CN113254880B - Method and device for calculating leakage accident probability of LNG fuel power ship and storage medium - Google Patents
Method and device for calculating leakage accident probability of LNG fuel power ship and storage medium Download PDFInfo
- Publication number
- CN113254880B CN113254880B CN202110606274.5A CN202110606274A CN113254880B CN 113254880 B CN113254880 B CN 113254880B CN 202110606274 A CN202110606274 A CN 202110606274A CN 113254880 B CN113254880 B CN 113254880B
- Authority
- CN
- China
- Prior art keywords
- probability
- event
- risk
- leakage
- ship
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 52
- 239000000446 fuel Substances 0.000 title claims abstract description 44
- 238000003860 storage Methods 0.000 title claims abstract description 24
- 238000004364 calculation method Methods 0.000 claims abstract description 62
- 238000009826 distribution Methods 0.000 claims description 60
- 230000006870 function Effects 0.000 claims description 38
- 239000002828 fuel tank Substances 0.000 claims description 35
- 238000005315 distribution function Methods 0.000 claims description 27
- 230000004044 response Effects 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 11
- 230000007774 longterm Effects 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 9
- 206010000369 Accident Diseases 0.000 claims description 6
- KJLPSBMDOIVXSN-UHFFFAOYSA-N 4-[4-[2-[4-(3,4-dicarboxyphenoxy)phenyl]propan-2-yl]phenoxy]phthalic acid Chemical compound C=1C=C(OC=2C=C(C(C(O)=O)=CC=2)C(O)=O)C=CC=1C(C)(C)C(C=C1)=CC=C1OC1=CC=C(C(O)=O)C(C(O)=O)=C1 KJLPSBMDOIVXSN-UHFFFAOYSA-N 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 239000007789 gas Substances 0.000 description 43
- 235000011470 Adenanthera pavonina Nutrition 0.000 description 23
- 240000001606 Adenanthera pavonina Species 0.000 description 23
- 230000006399 behavior Effects 0.000 description 15
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 10
- 206010039203 Road traffic accident Diseases 0.000 description 9
- 238000012937 correction Methods 0.000 description 9
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 9
- 150000001875 compounds Chemical class 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 6
- 239000010410 layer Substances 0.000 description 6
- 238000011161 development Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 239000011241 protective layer Substances 0.000 description 5
- 238000012795 verification Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 4
- 239000002283 diesel fuel Substances 0.000 description 3
- 238000001704 evaporation Methods 0.000 description 3
- 230000008020 evaporation Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000001012 protector Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 238000009834 vaporization Methods 0.000 description 2
- 230000008016 vaporization Effects 0.000 description 2
- YBJHBAHKTGYVGT-ZKWXMUAHSA-N (+)-Biotin Chemical compound N1C(=O)N[C@@H]2[C@H](CCCCC(=O)O)SC[C@@H]21 YBJHBAHKTGYVGT-ZKWXMUAHSA-N 0.000 description 1
- 238000012935 Averaging Methods 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 239000000809 air pollutant Substances 0.000 description 1
- 231100001243 air pollutant Toxicity 0.000 description 1
- 238000013398 bayesian method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 239000012774 insulation material Substances 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 231100000719 pollutant Toxicity 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- FEPMHVLSLDOMQC-UHFFFAOYSA-N virginiamycin-S1 Natural products CC1OC(=O)C(C=2C=CC=CC=2)NC(=O)C2CC(=O)CCN2C(=O)C(CC=2C=CC=CC=2)N(C)C(=O)C2CCCN2C(=O)C(CC)NC(=O)C1NC(=O)C1=NC=CC=C1O FEPMHVLSLDOMQC-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- 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
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Analysis (AREA)
- Educational Administration (AREA)
- Primary Health Care (AREA)
- Mathematical Physics (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Computational Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Mathematical Optimization (AREA)
- Development Economics (AREA)
- Pure & Applied Mathematics (AREA)
- Evolutionary Biology (AREA)
- Probability & Statistics with Applications (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Computational Biology (AREA)
- Quality & Reliability (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Algebra (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a method and a device for calculating the leakage accident probability of an LNG fuel power ship and a computer readable storage medium, wherein the method comprises the following steps: acquiring data of a risk scene corresponding to an outcome event, and determining the probability of an initial event in the risk scene corresponding to the outcome event according to the data of the risk scene corresponding to the outcome event; determining the risk scene frequency corresponding to the initial event according to the probability of the initial event in the risk scene corresponding to the consequence event; acquiring the probability of occurrence of an outcome event according to the risk scene frequency corresponding to the initial event, and determining the risk probability of the leakage accident according to the probability of occurrence of the outcome event; the method for calculating the leakage accident probability of the LNG fuel power ship realizes the quantitative calculation of the leakage accident probability of the LNG fuel power ship.
Description
Technical Field
The invention relates to the technical field of leakage of LNG fuel powered ships, in particular to a method and a device for calculating the probability of leakage accidents of an LNG fuel powered ship and a computer readable storage medium.
Background
At present, diesel fuel is mainly used in inland river ship power plants in China, air pollutants discharged by the diesel fuel have serious harm to human health and environment, and the healthy development of shipping industry is seriously restricted by the energy structure of the ship fuel mainly comprising diesel. With the energy and environmental problems becoming the focus of worldwide attention, how to effectively reduce the proportion of diesel oil in an energy structure and reduce the emission of atmospheric pollutants of ships is a problem to be solved urgently by constructing a green shipping economy development mode with low energy consumption, low emission and low pollution, and energy conservation, emission reduction and green shipping become important directions for the development of river shipping in China.
The contradiction between the gradually-increased demand for passing a brake and the inability to pass through the three gorges dam of the LNG-fueled ship becomes one of the important bottlenecks for restricting the rapid development of LNG-fueled ships in inland rivers. Because LNG has dangerous characteristics of low temperature, flammability, easy diffusion and the like, once leakage occurs in semi-closed spaces such as ship locks, ship lifts and the like, serious consequences such as combustion, explosion and the like can be caused, and great harm is caused to personnel safety, ship lock structures and the like; quantitative calculation of the leakage accident probability of the LNG fuel power ship is needed to provide corresponding risk prevention and countermeasure measures.
Disclosure of Invention
In view of the above, it is desirable to provide a method, an apparatus and a computer readable storage medium for calculating a leakage accident probability of an LNG-fueled ship, so as to solve the problem that the leakage accident probability of the LNG-fueled ship cannot be quantitatively calculated in the prior art.
The invention provides a method for calculating the leakage accident probability of an LNG fuel power ship, which comprises the following steps:
acquiring data of a risk scene corresponding to an outcome event, and determining the probability of an initial event in the risk scene corresponding to the outcome event according to the data of the risk scene corresponding to the outcome event;
determining the risk scene frequency corresponding to the initial event according to the probability of the initial event in the risk scene corresponding to the consequence event;
and acquiring the probability of occurrence of an outcome event according to the risk scene frequency corresponding to the initial event, and determining the risk probability of the leakage accident according to the probability of occurrence of the outcome event.
