Falling risk assessment method for external wall insulation system

Abstract

The present invention relates to a method for assessing the risk of falling off of an external wall insulation system, including: determining each scoring item of the external wall insulation system, and assigning a deduction for each scoring item; determining the multiple relationship between the effect design value and the resistance design value of the external wall insulation system, and assigning a deduction for the multiple interval in which the multiple relationship is located; subtracting the sum of two deductions from the initial score to obtain a final value, and judging the risk level according to the risk level interval in which the final value is located. The above-mentioned method for assessing the risk of falling off of an external wall insulation system, through big data risk probability analysis and application of probabilistic limit state design methods, can take into account the experience summary of accident cases that have occurred and the essential causes of material damage mechanisms at the same time, improve the accuracy of the risk assessment of falling off, and provide an assessment basis for the inspection, identification, repair and reinforcement of the external wall insulation system.

Description

Technical Field

[0001] The invention relates to the field of civil engineering, and in particular to a method for assessing the risk of falling off of an external wall thermal insulation system. Background Art

[0002] In recent years, the urban problem of falling objects from high altitudes has occurred frequently. Among them, the shedding of the exterior insulation system of the building exterior wall is one of the main types of falling objects from high altitudes. Nowadays, many buildings are gradually entering the "middle-aged and old age". According to incomplete statistics, there are more than 300 publicly reported exterior wall shedding accidents each year, which seriously threaten people's lives and property safety. However, due to the deterioration of the exterior wall and the complex shedding mechanism, the detection methods are limited, and there is currently no method that can comprehensively assess its shedding risk. Summary of the invention

[0003] Based on this, it is necessary to provide an accurate risk assessment method for the external wall insulation system to address the above-mentioned technical issues, taking into account the experience summary of existing accident cases and the essential causes of material damage mechanisms.

[0004] A method for assessing the risk of external wall thermal insulation system falling off, the method comprising:

[0005] Determine the scoring items of the external wall insulation system and assign deduction points to each scoring item;

[0006] Determine the multiple relationship between the effect design value and the resistance design value of the external wall insulation system, and assign deduction points to the multiple interval in which the multiple relationship lies;

[0007] The final value is obtained by subtracting the sum of two deductions from the initial score, and the degree of risk is determined based on the risk level range in which the final value falls.

[0008] Furthermore, the determination of the scoring items of the external wall thermal insulation system includes:

[0009] Establish a database of all types of shedding cases;

[0010] Establish a list of risk factors for dropout;

[0011] Find each scoring item in the risk factor list.

[0012] Furthermore, the deduction of points for each scoring item is assigned, including:

[0013] Calculate the dropout risk probability based on the dropout risk factor list;

[0014] Deduction points are assigned based on the risk probability.

[0015] Furthermore, the list of risk factors for falling out is established, including:

[0016] The fault tree method is used to refine the risk level from the overall to the part in a tree-like manner to identify the basic risk factors.

[0017] Further, the calculating of the probability of falling off risk includes:

[0018] The Monte Carlo method is used to calculate the risk probability of risk factors.

[0019] Furthermore, the method further comprises:

[0020] The effect design value is determined based on experimental research and finite element analysis and is expressed as:

[0021]

[0022] In the formula, S d is the design value of the effect, is the effect of the standard value of the ith permanent action, is the effect of the standard value of wind load, is the effect of the standard value of temperature stress, is the effect of the jth variable action standard value, is the partial coefficient of the ith permanent action, Partial factor for wind load, is the partial coefficient of temperature stress, is the partial coefficient of the jth variable action, ψ cj is the combined value coefficient of the jth variable action.

[0023] Furthermore, the method further comprises:

[0024] The design resistance value is determined based on material strength, material partial factor and structural form.

[0025] Furthermore, the multiple relationship between the effect design value and the resistance design value is:

[0026] γ0S d ≤R d ; R d <γ0S d ≤1.2R d ; 1.2R d <γ0S d ≤1.5R d and γ0S d >1.5R d ; In the formula, γ0 is the severity coefficient of the external wall falling off; R d is the design value of resistance.

