Method for predicting damage degree of island building group after being hit

Abstract

The invention relates to a method for predicting the damage degree of an island building group after being hit, and the method comprises the following steps: dividing the island building group into n building samples, and distributing different damage evaluation weights for each building sample; random variables influencing the damage degree of the island building group are screened, and related parameters of the random variables are determined; establishing an island reef building group damage model; generating m groups of data of random variables based on a random sampling method, inputting the m groups of data into the island building group damage model for damage simulation, and obtaining damage data of each building sample; setting a damage threshold value, judging whether the damage data of each building sample reaches the damage threshold value or not, and determining the damage failure rate of each building sample; and determining the average damage target number of the island building group. The method can perform toughness evaluation on the anti-deliberate strike capability and damage degree of the deep sea island building group, considers the uncertain data boundary of the complex environment, and provides scientific data and information basis for the determination of the protection grade of the deep sea island.

Description

Technical Field

[0001] The present invention relates to the technical field of building structures, in particular to the anti-strike capability of building structures, and specifically to a method for predicting the degree of damage to island reef building complexes after being struck. Background Art

[0002] At present, deep-sea islands and reefs and their affiliated buildings and facilities have gradually become potential primary targets. In this context, how to assess the resilience of these islands and reefs and facilities when they are deliberately attacked and make reasonable defense decisions based on this to improve their protection capabilities has become an urgent need.

[0003] Traditional prediction methods usually rely on some simplified assumptions, such as using linear elastic analysis or only considering the effect of a single load to predict the structural response. However, this method ignores the interaction of multiple factors in the actual environment and the possible uncertainty and complexity, so its prediction results may not accurately reflect the actual situation.

[0004] Therefore, a more advanced prediction method is urgently needed to take into account the degree of damage to deep-sea islands and reefs and their affiliated buildings after being hit under the combined effect of multiple factors, to achieve the construction of a new protection system, to enhance the overall protection performance of islands and reefs and related facilities, and to ensure that they can maintain stable functions in a complex and changing security environment. Summary of the invention

[0005] In view of the deficiencies in the prior art, the main purpose of the present invention is to provide a method for predicting the degree of damage to island reef buildings after being hit, so as to solve the problems of imperfect current prediction methods and low prediction accuracy.

[0006] The technical solution of the present invention is as follows:

[0007] The present invention proposes a method for predicting the degree of damage to an island reef building complex after being hit, comprising the following steps:

[0008] Divide the island and reef building complex into n building samples, and assign different damage assessment weights to each building sample;

[0009] Screening random variables that affect the degree of damage to the island and reef building complex, and determining relevant parameters of the random variables;

[0010] Establishing a damage model for island and reef building complexes based on at least some relevant parameters of the random variables;

[0011] Generate m groups of data of random variables based on random sampling method, and input the m groups of data into the damage model of the island and reef building group to perform damage simulation, so as to obtain damage data of each building sample;

[0012] Set a damage threshold to determine whether the damage data of each building sample reaches the damage threshold. If it reaches the damage threshold, the damage data will be included in the damage failure data set. If it does not reach the damage threshold, the damage data will be included in the damaged data set to determine the damage failure rate of each building sample.

[0013] The average number of damaged targets of the island reef building complex is determined based on the damage assessment weight and damage failure rate of each building sample.

[0014] In some embodiments, the dividing of the island and reef building complex into n building samples and assigning a different damage assessment weight to each building sample specifically includes:

[0015] According to one or more of the importance, anti-destruction ability and dangerousness of the building, the island and reef building complex is divided into n relatively independent building samples;

[0016] Each building sample is analyzed and assigned different weights according to its importance, ability to withstand destruction, and degree of danger;

[0017] Determine the weight function:

[0018]

[0019] Among them, u(x) represents the importance coefficient, v(x) represents the anti-destruction coefficient, w(x) represents the danger coefficient, and F(x) represents the weight of each building sample when evaluating the degree of damage to the island reef building complex.

[0020] In some embodiments, the random variables include one or more of missile lethality, missile hit accuracy, building component geometric parameters, and building component material parameters.

[0021] In some embodiments, the parameters related to the missile's lethality include warhead equivalent W, explosion distance R, and inherent variability ln; wherein the expression of warhead equivalent W is:

[0022]

[0023] Where W n is the nominal explosive equivalent, W u To consider the influence weight of user factors, W NEQ To consider the impact weight of explosive factors;

[0024] And / or, in the missile hit accuracy, the missile landing near the aiming point along the projectile direction and the vertical direction obeys the normal distribution:

[0025]

[0026]

[0027] Where F(x, y) is the probability density function of the missile landing point near the aiming point, σ is the variance of x and y, x is the direction of the missile landing near the aiming point, y is the vertical direction, P is the probability of the missile landing near the aiming point, R p is the standard deviation of the dispersion radius under any probability P;

[0028] And / or, the geometric parameters of the building component include one or more of the cross-sectional height and width of the component, and the height and span of the component;

[0029] And / or, the material parameters of the building component include one or more of the yield strength, elastic modulus, compressive strength, and tensile strength of the component material.