Further, determining the probability of the initial event in the risk scenario corresponding to the consequence event according to the data of the risk scenario corresponding to the consequence event, specifically including: and determining the ship collision risk scene corresponding to the fuel tank leakage consequence event and the initial event probability of the ship fire risk scene according to the data of the risk scene corresponding to the consequence event.
Further, determining the initial event probability of the ship collision risk scene and the ship fire risk scene corresponding to the fuel tank leakage consequence event according to the data of the risk scene corresponding to the consequence event, including:
determining the ship collision risk scene corresponding to the fuel tank leakage consequence event and the initial event probability of the ship fire risk scene according to the data of the ship collision risk scene and the ship fire risk scene corresponding to the fuel tank leakage consequence event and a corresponding initial event probability formula;
the initial event probability formula of the ship collision risk scene corresponding to the fuel tank leakage consequence event is
The initial event probability formula of the ship fire risk scene is
Wherein A is the proportion of collision accidents in the total number of accidents of the river trunk ships, B is the proportion of fire accidents in the total number of accidents of the river trunk ships, N is the total number of annual average sluice ships in the dam area in the river,
the expected value of the distribution function of the number of the river trunk monthly ship accidents,
the average contribution factor of the dam area in the river to the total number of accidents of the ship in the river trunk is obtained.
Further, determining the probability of the initial event in the risk scene corresponding to the consequence event according to the data of the risk scene corresponding to the consequence event, further comprising:
determining the initial event probability of the pipeline or equipment failure risk scene corresponding to the gas supply system leakage consequence event according to the pipeline or equipment failure risk scene corresponding to the gas supply system leakage consequence event and a Bayesian formula; the Bayes formula is
Wherein
，i=2，m=1,2,…,6，
、
Respectively, a prior function and a likelihood function of the pipeline or equipment failure class.
Further, determining the probability of the initial event in the risk scene corresponding to the consequence event according to the data of the risk scene corresponding to the consequence event, further comprising:
determining the initial event probability of the human error scene corresponding to the air supply system leakage consequence event according to the human error risk scene data corresponding to the air supply system leakage consequence event and an air supply system leakage probability formula; the leakage probability formula of the gas supply system is
Wherein T is the allowable response time after human error, T is the actual response time after considering the influence factor of the brake passing,
、
、
is a distribution shape parameter.
Further, determining the probability of the initial event in the risk scene corresponding to the consequence event according to the data of the risk scene corresponding to the consequence event, further comprising: according to the power system long-term outage risk scene data corresponding to the safety valve take-off leakage consequence event and the safety valve take-off probability formula
Determining the initial event probability of the power system long-term outage risk scene corresponding to the safety valve take-off leakage consequence event; wherein the content of the first and second substances,
initial event probability, t, of a power system long-term outage risk scenario corresponding to a safety valve jump-out leakage consequence eventvFor the possibility of a safety valve in the process of passing a brakeMaximum leakage time of tsThe average lockdown time of an LNG fuelled ship.
Further, determining a risk scenario frequency corresponding to the initial event according to the probability of the initial event in the risk scenario corresponding to the consequence event, specifically including:
determining the frequency of the risk scene corresponding to the initial event according to a probability and frequency calculation formula of the initial event in the risk scene corresponding to the consequence event; the frequency is calculated by the formula
Wherein ci-m represents the mth risk scenario corresponding to the ith outcome event, n represents the nth independent protection layer corresponding to the mth risk scenario,
for the mth risk scenario frequency corresponding to the ith outcome event,
is the probability of the initial event in the mth risk scenario corresponding to the ith outcome event,
the failure probability of the nth independent protection layer in the mth risk scenario.
Further, according to the risk scene frequency corresponding to the initial event, obtaining the occurrence probability of the consequence event, and determining the risk probability of the leakage accident according to the occurrence probability of the consequence event, specifically including: acquiring the probability of occurrence of an outcome event according to the risk scene frequency corresponding to the initial event and the probability formula of occurrence of the outcome event, and determining the risk probability of the leakage accident according to the probability of occurrence of the outcome event and the risk probability formula; the probability formula of the occurrence of the consequence event is
The risk probability formula is
，PLiFor the occurrence probability of the consequence event i in the time T, i =1, 2 and 3 respectively represent three consequence events of fuel tank leakage, gas supply system leakage and safety valve jump leakage, wherein W is an over-brake mode factor, and S is an over-brake stage factor;
is the occurrence probability of the ith outcome event.
The invention also provides a device for calculating the probability of the leakage accident of the LNG fuel powered ship, which comprises a processor and a memory, wherein the memory is stored with a computer program, and when the computer program is executed by the processor, the method for calculating the probability of the leakage accident of the LNG fuel powered ship is realized according to any technical scheme.
The invention also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the LNG-fueled ship leakage accident probability calculation method according to any one of the above technical solutions.
Compared with the prior art, the invention has the beneficial effects that: determining the probability of an initial event in a risk scene corresponding to an effect event according to the data of the risk scene corresponding to the effect event by acquiring the data of the risk scene corresponding to the effect event; determining the risk scene frequency corresponding to the initial event according to the probability of the initial event in the risk scene corresponding to the consequence event; acquiring the probability of occurrence of an outcome event according to the risk scene frequency corresponding to the initial event, and determining the risk probability of the leakage accident according to the probability of occurrence of the outcome event; the method and the device realize the quantitative calculation of the leakage accident probability of the LNG fuel power ship.
Drawings
Fig. 1 is a schematic flow chart of a method for calculating a leakage accident probability of an LNG-fueled ship according to the present invention;
FIG. 2 is a statistical situation of the water traffic accidents of the Yangtze river and the moon;
FIG. 3 is a Gamma distribution verification P-P diagram of the moon ship accident number of the Yangtze river trunk line provided by the invention;
FIG. 4 is a probability error histogram of pipeline or equipment failure type initial events provided by the present invention.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
Example 1
The embodiment of the invention provides a method for calculating the probability of an accident of leakage of an LNG fuel powered ship, which has a flow schematic diagram, and as shown in FIG. 1, the method comprises the following steps:
s1, acquiring data of a risk scene corresponding to an outcome event, and determining the probability of an initial event in the risk scene corresponding to the outcome event according to the data of the risk scene corresponding to the outcome event;
s2, determining the risk scene frequency corresponding to the initial event according to the probability of the initial event in the risk scene corresponding to the consequence event;
s3, obtaining the probability of the occurrence of the consequence event according to the risk scene frequency corresponding to the initial event, and determining the risk probability of the leakage accident according to the probability of the occurrence of the consequence event.
