A fragment cumulative damage assessment method and system
By constructing the damage ability matrix function and cumulative damage model of the fragment warhead, combined with the shooting error, the problem of insufficient accuracy of prediction of cumulative damage probability for multiple shootings in traditional methods is solved, and high-precision fragment warhead evaluation is achieved, which improves the reliability of the evaluation. and precision.
Patent Information
- Application Number
- CN202411149318.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-21
- Publication Date
- 2024-12-17
- Estimated Expiration
- 2044-08-21
AI Technical Summary
Traditional empirical or simplified model-based fracture warhead damage assessment methods are difficult to meet the needs of high-precision assessment, especially in the prediction of cumulative damage probability caused to the target by multiple shots, which fail to fully consider the random errors during the shooting process.
By setting up the experimental fragment warhead, presetting its parameters and constructing a damage ability matrix function, combining the target area characteristics and shooting error factors, a fragment cumulative damage model is constructed, and the cumulative damage probability under single and multiple shots is calculated and predicted.
The evaluation accuracy and reliability are improved. Through the introduction of detailed parameters and error functions, the damage effect is comprehensively considered, the uncertainty of the evaluation results is quantified, and the experimental verification model is in line with expectations.
Smart Images
Figure CN118673264B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of warhead blasting, and in particular to a fragment cumulative damage assessment method and system. Background Art
[0002] In modern military tactics and weapon system analysis, it is crucial to accurately assess the damage capability of weapons on targets. As a common type of weapon, the damage effect of fragmentation warheads is affected by many factors, including warhead design, target characteristics, and shooting errors. Traditional damage assessment methods based on experience or simplified models have gradually failed to meet the needs of high-precision assessment. It is difficult to strike a balance between computational efficiency and accuracy, and random errors in the shooting process, such as aiming errors and meteorological conditions, are not fully considered. They are not suitable for predicting the cumulative damage probability caused by multiple shots to the target. Summary of the invention
[0003] In view of the defects of the related art, the present invention provides a fragment cumulative damage assessment method and system, aiming to solve the problem that the prior art is not suitable for predicting the cumulative damage probability caused by multiple shootings to the target.
[0004] The technical solution is as follows:
[0005] The present invention provides a fragment cumulative damage assessment method, comprising the following steps:
[0006] Step S1: setting the fragment warhead for the experiment, presetting the parameters of the fragment warhead, including the mass, caliber, fragment size and quantity of the fragment warhead; and constructing a fragment warhead damage capability matrix function to reflect the damage capability of the warhead to the target at different ranges and yaw angles;
[0007] Step S2: Setting a simulated target area, defining that the performance of each part in the target area being damaged by the attack is uniform, simulating the physical size and spatial direction of different types of damaged targets on the battlefield by setting different target area areas and range axial angles, and calculating the core damaged area in combination with the material, shape of the fragments and the anti-destructiveness of the target material;
[0008] Step S3: Construct a fragment cumulative damage model, and calculate and predict the cumulative damage probability caused by warhead fragments to the target in single shooting and multiple shooting situations by combining the damage capability of the fragments, the regional characteristics of the target, and the error factors of the shooting.
[0009] The present invention provides a fragment cumulative damage assessment system to implement the above-mentioned fragment cumulative damage assessment method, the system comprising:
[0010] The experimental fragment warhead setting module is used to preset the parameters of the fragment warhead, including the mass, caliber, fragment size and quantity of the fragment warhead; and to construct a fragment warhead damage capability matrix function to reflect the damage capability of the warhead to the target at different ranges and yaw angles;
[0011] The target area setting module is used to define that the performance of each part of the target area being damaged by the attack is uniform. By setting different target area areas and range axial angles, the physical size and spatial direction of different types of damage targets on the battlefield are simulated. At the same time, the core damage area is calculated by combining the material, shape of the fragments and the anti-destruction property of the target material;
[0012] The fragment cumulative damage calculation module is used to calculate and predict the cumulative damage probability caused by warhead fragments to the target in single and multiple shots, based on the fragment's destructive capability, the target's regional characteristics, and the shooting error factor.