[0030] In some embodiments, the establishment of the island and reef building complex damage model based on at least part of the relevant parameters of the random variables specifically includes:

[0031] Collect the component geometric parameters and component material parameters of each building sample;

[0032] Use geographic information system or CAD software to establish a unified coordinate system to determine the size, location and relationship of each component in the island and reef building complex;

[0033] The concrete structures, beam-column structures, and wall structures in the island and reef building complexes are simplified, and a damage model of the island and reef building complexes is established using 3D modeling software or finite element analysis software.

[0034] In some embodiments, the damage data includes proportional distance and shock wave overpressure peak value, wherein the proportional distance Z is expressed as:

[0035]

[0036] In the formula, R is the explosion distance, W is the warhead equivalent;

[0037] The shock wave overpressure peak The expression is:

[0038] .

[0039] In some embodiments, the damage threshold is set to determine whether the damage data of each building sample reaches the damage threshold, if it reaches the damage threshold, the damage data is counted into the damage failure data set, if it does not reach the damage threshold, the damage data is counted into the damaged data set, and the damage failure rate of each building sample is determined, specifically including:

[0040] Determining the damage assessment criteria of the proportional distance and the shock wave overpressure peak value;

[0041] A damage rating table is obtained by comprehensively considering the proportional distance and the damage assessment criteria of the shock wave overpressure peak value, wherein the damage rating table is divided into severe damage, heavy damage, moderate damage, and no damage or slight damage;

[0042] The damage rating is determined based on the damage data of each building sample, where the damage rating of severe damage or heavy damage is included in the damage failure data set, and the damage rating of moderate damage, no damage, or light damage is included in the damaged data set;

[0043] Determine the damage failure rate G of each building sample based on the damage failure data set i :

[0044] .

[0045] In some embodiments, the damage assessment criteria of the proportional distance are: when the proportional distance is 5-7, the degree of building damage is partial shattering of door and window glass, most of the door and window glass on the pressure surface is shattered, window frame damage and wall cracks; when the proportional distance is 3-5, the degree of building damage is large cracks in the wall, falling tiles, broken pillars of wooden buildings, loose roof frames / collapse of brick walls; when the proportional distance is 1-3, the degree of building damage is damage to earthquake-resistant concrete, collapse of small houses, and damage to large steel frame structures;

[0046] In some embodiments, the damage assessment criteria of the shock wave overpressure peak are: when the shock wave overpressure peak is 1-1.5, the degree of building damage is partial damage to door and window glass; when the shock wave overpressure peak is 3.4-7.6, the degree of building damage is slight damage to some buildings; when the shock wave overpressure peak is 7.6-12.4, the degree of building damage is bending of metal panels; when the shock wave overpressure peak is 12.4-20, the degree of building damage is collapse of concrete block walls; when the shock wave overpressure peak is ≥34.5, the degree of building damage is collapse of wooden frame structures; when the shock wave overpressure peak is 27.6-48.3, the degree of building damage is serious damage to steel frame structures; when the shock wave overpressure peak is 41.4-62.1, the degree of building damage is serious damage to steel-concrete structures; when the shock wave overpressure peak is 69-82.7, the degree of building damage is complete destruction of most buildings;

[0047] In some embodiments, the damage rating is: when the proportional distance is 5-7 and the shock wave overpressure peak is 1-1.5, the damage rating is no damage or slight damage; when the proportional distance is 5-7 and the shock wave overpressure peak is 3.4-7.6 and 7.6-12.4, the damage rating is moderate damage; when the proportional distance is 3-5 and the shock wave overpressure peak is 12.4-20 and ≥34.5, the damage rating is severe damage; when the proportional distance is 1-3 and the shock wave overpressure peak is 27.6-48.3, 41.4-62.1 and 69-82.7, the damage rating is severe damage.

[0048] In some embodiments, the determining the average number of damaged targets of the island reef building complex based on the damage assessment weight and damage failure rate of each building sample specifically includes:

[0049] Determine the damage rate G of island and reef buildings:

[0050]

[0051] Where i=1,2,3...n, n is the number of building samples; F(x i ) is the damage assessment weight of the i-th building sample; G i is the damage failure rate of the i-th building sample;

[0052] Define the total number of island and reef building groups H:

[0053]

[0054] According to the damage rate of island and reef building complexes and the total number of targets in island and reef building complexes, the average number of damaged targets N in island and reef building complexes is determined as follows:

[0055] .

