CN111325385A - Building fire disaster damage estimation method based on BIM and numerical simulation - Google Patents
Building fire disaster damage estimation method based on BIM and numerical simulation Download PDFInfo
- Publication number
- CN111325385A CN111325385A CN202010084623.7A CN202010084623A CN111325385A CN 111325385 A CN111325385 A CN 111325385A CN 202010084623 A CN202010084623 A CN 202010084623A CN 111325385 A CN111325385 A CN 111325385A
- Authority
- CN
- China
- Prior art keywords
- building
- fire
- damage
- component
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Educational Administration (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a building fire disaster damage estimation method based on BIM and numerical simulation, which comprises the following steps: building information BIM model is established and converted into fire model, and the development condition of fire in the building is simulated by using numerical simulation method; extracting fire simulation data, and performing temperature data integration and smoke data integration; writing the integrated data into an attribute table of a building information model, determining the damage degree of various building components according to the integrated temperature data, and performing fouling area statistics according to the integrated smoke data; determining the damage repair sum of the building component and the smoke contamination repair sum of the building component after the fire according to the damage degree of the component and the counted smoke contamination area; and carrying out visual display of damage of the building components and visual display of economic losses of the building. The method can accurately simulate the fire spreading condition in the building after the fire occurs, give the damage assessment and economic loss estimation which are accurate to the component level, and provide technical support for fire departments, insurance industries and the like.
Description
Technical Field
The invention relates to the technical field of civil engineering disaster prevention and reduction, in particular to a building fire disaster damage prediction method based on BIM and numerical simulation.
Background
Fire disasters are inevitable disasters in modern society, and loss caused by fire disasters is increased day by day along with social development. 2 months and 2 nights in 2009, a fire disaster occurs in the central sight north building, which leads to 1 fire fighter to sacrifice and 6 firemen and 2 constructors to be injured. The area of the building which is fired and smokes is 2.1 ten thousand square meters, which causes direct economic loss of 1.6 million yuan. Nowadays, no matter the building insurance evaluation in the fire protection industry or the fire protection modification of old buildings by fire departments, a method for quantitatively evaluating the structural damage and economic loss caused by building fire is urgently needed.
In the current research work, scholars at home and abroad propose corresponding calculation models from various angles such as qualitative analysis, semi-quantitative analysis, probability estimation and the like according to the building Fire loss (LinYS, LinCH, Huang PC. construction of explanatory Fire-loss model for building fires [ J ]. Fire Safety Journal,2009,44(8): 1046-; Brownman, Sunjian. the direct loss estimation of building Fire based on the coupling of Fire dynamics and probability statistics theory [ J ]. Chinese engineering science, 2004,6 (8); Tianyumin. research on the evaluation model of building Fire property loss [ J ]. Fire science and technology, 2015(1): 123-). However, in the existing method, the fire loss is mainly considered as a disaster loss, and the fire loss condition is macroscopically predicted only from the characteristic of randomness in the dual-nature law of the fire, and the development of the fire itself is not considered; for a specific building, most of the research on the fire property loss is based on fire loss evaluation in a qualitative description or semi-quantitative scoring mode, a quantitative property loss evaluation method is lacked, the damage condition of a building component after the fire cannot be accurately evaluated, and the loss caused by smoke pollution in the fire is not considered.
To perform fine building fire disaster damage estimation, high-precision building model information and reasonable and credible fire simulation data are needed. The Building Information Model (BIM) is a working method for applying a digitalized three-dimensional building model as a core to building engineering, and can store and display detailed information of single building component levels; computational Fluid Dynamics (CFD) is a key method for simulating fire in the present situation, in which discrete distributions of fluid flow fluently over continuous areas can be obtained by numerically solving differential equations for controlling fluid flow, thereby approximately simulating fluid flow.
Therefore, the BIM and the numerical simulation method are combined to provide a damage assessment and economic loss estimation method accurate to the component level, and technical support is provided for fire protection modification of old buildings and building fire risk assessment of the insurance industry of fire protection departments.