[0027] Furthermore, the risk level range includes:

[0028] A: 0≤final value≤20, the risk level is relatively high;

[0029] B: 20<final value≤40, the risk level is high;

[0030] C: 40<final value≤60, low risk;

[0031] D: The final value is above 60, and the risk level is relatively low.

[0032] Furthermore, the initial score is 100.

[0033] The above-mentioned external wall external insulation system falling risk assessment method determines each scoring item through big data risk probability analysis, and determines the multiple relationship between the effect design value and the resistance design value by applying the probabilistic limit state design method. It can take into account the experience summary of existing accident cases and the essential causes of material damage mechanism, improve the accuracy of falling risk assessment, and provide an assessment basis for the inspection, identification, repair and reinforcement of the external wall external insulation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The present invention is a flow chart of a method for assessing the risk of external wall insulation system falling off in one embodiment. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] like Figure 1 As shown, in one embodiment, a method for assessing the risk of external wall thermal insulation system falling off includes the following steps:

[0037] Step S110, determine each scoring item of the external wall insulation system, and assign deductions to each scoring item. Determining each scoring item of the external wall insulation system includes: establishing a database of all types of falling cases; establishing a list of falling risk factors; and finding each scoring item in the risk factor list. Assigning deductions to each scoring item includes: calculating the falling risk probability according to the falling risk factor list; and assigning deductions according to the risk probability. The list of falling risk factors can be established by using the fault tree method to refine the list from the overall to the partial in a tree-like manner, so as to identify the basic risk factors. In addition, the Monte Carlo method can be used to calculate the risk probability of risk factors, wherein the greater the risk probability, the more deductions.

[0038] The specific parameters and deduction values ​​of step S110 can be referred to the following table:

[0039]

[0040]

[0041] The above scoring items may include base materials, external insulation type, finishing layer type and completion time, etc. This is only an example. The specific scoring items can be determined based on the specific risk factor list.

[0042] Step S120, determine the multiple relationship between the effect design value and the resistance design value of the external wall insulation system, and assign a deduction value to the multiple interval in which the multiple relationship is located. The effect design value can be obtained based on experimental research and finite element analysis combined with the formula of the effect design value Calculate; where S d is the design value of the effect, is the effect of the standard value of the ith permanent action, is the effect of the standard value of wind load, is the effect of the standard value of temperature stress, is the effect of the jth variable action standard value, is the partial coefficient of the ith permanent action, Partial factor for wind load, is the partial coefficient of temperature stress, is the partial coefficient of the jth variable action, ψ cj is the combined value coefficient of the jth variable action. The design value of this effect is applicable to the basic combination of permanent and transient conditions.

[0043] The resistance design value can be determined based on the material strength (including the material tensile design value, material shear design value and bond strength design value), material partial coefficient and structural form. Based on the standard value of material strength, the material discreteness and the adverse effects caused by construction deviation are considered and the material strength is judged by dividing it by a material partial coefficient greater than 1.

[0044] The multiple relationship between the above effect design value and resistance design value is: γ0S d ≤R d ; R d <γ0S d ≤1.2R d ; 1.2R d <γ0S d ≤1.5R d and γ0S d >1.5R dWhere γ0 is the severity coefficient of the external wall falling off; R d is the design value of resistance.

[0045] Depending on whether the limit state expression is satisfied, the specific parameters and deduction points of step S120 can be referred to the following table:

[0046]

[0047] Step S130, the final score is obtained by subtracting the sum of the two deductions from the initial score, and the risk level is determined according to the risk level interval in which the final score is located. The initial score is 100.