In one embodiment, the identification results of the risk factors of the LNG-fueled ship leakage accident are shown in table 1;
TABLE 1
The number of a ship collision risk scene corresponding to the fuel tank leakage consequence event is C1-1, the number of a flange joint sealing element failure risk scene corresponding to the gas supply system leakage consequence event is C2-1, and the numbers of risk scenes corresponding to the other consequence events are repeated.
Identification of independent protective layers based on risk identification of related contentIn addition, the failure probability of an independent protective layer has been assigned based on relevant data and research results, and therefore, how to obtain the probability of an initial event in a LOPA (protective layer analysis) risk scenario
Becomes the key to calculating the risk probability.
According to the LOPA risk identification result, fuel tank leakage, gas supply system leakage and safety valve jump leakage are three consequence events of the brake passing system, and considering that the corresponding initial events are different in nature and the probability of all the initial events can not be obtained by using the same probability calculation method, therefore, the appropriate initial event probability calculation methods are selected respectively to ensure the accuracy of risk probability calculation.
For fuel tank leakage in an outcome event, initial events corresponding to risk scenes C1-1 and C1-2 are ship collision and ship fire respectively, and as the occurrence of the ship accident is greatly influenced by the conditions of a navigation water area and the characteristics of a navigation ship and the statistical data of the Yangtze river water traffic accident is rich, the probability of the initial event can be calculated by using a probability calculation method based on statistical distribution, the distribution rule of the three gorges dam region is obtained by using the Yangtze river trunk water traffic accident data fitting, and then the probability of the ship accident initial event is solved.
For the leakage of the air supply system in the consequent event, the corresponding initial events in the LOPA risk scenarios C2-1 to C2-7 can be divided into two categories, namely pipeline or equipment failure and human error. The initial event of pipeline or equipment failure is mostly based on statistical data to carry out probability calculation, while the initial event of human error is mostly based on the subjective factors of people to determine the standard of quantitative judgment, and the two have obvious difference on calculation, so the probability calculation method is further refined. Based on the analysis, for initial events of failure of pipelines or equipment in risk scenes C2-1 to C2-6, considering that the history of LNG as ship fuel is short, accident sample data per se is less, and long-term and continuous failure data records are lacked, therefore, in order to overcome the problem of sample data shortage, a Bayesian estimation method is provided for carrying out quantitative calculation on the failure probability of the pipelines or the equipment by combining with a universal failure database internationally, and the accuracy of quantitative risk calculation of the LNG fuel powered ship passing gate system is improved. For the initial event of human error with the scene number of C2-7, according to the result of risk identification, the situation is further expanded mainly because the human error causes mechanical damage and does not take appropriate reaction in time, so a human reliability analysis (HCR) method with strong reliability is selected to perform quantitative calculation of human error.
For the jump leakage of the safety valve in the consequence event, the initial event corresponding to the LOPA risk scene C3-1 is mainly due to the fact that the power system is stopped for a long time, and the enclosure material of the storage tank cannot be completely insulated, so that the LNG absorbs heat from the external environment and evaporates to form gas, and the pressure in the gas supply system is increased. And selecting proper probability calculation methods for initial events with different properties respectively, and finally realizing quantitative calculation of the leakage accident risk probability of the whole LNG fuel power ship.
Preferably, determining the probability of the initial event in the risk scenario corresponding to the consequence event according to the data of the risk scenario corresponding to the consequence event specifically includes: and determining the ship collision risk scene corresponding to the fuel tank leakage consequence event and the initial event probability of the ship fire risk scene according to the data of the risk scene corresponding to the consequence event.
In one specific implementation, according to the probability calculation method of each initial event, the probability of the initial event corresponding to the fuel tank leakage, the gas supply system leakage and the safety valve jump leakage in the lockage system is respectively calculated
Performing expansion calculation; according to a frequency calculation formula of the LOPA risk scene, combining the calculation result of the initial event probability and the failure probability of the independent protection layer
According to the LOPA risk scene probability calculation table, the LOPA risk scene frequency corresponding to each initial event
Calculating; according to the calculation result of each LOPA risk scene frequency, the occurrence probability of three consequent events, namely fuel tank leakage, gas supply system leakage and safety valve jump leakage
Calculating; calculating two risk probability correction factors of a lockage mode factor W and a lockage stage factor S according to a risk probability model of the lockage system, and simultaneously combining a probability calculation result of an effect event to obtain a risk probability P of the lockage systemLiAnd finally, modeling and calculating the risk probability.
Preferably, the determining the initial event probability of the ship collision risk scenario and the ship fire risk scenario corresponding to the fuel tank leakage consequence event according to the data of the risk scenario corresponding to the consequence event includes:
determining the ship collision risk scene corresponding to the fuel tank leakage consequence event and the initial event probability of the ship fire risk scene according to the data of the ship collision risk scene and the ship fire risk scene corresponding to the fuel tank leakage consequence event and a corresponding initial event probability formula;
the initial event probability formula of the ship collision risk scene corresponding to the fuel tank leakage consequence event is
The initial event probability formula of the ship fire risk scene is
Wherein A is the proportion of collision accidents in the total number of accidents of the river trunk ships, B is the proportion of fire accidents in the total number of accidents of the river trunk ships, N is the total number of annual average sluice ships in the dam area in the river,
the expected value of the distribution function of the number of the river trunk monthly ship accidents,
the average contribution factor of the dam area in the river to the total number of accidents of the ship in the river trunk is obtained.
In a specific embodiment, for the fuel tank leakage consequence event, the probability calculation of the fuel tank leakage corresponding to the initial event is realized by performing statistics and analysis on the existing ship accident data of the Yangtze main line and obtaining the distribution function of the ship accidents in the three gorges dam region by using a statistical fitting method on the basis.
Solving the occurrence probability of the ship accident initial event by using a statistical distribution probability calculation method based on ship accident data; considering that the sample size of ship accident data in the three gorges dam region is small, the annual data and the monthly data are discontinuous, the annual or monthly distribution function of the ship accidents cannot be obtained, the statistical data sample size of the ship accidents in the Yangtze river trunk line is relatively rich, and the distribution function of the ship accidents can be conveniently obtained by a statistical fitting method. Under the condition that the statistical distribution of ship accidents in the three gorges dam region conforms to the overall ship accident distribution rule of the Yangtze main line, the following steps are carried out:
，
in the formula (I), the compound is shown in the specification,
the distribution function of the monthly ship accidents of the Yangtze river trunk line is obtained;
is a lunar vessel in the three gorges dam regionA ship accident distribution function; x is the moon observation value of the water traffic accident of the Yangtze river trunk;
the average contribution factor of the three gorges dam region to the total number of ship accidents of the Yangtze river trunk line represents the ratio of the number of ship accidents of the three gorges dam region to the total number of ship accidents of the Yangtze river trunk line, and can be generally obtained from related data of ship accident statistics;
is a function of
The expected value of (1) represents the number of monthly ship accidents in the three gorges dam region;
is a function of
The expected value of (1) represents the total number of moon ship accidents of the Yangtze river trunk.