Disclosure of Invention
The invention aims to provide a building fire disaster damage estimation method based on BIM and numerical simulation, which can realize damage estimation and economic loss estimation accurate to the component level and provide technical support for fire departments to estimate the building fire risk in building fire improvement and insurance industry.
To solve the above technical problem, an embodiment of the present invention provides the following solutions:
a building fire disaster damage prediction method based on BIM and numerical simulation comprises the following steps:
s1, building a building information model, converting the building information model into a fire model, and simulating the development condition of the indoor fire of the building by using a numerical simulation method;
s2, extracting fire simulation data, and performing temperature data integration and smoke data integration;
s3, writing the integrated data into an attribute table of the building information model, determining the damage degree of various building components according to the integrated temperature data, and performing fouling area statistics according to the integrated smoke data;
s4, determining the damage repair sum of the building component and the smoke pollution repair sum after the fire according to the damage degree of the component and the counted smoke pollution area;
and S5, visually displaying the damage of the building component and the economic loss of the building.
Preferably, in the step S2, the extracted fire simulation data includes a building component surface temperature value, a building component ID, and building component coordinate range information.
Preferably, the step S2 specifically includes:
screening the ID and coordinate range information of each building component, and performing integration and normalization processing on the repeated information;
extracting temperature data of a solid boundary of the fire model, wherein the temperature data comprises a temperature value and a corresponding coordinate range;
and matching the temperature values of the corresponding coordinate ranges with the corresponding building component IDs, sequencing the temperature values of the building components from large to small, and selecting the temperature value with 5% of rank as the surface temperature of the building component.
Preferably, in step S3, the step of determining the damage degree of each type of building component according to the integrated temperature data includes:
screening out corresponding building components according to the types of the building components by taking the ID of the building components as a medium, and writing in matched temperature values;
and judging the damage degree and the damage rate of the building component according to the surface temperature of the building component and the industry standard, and writing the damage degree and the damage rate into an attribute table of the corresponding component.
Preferably, in the step S3, the step of performing fouling area statistics according to the integrated smoke data includes:
acquiring a room boundary according to the room number in the building information model, constructing a bounding box, and selecting all building components contained in the room;
determining the fouling range by using the height of the smoke layer: if the height of the smoke layer exceeds half of the height of the building layer, the whole periphery of the room is considered to be polluted, otherwise, only the ceiling is considered to be polluted;
and acquiring the areas of the polluted ranges of all the rooms, and counting to obtain the total area of the buildings polluted by the smoke.
Preferably, in the step S4, the step of determining the repair sum for damage to the building component and the repair sum for smoke contamination after the fire includes:
multiplying the unit loss data of the building components by the repair engineering measurement data to obtain the repair amount of each building component;
and adding the repairing sums of all the building components to obtain the integral repairing sum of the building.
Preferably, in the step S5, the building element damage visualization is displayed as five different colors according to the damage degree of the building element, and the five colors are sequentially from weak to strong according to the damage degree: blue, green, yellow, orange, red.
Preferably, in the step S5, the building economic loss visualization divides the economic loss into four levels according to the ratio of the repair cost to the construction cost, and sequentially: 0-25% is semitransparent white, 25-50% is green, and 50-75% is yellow; 75% -100% is red.
The scheme of the invention at least comprises the following beneficial effects:
the method can accurately simulate the fire spreading condition in the building after the fire, gives the damage assessment and economic loss estimation which are accurate to the component level, and provides technical support for the fire department to the building fire improvement and the insurance industry to assess the fire risk of the building.