[0013] The present invention has the following beneficial effects:
[0014] The present invention provides a fragment cumulative damage assessment method and system. Through a large number of experiments, detailed fragment warhead parameters and damage capability matrix functions are introduced to improve the accuracy of the assessment. By introducing the shooting error function and the calculation of random dispersion errors, the influence of these factors on the damage effect is more comprehensively considered. By calculating the confidence interval, the uncertainty of the assessment result is quantified, the reliability of the assessment is improved, and the model is verified to be in line with expectations through experiments. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Figure 1 is a flow chart of a fragment cumulative damage assessment method provided by an embodiment of the present invention;
[0016] Figure 2 It is a flow chart of setting fragment warhead parameters and constructing a fragment warhead damage capability matrix function provided by an embodiment of the present invention;
[0017] Figure 3 is a flow chart of constructing a fragment cumulative damage model provided by an embodiment of the present invention;
[0018] Figure 4 It is a structural diagram of a fragment cumulative damage assessment system provided in an embodiment of the present invention. DETAILED DESCRIPTION
[0019] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.
[0020] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.
[0021] See also Figure 1 The present invention provides a fragment cumulative damage assessment method, comprising the following steps:
[0022] Step S1: setting the fragment warhead for the experiment, presetting the parameters of the fragment warhead, including the mass, caliber, fragment size and quantity of the fragment warhead; and constructing a fragment warhead damage capability matrix function to reflect the damage capability of the warhead to the target at different ranges and yaw angles;
[0023] Step S2: Setting a simulated target area, defining that the performance of each part in the target area being damaged by the attack is uniform, simulating the physical size and spatial direction of different types of damaged targets on the battlefield by setting different target area areas and range axial angles, and calculating the core damaged area in combination with the material, shape of the fragments and the anti-destructiveness of the target material;
[0024] Step S3: Construct a fragment cumulative damage model, and calculate and predict the cumulative damage probability caused by warhead fragments to the target in single shooting and multiple shooting situations by combining the damage capability of the fragments, the regional characteristics of the target, and the error factors of the shooting.
[0025] See also Figure 2, Step S1: Set the fragment warhead for the experiment, preset the parameters of the fragment warhead, including the mass, caliber, fragment size and quantity of the fragment warhead; and construct the fragment warhead damage capability matrix function, which is used to reflect the damage capability of the warhead to the target at different ranges and yaw angles, specifically including:
[0026] Step S11: Determine the mass m of the fragment warhead, clarify the caliber d of the warhead, and at the same time measure the average size s and number n of fragments generated by the same type of warhead after explosion under the same conditions through multiple experiments, and use them as the size and number of fragments of the fragment warhead in this experiment;
[0027] Since the mass of the fragment warhead determines the kinetic energy and penetration of the warhead, the caliber of the warhead determines the dispersion range and damage area of the fragments, and the size and number of the fragments determine the density and coverage of the fragment cloud, it is necessary to obtain the above-mentioned relevant parameters of the experimental fragment warhead;
[0028] Step S22: construct a fragment warhead damage capability matrix function to reflect the damage capability of the warhead to the target at different ranges and yaw angles; define that the fragments scatter outward from the warhead detonation point at a speed v, and the distribution of the speed obeys a normal distribution, then the flight distance of the fragments is calculated using the following formula:
[0029] ; (1)
[0030] Where g is the acceleration due to gravity, is the elevation angle of the fragment velocity vector;
[0031] Define the damage probability density function of fragments It is a function of the fragment flight distance L, which can be approximately described by Gaussian distribution:
[0032] ; (2)
[0033] in, is the average flight distance, is the standard deviation;
[0034] Define the damage matrix function , which indicates the warhead fragments at different ranges r and yaw angles The damage capability under the condition of , is calculated as follows:
[0035] ; (3)
[0036] Its distance from the fragments based on range and yaw angle related.