When determining the distribution function of the ship accidents of the Yangtze river trunk line
After the expression, the corresponding accident distribution function of the three gorges ship
Can also obtain a function
The expected value is also available
And expressing, after obtaining the expected value of the number of monthly ship accidents in the three gorges dam region, obtaining the ratio of the number of annual ship accidents to the total number of lockage ships in the three gorges dam region, and finally quantifying the LNG leakage probability caused by the annual ship accidents. At the same time, the initial event corresponding to the fuel tank leakage consequence event is consideredThe method also comprises two types of ship collision and ship fire, so that the occupation ratio of the two types of collision and fire in the total number of ship accidents in the Yangtze river trunk line is also required to be respectively calculated; defining the LOPA risk scenario C1-1 corresponding to an initial event probability of
The initial event probability corresponding to scenario C1-2 is
Then, there is,
in the formula, A represents the proportion of collision accidents in the total number of accidents of the ships of the Yangtze river trunk, B represents the proportion of fire accidents in the total number of accidents of the ships of the Yangtze river trunk, and the values of A and B can be obtained by carrying out statistical analysis on corresponding ship accident data; n is the total number of annual average ship passing through the gate in the three gorges dam region and can be obtained through relevant statistical data of navigation ships;
is a function of
Is calculated from the expected value of (c).
According to a probability calculation method based on statistical distribution, a distribution function of the number of moon ship accidents of the Yangtze river trunk line is obtained through accurate fitting
Then the expected value is obtained
And the value of the parameter A, B is key to calculating the probability of the occurrence of an initial event of the marine accident class.
In solving for
Before, the function should be determined first
The distribution form of (a); according to the Yangtze river ship accident statistical data, 48 sample data are selected to analyze the monthly accident statistical condition, the variance of the near-four-year monthly overwater traffic accident statistical value is used as an abnormal data detection index, 2 data which are more than 3 times of the total standard deviation and obviously deviate from most observed values are removed, linear interpolation is carried out, and the Yangtze river monthly overwater traffic accident statistical condition is obtained, and is shown in figure 2.
As can be seen from fig. 2, the moon ship accident of the Yangtze river trunk line shows a certain periodic variation rule, and in order to obtain a distribution function obeyed by the moon ship accident number of the Yangtze river trunk line, the distribution of the accident number is primarily verified by using a distribution probability verification P-P diagram, and the moon ship accident number Gamma distribution verification P-P diagram of the Yangtze river trunk line is shown in fig. 3. The P-P graph is used as a tool for preliminarily checking a parameter distribution function, the closer the data points are to a straight line, the more the group of data accords with certain distribution, and the preliminary checking of the P-P graph shows that the monthly distribution of the water ship accidents of the Yangtze river trunk line basically accords with Gamma distribution.
To further find out a function
The expression (2) is obtained by fitting and solving a curve equation satisfied by the sample data by using MATLAB, and performing distribution verification by using a mean square error function (MSE). The mean square error is the square root of the ratio of the square of the deviation between the predicted value and the true value to the observation frequency n, and can be used for measuring the goodness of the similarity of a curve fitting value, and when the mean square error is smaller, the curve is closer to a true value; table 2 shows the calculation of five common distribution function MSE values of Gamma distribution, normal distribution, Beta distribution, rayleigh distribution, and exponential distribution in the MATLAB fitting solution.
TABLE 2
According to the above table, the MSE value of Gamma distribution is the minimum and is consistent with the conclusion of primary verification by using a P-P diagram, so that the distribution function of the number of monthly ship accidents of the Yangtze river main line
Can be expressed as
In the formula, x is an observed value of a lunar ship accident in a three gorges dam region;
the average contribution factor of the three gorges dam region to the total number of ship accidents of the Yangtze river trunk line is calculated according to statistical data
Take 0.027.
Solving a distribution function according with the number of monthly ship accidents of the Yangtze river trunk line based on the MATLAB calculation result
Respectively are
，
Then the expected value for the Gamma distribution is:
calculated, distribution function
Expected value of
70.46, the distribution function of the number of the moon ship accidents in the three gorges dam region also conforms to Gamma distribution, and then the distribution function of the number of the moon ship accidents in the three gorges dam region can be obtained
Expected value of
Is 1.90.
On the calculation of the ratio of the collision accident to the parameter A and the ratio of the fire accident to the parameter B, through statistical analysis of two types of accident situations of ship collision and fire in the water traffic accident of the Yangtze river trunk from 2008 to 2018, the statistical situation of the types of the water traffic accident from 2008 to 2018 is shown in Table 3,
TABLE 3
It can be seen that the number of collision accidents occupies about half of the total number of water traffic accidents, the annual average percentage is about 45.5%, and the number of fire accidents is relatively small, about 5.40%, so that the parameter a can be determined to be 0.455 and the parameter B can be determined to be 0.054.
The initial event occurrence probability corresponding to the LOPA risk scenario C1-1 can be calculated
Is composed of
Probability of occurrence of initial event corresponding to second/year risk scenario C1-2
Is composed of
The next time/year.
For the leakage consequence events of the gas supply system, the corresponding initial events can be divided into two types, namely pipeline or equipment failure and human error according to the properties, and in consideration of the great difference of the properties of the two types of initial events, a proper initial event probability calculation method is selected according to the theoretical basis of the probability analysis method.
For initial events (risk scenes C2-1 to C2-6) of pipeline or equipment failure, a probability calculation method of Bayesian estimation is adopted, the existing failure database at home and abroad is used as a data source of a prior distribution function and a likelihood function in Bayesian estimation, the probability distribution forms of the prior distribution and the likelihood function are determined through a probability conjugate distribution principle, the expression form of the posterior distribution function is deduced, and the expected value is obtained, namely the probability of the initial events of pipeline or equipment failure.
For the human-induced fault initial event (risk scenario C2-7), the probability of the human-induced fault initial event is quantified by using a human-induced reliability analysis method (HCR method) and according to a probability calculation formula of the human-induced fault in the HCR method.
Preferably, the determining, according to the data of the risk scenario corresponding to the consequence event, the probability of the initial event in the risk scenario corresponding to the consequence event further includes:
determining the initial event probability of the pipeline or equipment failure risk scene corresponding to the gas supply system leakage consequence event according to the pipeline or equipment failure risk scene corresponding to the gas supply system leakage consequence event and a Bayesian formula; the Bayes formula is
Wherein
，i=2，m=1,2,…,6，
、
Respectively, a prior function and a likelihood function of the pipeline or equipment failure class.