Drawings
FIG. 1 is a flow chart of a building fire disaster damage prediction method based on BIM and numerical simulation according to an embodiment of the present invention;
FIG. 2 is a three-dimensional schematic of a building in an embodiment of the invention;
FIG. 3 is a schematic diagram of a building fire model in an embodiment of the invention;
FIG. 4 is a schematic diagram of a fire simulation data integration process according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of a process for associating temperature data with a building component in an embodiment of the present invention;
FIG. 6 is a schematic flow chart of the statistics of the area of smoke fouling in an embodiment of the invention;
fig. 7 is a diagram illustrating a disaster result in an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
The embodiment of the invention provides a building fire disaster damage estimation method based on BIM and numerical simulation, as shown in FIG. 1, the building fire disaster damage estimation method comprises the following steps:
s1, building a building information model, converting the building information model into a fire model, and simulating the development condition of the indoor fire of the building by using a numerical simulation method;
s2, extracting fire simulation data, and performing temperature data integration and smoke data integration;
s3, writing the integrated data into an attribute table of the building information model, determining the damage degree of various building components according to the integrated temperature data, and performing fouling area statistics according to the integrated smoke data;
s4, determining the damage repair sum of the building component and the smoke pollution repair sum after the fire according to the damage degree of the component and the counted smoke pollution area;
and S5, visually displaying the damage of the building component and the economic loss of the building.
The method can accurately simulate the fire spreading condition in the building after the fire, gives the damage assessment and economic loss estimation which are accurate to the component level, and provides technical support for the fire department to the building fire improvement and the insurance industry to assess the fire risk of the building.
Further, in step S2, the extracted fire simulation data includes a building element surface temperature value, a building element ID, and building element coordinate range information.
Further, step S2 specifically includes:
screening the ID and coordinate range information of each building component, and performing integration and normalization processing on the repeated information;
extracting temperature data of a solid boundary of the fire model, wherein the temperature data comprises a temperature value and a corresponding coordinate range;
and matching the temperature values of the corresponding coordinate ranges with the corresponding building component IDs, sequencing the temperature values of the building components from large to small, and selecting the temperature value with 5% of rank as the surface temperature of the building component.
Further, in step S3, the step of determining the damage degree of each type of building component according to the integrated temperature data includes:
screening out corresponding building components according to the types of the building components by taking the ID of the building components as a medium, and writing in matched temperature values;
and judging the damage degree and the damage rate of the building component according to the surface temperature of the building component and the industry standard, and writing the damage degree and the damage rate into an attribute table of the corresponding component.
The step of performing fouling area statistics according to the integrated smoke data comprises the following steps:
acquiring a room boundary according to the room number in the building information model, constructing a bounding box, and selecting all building components contained in the room;
determining the fouling range by using the height of the smoke layer: if the height of the smoke layer exceeds half of the height of the building layer, the whole periphery of the room is considered to be polluted, otherwise, only the ceiling is considered to be polluted;
and acquiring the areas of the polluted ranges of all the rooms, and counting to obtain the total area of the buildings polluted by the smoke.
Further, in step S4, the step of determining the repair amount of damage to the building component and the repair amount of smoke contamination after the fire includes:
multiplying the unit loss data of the building components by the repair engineering measurement data to obtain the repair amount of each building component;
and adding the repairing sums of all the building components to obtain the integral repairing sum of the building.
Further, in step S5, the building element damage visualization is displayed as five different colors according to the damage degree of the building element, and the five colors are sequentially from weak to strong according to the damage degree: blue, green, yellow, orange, red.
The construction economic loss is visualized, the economic loss is divided into four levels according to the proportion of the repair cost to the construction cost for display, and the four levels are as follows: 0-25% is semitransparent white, 25-50% is green, and 50-75% is yellow; 75% -100% is red.
In the specific implementation, as shown in fig. 2, a BIM model of a floor level building of a hospital in a certain area of china is established, and a fire simulation software FDS is imported through an intermediate conversion file and converted into a fire model (fig. 3) to perform fire simulation. After the simulation is completed, according to the characteristic that the three-dimensional position coordinate information of the same building component is the same as the corresponding fire scene temperature coordinate, the integration of the data is completed according to the flow shown in fig. 4, and the IDs of different building components and the corresponding fire temperature data can be obtained. Similarly, the number of each room and the relative height data of the smoke layer are obtained by processing the room smoke layer height monitoring information.