[0037] Preferably, a specific embodiment is provided, in which the mass of the fragment warhead is selected to be 15 kg to ensure that the warhead has sufficient penetration ability and maintains the stability of the trajectory; the caliber of the warhead is selected to be 155 mm to ensure a wide fragment dispersion range and increase the damage area to the target; the average size of the measured fragments is 10 mm, and the number of fragments is 5,000, ensuring the effectiveness of the coverage area.
[0038] Preferably, a specific embodiment is provided, in which the target area is defined as a rectangular area, and two targets with similar shapes and proportions but different sizes are designed, wherein the area of the first target is 1000 square meters and the area of the other target is 500 square meters; the angles with the range axis are 30 degrees and 50 degrees respectively; the core damage area Aera is calculated in combination with the material, shape of the fragments and the anti-destruction property of the target material.
[0039] See also Figure 3 Step S3: Construct a cumulative damage model, combine the damage capability of fragments, the regional characteristics of the target and the error factor of shooting, calculate and predict the cumulative damage probability caused by warhead fragments to the target in single shooting and multiple shooting, specifically including:
[0040] Step S31: Determine the shooting error function of the bullet fragments. The shooting error depends on the repetition error in the bullet data preparation. These errors can be expressed by the straight error probability along the straight line path of the shooting and the lateral error probability perpendicular to the straight line path. They obey the normal distribution and are independent of each other. The following formula is used: ; (4)
[0041] in, and is the random error of the i-th factor involved in the warhead fire preparation, which includes but is not limited to aiming error, meteorological conditions, observation error, calculation error and equipment error; and is the repeatability error in the longitudinal and transverse directions;
[0042] Errors due to ballistic dispersion occur in every round fired from the weapon system. In order to more accurately calculate the fire efficiency against ground targets from the firing position, it is necessary to introduce vertical and lateral random dispersion errors. The standard deviation of the random dispersion errors is calculated based on the normal distribution as follows: ; (5)
[0043] in, represents the random scattered error in the vertical direction, Represents the random dispersion error in the horizontal direction; and It is the calculation method of the standard deviation of repeated errors in the firepower data preparation process. and This is the calculation method of the standard deviation of the non-repetitive error caused by the dispersion of the bullet trajectory. and is the standard deviation calculated based on a normal distribution;
[0044] Step S32: Grid the target, create a bounding box surrounding all targets, and evenly generate grid points within the bounding box. These grid points are used as integration points to calculate the damage value of the entire target. The damage probability of the entire target can be calculated as follows: ; (6)
[0045] in, is the probability of damage caused at the sth grid point, Probability of direct damage and lateral damage probability Joint decision, is the damage probability of the entire target, and N is the total number of grid points within the target;
[0046] Step S33: For a target that can be destroyed with a single hit, the vertical damage probability and lateral damage probability and the probability of damage from a single hit Calculate using the following formula:
[0047] ; (7)
[0048] in, and is the length of the target damage area in the vertical direction and the width in the horizontal direction. and are the mean errors in length and width respectively, erf is the error function, which uses the cumulative distribution function describing the normal distribution, and its calculation result is between -1 and 1;
[0049] For a target that can only be destroyed by multiple hits, the damage probability is calculated as follows:
[0050] ; (8)
[0051] n is the number of shots.
[0052] The judgment of targets that can be destroyed with a single hit and targets that can be destroyed only with multiple hits is based on multiple factors: for high-value targets, such as the enemy's command and control center or important technical equipment, only one precision strike may be needed to disable them; using high-explosive bombs, bunker-buster bombs or other ammunition with high destructive power, only one shot may be needed to cause sufficient damage to the target; when it is necessary to minimize damage to the surrounding area, such as in an urban environment or close to friendly forces, a single precision strike can reduce collateral damage; for weapons with lower destructive power, multiple shots may be required to ensure that the target is effectively destroyed; for hard targets with high anti-destruction capabilities, such as reinforced bunkers or underground facilities, multiple strikes may be required to penetrate their defenses; in some cases, multiple shots may be required to increase the probability of hitting the target, especially when the target is moving or shooting conditions are not ideal.
