Batch CFD data analysis method and device and storage medium

Abstract

The invention discloses a batch CFD data analysis method and device and a storage medium, and belongs to the technical field of computer-aided engineering. According to the method, based on a preset standardized naming rule, standardized naming is conducted on model components and boundary conditions of a geometric model, and the geometric model obtained after standardized naming is exported as a grid file capable of being recognized by a CFD solver; obtaining a CFD solving macro command template containing replaceable variables, dynamically modifying template variables according to the grid file and naming of the grid file, generating a special macro command, performing batch calculation, and exporting a result file according to a set format; and automatically reading all result files, summarizing and analyzing the data according to a naming analysis model and working condition information, and automatically generating a visual chart and an analysis report. According to the method, through standardized naming and scripted control, unattended operation automation of the whole process from the geometric model to the analysis report is achieved, and CFD simulation efficiency and traceability are remarkably improved.

Description

Technical Field

[0001] This invention relates to a batch CFD data analysis method, apparatus, and storage medium, belonging to the field of computer-aided engineering technology. Background Technology

[0002] In modern industrial design, such as aerospace and automotive manufacturing, computational fluid dynamics (CFD) simulation has become a core tool for product performance verification and optimization. A typical complete CFD analysis workflow includes three main stages: preprocessing (geometry cleaning, discretization), solution computation, and post-processing (results analysis and visualization). Different analysis items usually require different strategies in these three stages.

[0003] Currently, this process faces the following technical challenges:

[0004] The process is fragmented and involves a lot of manual intervention: preprocessing, solving, and postprocessing are usually done by different software, and data transfer and settings between each stage rely on a lot of manual operations, which is inefficient and prone to human error.

[0005] Model management is complex: When multiple design variations or different operating conditions of the same product need to be analyzed in batches, the naming and management of model files become extremely complex, making it difficult to guarantee the accuracy and traceability of the process.

[0006] Lack of integrated automation: Existing automation solutions are mostly limited to the internal workings of single software (such as parameterization studies within CFD software itself), making it difficult to achieve end-to-end automation from preprocessing to postprocessing. In particular, the low level of automation in preprocessing software has become a bottleneck in the entire automation process.

[0007] Low data analysis efficiency: Simulation results (such as drag coefficient, pressure drop, flow field data, etc.) are usually exported in the form of independent files, which require analysts to manually organize, summarize and draw charts, which is time-consuming and difficult to standardize.

[0008] Therefore, there is an urgent need in this field for a technical solution that can connect preprocessing, solving, and postprocessing to achieve full-process automation, standardization, and batch processing. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the prior art and provide a batch CFD data analysis method, device and storage medium that achieves unattended automation of the entire process from geometric model to final analysis report through standardized naming rules and scripted control.

[0010] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0011] In a first aspect, the present invention provides a method for batch CFD data analysis, comprising:

[0012] Based on the preset standardized naming rules, the model components and boundary conditions of the geometric model are standardized and named, and the standardized geometric model is exported as a mesh file that can be recognized by the CFD solver.

[0013] Obtain the CFD macro command template corresponding to the simulation analysis item, wherein the macro command template contains replaceable variables for receiving external input;

[0014] Based on the standardized naming rules used in the mesh file, the replaceable variables in the CFD solver macro command template are dynamically modified to generate the corresponding CFD solver macro commands;

[0015] Based on the CFD solver macro command, the CFD solver is controlled to perform batch calculations and export result files using standardized naming rules.

[0016] Based on the standardized naming rules, all exported result files are automatically read, and the data in the result files is parsed, summarized, and statistically analyzed. Based on the summarized data, visualization charts and analysis reports are automatically generated.

[0017] Furthermore, the process of standardizing the naming of model components and boundary conditions of the geometric model, and exporting the standardized-naming geometric model as a mesh file recognizable by the CFD solver, includes:

[0018] For different CFD analysis items, call the corresponding parameterized and normalized preprocessing scripts;

[0019] Run the preprocessing script to automatically perform mesh generation on the input geometric model;

[0020] Based on the preset naming rules for components and boundary conditions, generate a standardized name for the meshed geometric model;

[0021] Export the normalized and named geometric model as a mesh file that can be recognized by the CFD solver.

[0022] Furthermore, the CFD solver macro command template is a script template written in Python.

[0023] Furthermore, based on the standardized naming rules used in the mesh file, the replaceable variables in the CFD solver macro command template are dynamically modified, wherein the replaceable variables include the geometric model name, the path of the mesh file to be imported, the boundary condition parameters, and the output file path.

[0024] Furthermore, based on the aforementioned CFD solver macro commands, the CFD solver performs batch calculations and exports result files using standardized naming rules, including:

[0025] Construct a key-value dictionary by combining the CFD solver executable file to be invoked with the corresponding CFD solver macro command file;

[0026] Based on loop statements and thread pool mechanisms, the CFD solver is called in batches. According to the key-value dictionary, the corresponding CFD solver macro command file is loaded and executed to obtain multiple result files.

[0027] Export the resulting file as a CSV file.

[0028] Furthermore, the automatic generation of visualization charts and analysis reports includes:

[0029] Write a post-processing script to automatically scan and read all result files in a specified directory;

[0030] The filename of the result file is parsed using regular expressions to extract the model identifier and operating condition parameter information.

[0031] Read the specific data from each result file, and summarize and organize it according to the extracted model identifier and working condition parameter information to obtain the summary data;

[0032] It calls upon a visualization library to automatically generate standardized analytical charts based on the summarized data;

[0033] The summarized data, analysis charts, and model identifiers and operating condition parameter information parsed from file names are integrated to automatically generate a structured analysis report document.

[0034] Secondly, the present invention provides a batch CFD data analysis apparatus for implementing the batch CFD data analysis method described in any of the preceding claims, comprising:

[0035] The preprocessing module is used to standardize the naming of model components and boundary conditions of the geometric model based on preset standardized naming rules, and export the standardized-named geometric model as a mesh file that can be recognized by the CFD solver.

[0036] The acquisition module is used to acquire the CFD macro command template corresponding to the simulation analysis item. The macro command template contains replaceable variables for receiving external input.

[0037] The modification module is used to dynamically modify the replaceable variables in the CFD solver macro command template according to the normalized naming rules used in the mesh file, and generate the corresponding CFD solver macro commands.

[0038] The batch calculation module is used to control the CFD solver to perform batch calculations based on the CFD solver macro commands and export result files using standardized naming rules.

[0039] The analysis module is used to automatically read all exported result files based on the standardized naming rules, perform parsing, summarizing and statistical analysis on the data in the result files, and automatically generate visualization charts and analysis reports based on the summarized data.

[0040] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0041] Fourthly, the present invention provides a computer device, comprising:

[0042] Memory, used to store computer programs / instructions;

[0043] A processor for executing the computer program / instructions to implement the steps of any of the methods described above.

[0044] Fifthly, the present invention provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of any of the methods described above.

[0045] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0046] 1. This invention provides a batch CFD data analysis method, apparatus, and storage medium. By constructing a parameterized preprocessing script template library, templated CFD solver macro commands, and automated scheduling and post-processing scripts, it achieves end-to-end full-link automation from preprocessing and solver calculations to data post-processing. This method integrates the traditional discrete process that relies on manual operation and multiple software switching into an integrated automated pipeline, significantly reducing manual intervention and repetitive operations. It is particularly suitable for large-scale parameterized research and multi-condition batch analysis, and can shorten the analysis task that originally required several days to complete to be completed automatically within a few hours.

[0047] 2. The system of this invention uses a standardized naming convention throughout the process as its core, uniformly linking geometric models, mesh files, solver settings, calculation results, and analysis reports. This mechanism ensures consistency in the analysis process and reliable traceability of results, effectively avoiding human errors and data discrepancies caused by chaotic file management and inconsistent naming, thus improving the reliability and reproducibility of the simulation process.

[0048] 3. This invention adopts a "template + script" construction method. Users only need to maintain and adjust the preprocessing specifications and macro command templates to quickly adapt to new analysis models or analysis types. The system has a clear structure, high modularity, is easy to expand and maintain, and has strong robustness and cross-project reusability.

[0049] 4. This invention uses Python as the core for system integration and scheduling, flexibly calling and controlling commercial tools such as preprocessing software and CFD solvers, breaking through the technical barriers to collaborative work between different software platforms. The system supports users in customizing analysis processes according to actual needs, building a highly flexible and customizable automated simulation analysis environment.

[0050] 5. Through a thread pool-based batch scheduling mechanism, the system can perform parallel simulation calculations for multiple analysis items and multiple sets of working conditions, making full use of computing resources, significantly shortening the overall time required for large-scale batch analysis, and improving the overall throughput of simulation analysis.

[0051] 6. The post-processing script of this invention can automatically extract, summarize, and statistically analyze simulation results data, and call a visualization library to generate standardized graphs, cloud maps, and other analytical charts. Ultimately, it automatically generates a structured analysis report containing key data, charts, and operating condition descriptions. This function eliminates the tedious process of manually organizing data and creating tables, ensuring the consistency and professionalism of the output results. Attached Figure Description

[0052] Figure 1 This is a flowchart of a batch CFD data analysis method provided in an embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram of the fitting results of flow-pressure drop data in a multi-segment pipeline of a cooling system for a new energy vehicle provided in an embodiment of the present invention. Detailed Implementation

[0054] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0055] Example 1: This example introduces a batch CFD data analysis method, including:

[0056] Based on the preset standardized naming rules, the model components and boundary conditions of the geometric model are standardized and named, and the standardized geometric model is exported as a mesh file that can be recognized by the CFD solver.

[0057] Obtain the CFD macro command template corresponding to the simulation analysis item, wherein the macro command template contains replaceable variables for receiving external input;

[0058] Based on the standardized naming rules used in the mesh file, the replaceable variables in the CFD solver macro command template are dynamically modified to generate the corresponding CFD solver macro commands;

[0059] Based on the CFD solver macro command, the CFD solver is controlled to perform batch calculations and export result files using standardized naming rules.

[0060] Based on the standardized naming rules, all exported result files are automatically read, and the data in the result files is parsed, summarized, and statistically analyzed. Based on the summarized data, visualization charts and analysis reports are automatically generated.

[0061] like Figure 1 As shown, the batch CFD data analysis method provided in this embodiment involves the following steps in its application process:

[0062] A. Construction of a parametric and normalized preprocessing script template library. For different analysis items, targeted parametric and normalized preprocessing scripts are constructed, and preprocessing software is used to automatically process a series of geometric models. The automated processing includes: geometry cleanup, mesh discretization, and setting normalized names for different components and boundary conditions of the model according to preset rules. The script iterates through all processed models and, based on their normalized names, exports them as mesh files recognizable by the CFD solver.

[0063] B. Templated CFD Solving, Calculation, and Export File Compilation. For different analysis items, a CFD macro command template library written in Python is provided. This template library contains the basic simulation settings, but the key parameters such as model name, imported mesh file, mesh strategy, boundary conditions, and output file path are replaceable variables; wherein, the imported mesh file is exported from step A.

[0064] C. Develop an automated scheduling script. Based on simulation requirements, this script reads the mesh file generated in step A and its standardized naming, dynamically modifies the corresponding variables in the Python macro command template, and generates an executable, dedicated macro command file for the model. When solving multiple analysis items in parallel, a dictionary is used to create key-value pairs between the CFD solver executable file and the allocated dedicated macro command files. Combined with loop statements and a thread pool, the CFD solver is called in batches to automatically run calculations in batches. Based on the settings in the macro commands, the CFD solver is controlled to export the calculation results file according to a preset format, preferably CSV.

[0065] D. Automated Data Post-processing and Visualization. A Python-based data post-processing script library is used to automatically scan and read all CSV format result files exported in step C. Based on standardized file naming, the library automatically identifies model categories and operating conditions, and performs data parsing, summarization, and statistical analysis. Based on the summarized data, the library automatically generates standardized charts and can automatically generate analysis reports containing key data and charts.

[0066] The core innovation of this embodiment lies in the construction of targeted named databases, parameterized template libraries, and automated execution engines for drag coefficient analysis, engine compartment thermal management analysis, cockpit thermal management analysis, and cooling system flow resistance analysis. An automated simulation analysis framework, using standardized naming as a link, integrates pre-processing software, a CFD solver, and Python post-processing scripts. This framework, through a custom scripting system, unifies the previously cumbersome work of manually completing the entire process or requiring secondary development for different analysis items into a single simulation analysis platform. It can simultaneously perform automated simulations of multiple analysis items, seamlessly connecting isolated analysis steps to form a complete, batch-executable automated pipeline.

[0067] The CFD data analysis method in this embodiment is mainly divided into four parts: First, for different analysis items, the preprocessing software performs standardized naming of components, automatic mesh generation, and exports mesh files that can be recognized by the CFD solver (standardized naming); second, a CFD macro command template library containing replaceable variables is written using Python software; third, an automated scheduling script is developed in Python using a combination of loop statements and thread pools to automatically run calculations in batches; and fourth, automated data post-processing and visualization scripts are written to post-process the calculation results.

[0068] Compared with existing analysis techniques, the CFD data analysis method of this embodiment has the following advantages:

[0069] 1. Full-process automation: For different analysis items, it has achieved end-to-end full-link automation from pre-processing and solving to post-processing for the first time, which greatly reduces manual intervention and improves simulation efficiency, especially suitable for large-scale parametric research and optimization design.

[0070] 2. Strong standardization and traceability: Through standardized naming rules throughout the process, the model, simulation settings and result data are closely linked, ensuring the accuracy of the process and the traceability of the results, and avoiding human error.

[0071] 3. High robustness and reusability: By adopting the "template + script" approach, users only need to maintain the preprocessing specifications and macro command templates to easily adapt to new analysis models. The system is highly robust and reusable.

[0072] 4. Deep integration and flexibility: By using Python as a "glue", different commercial software can be flexibly called and controlled, solving the technical problem of multi-platform software collaboration and forming a unified and highly customized analysis system.

[0073] 5. Parallelization of multi-analysis item operations: By using loops and thread pools, multiple analysis items can be calculated in parallel, saving working time.

[0074] The following description, in conjunction with a preferred embodiment, illustrates the content involved in the above embodiments.

[0075] This embodiment presents a CFD data analysis method that enables rapid batch calculations. The following is an example of the automated batch analysis of 13 pipe sections in a new energy vehicle's cooling system, illustrating the specific steps:

[0076] (1) Analysis item;

[0077] Based on the flow range of the pipeline, the 13 pipeline segments were divided into two analysis items, and each analysis item was run in batches of 9 and 4 pipeline segments respectively.

[0078] (2) Pretreatment;

[0079] For pipe flow resistance calculation, a corresponding naming convention was selected, and 13 different pipe models were meshed in the pre-processing software. The pipe inlet, body, and outlet were standardized and named according to the naming convention pipeXX_in, pipeXX, and pipeXX_out (XX being 01-13). The pre-processing software's scripting function was used to batch export 13 mesh files, named pipeXX.

[0080] (3) Automated solution;

[0081] a) Select the corresponding macro command template in the macro command template library, which includes editable macro command name, import mesh path and file name, pipe inlet name, outlet name, boundary conditions, stop conditions, export file path and name, etc.

[0082] b) Generate scripts based on macro command templates, call macro command templates and adjust them according to requirements, set the flow rate for each pipeline, and set the stop condition to 1000 steps to generate 9 and 4 macro commands in batches respectively;

[0083] c) Automatic execution: The called CFD solver file and its corresponding macro commands are made into a dictionary of key-value pairs. Loop statements and thread pools are used to automatically calculate the pressure loss in batches for multiple flow rates of the two analysis items. After the flow rate calculation for each pipeline is completed, the pipeline name, flow rate and pressure loss are exported respectively, and pipeXX_kkL / min.CSV is automatically generated (XX is 01-13, kk is the set 6 sets of flow rates, and a total of 78 .CSV files are generated).

[0084] (4) Automated post-processing;

[0085] Select the corresponding automated post-processing script to automatically read 78 pipeXX_kkL / min.CSV files, extract the pipe name (pipeXX) and flow rate (kk) using regular expressions, and extract the pressure drop value from the 1001st row of each file. These values ​​are then summarized into a single .CSV file. The script automatically performs quadratic equation fitting for each pipeline and plots a flow rate-pressure drop curve, as shown below. Figure 2 As shown.

[0086] This embodiment achieves fully automated simulation analysis and post-processing of 13 pipeline segments, reducing the original 4-day manual workload to just a few hours (using off-hours for calculation), fully demonstrating the effectiveness and superiority of the invention.

[0087] Example 2: This example provides a batch CFD data analysis device for implementing the batch CFD data analysis method described in any one of Examples 1, comprising:

[0088] The preprocessing module is used to standardize the naming of model components and boundary conditions of the geometric model based on preset standardized naming rules, and export the standardized-named geometric model as a mesh file that can be recognized by the CFD solver.

[0089] The acquisition module is used to acquire the CFD macro command template corresponding to the simulation analysis item. The macro command template contains replaceable variables for receiving external input.

[0090] The modification module is used to dynamically modify the replaceable variables in the CFD solver macro command template according to the normalized naming rules used in the mesh file, and generate the corresponding CFD solver macro commands.

[0091] The batch calculation module is used to control the CFD solver to perform batch calculations based on the CFD solver macro commands and export result files using standardized naming rules.

[0092] The analysis module is used to automatically read all exported result files based on the standardized naming rules, perform parsing, summarizing and statistical analysis on the data in the result files, and automatically generate visualization charts and analysis reports based on the summarized data.

[0093] Example 3: This example provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described in Example 1.

[0094] Example 4: This example provides a computer device, including:

[0095] Memory, used to store computer programs / instructions;

[0096] A processor for executing the computer program / instructions to implement the steps of any of the methods described in Embodiment 1.

[0097] Example 5: This example provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the method described in any one of Examples 1.

[0098] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

[0099] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0101] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0102] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure and not to limit its protection scope. Although this disclosure has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading this disclosure, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims.

Claims

1. A batch CFD data analysis method, characterized in that, include: Based on the preset standardized naming rules, the model components and boundary conditions of the geometric model are standardized and named, and the standardized geometric model is exported as a mesh file that can be recognized by the CFD solver. Obtain the CFD macro command template corresponding to the simulation analysis item, wherein the macro command template contains replaceable variables for receiving external input; Based on the standardized naming rules used in the mesh file, the replaceable variables in the CFD solver macro command template are dynamically modified to generate the corresponding CFD solver macro commands; Based on the CFD solver macro command, the CFD solver is controlled to perform batch calculations and export result files using standardized naming rules. Based on the standardized naming rules, all exported result files are automatically read, and the data in the result files is parsed, summarized, and statistically analyzed. Based on the summarized data, visualization charts and analysis reports are automatically generated.

2. The batch CFD data analysis method according to claim 1, characterized in that, The process of standardizing the naming of model components and boundary conditions of the geometric model, and exporting the standardized-naming geometric model as a mesh file recognizable by the CFD solver, includes: For different CFD analysis items, call the corresponding parameterized and normalized preprocessing scripts; Run the preprocessing script to automatically perform mesh generation on the input geometric model; Based on the preset naming rules for components and boundary conditions, generate a standardized name for the meshed geometric model; Export the normalized and named geometric model as a mesh file that can be recognized by the CFD solver.

3. The batch CFD data analysis method according to claim 1, characterized in that, The CFD solver macro command template is a script template written in Python.

4. The batch CFD data analysis method according to claim 1, characterized in that, Based on the standardized naming rules used in the mesh file, the replaceable variables in the CFD solver macro command template are dynamically modified, wherein the replaceable variables include the geometric model name, the path of the mesh file to be imported, the boundary condition parameters, and the output file path.

5. The batch CFD data analysis method according to claim 1, characterized in that, Based on the aforementioned CFD solver macro commands, the CFD solver performs batch calculations and exports result files using standardized naming rules, including: Construct a key-value dictionary by combining the CFD solver executable file to be invoked with the corresponding CFD solver macro command file; Based on loop statements and thread pool mechanisms, the CFD solver is called in batches. According to the key-value dictionary, the corresponding CFD solver macro command file is loaded and executed to obtain multiple result files. Export the resulting file as a CSV file.

6. The batch CFD data analysis method according to claim 1, characterized in that, The automatic generation of visualization charts and analysis reports includes: Write a post-processing script to automatically scan and read all result files in a specified directory; The filename of the result file is parsed using regular expressions to extract the model identifier and operating condition parameter information. Read the specific data from each result file, and summarize and organize it according to the extracted model identifier and working condition parameter information to obtain the summary data; It calls upon a visualization library to automatically generate standardized analytical charts based on the summarized data; The summarized data, analysis charts, and model identifiers and operating condition parameter information parsed from file names are integrated to automatically generate a structured analysis report document.

7. A batch CFD data analysis apparatus, used to implement the batch CFD data analysis method according to any one of claims 1-6, characterized in that, include: The preprocessing module is used to standardize the naming of model components and boundary conditions of the geometric model based on preset standardized naming rules, and export the standardized-named geometric model as a mesh file that can be recognized by the CFD solver. The acquisition module is used to acquire the CFD macro command template corresponding to the simulation analysis item. The macro command template contains replaceable variables for receiving external input. The modification module is used to dynamically modify the replaceable variables in the CFD solver macro command template according to the normalized naming rules used in the mesh file, and generate the corresponding CFD solver macro commands. The batch calculation module is used to control the CFD solver to perform batch calculations based on the CFD solver macro commands and export result files using standardized naming rules. The analysis module is used to automatically read all exported result files based on the standardized naming rules, perform parsing, summarizing and statistical analysis on the data in the result files, and automatically generate visualization charts and analysis reports based on the summarized data.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When executed by a processor, the computer program implements the steps of the method described in any one of claims 1-6.

9. An electronic device, characterized in that, include: Memory, used to store computer programs / instructions; A processor for executing the computer program / instructions to implement the steps of the method according to any one of claims 1-6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1-6.

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