After finishing the arrangement of the fire simulation data, hanging the fire temperature data with corresponding building components in the BIM model one by taking the ID as an index; and (4) taking the room number as an index, and judging whether the whole room is filled with smoke by using the smoke layer height data so as to complete the statistics of the smoke polluted area of the building. The flow of attaching the fire scene temperature data to the building component is shown in fig. 5, the coordinate information of the building component is selected, the temperature point data meeting the range is screened one by one, the selected temperature data and the ID of the building component are stored in an array, and the array is output after all the temperature point data are screened once and is continuously matched with the next building component.
The statistics of the smoke pollution area mainly uses the room number as a basis, the boundary range of each room is filtered in the building information model, all building components in the range are screened, and then the smoke pollution area is calculated according to the relative height of the smoke layer in the room, and the specific flow is shown in fig. 6.
And after the information is hung, evaluating the damage degree of each building component by taking the surface temperature value of the building component as a criterion, and determining the burning loss rate of each building component. Then, extracting the metering data of each building component from the BIM model, and determining the corresponding construction cost according to the existing construction budget; and calculating the cost required by the repair of the building components with different burning degrees by combining the existing building repair quota.
After the disaster damage estimation is completed, the specific damage result and the repair amount of each building component can be checked in the attribute table of the BIM model, as shown in fig. 7. In addition, in order to conveniently and more intuitively show the disaster damage condition of the building, the components are colored from weak to strong according to the damage degree of the building components: the material is perfectly blue, slightly burned to green, generally burned to yellow, seriously burned to orange and completely burned to red; the economic loss visualization is divided into four levels according to the proportion of the repair cost to the construction cost, and the four levels are sequentially as follows: 0-25% is semitransparent white, 25-50% is green, and 50-75% is yellow; 75% -100% is red.
The estimated economic loss condition of the hospital building according to the method of the invention is as follows:
besides the repair cost caused by the damage of the component caused by the fire passing through the building, the building smoke pollution repair amount is calculated according to the smoke passing area of the building, and the following steps are carried out:
comparing the loss results of two calculations, it can be seen that in a general small building fire accident, the damage of fire burning to the building itself is small, and the post-disaster repair amount only accounts for 4.82% of the building cost. Among these losses, there are repair costs due to damage to the member and stain repair costs due to the surface of the member being submerged by smoke generated from a fire, which accounts for 11.7% of the total amount of the stain repair costs, and cannot be ignored.
Through the steps, the method realizes the fine estimation of the fire disaster damage of the building component level, can further accurately estimate the damage and the loss condition to the specific building component, can provide specific component loss distribution, and provides an important reference basis for the recovery of the building after the disaster.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A building fire disaster damage prediction method based on BIM and numerical simulation is characterized by comprising the following steps:
s1, building a building information model, converting the building information model into a fire model, and simulating the development condition of the indoor fire of the building by using a numerical simulation method;
s2, extracting fire simulation data, and performing temperature data integration and smoke data integration;
s3, writing the integrated data into an attribute table of the building information model, determining the damage degree of various building components according to the integrated temperature data, and performing fouling area statistics according to the integrated smoke data;
s4, determining the damage repair sum of the building component and the smoke pollution repair sum after the fire according to the damage degree of the component and the counted smoke pollution area;
and S5, visually displaying the damage of the building component and the economic loss of the building.
2. The method according to claim 1, wherein the extracted fire simulation data in step S2 includes a building component surface temperature value, a building component ID, and building component coordinate range information.
3. The method according to claim 2, wherein the step S2 specifically includes:
screening the ID and coordinate range information of each building component, and performing integration and normalization processing on the repeated information;
extracting temperature data of a solid boundary of the fire model, wherein the temperature data comprises a temperature value and a corresponding coordinate range;
and matching the temperature values of the corresponding coordinate ranges with the corresponding building component IDs, sequencing the temperature values of the building components from large to small, and selecting the temperature value with 5% of rank as the surface temperature of the building component.
4. The method according to claim 3, wherein the step of determining the damage degree of each building component according to the integrated temperature data in step S3 includes:
screening out corresponding building components according to the types of the building components by taking the ID of the building components as a medium, and writing in matched temperature values;
and judging the damage degree and the damage rate of the building component according to the surface temperature of the building component and the industry standard, and writing the damage degree and the damage rate into an attribute table of the corresponding component.