[0053] Since the calculation results of the damage probability rely on the random sampling process, the validity of the results is related to the number of experimental simulations. Therefore, it is necessary to obtain statistical results by repeating the experiments many times. The statistical results are used as approximate values to more accurately reflect the actual results. Therefore, it is necessary to construct a confidence interval for the calculation results. The confidence interval needs to satisfy the characteristic that the confidence interval becomes narrower as the number of simulation calculations increases, so as to quantify the uncertainty of the calculation results.
[0054] Step S34: When calculating the damage probability of the entire target, the confidence interval CI is defined using the following calculation method:
[0055] ; (9)
[0056] Where m is the number of times the simulation experiment is repeated. is the critical value of the standard normal distribution, corresponding to a given confidence level, and ST is the standard deviation of the sample, which is related to the dispersion of the results.
[0057] Provide a preferred embodiment, set 10 repeated experiments, calculate the average damage probability , the sample standard deviation ST is 0.05. In order to obtain a confidence interval at a 95% confidence level, the critical value of the standard normal distribution is Taking the value as 1.96, the CIs are calculated to be 0.75+0.0098=0.7598 and 0.75−0.0098=0.7402, respectively. That is, at a confidence level of 95%, the confidence interval of the simulated damage probability is approximately from 74.02% to 75.98%.
[0058] See also Figure 4 The present invention provides a fragment cumulative damage assessment system 100, which implements the fragment cumulative damage assessment method. The system includes:
[0059] Experimental fragment warhead setting module 1 is used to preset the parameters of the fragment warhead, including the mass, caliber, fragment size and quantity of the fragment warhead; and to construct a fragment warhead damage capability matrix function to reflect the damage capability of the warhead to the target at different ranges and yaw angles;
[0060] Target area setting module 2 is used to define that the performance of each part of the target area being damaged by the attack is uniform. By setting different target area areas and range axial angles, the physical size and spatial direction of different types of damage targets on the battlefield are simulated. At the same time, the core damage area is calculated in combination with the material, shape of the fragments and the anti-destructiveness of the target material;
[0061] The fragment cumulative damage calculation module 3 is used to calculate and predict the cumulative damage probability caused by the warhead fragments to the target in a single shot and multiple shots, based on the damage capability of the fragments, the regional characteristics of the target and the error factors of the shooting.
[0062] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A fragment cumulative damage assessment method, characterized in that: The following steps are involved: Step S1: Set up the fragment warhead for the experiment, preset the parameters of the fragment warhead, including the mass, caliber, fragment size and quantity of the fragment warhead; and construct a fragment warhead damage capability matrix function to reflect the damage capability of the warhead to the target at different ranges and yaw angles; specifically: Step S11: Determine the mass m of the fragment warhead, clarify the caliber d of the warhead, and at the same time measure the average size s and number n of fragments generated by the same type of warhead after explosion under the same conditions through multiple experiments, and use them as the size and number of fragments of the fragment warhead in this experiment; Step S22: constructing a fragment warhead damage capability matrix function; defining that the fragments scatter outward from the warhead detonation point at a speed v, and the distribution of the speed obeys a normal distribution, then the flight distance of the fragments is calculated using the following formula: ； （1） Where g is the acceleration due to gravity, is the elevation angle of the fragment velocity vector; Define the damage probability density function of fragments It is a function of the fragment flight distance L, described by Gaussian distribution: ; (2) in, is the average flight distance, is the standard deviation; Define the damage matrix function , which indicates the warhead fragments at different ranges r and yaw angles The damage capability under the condition of , is calculated as follows: ; (3) Its distance from the fragments based on range and yaw angle related; Step S2: Setting a simulated target area, defining that the performance of each part in the target area being damaged by the attack is uniform, simulating the physical size and spatial direction of different types of damaged targets on the battlefield by setting different target area areas and range axial angles, and calculating the core damaged area in combination with the material, shape of the fragments and the anti-destructiveness of the target material; Step S3: construct a fragment