[0048] For example, the final value S = 100-(a1+a2+…+a n )-b1

[0049] The risk level interval division in step S130 can refer to the following table:

[0050] Score range 0≤S≤20 20＜S≤40 40＜S≤60 60 and above Risk level Larger big Small Smaller Risk Level A B C D

[0051] For example, Building 4# of a certain community was completed in April 2011. The building's exterior walls were finished with a glass bead insulation mortar system and paint. The specific methods for the exterior of the exterior wall (from the inside to the outside) were: 1. Base layer; 2. 10mm thick 1:3 cement mortar leveling; 3. Interface agent; 4. 30mm thick glass bead insulation mortar; 5. 3mm thick anti-cracking mortar, pressed into alkali-resistant plastic-coated glass fiber mesh cloth; 6. Special exterior wall putty plus exterior wall paint surface layer. No external wall insulation system was found to fall off after visual observation on site, cracks were found in the finishing layer, and no water seepage was found; on-site damage inspection of the corners of the exterior wall found that the overlap length of some glass fiber meshes was insufficient; the hollowing rate of the external wall insulation system was detected by infrared thermal imager and was 21%; the tensile bonding strength of the external wall system was tested by sensor force measurement system and was 0.059MPa.

[0052] According to step S110, the deduction items a1=-10, a2=-20, a3=-10, and a4=-10 are determined in sequence. According to step S120, the deduction item b1=-30 is determined. The formula S=100-(a1+a2+…+a n )-b1 calculates the final score to be 20, and conducts risk rating based on the risk range of the final score, and is ultimately assessed as A.

[0053] The above-mentioned external wall external insulation system falling risk assessment method determines each scoring item through big data risk probability analysis, and determines the multiple relationship between the effect design value and the resistance design value by applying the probabilistic limit state design method. It can take into account the experience summary of existing accident cases and the essential causes of material damage mechanism, improve the accuracy of falling risk assessment, and provide an assessment basis for the inspection, identification, repair and reinforcement of the external wall external insulation system.

[0054] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for assessing the risk of external wall thermal insulation system falling off, characterized in that: The method comprises: Determine the scoring items of the external wall insulation system and assign deduction points to each scoring item; Determine the multiple relationship between the effect design value and the resistance design value of the external wall insulation system, and assign deduction points to the multiple interval in which the multiple relationship lies; The final score is obtained by subtracting the sum of the two deductions from the initial score, and the risk level is determined based on the risk level range in which the final score falls. Determining the scoring items of the external wall thermal insulation system includes: Establish a database of all types of shedding cases; Establish a list of risk factors for dropout; Find each scoring item in the risk factor list; The assigning of deduction points for each scoring item includes: Calculate the dropout risk probability based on the dropout risk factor list; Assign deduction points based on risk probability; The method further comprises: The effect design value is determined based on experimental research and finite element analysis and is expressed as: In the formula, S d is the effect design value, is the effect of the standard value of the ith permanent action, is the effect of the standard value of wind load, is the effect of the standard value of temperature stress, is the effect of the jth variable action standard value, is the partial coefficient of the ith permanent action, Partial factor for wind load, is the partial coefficient of temperature stress, is the partial coefficient of the jth variable action, ψ cj is the combined value coefficient of the jth variable action; The method further comprises: The design resistance value is determined based on material strength, material partial factor and structural form.

2. The method for assessing the risk of external wall thermal insulation system falling off according to claim 1 is characterized in that: The list of risk factors for dropouts is as follows: The fault tree method is used to refine the risk level from the overall to the part in a tree-like manner to identify the basic risk factors.

3. The method for assessing the risk of external wall thermal insulation system falling off according to claim 1, characterized in that: The calculating of the probability of falling off risk comprises: The Monte Carlo method is used to calculate the risk probability of risk factors.

4. The method for assessing the risk of external wall thermal insulation system falling off according to claim 1, characterized in that: The multiple relationship between the effect design value and the resistance design value is: γ0S d ≤R d ; R d <γ0S d ≤1.2R d ; 1.2R d <γ0S d ≤1.5R d and γ0S d >1.5R d ; In the formula, γ0 is the severity coefficient of the external wall falling off; R d is the design value of resistance.

5. The method for assessing the risk of external wall thermal insulation system falling off according to claim 1, characterized in that: The risk level range includes: A: 0≤final value≤20, the risk level is relatively high; B: 20<final value≤40, the risk level is high; C: 40<final value≤60, low risk; D: The final value is above 60, and the risk level is relatively low.

6. The method for assessing the risk of external wall thermal insulation system falling off according to claim 5, characterized in that: The initial score is 100.

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