5. The method for predicting the damage to the building fire according to claim 3, wherein in step S3, the step of performing statistics on the fouling area according to the integrated smoke data includes:
acquiring a room boundary according to the room number in the building information model, constructing a bounding box, and selecting all building components contained in the room;
determining the fouling range by using the height of the smoke layer: if the height of the smoke layer exceeds half of the height of the building layer, the whole periphery of the room is considered to be polluted, otherwise, only the ceiling is considered to be polluted;
and acquiring the areas of the polluted ranges of all the rooms, and counting to obtain the total area of the buildings polluted by the smoke.
6. The method for estimating the damage to the building fire according to claim 1, wherein in step S4, the step of determining the damage repair amount and the smoke contamination repair amount of the building component after the fire includes:
multiplying the unit loss data of the building components by the repair engineering measurement data to obtain the repair amount of each building component;
and adding the repairing sums of all the building components to obtain the integral repairing sum of the building.
7. The method according to claim 1, wherein in step S5, the building element damage visualization is displayed in five different colors according to the damage degree of the building element, and the five colors are sequentially from weak to strong according to the damage degree: blue, green, yellow, orange, red.
8. The method for predicting fire damage of a building according to claim 1, wherein in step S5, the building economic loss visualization divides the economic loss into four levels according to the ratio of the repair cost to the construction cost, and sequentially: 0-25% is semitransparent white, 25-50% is green, and 50-75% is yellow; 75% -100% is red.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010084623.7A CN111325385B (en) | 2020-02-10 | 2020-02-10 | Building fire disaster damage estimation method based on BIM and numerical simulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010084623.7A CN111325385B (en) | 2020-02-10 | 2020-02-10 | Building fire disaster damage estimation method based on BIM and numerical simulation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111325385A true CN111325385A (en) | 2020-06-23 |
| CN111325385B CN111325385B (en) | 2020-11-06 |
Family
ID=71172674
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010084623.7A Active CN111325385B (en) | 2020-02-10 | 2020-02-10 | Building fire disaster damage estimation method based on BIM and numerical simulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111325385B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113593333A (en) * | 2021-05-20 | 2021-11-02 | 中国人民解放军总参谋部第六十研究所 | Be applied to building simulator of real soldier's combat training |
| CN113888950A (en) * | 2021-11-08 | 2022-01-04 | 中国科学技术大学 | Village historic building fire induces building group fire simulation experiment device under effect of environmental wind |
| CN114036613A (en) * | 2021-11-09 | 2022-02-11 | 香港理工大学 | Building fire protection design evaluation method and device based on artificial intelligence |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101763605A (en) * | 2010-01-28 | 2010-06-30 | 成都东哈科技有限公司 | Three-dimensional digital urban fire protection pre-control and management system |
| CN105512394A (en) * | 2015-12-08 | 2016-04-20 | 东南大学 | Analysis system and analysis method for overall fire resistance of beam-post wood structure frame |
| CN108108545A (en) * | 2017-12-15 | 2018-06-01 | 石化盈科信息技术有限责任公司 | Display methods and device are deduced in fire incident simulation based on GIS-Geographic Information System |
| CN109544386A (en) * | 2018-11-07 | 2019-03-29 | 北京科技大学 | A kind of building concentration earthquake insurance rating method based on Building Information Model |
-
2020
- 2020-02-10 CN CN202010084623.7A patent/CN111325385B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101763605A (en) * | 2010-01-28 | 2010-06-30 | 成都东哈科技有限公司 | Three-dimensional digital urban fire protection pre-control and management system |