[0056] In some embodiments, the method for predicting the degree of damage to the island and reef building complex after being hit also includes: analyzing the sensitivity of random variables, comparing the impact of different parameters on the degree of damage to the island and reef building complex, and guiding the construction of new protective structures for the island and reef.

[0057] In some embodiments, the analysis of random variable sensitivity, comparison of the impact of different parameters on the degree of damage to island and reef building complexes, and guidance for the construction of new island and reef protection structures specifically include:

[0058] Taking the mean of the random variables that affect the damage degree of the island-reef building complex, forming the initial conditions of the model for analyzing the impact of the island-reef building complex under this situation, and evaluating the damage degree of the island-reef building complex;

[0059] Take the upper or lower limit of a random variable and select the mean value of the remaining random variables to form the initial conditions of the model for the analysis of the impact of the island and reef building complex under this situation, and evaluate the degree of damage to the island and reef building complex;

[0060] The damage degree of island reef building complexes corresponding to all random variables is simulated, where the damage degree of island reef building complexes is quantified by the average damage target of the island reefs, and the deviation values ​​are arranged in descending order;

[0061] The influence of the variability of different random variables on the average number of damaged targets of islands and reefs is analyzed. If the ranking position is high, the result is sensitive to the variation of the parameter, and its variability has a great influence on the probability analysis of the damage degree of the building group; if the ranking position is low, the result is insensitive to the variation of the parameter, and its variability has a small influence on the probability analysis of the damage degree of the building group;

[0062] Construct an island and reef protection system for highly sensitive random variables to reduce the probability of damage to island and reef complexes.

[0063] The beneficial effects of the present invention over the prior art are as follows: the present invention proposes a method for predicting the degree of damage to island and reef buildings after being hit. The method solves the problem of imperfect current prediction methods and low accuracy of damage assessment. By determining the average number of damaged targets, the present invention can provide a deeper understanding of their vulnerability and potential risks. This helps to formulate targeted risk management measures and reduce possible future losses.

[0064] The present invention can determine the average number of damaged targets of island reef building groups based on the damage assessment weight and damage failure rate of each building sample, so as to help determine the protection level of the island reef.

[0065] Based on the average number of damaged targets, the present invention studies known damage situations, can assess the potential losses in similar future attacks, take preventive measures, and strengthen the protection of key facilities. From the damage results, information such as building structural characteristics and material properties can be obtained, which can be used to improve the design of island and reef buildings.

[0066] In the present invention, with the data support of the average number of damaged targets, decision makers can determine the protection level of islands and reefs more scientifically. This helps to allocate resources reasonably and ensure that key areas and buildings are fully protected. At the same time, by accurately assessing risks and scientifically determining the protection level, the present invention helps to optimize the layout and resource allocation of the island and reef defense system. This can not only improve the overall efficiency of the defense system, but also reduce unnecessary cost waste.

[0067] The present invention uses the Monte Carlo method, adopts a large number of random sample analyses, and introduces a probability statistical method to evaluate the damage rate of island reef building groups after being hit. It can handle the uncertainty of input parameters well and make the evaluation results closer to the actual situation.

[0068] The present invention is suitable for parallel computing, can utilize high-performance computing resources to accelerate the simulation process, and can improve evaluation efficiency when dealing with problems of higher complexity.

[0069] The variable sensitivity analysis conducted in the present invention can intuitively reflect the impact of different parameters on the degree of damage to building groups and provide guidance for the construction of new protective structures for islands and reefs.

[0070] It should be understood that the contents described in the Summary of the Invention section are not intended to limit the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easy to understand through the following description. In addition, the implementation of any embodiment of the present invention does not mean that multiple or all of the above-mentioned beneficial effects must be possessed or achieved at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0072] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment in size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0073] Figure 1 Schematic diagram of the flow of a method for predicting the extent of damage to an island reef building complex after being hit according to some embodiments of the present invention. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in conjunction with the embodiments and drawings. Here, the illustrative embodiments of the present invention and their description are used to explain the present invention, but are not intended to limit the present invention.

[0075] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0076] It should be understood that the terms "include / comprise", "consist of..." or any other variations are intended to cover non-exclusive inclusion, so that a product, device, process or method that includes a series of elements includes not only those elements, but also may include other elements not explicitly listed when necessary, or also includes elements inherent to such product, device, process or method. In the absence of more restrictions, the elements defined by the sentence "include / comprise...", "consist of..." do not exclude the presence of other identical elements in the product, device, process or method that includes the elements.

[0077] It is also necessary to understand that terms such as "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside" and "outside" to indicate directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device, component or structure must have a specific direction, be constructed or operate in a specific direction, and should not be understood as a limitation on the present invention.

[0078] The implementation of the present invention is described in detail below in conjunction with preferred embodiments.

[0079] The present invention proposes a method for predicting the degree of damage to island reef buildings after being hit. Figure 1The flowchart shown includes the following steps: S10: dividing the island and reef building complex into n building samples, and assigning different damage assessment weights to each building sample; S20: screening random variables that affect the damage degree of the island and reef building complex, and determining the relevant parameters of the random variables; S30: establishing an island and reef building complex damage model based on at least part of the relevant parameters of the random variables; S40: generating m groups of data of random variables based on the random sampling method, and inputting the m groups of data into the island and reef building complex damage model for damage simulation, and obtaining the damage data of each building sample; S50: setting a damage threshold, judging whether the damage data of each building sample reaches the damage threshold, if it reaches the damage threshold, the damage data is included in the damage failure data set, if it does not reach the damage threshold, the damage data is included in the damaged data set, and the damage failure rate of each building sample is determined; S60: determining the average number of damaged targets in the island and reef building complex based on the damage assessment weight and damage failure rate of each building sample.

[0080] In step S10, the island and reef building complex is divided into n building samples, and a different damage assessment weight is assigned to each building sample.

[0081] This step specifically includes:

[0082] According to one or more of the importance, anti-destruction capability and dangerousness of the buildings on the islands and reefs, the island and reef building complexes are divided into n relatively independent building samples;

[0083] It is easy to understand that these samples can be a single building or a type of buildings in a building complex with the same importance and / or anti-destruction capability and / or explosion resistance level.

[0084] The island and reef building complex can be divided into administrative office areas, residential areas, energy storage areas and temporary facilities according to the building functions.

[0085] Importance usually refers to the functional value of a building in an island or reef complex. Functional value generally refers to the function that a building undertakes and is essential to the overall operation of an island or reef. For example, key facilities such as administrative offices and energy storage areas usually have a high degree of importance.

[0086] Destruction resistance refers to the ability of a building to maintain structural integrity and normal function when it is damaged by external forces. This is usually related to factors such as the building's structural design, material selection, and construction quality. Specifically, the building's destruction resistance can be evaluated from the following aspects:

[0087] Structural stability: whether the structural design of the building is reasonable and whether it can remain stable when subjected to external forces.

[0088] Material strength: whether the building materials have sufficient strength and toughness to resist damage from external forces.

[0089] Construction quality: whether the specifications and standards are followed during the construction process and whether the construction quality meets the requirements.

[0090] The degree of danger refers to the potential harm that a building may cause to people, property and the environment under the influence of natural or human factors. If flammable, explosive or other dangerous goods are stored in the building, the potential risk level increases.

[0091] Each building sample is analyzed and assigned different weights according to its importance, ability to withstand destruction, and degree of danger;

[0092] In this step, a professional assessment team generally assesses the importance, anti-destruction capability and degree of danger of each building sample based on their own professional knowledge and practical experience. Based on the assessment results, the professional assessment team will further determine the weight of each building sample.

[0093] Determine the weight function:

[0094]

[0095] Among them, u(x) represents the importance coefficient, v(x) represents the anti-destruction coefficient, w(x) represents the risk coefficient, and F(x) represents the weight of each building sample when evaluating the damage degree of the island reef building complex, F(x)∈(0,1), When F(x) tends to 0, it means that the importance of the building sample is very low, and its anti-destruction ability is very weak, and the degree of danger is very low, such as temporary facilities. When F(x) tends to 1, it means that the importance of the building sample is very high, and its anti-destruction ability is very strong, and the degree of danger is very high, such as energy storage.

[0096] In step S20, random variables that affect the degree of damage to the island and reef building complex are screened, and relevant parameters of the random variables are determined.

[0097] In this step, the random variables that affect the degree of damage to the island and reef building complex include one or more of the missile killing capability L, the missile hitting accuracy CEP, the geometric parameters of the building components, and the material parameters of the building components.

[0098] In one embodiment, the relevant parameters (influencing factors) of the missile's lethality L mainly include warhead equivalent W, explosion distance R, and inherent variability ln.

[0099] Among them, the warhead equivalent W is mainly determined by the user factor and the explosive factor:

[0100]

[0101] Where W n is the nominal explosive equivalent; W uTo consider the influence weight of user factors, including the variability caused by the use of explosives; W NEQ To consider the impact weight of explosive factors, the variability of explosive equivalent caused by the variability of explosive raw materials and the change of component ratio during the production process of explosives is included.

[0102] The explosion distance R generally refers to the straight-line distance between the explosion point and the building sample.

[0103] The inherent variability ln is an inherent property of the missile, and its deviation is generally small. Specifically, when defining the missile explosive load, the variability of the data read by the relevant personnel and the variability of the instrument data error will lead to the inherent variability of the explosive load.

[0104] In one embodiment, the missile hit accuracy CEP refers to the radius of a circle centered at the aiming point and containing 50% of the impact points. The smaller this radius is, the higher the missile hit accuracy is.

[0105] The falling bullets near the aiming point follow a normal distribution along the projectile direction and in the vertical direction (x and y directions):

[0106]

[0107]

[0108] Where F(x, y) is the probability density function of the missile landing point near the aiming point, σ is the variance of x and y, x is the direction of the missile landing near the aiming point, y is the vertical direction, P is the probability of the missile landing near the aiming point, R p is the standard deviation of the dispersion radius under any probability P; in actual situations, CEP is about 1.18σ;

[0109] It is easy to understand that F is the probability density function, and the integral can get the probability distribution function. Rp is the standard deviation of the dispersion radius of the probability distribution function. When P=50%, R50% is the missile hit accuracy CEP. It is a length statistic, that is, when multiple missiles are fired at a target, half of the missiles must fall within a circle with the average impact point as the center and the circular probability deviation as the radius.

[0110] In one embodiment, the geometric parameters of the building components include one or more of the cross-sectional height and width of the component, and the height and span of the component. The variability thereof is generally caused by the geometric dimension deviation of the component during the transportation, installation, movement and other processes during the construction process. It is easy to understand that the building components are generally walls, columns, beams, floor slabs, roofs, etc.

[0111] In one embodiment, the material parameters of the building component include one or more of the yield strength, elastic modulus, compressive strength, and tensile strength of the component material. The variability is generally affected by factors such as material differences, construction technology, and environmental conditions. It is easy to understand that the material of the component is generally steel, concrete, and the like.

[0112] In step S30, a damage model of island and reef building complexes is established based on at least some relevant parameters of the random variables, specifically including:

[0113] Collect the component geometric parameters and component material parameters of each building sample;

[0114] Use geographic information system or CAD software to establish a unified coordinate system to determine the size, location and relationship of each component in the island and reef building complex;

[0115] The concrete structures, beam-column structures, and wall structures in the island and reef building complexes are simplified, and a damage model of the island and reef building complexes is established using 3D modeling software or finite element analysis software.

[0116] In the actual operation of this step, it is necessary to pay attention to key issues such as the rationality of the simplified processing, model verification and software selection to ensure the accuracy and reliability of the simulation results.

[0117] In step S40, m groups of data of random variables are generated based on the random sampling method, and the m groups of data are input into the damage model of the island reef building complex to perform damage simulation, so as to obtain the damage data of each building sample.

[0118] This step specifically includes:

[0119] Based on the random sampling method, m groups of data of random variables are generated as sample initial conditions. The relevant conditions of the missile strike are determined according to the initial conditions. The sample initial conditions include various relevant parameters determined by random variables that affect the degree of damage to the island and reef building complex. Since the building samples will be hit by missiles at random positions, the range of random parameter changes is generated according to the probability distribution of missile lethality and hit accuracy, as shown in Table 1. The specific values ​​of parameters such as missile hit position, warhead equivalent, explosion distance, inherent variability, etc. are determined by given analysis steps, and m groups of simulated missile attack parameters are obtained.

[0120] Table 1 Related parameters of random variables and their distribution

[0121]

[0122] Take appropriate finite element simulation software, such as ANSYS LS-DYNA, AUTODYN, etc., and use computing resources to perform digital simulation according to the above-mentioned island and reef building group damage model to simulate the missile attack process. After running a single simulation to verify the effectiveness of the model, run the initial conditions for the i-th building sample and simulate and analyze them in turn; then do the same operation for the i+1 building sample, and repeat the simulation to obtain the simulation results of n building samples under the initial conditions; after the simulation is completed, monitor the model data, including the remaining bearing capacity, proportional distance, shock wave overpressure peak value and other data.

[0123] The present invention uses the Monte Carlo method, adopts a large number of random sample analyses, and accelerates the simulation process using high-performance computing resources. It can improve the evaluation efficiency when dealing with complex problems, thereby realizing the digitization of island and reef information. At the same time, the introduction of probabilistic statistical methods to evaluate the degree of damage can handle the uncertainty of input parameters, making the evaluation results closer to the actual situation.

[0124] In some embodiments, proportional distance and shock wave overpressure peak are taken as the damage data of each building sample for detailed description.