In one embodiment, for calculating the failure probability of a pipe or equipment using a Bayesian method, it is most important to obtain a posterior distribution function in a Bayesian estimation as the failure probability of the pipe or equipment
The posterior function can be obtained by a prior function
And normalized likelihood function
The result is obtained according to the Bayesian formula,
can be represented by the following formula:
in the formula (I), the compound is shown in the specification,
specific data representative of the LNG industry is presented,
representing the general data of other industries, wherein both the general data and the general data can be obtained from corresponding failure databases;
according to the basic theory of Bayesian probability calculation method, prior function
And likelihood function
The determination of the distribution form mostly follows the conjugate distribution theorem, i.e. the likelihood function is also called the conjugate likelihood function of the prior distribution, assuming that the prior distribution and the posterior distribution belong to the same type of distribution function[80]. Selecting Gamma distribution and its conjugate likelihood function Poisson distribution as Bayesian distribution function of initial event of pipeline or equipment failure, i.e. assuming failure probability of pipeline or equipment
And its prior function
All satisfy Gamma distribution, likelihood function after normalization
If the poisson distribution is satisfied, then:
in the formula, beta is a proportion parameter, alpha is a shape parameter which are dimensionless numbers, and the distribution shape of the prior function is determined; x and t are shape parameters of the poisson distribution and represent the number of times a certain initial event occurs within t hours as x.
According to the variance calculation formula expected by the Gamma function, the prior function can be obtained
Is expected to
Is alpha/beta, variance
Is alpha/beta2(ii) a Therefore, through the expression of the prior function and the likelihood function, the expression of the posterior function can be derived, and the expression includes:
according to the distribution expression of the failure probability of the pipeline or the equipment, the distribution parameters of the posterior function
And
distribution parameters of available prior functions
And
and the parameters x and t in the likelihood function are expressed as follows:
according to the calculation formula of expectation and variance of Gamma function, posterior distribution function
Expected value of
I.e. the probability of failure of the pipe or equipment
As shown in the following formula:
in the formula (I), the compound is shown in the specification,
and
is the distribution parameter of the prior function, and x and t are the distribution parameters of the likelihood function.
Expected value of a posteriori function
Namely the occurrence probability of the initial event of the failure of the pipeline or the equipment in the LOPA risk scene
The method can be solved by using distribution parameters of a prior function and a likelihood function, so that the key for solving the failure probability of the pipeline or equipment is the calculation of the prior distribution function and the likelihood function.
Based on the related content of the probability calculation method of Bayesian estimation, on the basis of assuming that the prior function of the initial event obeys Gamma distribution, the initial event probability corresponding to the LOPA risk scenes of C2-1 to C2-6 is calculated by utilizing a database (HCRD database, OGP risk evaluation data catalogue, sea-land reliability database or European industrial reliability database); the prior distribution information of the initial event mainly comes from general failure databases such as HCRD (hybrid gas turbine protector), OGP (open gas turbine protector) and the like, wherein the HCRD database provides leakage data of hydrocarbons in the global range, and the leakage data comprise failure probabilities of equipment such as pipeline joints, valves, heat exchangers and the like; table 4 is a prior probability summary of the initial event of the failure class of the pipe or the equipment of the passing brake system.
TABLE 4
In the aspect of information sources of the likelihood functions, according to the relational database, statistical data about the failure probability of pipelines or equipment of the LNG fuel powered ship is almost blank at present, and considering that the structure and the arrangement of a gas supply system of the LNG fuel powered ship are similar to those of terrestrial LNG processing pipelines and equipment, such as equipment with a heat exchanger, an evaporator and the like, and the working environment of the gas supply system is similar to that of the LNG fuel powered ship, the related information of the likelihood functions is obtained mainly through a DNV marine equipment reliability database, an LNG processing industry data report and the like. Table 5 is a list of likelihood function information for initial events of pipeline or equipment failure type.
TABLE 5
Combining the prior function information and the related content of the likelihood function information, the shape parameter of the Gamma distribution of the posterior function can be calculated
And
to further find the expected value of the a posteriori function
That is, the probability of occurrence of the initial event of failure of the pipe or equipment of the passing brake system
. Calculated, initial event probability of pipeline or equipment failure class, as shown in table 6.
TABLE 6
According to the calculation result of the pipeline or equipment failure type initial event probability, the accuracy degree of Bayesian estimation is evaluated, and the range of the confidence interval corresponding to the 95% confidence level is calculated to be used as the error range of Bayesian estimation. According to the statistical principle, for Gamma distribution, the upper limit of the confidence interval corresponding to the 95% confidence level is
And lower limit
The calculation can be made using the following formula:
in the formula (I), the compound is shown in the specification,
the chi-squared distribution function is represented,
and
the quantile of chi-square distribution whose value can be obtained by referring to the chi-square distribution critical probability table corresponding to the degree of freedom, and table 7 is the chi-square distribution critical probability table.
TABLE 7
With reference to the related contents of table 7, error ranges of the initial event probabilities of the LOPA risk scenarios C2-1 to C2-6 solved by using bayesian estimation are respectively obtained, as shown in table 8, and fig. 4 is an initial event occurrence probability histogram with error lines.
Error range cases were calculated based on the initial event probabilities of the bayesian estimates as shown in table 8.
TABLE 8
As can be seen from fig. 4, the failure of the flange joint seal, the failure of the pipeline valve, and the rupture of the gas supply pipeline are the three initial events with the highest probability; when the Bayes estimation method is used for probability calculation, the probability calculation precision of initial events of evaporator failure and supercharging device failure is relatively higher, and the probability calculation of all pipeline or equipment failure initial events is within 3 times of the allowable error range, so that the accuracy of solving the pipeline or equipment failure initial events by using the Bayes estimation-based probability calculation method is higher.
Preferably, the determining, according to the data of the risk scenario corresponding to the consequence event, the probability of the initial event in the risk scenario corresponding to the consequence event further includes:
determining the initial event probability of the human error scene corresponding to the air supply system leakage consequence event according to the human error risk scene data corresponding to the air supply system leakage consequence event and an air supply system leakage probability formula; the leakage probability formula of the gas supply system is
Wherein T is the allowable response time after human error, T is the actual response time after considering the influence factor of the brake passing,
、
、
is a distribution shape parameter.
In one embodiment, the risk identification result of the lockage system is used to identify the leakage of the gas supply system caused by human errors, which mainly takes into account the mechanical damage of the pipeline or equipment caused by human errors, and the LNG leakage caused by taking no effective measures within a certain period of time.
And calculating the human factor error probability by adopting an HCR (human factor response) method according to the determined initial event probability calculation method. By combining the actual process of the LNG fuel power ship lockage, the factors which possibly cause human errors in the lockage system are used as behavior correction factors of response time, so that the leakage probability of the gas supply system caused by the human errors is reduced
Calculating;
this can be calculated from a three parameter weibull distribution as shown below:
wherein T is the response time allowed after human error, and the unit is second, which can be generally defined according to the related emergency response requirement of ship lockage, T is the actual response time corrected by considering the lockage influence factor, and the unit is second,
、
、
is a distribution shape parameter. Thus, for human error probability
For the calculation of (2), it is most important to obtain the distribution shape parameter
、
、
And calculating the corrected actual response time T.
Distribution shape parameter
、
、
The degree of influence of the behavior type of the person on the human factor error probability is represented as a dimensionless number, the value of the dimensionless number can be generally referred to the results of the existing simulation tests at home and abroad, wherein the behavior type of the person is divided into a skill type, a rule type and a knowledge type by using the most assignment method, and the skill type, the rule type and the knowledge type respectively correspond to the skill type, the rule type and the knowledge type
、
、
Value of (2), distribution shape parameter
、
、
The values of (a) are, as shown in table 9,
TABLE 9
According to the actual situation of the LNG fuel power ship lockage system, considering that the lockage operation of a crew is mainly based on a series of training and practice so as to achieve the purpose of skilled operation, the behavior type of a person in the lockage process is defined as a skill type, and the distribution shape parameters of the skill type
、
、
Are respectively 0.407, 1.200 and 0.700.
According to the related content of the HCR method, the corrected actual response time T can be obtained by defining a corresponding behavior correction factor KnThe standard person response time Tc is corrected and obtained as shown in the following formula,
in the formula, T is the corrected actual response time of the personnel and the unit is second; t isCThe response time of a standard person is in seconds, generally the shortest time for a human body to generate effective reaction, and Tc can be 6s according to related research;
a behavior parameter that is a weighted behavior modification factor;
for each behavior modification factorThe weight of (c).
Combining the actual situation of the LNG fuel power ship lockage, providing 5 behavior correction factors of people in the lockage process, respectively selecting corresponding lockage system behavior correction factors for each behavior correction factor, and respectively selecting behavior parameters K and weight of each correction factor
Quantification is performed, and values of behavior correction factors and behavior parameters of the passing gate system are shown in table 10.
In the table, H is the average time to be gated of the three gorges ship in 2019, and the longer the average time to be gated is, the longer the downtime of the ship air supply system is, and the higher the probability of the air supply system failure possibly caused by the operation of personnel is; the MTBF (mean Time Between failure) represents the mean Time Between failures and can represent the continuous working capacity of the gas supply system, and the larger the MTBF value of the gas supply system is, the lower the possibility of the gas supply system to fail in the process of operating personnel is.
The probability calculation of a human error-like initial event for the consequences of gas supply leakage due to human error is shown in table 11, in combination with the parameters associated with the five behavior modification factors of the lockage system.
TABLE 11
The probability of the human error initial event corresponding to the LOPA risk scene C2-7 is calculated
Was 0.0013.
Preferably, the wind corresponding to the consequence event is determined according to the data of the risk scene corresponding to the consequence eventThe probability of the initial event in the risk scenario further comprises: according to the power system long-term outage risk scene data corresponding to the safety valve take-off leakage consequence event and the safety valve take-off probability formula
Determining the initial event probability of the power system long-term outage risk scene corresponding to the safety valve take-off leakage consequence event; wherein the content of the first and second substances,
initial event probability, t, of a power system long-term outage risk scenario corresponding to a safety valve jump-out leakage consequence eventvFor the maximum possible leakage time of the safety valve during the switching-off process, tsThe average lockdown time of an LNG fuelled ship.
According to the risk identification result of the switching-off system, the initial event corresponding to the tripping leakage of the safety valve is that the fuel power system is stopped for a long time, the LNG storage tank cannot be completely insulated from the outside, and the LNG absorbs a large amount of heat to be evaporated, so that the pipeline overpressure caused by excessive BOG gas in the storage tank causes the tripping of the safety valve. The safety valve is used as an automatic valve commonly used in the LNG industry, can prevent the pressure in a container from exceeding a safety value by discharging certain fluid, and is closed and prevents the fluid from continuing to flow after the pressure in the container is recovered to the recoil pressure of the safety valve.
The most dangerous situation is that all BOG gas generated in the switching period is discharged by the safety valve, the possible maximum leakage time of the safety valve is calculated, and the tripping probability of the safety valve in the switching period is obtained, and then:
in the formula (I), the compound is shown in the specification,
the probability of take-off of the safety valve; t is tvThe maximum possible leakage time of the safety valve in the process of switching off is s; t is tsAveraging for LNG-fueled vesselsThe unit of the gate-passing time is h, and the gate-passing time can be obtained according to the vessel navigation statistical data of the three gorges.
Therefore, the key for calculating the tripping leakage probability of the safety valve is to calculate the maximum possible leakage time t of the safety valve in the process of switching overv. BOG gas generated by the LNG storage tank during the waiting period of the LNG fuel power ship is leaked by the jump of the safety valve tvThe calculation can be made using the following formula:
in the formula (I), the compound is shown in the specification,
the total mass of BOG gas generated in the LNG storage tank during the whole lockage period is kg; w is the relief rate of the relief valve in kg/s;
is the density of the LNG;
the filling rate of the fuel tank of the LNG fuel power ship; v is the volume of the fuel tank of the LNG fuel power ship and has the unit of m3；
The daily average boil-off rate of the LNG fuel tank, defined as the mass of LNG vaporized in 24 hours as a percentage of the total mass, is used to characterize the severity of gas production in the LNG tank. And respectively calculating the daily average evaporation rate of the LNG fuel tank and the discharge rate of the safety valve according to the discharge probability model of the safety valve of the lockage system, thereby obtaining the jump leakage probability of the safety valve.
Average daily evaporation rate of LNG
The common methods of calculating (A) are mainly experimental method, natural pressurization method, liquid level difference method and the like, and can be generally carried out by the following formulaAnd (3) calculating:
in the formula (I), the compound is shown in the specification,
is the latent heat of vaporization of LNG, and is 455.87 kJ/kg;
the storage density of LNG is 422.5kg/m3；
The filling rate of the fuel tank of the LNG fuel power ship is generally 75%; v is the volume of the fuel tank of the LNG fuel power ship, and the volume of the fuel tank of the research ship type selected in the text is 20m3(ii) a Q is the daily heat leakage quantity of the LNG storage tank, and the unit is KW.
At LNG storage tank day heat leakage Q's calculation, the external environment temperature does not change during the supposition of passing brake, and temperature distribution is even in the LNG storage tank, then has:
in the formula, K is the heat conduction coefficient of the storage tank material, the unit is W/(m.K), the commonly used storage tank heat insulation material is taken, and K is 0.04W/(m.K); t is0The external environment temperature is 290K; t is the vaporization temperature of LNG and is 112K; a is the effective heat transfer area of the storage tank, and the unit is m2。
For the calculation of the effective heat transfer area A, besides the self-heating area At of the storage tank, the heating area Ap of the pipeline where the safety valve is located is also considered, and the calculation can be carried out by the following formula:
wherein D istAnd LtThe diameter and the effective length of the LNG storage tank are respectively 2.5m and 5 m; dpAnd LtThe diameter and effective length of the pipeline where the safety valve is located are 0.05m and 4m respectively. Daily evaporation rate of available LNG storage tank
It was 0.44%.
