A quick prediction method for tailings dam break disaster based on breach morphology dynamic evolution

Abstract

The application discloses a kind of based on breach morphology dynamic evolution's tailing pond dam-break disaster fast prediction method, it is related to tailing pond dam-break disaster prediction technical field, its technical scheme key points are as follows: including the following steps: obtaining breach morphology dynamic evolution law database;Breach morphology-hydraulic coupling model is constructed, and is embedded into ground surface disaster dynamics simulation software, input breach morphology dynamic evolution law database, output the geometric size of each time step;The geometric size of each time step is regarded as time-varying boundary condition, and the grid boundary of breach area is dynamically reconstructed, the dynamic evolution of breach boundary is realized, disaster consequence parameter in the whole process from breach starting to stable is simulated, and the whole process, accurate prediction of disaster consequence is realized.The application can dynamically reflect the evolution process of breach, the method for fast and accurate prediction of disaster consequence, solve the problem of static hypothesis and low calculation efficiency.

Description

Technical Field

[0001] This invention relates to the field of tailings dam failure disaster prediction technology, and more specifically, to a rapid prediction method for tailings dam failure disasters based on the dynamic evolution of breach morphology. Background Technology

[0002] Tailings are solid waste materials discharged after ore beneficiation in metallic or non-metallic mines. Tailings dams are a group of structures formed with other facilities to store tailings, regulate floods, ensure backwater, protect the environment, dam valleys, enclose land, or utilize depressions. The causes of tailings dam failure are multifaceted and complex, involving numerous disciplines. Currently, most research tends to conduct safety assessments and predictions of tailings dams based on a single failure mode. However, in reality, tailings dam failure is often the result of multiple factors acting together, and the specific composition and condition of each tailings dam vary, making assessments based on a single failure mode insufficient to reflect the true risk.

[0003] Existing methods for predicting tailings dam failure disasters mainly have the following problems:

[0004] The static breach assumption has its limitations: traditional methods often simplify the breach shape to a fixed size (such as rectangular or trapezoidal) or assume "instantaneous total breach," ignoring the dynamic evolution of the breach as it gradually widens and cuts downward due to water erosion during the actual dam break. This leads to an estimation error of 30%-50% in the peak discharge flow, severely affecting the accuracy of downstream inundation range prediction.

[0005] Insufficient computational efficiency and practicality: Although there are sophisticated numerical models based on computational fluid dynamics (such as the VOF method), these models are usually computationally expensive and time-consuming (days to weeks), and most of them treat the breach as a fixed boundary, making it difficult to meet the urgent need for rapid prediction during the "golden rescue time" after a disaster.

[0006] Insufficient coupling of physical mechanisms: Existing models fail to couple the evolution of breach morphology with dam material properties (such as shear strength) and hydrodynamic conditions in real time, resulting in an inability to accurately reflect the impact of fluid-structure interaction on disaster consequences during dam breaches. Summary of the Invention

[0007] The purpose of this invention is to provide a rapid prediction method for tailings dam failure disasters based on the dynamic evolution of breach morphology. This method can dynamically reflect the breach evolution process and quickly and accurately predict the disaster consequences, thus solving the problems of static assumptions and low computational efficiency mentioned above.

[0008] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0009] The first aspect of this invention provides a rapid prediction method for tailings dam failure disasters based on the dynamic evolution of breach morphology, comprising the following steps:

[0010] Obtain a database of dynamic evolution patterns of breach morphology;

[0011] A breach morphology-hydraulic coupling model was constructed and embedded into a surface disaster dynamics simulation software. The database of dynamic evolution laws of breach morphology was input, and the geometric dimensions of each time step were output.

[0012] By using the geometric dimensions of each time step as time-varying boundary conditions, the grid boundary of the breach region is dynamically reconstructed, realizing the dynamic evolution of the breach boundary. The parameters of the disaster consequences are simulated throughout the entire process from the initiation of the breach to stabilization, enabling accurate prediction of the entire process of disaster consequences.

[0013] A second aspect of the present invention also provides an apparatus / device / system for rapid prediction of tailings dam failure disasters based on dynamic evolution of breach morphology, comprising a memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the above method.

[0014] A third aspect of the present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, characterized in that the computer program / instructions, when executed by a processor, implement the steps of the above-described method.

[0015] A fourth aspect of the present invention also provides a computer program product, including a computer program / instructions, characterized in that, when the computer program / instructions are executed by a processor, they implement the steps of the above-described method.

[0016] In summary, the present invention has the following beneficial effects:

[0017] 1. Significantly improved prediction accuracy: Compared with the traditional static breach method, the prediction error of peak discharge flow rate has been reduced from >30% to <5% (verification case: peak flow rate of 25,000 m³ / s under the condition of complete collapse of Tiangao tailings dam, with an actual measurement error of only 3.6%). The accuracy of inundation range prediction has been improved from 70% to over 90% (case: backtracking verification of the Brumadinho dam breach in Brazil).

[0018] 2. Breakthrough in computational efficiency: Through GPU parallel computing (NVIDIA CUDA), simulation time is reduced from several days in traditional numerical models to 4-6 hours (1 million grid cells), meeting the timeliness requirements for emergency response. The dynamic boundary update mechanism improves computational stability, and the time step is adaptively adjusted to avoid non-physical oscillations.

[0019] 3. Quantification of Engineering Application Value: It can accurately predict the arrival time of critical facilities (e.g., 46s for pumping stations, 1600s for residential areas), providing a precise time window for evacuation plans. The prediction error of the accumulation thickness is <10%, supporting the design of downstream protection projects (e.g., optimization of the height of sand retaining dams).

[0020] 4. High Adaptability: Model parameters can be adjusted according to different dam types (upstream / midline / downstream), applicable to over 90% of tailings dam scenarios. Real-time prediction and updates of breach morphology can be achieved through machine learning interfaces (such as XGBoost), adapting to complex working conditions. This technology has been validated through physical model experiments and historical case studies, demonstrating significant technological advancement and engineering application value, providing a complete dynamic prediction solution for tailings dam safety management. Attached Figure Description

[0021] Figure 1 This is a flowchart of a rapid prediction method for tailings dam failure disaster based on dynamic evolution of breach morphology in Embodiment 1 of the present invention;

[0022] Figure 2 This is a flowchart of a rapid prediction method for tailings dam failure disasters based on dynamic evolution of breach morphology in Embodiment 2 of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments 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, and 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.

[0024] Example 1:

[0025] A rapid prediction method for tailings dam failure disasters based on the dynamic evolution of breach morphology, such as Figure 1 As shown, it includes the following steps:

[0026] S1: Construct a database of breach evolution patterns

[0027] This step aims to obtain firsthand data on the dynamic evolution of the breach morphology during tailings dam overtopping failure through systematic physical model experiments, and to construct a high-precision database of the dynamic evolution laws of breach morphology across multiple scenarios. This database serves as the physical foundation for the establishment and calibration of all subsequent mathematical models.

[0028] 1. Design and build the physical model:

[0029] A large-scale (1:12) physical model of the tailings dam was used to ensure that the main physical processes (such as water erosion and dam instability) remained similar to the prototype. The model dam was constructed based on different dam types in actual engineering (such as upstream, midline, and downstream types). Typical tailings sand was used as the dam material, and its key physical properties were strictly controlled, such as: (dry density: 1.65-1.70 g / cm³, internal friction angle: approximately 28°). The dam strength under different working conditions was simulated by controlling the initial moisture content and compaction degree.

[0030] 2. Test Condition Design:

[0031] The system systematically alters key influencing factors to simulate dam-break conditions under multiple scenarios, including: hydrological conditions (different inflow rates, rainfall intensities, and initial reservoir water levels); dam material properties (such as particle size distribution, density, and shear strength); and dam structural parameters (such as dam height and slope ratio).

[0032] 3. Data Acquisition and Measurement:

[0033] In the experiment, a high-speed camera, a 3D laser scanner, and a pore water pressure sensor were used to accurately collect time-varying sequence data of key morphological parameters such as breach width, depth, widening rate, and incision rate.

[0034] The key morphological parameters collected include: the change sequence of the ulcer width (B) over time (t), the change sequence of the ulcer depth (D) over time (t), the ulcer widening rate (dB / dt), the ulcer incision rate (dD / dt), and the change sequence of the ulcer cross-sectional area over time.

[0035] 4. Construction of a pattern database:

[0036] The time-series data (morphological parameters, hydrodynamic conditions, and material parameters) collected under all the above-mentioned test conditions were organized, calibrated, and standardized.

[0037] A structured database of dynamic evolution patterns of breach morphology was constructed. This database records the complete dynamic evolution trajectory of breach geometry from initiation to development and stabilization under different initial and boundary conditions.

[0038] S2: Establish a coupled model of breach morphology and hydrodynamics.

[0039] Based on the experimental data obtained in step S1, a mathematical model for the dynamic evolution of the breach is constructed by combining data-driven approaches with physical mechanisms. The core of this model includes:

[0040] 1. Ulceration rate model

[0041] The lateral propagation rate of the breach is driven by the difference between the water flow shear stress and the critical shear strength of the dam material, and is corrected by the sediment index. The formula is expressed as:

[0042]

[0043] Where B is the breach width (m), t is time (s), k is an empirical coefficient, and τ is the water flow shear stress (Pa). Here, denoted as ζ, represents the critical shear strength (Pa) of the dam material, and ζ is the sediment index, used to reflect the influence of particle size distribution. This model ensures the physical rationality of breach propagation and is applicable to different dam material properties.

[0044] 2. Collaborative Evolution Model of Usage Depth-Width

[0045] Establish a quantitative model to describe the mutual constraints and coordinated development of breach depth and width during the breaching process, so as to ensure the physical rationality of the evolution of breach geometry.

[0046] Based on statistical data from experiments, the ulcer depth D and width B show a strong linear positive correlation, with the following formula:

[0047]

[0048] Here, α and β are fitting coefficients, determined through physical model experiments (e.g., for tailings sand, α≈0.5, β≈0.1). This model constrains the coordinated development of the breach geometry, avoiding non-physical deformations in the simulation.

[0049] 3. Dynamic equations of reservoir water level changes

[0050] Reservoir water level changes are controlled by the balance between inflow and outflow from the breach, as shown in the formula:

[0051]

[0052] Where V is the reservoir storage capacity (m³), q is the inflow rate (m³ / s), and Q is the outflow rate from the breach (m³ / s). Combining this with the water surface area As (m²), the rate of change of water level is expressed as:

[0053]

[0054] This equation couples the breach morphology evolution with hydrodynamic conditions, enabling dynamic simulation of reservoir water levels.

[0055] 4. Calculation model for breach flow rate and velocity

[0056] The breach discharge process can be generalized as a broad-crested weir flow with varying bottom elevation, and the flow rate formula is:

[0057]

[0058] in, Let be the flow coefficient (calibrated to 1.43), H be the reservoir water level elevation (m), and z be the breach bottom elevation (m). The average flow velocity at the breach cross-section is calculated based on the principle of energy conservation.

[0059]

[0060] Where ϕ is the velocity coefficient (taken as 0.85–0.95), g is the gravitational acceleration (9.81 m / s²), and h is the water depth at the breach cross-section (m). These formulas provide quantitative predictions of key hydraulic parameters.

[0061] S3: Numerical Simulation of Dynamic Breach Boundary

[0062] This step uses the output of the breach morphology-hydraulic coupling model established in S2 as time-varying boundary conditions, and embeds it into mature surface disaster dynamics simulation software (developed by the Chinese Academy of Sciences). Massflow In this process, the dynamic evolution of the breach boundary is realized.

[0063] 1. Boundary conditions

[0064] In numerical simulation software, the initial location of the tailings dam breach is defined as an internal boundary or a deformable boundary, rather than a traditional fixed boundary.

[0065] Compile the S2 model (including the breach widening rate model, depth-width co-evolution model, reservoir water level change equation, and flow rate and velocity calculation model) into user-defined functions or couple it with the main solver through an application programming interface.

[0066] 2. Dynamic update mechanism

[0067] Within each time step of the numerical simulation (typically Δt=0.1s), the master solver transmits parameters such as the reservoir water level (H) and dam material properties at the current moment to the S2 coupled model.

[0068] The S2 coupled model calculates the breach width (B), depth (D), and bottom elevation (z) in real time based on the input parameters for that time step.

[0069] Based on these updated geometric dimensions, the master solver dynamically reconstructs the mesh boundary of the breach region, thereby transforming the breach from a static parameter into a "living boundary" that evolves dynamically with the simulation process.

[0070] 3. Computational Grid and Parameter Settings

[0071] Grid type: An unstructured grid is used to accommodate complex downstream terrain. The total number of grid cells is typically between 500,000 and 1,000,000.

[0072] Mesh refinement: Mesh refinement is carried out near the breach and in the main downstream flow channel area, with a resolution of 2-3 meters, to ensure accurate capture of key fluid dynamic processes; in flat or less affected areas, the mesh can be widened to a resolution of 10 meters to balance computational efficiency.

[0073] Boundary conditions: Bottom boundary: The Coulomb friction model is adopted, and the friction coefficient is set according to the characteristics of the dam material and the downstream surface, with a typical value of 0.43. Lateral boundary: Set as an open boundary to allow tailings sand flow to flow freely out of the computational domain.

[0074] S4: Rapid Prediction and Output of Disaster Consequences

[0075] The numerical model integrating dynamic breach boundaries is used to quickly simulate the evolution path of tailings sand flow, inundation range, spatiotemporal distribution of flow velocity and flow rate, impact force, and final accumulation thickness in the downstream area from the initiation of the breach to its stabilization. The results are output in the form of visual charts and data files, enabling accurate prediction of the entire process of disaster consequences.

[0076] 1. Simulation solution and output parameters

[0077] Evolution path and inundation extent: by tracking the flow depth at each time step (h is the flow depth of the tailings sand flow at a certain point) is used to determine this. The inundation range is the sum of all areas that were once covered by tailings sand (h>0) after the simulation ends, and is output in the form of a vector polygon; the evolution path is the trajectory of the flow depth front as it advances over time.

[0078] The spatiotemporal distribution of flow velocity is obtained directly from the solution obtained by each grid at each time step. and (u and v are the depth-average flow velocities of the tailings sand flow at that point in the x and y directions, respectively), which are synthesized into a velocity vector field.

[0079] Spatiotemporal distribution of flow: At a specific cross-section, the flow can be transmitted through... Calculation, where and These are the flow depth and normal velocity at grid i in the cross section. That is the grid width.

[0080] Impact force: Using the flow velocity v obtained from the solution, substitute it into the empirical formula. (ρ=2100kg / m3, drag coefficient =1.2) to perform the calculation.

[0081] Stacking thickness: At the end of the simulation, the final flow depth h on each grid is the stacking thickness.

[0082] 2. Data output format and precision

[0083] All forecast results are output in visual charts and standard data file formats to facilitate emergency decision-making and subsequent analysis.

[0084] Flooding range: The output is in vector Shapefile format, with spatial accuracy up to ±5 meters.

[0085] Flow velocity / flow rate spatiotemporal matrix: The output is in CSV format, with a data sampling frequency of 1Hz, and includes location coordinates, timestamps, and corresponding values.

[0086] Impact force distribution and accumulation thickness: The output is in GeoTIFF raster format, which is convenient for spatial analysis in GIS software.

[0087] Arrival time of critical facilities: Automatically outputs the precise time when the tailings sand front arrives at downstream critical facilities (such as pumping stations and residential areas), providing quantitative basis for evacuation plans.

[0088] Example 2:

[0089] A rapid prediction method for tailings dam failure disasters based on the dynamic evolution of breach morphology, such as Figure 2 As shown, it includes the following steps:

[0090] S100. Obtain a database of dynamic evolution patterns of breach morphology;

[0091] This database records the complete dynamic evolution trajectory of the breach geometry from initiation to development and stabilization under different initial and boundary conditions.

[0092] S200. Construct a breach morphology-hydraulic coupling model and embed it into the surface disaster dynamics simulation software. Input the breach morphology dynamic evolution law database and output the geometric dimensions of each time step.

[0093] S300 uses the geometric dimensions of each time step as time-varying boundary conditions to dynamically reconstruct the grid boundary of the breach area, realize the dynamic evolution of the breach boundary, simulate the disaster consequence parameters from the initiation of the breach to the stabilization process, and achieve full-process and accurate prediction of disaster consequences.

[0094] In step S100 of this embodiment, obtaining the database of dynamic evolution law of breach morphology includes: using a tailings dam physical model, collecting sequence data of key morphological parameters changing over time using sensors in the experiment, and performing preprocessing to obtain the database of dynamic evolution law of breach morphology.

[0095] In step S100 of this embodiment, the key morphological parameters include: the change sequence of ulcer width over time, the change sequence of ulcer depth over time, the ulcer widening rate, the ulcer incision rate, and the change sequence of ulcer cross-sectional area over time.

[0096] In step S100 of this embodiment, preprocessing includes sorting, proofreading, and standardization.

[0097] In step S200 of this embodiment, the breach morphology-hydraulic coupling model includes:

[0098] model of ulcer widening rate:

[0099] The lateral propagation rate of the breach is driven by the difference between the water flow shear stress and the critical shear strength of the dam material, and is corrected by the sediment index. The formula is as follows:

[0100] ;

[0101] Where B is the breach width, t is time, k is an empirical coefficient, and τ is the water flow shear stress. ζ represents the critical shear strength of the dam material, and ζ represents the sediment index.

[0102] Ulcer depth-width co-evolution model:

[0103] Establish a quantitative model to describe the mutual constraints and coordinated development of breach depth and width during the breach process, so as to ensure the physical rationality of the evolution of breach geometry.

[0104] Based on statistical data from experiments, the ulcer depth D and width B show a strong linear positive correlation, with the following formula:

[0105] ;

[0106] Where α and β are fitting coefficients;

[0107] Dynamic equation of reservoir water level change:

[0108] Reservoir water level changes are controlled by the balance between inflow and outflow from the breach, as shown in the formula:

[0109] ;

[0110] Where V is the reservoir storage capacity, q is the inflow rate, Q is the outflow rate from the breach, and combined with the water surface area As, the rate of change of water level is expressed as:

[0111] ;

[0112] model for calculating flow rate and velocity at the breach:

[0113] The breach discharge process can be generalized as a broad-crested weir flow with varying bottom elevation, and the flow rate formula is:

[0114] ;

[0115] in, Here, H is the flow coefficient, H is the reservoir water level elevation, z is the breach bottom elevation, and the average flow velocity at the breach cross-section is calculated based on the principle of energy conservation.

[0116] ;

[0117] Where ϕ is the flow velocity coefficient, g is the gravitational acceleration, and h is the water depth at the breach cross-section.

[0118] In numerical simulation software, the initial location of the tailings dam breach is defined as an internal boundary or a deformable boundary, rather than a traditional fixed boundary.

[0119] Compile the breach morphology-hydraulic coupling model into a user-defined function or couple it with the main solver through an application programming interface.

[0120] Within each time step of the numerical simulation (typically Δt=0.1s), the master solver transmits parameters such as the current reservoir water level (H) and dam material properties to the breach morphology-hydraulic coupling model.

[0121] The breach morphology-hydraulic coupling model calculates the breach width (B), depth (D), and bottom elevation (z) in real time at the given time step based on the input parameters.

[0122] Based on these updated geometric dimensions, the master solver dynamically reconstructs the mesh boundary of the breach region, thereby transforming the breach from a static parameter into a "living boundary" that evolves dynamically with the simulation process.

[0123] In step S300 of this embodiment, the disaster consequence parameters include the evolution path of tailings sand flow in the downstream area, the inundation range, the spatiotemporal distribution of flow velocity and flow rate, the impact force, and the final accumulation thickness.

[0124] Disaster consequence parameters are output in the form of visual charts and data files.

[0125] The present invention also provides a device / equipment / system for rapid prediction of tailings dam failure disasters based on dynamic evolution of breach morphology, including a memory, a processor and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the above method.

[0126] The present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, characterized in that the computer program / instructions, when executed by a processor, implement the steps of the above-described method.

[0127] The present invention also provides a computer program product, including a computer program / instructions, characterized in that the computer program / instructions, when executed by a processor, implement the steps of the above-described method.

[0128] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A rapid prediction method for tailings dam failure disasters based on dynamic evolution of breach morphology, characterized by: Includes the following steps: Obtain a database of dynamic evolution patterns of breach morphology; A breach morphology-hydraulic coupling model was constructed and embedded into a surface disaster dynamics simulation software. The database of dynamic evolution laws of breach morphology was input, and the geometric dimensions of each time step were output. By using the geometric dimensions of each time step as time-varying boundary conditions, the grid boundary of the breach region is dynamically reconstructed, realizing the dynamic evolution of the breach boundary. The parameters of the disaster consequences are simulated throughout the entire process from the initiation of the breach to stabilization, enabling accurate prediction of the entire process of disaster consequences.

2. The rapid prediction method for tailings dam failure disaster according to claim 1, characterized in that: The process of obtaining the database of dynamic evolution law of breach morphology includes: using a tailings dam physical model, collecting sequence data of key morphological parameters changing over time using sensors in the experiment, and performing preprocessing to obtain the database of dynamic evolution law of breach morphology.

3. The rapid prediction method for tailings dam failure disaster according to claim 2, characterized in that: The key morphological parameters include: the change sequence of ulcer width over time, the change sequence of ulcer depth over time, the ulcer widening rate, the ulcer incision rate, and the change sequence of ulcer cross-sectional area over time.

4. The rapid prediction method for tailings dam failure disaster according to claim 2, characterized in that: The preprocessing includes sorting, proofreading, and standardization.

5. The rapid prediction method for tailings dam failure disaster according to claim 1, characterized in that: The disaster consequence parameters include the evolution path of tailings sand flow in the downstream area, the inundation range, the spatiotemporal distribution of flow velocity and flow rate, the impact force, and the final accumulation thickness.

6. The rapid prediction method for tailings dam failure disaster according to claim 1, characterized in that: The breach morphology-hydrodynamic coupling model includes: model of ulcer widening rate: The lateral propagation rate of the breach is driven by the difference between the water flow shear stress and the critical shear strength of the dam material, and is corrected by the sediment index. The formula is as follows: ； Where B is the breach width, t is time, k is an empirical coefficient, and τ is the water flow shear stress. ζ represents the critical shear strength of the dam material, and ζ represents the sediment index. Ulcer depth-width co-evolution model: Establish a quantitative model to describe the mutual constraints and coordinated development of breach depth and width during the breach process, so as to ensure the physical rationality of the evolution of breach geometry. Based on statistical data from experiments, the ulcer depth D and width B show a strong linear positive correlation, with the following formula: ； Where α and β are fitting coefficients; Dynamic equation of reservoir water level change: Reservoir water level changes are controlled by the balance between inflow and outflow from the breach, as shown in the formula: ； Where V is the reservoir storage capacity, q is the inflow rate, Q is the outflow rate from the breach, and combined with the water surface area As, the rate of change of water level is expressed as: ； model for calculating flow rate and velocity at the breach: The breach discharge process can be generalized as a broad-crested weir flow with varying bottom elevation, and the flow rate formula is: ； in, Here, H is the flow coefficient, H is the reservoir water level elevation, z is the breach bottom elevation, and the average flow velocity at the breach cross-section is calculated based on the principle of energy conservation. ； Where ϕ is the flow velocity coefficient, g is the gravitational acceleration, and h is the water depth at the breach cross-section.

7. The rapid prediction method for tailings dam failure disaster according to claim 1, characterized in that: The disaster consequence parameters are output in the form of visual charts and data files.

8. A device / equipment / system for rapid prediction of tailings dam failure disasters based on dynamic evolution of breach morphology, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program / instructions stored thereon, 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 1-7.

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 1-7.

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