cumulative damage model, and calculate and predict the cumulative damage probability caused by warhead fragments to the target in single shooting and multiple shooting situations by combining the damage capability of the fragments, the regional characteristics of the target, and the error factor of the shooting; specifically: Step S31: Determine the shooting error function of the bullet fragments. The shooting error depends on the repetition error in the bullet data preparation. It is expressed by the straight error probability along the straight line path of shooting and the lateral error probability perpendicular to the straight line path. It obeys the normal distribution and is independent of each other. The following formula is used: ； （4） in, and is the random error of the i-th factor involved in the warhead fire preparation, which includes but is not limited to aiming error, meteorological conditions, observation error, calculation error and equipment error; and is the repeatability error in the longitudinal and transverse directions; The random dispersion errors in the vertical and horizontal directions are introduced, and the standard deviation of the random dispersion errors is calculated based on the normal distribution, in the following way: ； （5） in, represents the random scattered error in the vertical direction, Represents the random dispersion error in the horizontal direction; and It is the calculation method of the standard deviation of repeated errors in the firepower data preparation process. and This is the calculation method of the standard deviation of the non-repetitive error caused by the dispersion of the bullet trajectory. and is the standard deviation calculated based on a normal distribution; Step S32: Grid the target, create a bounding box surrounding all targets, and evenly generate grid points within the bounding box. These grid points are used as integration points to calculate the damage value of the entire target. The damage probability of the entire target is calculated as follows: ； （6） in, is the probability of damage caused at the sth grid point, Probability of direct damage and lateral damage probability Joint decision, is the damage probability of the entire target, and N is the total number of grid points within the target; Step S33: For a target that can be destroyed with a single hit, the vertical damage probability and lateral damage probability and the probability of damage from a single hit Calculate using the following formula: ； （7） in, and is the length of the target damage area in the vertical direction and the width in the horizontal direction. and are the mean errors in length and width respectively, erf is the error function, which uses the cumulative distribution function describing the normal distribution, and its calculation result is between -1 and 1; For a target that can only be destroyed by multiple hits, the damage probability is calculated as follows: ； （8） n is the number of shots; Step S34: When calculating the damage probability of the entire target, the confidence interval CI is defined using the following calculation method: ； （9） Where m is the number of times the simulation experiment is repeated. is the critical value of the standard normal distribution, corresponding to a given confidence level, and ST is the standard deviation of the sample, which is related to the dispersion of the results.
2. A fragment cumulative damage assessment method according to claim 1, characterized in that: The step S2 specifically includes: The target area is defined as a rectangular area. Two targets with similar shapes and proportions but different sizes are designed. The area of the first target is 1,000 square meters, and the area of the other target is 500 square meters. The angles with the range axis are 30 degrees and 50 degrees respectively. The core damage area Aera is calculated based on the material, shape of the fragments and the anti-destruction properties of the target material.
3. A fragment cumulative damage assessment system, used to implement a fragment cumulative damage assessment method as claimed in any one of claims 1 to 2, characterized in that: The system includes: The experimental fragment warhead setting module is used to preset the parameters of the fragment warhead, including the mass, caliber, fragment size and quantity of the fragment warhead; and to construct a fragment warhead damage capability matrix function to reflect the damage capability of the warhead to the target at different ranges and yaw angles; The target area setting module is used to define that the performance of each part of the target area being damaged by the attack is uniform. By setting different target area areas and range axial angles, the physical size and spatial direction of different types of damage targets on the battlefield are simulated. At the same time, the core damage area is calculated by combining the material, shape of the fragments and the anti-destruction property of the target material; The fragment cumulative damage calculation module is used to calculate and predict the cumulative damage probability caused by warhead fragments to the target in single and multiple shots, based on the fragment's destructive capability, the target's regional characteristics, and the shooting error factor.