[0125] Among them, the expression of proportional distance Z is:

[0126]

[0127] Where R is the explosion distance and W is the warhead equivalent.

[0128] Shock wave overpressure peak The expression is:

[0129]

[0130] In step S50, a damage threshold is set to determine whether the damage data of each building sample reaches the damage threshold. If it reaches the damage threshold, the damage data is included in the damage failure data set; if it does not reach the damage threshold, the damage data is included in the damaged data set to determine the damage failure rate of each building sample.

[0131] In this step, the results are statistically processed, and according to the damage index of building components and the simulation status, different component damage criteria are used to determine whether the building sample has reached the damage threshold. Different component damage criteria require selecting appropriate parameters and damage assessment criteria to evaluate the destructive effect of the explosion on the components based on multiple factors such as the safety, functionality and reusability of the overall structure and the type of components.

[0132] At present, the shock wave parameters such as shock wave pressure, shock wave overpressure peak, impulse, and duration are mainly used to describe the propagation law of the incident shock wave generated by the missile explosion. The magnitude of each shock wave parameter is usually positively correlated with the proportional distance. Here we give a method based on the proportional distance Z and the shock wave overpressure peak. damage criteria.

[0133] In a specific embodiment, the method comprises the following steps:

[0134] Determine the damage assessment criteria for the proportional distance and the peak overpressure of the shock wave;

[0135] The damage rating table is obtained by comprehensively considering the damage assessment criteria of proportional distance and shock wave overpressure peak, which is divided into severe damage, heavy damage, moderate damage, no damage or slight damage;

[0136] The damage rating is determined based on the damage data of each building sample, where the damage rating of severe damage or heavy damage is included in the damage failure data set, and the damage rating of moderate damage, no damage, or light damage is included in the damaged data set;

[0137] In this step, after obtaining the damage result caused by a single missile to the building sample, the damage caused by the single missile is mathematically described and calculated. Given the number of strikes, the calculation results of each strike are accumulated and the results of the established damage model are statistically obtained.

[0138] Determine the damage failure rate of each building sample based on the damage failure data set:

[0139]

[0140] In some embodiments, the damage assessment criteria of the proportional distance are shown in Table 2. When the proportional distance is 5-7, the degree of building damage includes partial shattering of door and window glass, most shattering of door and window glass on the pressure surface, damaged window frames and wall cracks; when the proportional distance is 3-5, the degree of building damage includes large cracks in the wall, fallen tiles, broken pillars of wooden buildings and factories, loose roof trusses / collapse of brick walls; when the proportional distance is 1-3, the degree of building damage includes damage to earthquake-resistant concrete, collapse of small houses and damage to large steel frame structures.

[0141] Table 2 Damage assessment criteria for proportional distance

[0142]

[0143] In some embodiments, the damage assessment criteria of the shock wave overpressure peak are as shown in Table 3. When the shock wave overpressure peak is 1-1.5, the degree of building damage is partial damage to door and window glass; when the shock wave overpressure peak is 3.4-7.6, the degree of building damage is slight damage to some buildings; when the shock wave overpressure peak is 7.6-12.4, the degree of building damage is bending of metal panels; when the shock wave overpressure peak is 12.4-20, the degree of building damage is collapse of concrete block walls; when the shock wave overpressure peak is ≥34.5, the degree of building damage is collapse of wooden frame structures; when the shock wave overpressure peak is 27.6-48.3, the degree of building damage is serious damage to steel frame structures; when the shock wave overpressure peak is 41.4-62.1, the degree of building damage is serious damage to steel-concrete structures; when the shock wave overpressure peak is 69-82.7, the degree of building damage is complete destruction of most buildings.

[0144] Table 3 Damage assessment criteria for shock wave overpressure peak

[0145]

[0146] In some embodiments, the damage rating is as shown in Table 4. When the proportional distance is 5-7 and the shock wave overpressure peak is 1-1.5, the damage rating is no damage or slight damage; when the proportional distance is 5-7 and the shock wave overpressure peak is 3.4-7.6 and 7.6-12.4, the damage rating is moderate damage; when the proportional distance is 3-5 and the shock wave overpressure peak is 12.4-20 and ≥34.5, the damage rating is severe damage; when the proportional distance is 1-3 and the shock wave overpressure peak is 27.6-48.3, 41.4-62.1 and 69-82.7, the damage rating is severe damage.

[0147] Table 4 Damage Rating

[0148]

[0149] In step S60, the average number of damaged targets of the island reef building complex is determined based on the damage assessment weight and damage failure rate of each building sample.