| CN105512394A (en) * | 2015-12-08 | 2016-04-20 | 东南大学 | Analysis system and analysis method for overall fire resistance of beam-post wood structure frame |
| CN108108545A (en) * | 2017-12-15 | 2018-06-01 | 石化盈科信息技术有限责任公司 | Display methods and device are deduced in fire incident simulation based on GIS-Geographic Information System |
| CN109544386A (en) * | 2018-11-07 | 2019-03-29 | 北京科技大学 | A kind of building concentration earthquake insurance rating method based on Building Information Model |
Non-Patent Citations (4)
| Title |
|---|
| YANG ZHAO: "Study on the Data Exchanges between Building Information Model and Fire Dynamics Simulator", 《2018 JOINT INTERNATIONAL ADVANCED ENGINEERING AND TECHNOLOGY RESEARCH CONFERENCE》 * |
| 吴立志等: "商场类建筑火灾直接财产损失预估模型", 《消防科学与技术》 * |
| 杨艳军: "基于FDS模拟的建筑物火灾损失量化方法研究", 《武警学院学报》 * |
| 许镇 等: "基于BIM和FEMA P-58的建筑地震次生火灾模拟", 《消防科学与技术》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113593333A (en) * | 2021-05-20 | 2021-11-02 | 中国人民解放军总参谋部第六十研究所 | Be applied to building simulator of real soldier's combat training |
| CN113593333B (en) * | 2021-05-20 | 2022-12-06 | 中国人民解放军总参谋部第六十研究所 | Be applied to building simulator of real soldier's combat training |
| CN113888950A (en) * | 2021-11-08 | 2022-01-04 | 中国科学技术大学 | Village historic building fire induces building group fire simulation experiment device under effect of environmental wind |
| CN114036613A (en) * | 2021-11-09 | 2022-02-11 | 香港理工大学 | Building fire protection design evaluation method and device based on artificial intelligence |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111325385B (en) | 2020-11-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111325385B (en) | Building fire disaster damage estimation method based on BIM and numerical simulation | |
| CN115330957B (en) | Method for simulating diffusion of fire smoke in building and emergency scheme calling method | |
| Nadeem et al. | Bill of quantities with 3D views using building information modeling | |
| CN101071098A (en) | Underground steel gas pipe network pipeline corrosion prediction system | |
| CN111400800B (en) | Building construction quality control system and method based on BIM and VR technology | |
| CN104766160A (en) | Safety production diagnosing and early warning system based on inherent danger level of enterprise | |
| CN104778369A (en) | Method and system for decision making and early warning based on ground subsidence monitoring | |
| Simonen et al. | Embodied carbon as a proxy for the environmental impact of earthquake damage repair | |
| CN201229289Y (en) | Corrosion predicting device | |
| CN114862289B (en) | Construction parameter-based safety state confirmation method and device | |
| CN116050827A (en) | Fire risk assessment method for cable compartment of urban underground comprehensive pipe rack | |
| CN116363825B (en) | Method and device for displaying fire spreading trend, electronic equipment and medium | |
| CN107589063B (en) | Dynamic atmospheric corrosion area map data processing method, device and system | |
| CN113256084A (en) | BIM-based intelligent building economic index statistical and checking method and system | |
| CN116305498B (en) | Construction method and analysis method for tunnel digital twin modeling index judgment network model | |
| CN116975680A (en) | Method, device, system, electronic equipment and medium for processing fire alarm condition | |
| CN107818425B (en) | Evaluation method for gas explosion risk of coal face | |
| ElSharkawy | Workplace hazards and safety practices in the small-scale industries | |
| CN103336861B (en) | The auxiliary investigating system of sootiness carbon black vestige fire and method | |
| CN114021864A (en) | Method for identifying major risks and evaluating real-time dynamic risks of ammonia-related refrigeration enterprises | |
| Brandon | Cost versus quality: a zero sum game? | |
| Ji et al. | Factors influencing fire accidents in urban complexes: a combined DEMATEL and ISM study | |
| CN116386163B (en) | Method and system for patrol management, electronic equipment and storage medium | |
| Gao et al. | Design and simulation of building fire protection system based on BIM technology | |
| Thongsean et al. | Energy Performance and Thermal Comfort in a Library Building: A Case Study of Dhurakij Pundit University, Thailand |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |