corresponding to different return periods; Step 5: Simulate a typical strong wind process in the target area to obtain the maximum wind speed distribution of the target area. Step 6: For the maximum wind speed distribution during the process, use interpolation to determine the maximum wind speed of the reference meteorological station and the target area, and calculate the wind speed ratio. Step 7: Calculate the return period wind speed of the target area based on the return period wind speed of the reference meteorological station and the strong wind ratio.

2. The method for analyzing wind resistance parameters of a target area according to claim 1, characterized in that, Step one includes: The reference meteorological stations are one or more meteorological stations that meet the project requirements.

3. The method for analyzing wind resistance parameters of a target area according to claim 1, characterized in that, The correction of the annual maximum wind speed time series using the ratio method includes: Let the starting year of the abrupt change be year j. Calculate the average annual maximum wind speed for years 1-j and 1-n. and And based on the ratio of the two. The annual maximum wind speed before the abrupt change point is corrected, where n is the most recent year of the annual maximum wind speed record.

4. The method for analyzing wind resistance parameters of a target area according to claim 1, characterized in that, The process of extending the time series of the annual maximum wind speed includes: Calculate the annual maximum wind speed Vi2minmax based on 2-minute wind speed records, i=1, ..., n. Take the annual maximum wind speed Vimax for the same period and use the ratio... The annual maximum wind speed is calculated from the 2-minute wind speed record, and then combined with the existing annual maximum wind speed records to form a longer time series of annual maximum wind speeds.

5. The method for analyzing wind resistance parameters of a target area according to claim 1, characterized in that, The simulation of typical strong wind processes includes: selection of typical strong wind processes, debugging of numerical models, simulation of strong wind processes, and verification and correction of simulation results.

6. The method for analyzing wind resistance parameters of a target area according to claim 1, characterized in that, Step six includes: Based on the maximum wind speed distribution during the process, determine the maximum wind speed of the reference meteorological station and the target area during the process. and The maximum value is used to determine the wind ratio between the reference meteorological station and the target area. .

7. The method for analyzing wind resistance parameters of a target area according to claim 1, characterized in that, Step seven includes: Based on the return period wind speed of the aforementioned reference meteorological stations The ratio of the aforementioned strong winds Calculate the return period wind speed of the target area. = .

8. A computer device comprising a memory and a processor, wherein the memory stores executable code, and the processor, when executing the executable code, implements the method of any one of claims 1-7.

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