[0150] This step specifically includes:

[0151] Determine the damage rate G of island and reef buildings:

[0152]

[0153] Where i=1,2,3...n, n is the number of building samples; F(x i ) is the damage assessment weight of the i-th building sample; G i is the damage failure rate of the i-th building sample;

[0154] Define the total number of island and reef building groups H:

[0155]

[0156] According to the damage rate of island and reef building complexes and the total number of targets in island and reef building complexes, the average number of damaged targets N in island and reef building complexes is determined as follows:

[0157]

[0158] By determining the average number of damaged targets of island and reef building complexes, the present invention can intuitively understand the degree of damage that island and reef building complexes may suffer under specific attack conditions, so as to conduct resilience assessment on the island and reef building complexes' ability to resist deliberate attacks and the degree of damage, taking into account the uncertainty data boundaries of its complex environment, and providing scientific data and information basis for determining the protection level of deep-sea islands and reefs.

[0159] The present invention provides a range of results that is closer to the actual situation through a large number of iterative simulations, while allowing input parameters (such as new weapon lethality data) to be quickly changed and observing how these changes affect the final results, making the analysis process more flexible and responsive.

[0160] The Monte Carlo simulation in the present invention involves a variety of uncertain factors and complex problems involving multiple interacting variables, and can provide the relationship between various factors and their impact on the overall result, determine which targets are most vulnerable to attack and the expected degree of damage.

[0161] In some embodiments, the method for predicting the degree of damage to island and reef building complexes after being hit also includes: analyzing the sensitivity of random variables, comparing the impact of different parameters on the degree of damage to island and reef building complexes, and guiding the construction of new protective structures for islands and reefs.

[0162] This step specifically includes:

[0163] Take the mean of the random variables that affect the damage degree of the island reef building complex, form the initial conditions of the model for the analysis of the impact of the island reef building complex under this situation, and evaluate the damage degree of the island reef building complex;

[0164] Take the upper limit (mean + standard deviation) or lower limit (mean - standard deviation) of a random variable, and select the mean for all other variables to form the initial conditions of the model for the analysis of the impact of island reef buildings in this case, and evaluate the degree of damage to the island reef buildings;

[0165] The damage degree of island reef building complexes corresponding to all random variables is simulated, where the damage degree of island reef building complexes is quantified by the average damage target of the island reefs, and the deviation values ​​are arranged in descending order;

[0166] The influence of the variability of different random variables on the average number of damaged targets of islands and reefs is analyzed. The higher the ranking position, the more sensitive the result is to the variation of the parameter, and the greater the influence of its variability on the probability analysis of the damage degree of the building group; the lower the ranking position, the less sensitive the result is to the variation of the parameter, and the smaller the influence of its variability on the probability analysis of the damage degree of the building group;

[0167] Construct an island and reef protection system for highly sensitive random variables to reduce the probability of damage to island and reef complexes.

[0168] It is easy for those skilled in the art to understand that, under the premise of no conflict, the above-mentioned preferred solutions can be freely combined and superimposed.

[0169] 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 method for predicting the degree of damage to island and reef building complexes after being hit, characterized in that: The steps include: Divide the island and reef building complex into n building samples, and assign different damage assessment weights to each building sample; Screening random variables that affect the degree of damage to the island and reef building complex, and determining relevant parameters of the random variables; Establishing a damage model for island and reef building complexes based on at least some relevant parameters of the random variables; Generate m groups of data of random variables based on random sampling method, and input the m groups of data into the damage model of the island and reef building group to perform damage simulation, so as to obtain damage data of each building sample; Set a damage threshold to determine whether the damage data of each building sample reaches the damage threshold. If it reaches the damage threshold, the damage data will be included in the damage failure data set. If it does not reach the damage threshold, the damage data will be included in the damaged data set to determine the damage failure rate of each building sample. The average number of damaged targets of the island and reef building complex is determined based on the damage assessment weight and damage failure rate of each building sample.

2. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 1 is characterized in that: The island and reef building complex is divided into n building samples, and different damage assessment weights are assigned to each building sample, including: According to one or more of the importance, anti-destruction ability and dangerousness of the building, the island and reef building complex is divided into n relatively independent building samples; Each building sample is analyzed and assigned different weights according to its importance, ability to withstand destruction, and degree of danger; Determine the weight function: ； Among them, u(x) represents the importance coefficient, v(x) represents the anti-destruction coefficient, w(x) represents the danger coefficient, and F(x) represents the weight of each building sample when evaluating the degree of damage to the island reef building complex.

3. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 1 is characterized in that: The random variables include one or more of missile lethality, missile hit accuracy, geometric parameters of building components, and material parameters of building components.

4. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 3 is characterized in that: The relevant parameters of the missile's lethality include warhead equivalent W, explosion distance R, and inherent variability ln; the expression of warhead equivalent W is: ； Where W n is the nominal explosive equivalent, W u To consider the influence weight of user factors, W NEQ To consider the impact weight of explosive factors; And / or, in the missile hit accuracy, the missile landing near the aiming point along the projectile direction and the vertical direction obeys the normal distribution: ； ； Where F(x, y) is the probability density function of the missile landing point near the aiming point, σ is the variance of x and y, x is the direction of the missile landing near the aiming point, y is the vertical direction, P is the probability of the missile landing near the aiming point, R p is the standard deviation of the dispersion radius under any probability P; And / or, the geometric parameters of the building component include one or more of the cross-sectional height and width of the component, and the height and span of the component; And / or, the material parameters of the building component include one or more of the yield strength, elastic modulus, compressive strength, and tensile strength of the component material.

5. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 1 is characterized in that: The establishment of the island and reef building complex damage model based on at least part of the relevant parameters of the random variables specifically includes: Collect the component geometric parameters and component material parameters of each building sample; Use geographic information system or CAD software to establish a unified coordinate system to determine the size, location and relationship of each component in the island and reef building complex; The concrete structures, beam-column structures, and wall structures in the island and reef building complexes are simplified, and a damage model of the island and reef building complexes is established using 3D modeling software or finite element analysis software.

6. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 1 is characterized in that: The damage data includes proportional distance and shock wave overpressure peak value, wherein the proportional distance Z is expressed as: ； In the formula, R is the explosion distance, W is the warhead equivalent; The shock wave overpressure peak The expression is: 。 7. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 6 is characterized in that: The damage threshold is set to determine whether the damage data of each building sample reaches the damage threshold. If it reaches the damage threshold, the damage data is included in the damage failure data set; if it does not reach the damage threshold, the damage data is included in the damaged data set to determine the damage failure rate of each building sample, specifically including: Determining the damage assessment criteria of the proportional distance and the shock wave overpressure peak value; A damage rating table is obtained by comprehensively considering the proportional distance and the damage assessment criteria of the shock wave overpressure peak value, wherein the damage rating table is divided into severe damage, heavy damage, moderate damage, and no damage or slight damage; The damage rating is determined based on the damage data of each building sample, where the damage rating of severe damage or heavy damage is included in the damage failure data set, and the damage rating of moderate damage, no damage, or light damage is included in the damaged data set; Determine the damage failure rate G of each building sample based on the damage failure data set i : 。 8. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 7 is characterized in that: The determination of the average number of damaged targets of the island and reef building complex based on the damage assessment weight and damage failure rate of each building sample specifically includes: Determine the damage rate G of island and reef buildings: ； Where i=1,2,3...n, n is the number of building samples; F(x i ) is the damage assessment weight of the i-th building sample; G i is the damage failure rate of the i-th building sample; Define the total number of island and reef building groups H: ； According to the damage rate of island and reef building groups and the total number of targets in island and reef building groups, the average number of damaged targets N of island and reef building groups is determined: 。 9. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 1 is characterized in that: The method for predicting the degree of damage to the island and reef building complex after being hit also includes: analyzing the sensitivity of random variables, comparing the impact of different parameters on the degree of damage to the island and reef building complex, and guiding the construction of new protective structures for islands and reefs.

10. The method for predicting the degree of damage to island and reef building complexes after being hit according to claim 9 is characterized in that: The analysis of random variable sensitivity, comparison of the impact of different parameters on the degree of damage to island and reef building complexes, and guidance for the construction of new island and reef protection structures specifically include: Taking the mean of the random variables that affect the damage degree of the island-reef building complex, forming the initial conditions of the model for analyzing the impact of the island-reef building complex under this situation, and evaluating the damage degree of the island-reef building complex; Take the upper or lower limit of a random variable and select the mean value of the remaining random variables to form the initial conditions of the model for the analysis of the impact of the island and reef building complex under this situation, and evaluate the degree of damage to the island and reef building complex; The damage degree of the island and reef building complex corresponding to all random variables is simulated, where the damage degree of the island and reef building complex is quantified by the average damage target of the island and reef, and its deviation values ​​are arranged in descending order; The influence of the variability of different random variables on the average number of damaged targets of islands and reefs is analyzed. If the ranking position is high, the result is sensitive to the variation of the parameter, and its variability has a great influence on the probability analysis of the damage degree of the building group; if the ranking position is low, the result is insensitive to the variation of the parameter, and its variability has a small influence on the probability analysis of the damage degree of the building group; Construct an island and reef protection system for highly sensitive random variables to reduce the probability of damage to island and reef complexes.

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