On the calculation of the relief rate w of the safety valve, the relief rate is related to the pressure and the flow rate in the pipeline of the LNG fuel powered ship gas supply system, the flow can be divided into two basic forms of critical flow and subcritical flow according to the flow rate, and the relief rate calculation model corresponding to each form is different.
When the gas in the gas supply pipeline is in critical flow, the leakage rate is as follows:
When the gas in the gas supply pipeline flows in a subcritical mode, the leakage rate is as follows:
Wherein w is the leak rate in kg/s; cDFor the leakage coefficient, it is usually 0.61; a is the effective cross-sectional area of the leakage hole, unit m2；PatmIs atmospheric pressure in Pa; pTIs the absolute pressure of the gas supply system, in Pa; k is the adiabatic index of the gas at the leak, k being about 1.371 for natural gas; m is the molar mass of the methane gas and is 16.043 kg/mol; t is the initial temperature of the gas at the leak and is 112K; rAs a gas constant, 8.314J/(mol k) was obtained.
Absolute pressure P at overpressure in the line in which the safety valve is locatedTTo atmospheric pressure PatmIs 0.11, the criterion for critical flow is satisfied, and therefore, the relief valve bleed rate w can be calculated by equation 24. And solving the leakage rate model of the safety valve to determine that the tripping rate w of the lockage safety valve of the LNG fuel power ship is 3.07 kg/s.
The maximum possible leakage time t of the safety valve in the process of passing the brake of the LNG fuel power ship can be obtainedvThe parameters are substituted into a safety valve leakage probability model of an expression type 4-19 for 11.01s, and the take-off probability of the safety valve in the process of passing through the brake of the LNG fuel powered ship, namely the initial event occurrence probability corresponding to the LOPA risk scene C3-1, is calculated
Is composed of
. The trip safety valve take-off probability for LNG-fueled ships is shown in table 12.
TABLE 12
Preferably, determining the risk scene frequency corresponding to the initial event according to the probability of the initial event in the risk scene corresponding to the consequence event specifically includes:
determining the frequency of the risk scene corresponding to the initial event according to a probability and frequency calculation formula of the initial event in the risk scene corresponding to the consequence event; the frequency is calculated by the formula
Wherein ci-m represents the mth risk scenario corresponding to the ith outcome event, n represents the nth independent protection layer corresponding to the mth risk scenario,
for the mth risk scenario frequency corresponding to the ith outcome event,
is the probability of the initial event in the mth risk scenario corresponding to the ith outcome event,
the failure probability of the nth independent protection layer in the mth risk scenario.
Preferably, the method for determining the risk probability of the leakage accident according to the probability of the consequence event includes: acquiring the probability of occurrence of an outcome event according to the risk scene frequency corresponding to the initial event and the probability formula of occurrence of the outcome event, and determining the risk probability of the leakage accident according to the probability of occurrence of the outcome event and the risk probability formula; the probability formula of the occurrence of the consequence event is
The risk probability formula is
，PLiFor the occurrence probability of the consequence event i in the time T, i =1, 2 and 3 respectively represent three consequence events of fuel tank leakage, gas supply system leakage and safety valve jump leakage, wherein W is an over-brake mode factor, and S is an over-brake stage factor;
is the occurrence probability of the ith outcome event.
In one embodiment, the calculation of the risk probability includes the probability of LNG leakage occurring when the fuel tank, the gas supply system and the safety valve jump, and the influence of different lockage modes and lockage stages is comprehensively considered, so that the risk probability model is established as follows:
in the formula, PLiThe occurrence probability of a certain result event i within the time T (unit is year) after correction; i =1, 2 and 3, respectively representing three consequent events of fuel tank leakage, gas supply system leakage and safety valve take-off leakage; w is a lockage mode factor, represents the influence degree of different lockage modes of the LNG fuel power ship on the lockage system risk probability, and is a dimensionless number; s is a lockage stage factor, represents the influence degree of different lockage stages of the LNG fuel power ship on the lockage system risk probability, and is a dimensionless number;
is the occurrence probability of the ith consequence event of the brake-passing system.
Probability of occurrence of event i for a certain consequence
In other words, according to the risk identification result, the same consequence event corresponds to a plurality of initial events to form a plurality of LOPA risk scenarios, and therefore, the frequency of each LOPA risk scenario should be adjusted
Accumulating to obtain the probability of some event
. Meanwhile, according to the frequency calculation formula of the LOPA risk scene,
can be obtained by multiplying the initial event frequency by the probability of failure of all the individual protective layers, then:
in the formula, ci-m represents the mth LOPA risk scene corresponding to the ith outcome event; n represents the corresponding nth individual protective layer in the mth LOPA risk scenario;
the risk scene frequency of the mth LOPA corresponding to the ith outcome event;
the probability of the initial event in the mth LOPA risk scene corresponding to the ith outcome event is obtained;
the failure probability of the nth independent protection layer in the mth LOPA risk scenario.
Example 2
The embodiment of the invention provides a device for calculating the probability of an LNG fuel powered ship leakage accident, which comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for calculating the probability of the LNG fuel powered ship leakage accident in the embodiment 1 is realized.
Example 3
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the LNG-fueled ship leakage accident probability calculation method according to embodiment 1.
The invention discloses a method and a device for calculating the probability of an LNG fuel power ship leakage accident and a computer readable storage medium, wherein the probability of an initial event in a risk scene corresponding to an outcome event is determined according to the data of the risk scene corresponding to the outcome event by acquiring the data of the risk scene corresponding to the outcome event; determining the risk scene frequency corresponding to the initial event according to the probability of the initial event in the risk scene corresponding to the consequence event; acquiring the probability of occurrence of an outcome event according to the risk scene frequency corresponding to the initial event, and determining the risk probability of the leakage accident according to the probability of occurrence of the outcome event; the method and the device realize the quantitative calculation of the leakage accident probability of the LNG fuel power ship.
The technical scheme of the invention provides that a Bayesian estimation method is used for carrying out quantitative calculation on the failure probability of the pipeline or equipment, so that the accuracy of quantitative risk calculation of the lockage system of the LNG fuel powered ship is improved, and the problem of sample data shortage of accidents is solved; from the perspective of combining theory and engineering practice, the risk probability of the LNG fuel powered ship passing brake system is calculated quantitatively, scientific support can be provided for the formulation of the LNG fuel powered ship passing brake related policy, and meanwhile, the method has very important significance for promoting the development of Yangtze river green shipping.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (7)
1. A method for calculating the probability of an accident of leakage of an LNG fuel power ship is characterized by comprising the following steps:
acquiring data of a risk scene corresponding to an outcome event, and determining the probability of an initial event in the risk scene corresponding to the outcome event according to the data of the risk scene corresponding to the outcome event, wherein the method comprises the step of determining the probability of an initial event of a ship collision risk scene and a ship fire risk scene corresponding to a fuel tank leakage outcome event according to the data of the risk scene corresponding to the outcome event;
determining the frequency of the risk scene corresponding to the initial event according to a probability and frequency calculation formula of the initial event in the risk scene corresponding to the consequence event; the frequency is calculated by the formula
Wherein ci-m represents the mth risk scenario corresponding to the ith outcome event, n represents the nth independent protection layer corresponding to the mth risk scenario,
for the mth risk scenario frequency corresponding to the ith outcome event,
is the probability of the initial event in the mth risk scenario corresponding to the ith outcome event,
the failure probability of the nth independent protection layer in the mth risk scene;
acquiring the probability of occurrence of an outcome event according to the risk scene frequency corresponding to the initial event and the probability formula of occurrence of the outcome event, and determining the risk probability of the leakage accident according to the probability of occurrence of the outcome event and the risk probability formula; the probability formula of the occurrence of the consequence event is
The risk probability formula is
，PLiFor the occurrence probability of the consequence event i in the time T, i =1, 2 and 3 respectively represent three consequence events of fuel tank leakage, gas supply system leakage and safety valve jump leakage, wherein W is an over-brake mode factor, and S is an over-brake stage factor;
is the occurrence probability of the ith outcome event.
2. The LNG fuel powered ship leakage accident probability calculation method according to claim 1, wherein determining initial event probabilities of a ship collision risk scenario and a ship fire risk scenario corresponding to a fuel tank leakage consequence event according to data of a risk scenario corresponding to the consequence event comprises:
determining the ship collision risk scene corresponding to the fuel tank leakage consequence event and the initial event probability of the ship fire risk scene according to the data of the ship collision risk scene and the ship fire risk scene corresponding to the fuel tank leakage consequence event and a corresponding initial event probability formula;
the initial event probability formula of the ship collision risk scene corresponding to the fuel tank leakage consequence event is
The initial event probability formula of the ship fire risk scene is
Wherein A is the proportion of collision accidents in the total number of accidents of the ships of the Yangtze river trunk line, B is the proportion of fire accidents in the total number of accidents of the ships of the Yangtze river trunk line, N is the total number of annual gate-passing ships in the three gorges dam region,
the expected value of the distribution function of the number of monthly ship accidents of the Yangtze river trunk line.
3. The method for calculating the probability of the LNG-fueled ship leakage accident according to claim 1, wherein the probability of the initial event in the risk scenario corresponding to the consequence event is determined according to the data of the risk scenario corresponding to the consequence event, and further comprising:
determining the initial event probability of the pipeline or equipment failure risk scene corresponding to the gas supply system leakage consequence event according to the pipeline or equipment failure risk scene corresponding to the gas supply system leakage consequence event and a Bayesian formula; the Bayes formula is
Wherein
，i=2，m=1,2,…,6，
、
Respectively, a prior function and a likelihood function of the pipeline or equipment failure class.
4. The method for calculating the probability of the LNG-fueled ship leakage accident according to claim 1, wherein the probability of the initial event in the risk scenario corresponding to the consequence event is determined according to the data of the risk scenario corresponding to the consequence event, and further comprising:
determining the initial event probability of the human error scene corresponding to the air supply system leakage consequence event according to the human error risk scene data corresponding to the air supply system leakage consequence event and an air supply system leakage probability formula; the leakage probability formula of the gas supply system is
Wherein T is the allowable response time after human error, T is the actual response time after considering the influence factor of the brake passing,
、
、
is a distribution shape parameter.
5. The method for calculating the probability of the LNG-fueled ship leakage accident according to claim 1, wherein the probability of the initial event in the risk scenario corresponding to the consequence event is determined according to the data of the risk scenario corresponding to the consequence event, and further comprising: according to the number of power system long-term outage risk scenes corresponding to the safety valve take-off leakage consequence eventsAccording to the formula of the tripping probability of the safety valve
Determining the initial event probability of the power system long-term outage risk scene corresponding to the safety valve take-off leakage consequence event; wherein the content of the first and second substances,
initial event probability, t, of a power system long-term outage risk scenario corresponding to a safety valve jump-out leakage consequence eventvFor the maximum possible leakage time of the safety valve during the switching-off process, tsThe average lockdown time of an LNG fuelled ship.
6. An apparatus for calculating a probability of an LNG-fueled ship leakage accident, comprising a processor and a memory, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements the method for calculating a probability of an LNG-fueled ship leakage accident according to any one of claims 1 to 5.
7. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method for calculating a leak accident probability of an LNG-fueled ship according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110606274.5A CN113254880B (en) | 2021-06-01 | 2021-06-01 | Method and device for calculating leakage accident probability of LNG fuel power ship and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110606274.5A CN113254880B (en) | 2021-06-01 | 2021-06-01 | Method and device for calculating leakage accident probability of LNG fuel power ship and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113254880A CN113254880A (en) | 2021-08-13 |
| CN113254880B true CN113254880B (en) | 2021-10-19 |
Family
ID=77185602
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110606274.5A Active CN113254880B (en) | 2021-06-01 | 2021-06-01 | Method and device for calculating leakage accident probability of LNG fuel power ship and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113254880B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113868972B (en) * | 2021-09-07 | 2023-02-07 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Data processing method for fuel oil leakage safety based on air oil receiving scene |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106920035A (en) * | 2017-02-15 | 2017-07-04 | 中国石油化工股份有限公司 | A kind of marine oil and gas platform fire incident consequence quantitative estimation method |
| CN110570092A (en) * | 2019-08-12 | 2019-12-13 | 武汉理工大学 | LNG ship navigation safety field determining method |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101286024B1 (en) * | 2011-11-08 | 2013-07-18 | 한국건설기술연구원 | System of decision support for business management of liquefied natural gas(lng) plant |
| US20140310049A1 (en) * | 2011-12-09 | 2014-10-16 | Exxon Mobil Upstream Research Company | Method of generating an optimized ship schedule to deliver liquefied natural gas |
| CN106529809A (en) * | 2016-11-16 | 2017-03-22 | 深圳市燃气集团股份有限公司 | Implementation method for identification of dangerous scene of LNG storage tank leakage |
| CN110245856A (en) * | 2019-06-06 | 2019-09-17 | 中山大学 | A kind of LNG security risk assessment system based on Bayesian network |
| CN110232519A (en) * | 2019-06-11 | 2019-09-13 | 大连海事大学 | A kind of inland river Transportation of Dangerous Chemicals risk evaluating system |
-
2021
- 2021-06-01 CN CN202110606274.5A patent/CN113254880B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106920035A (en) * | 2017-02-15 | 2017-07-04 | 中国石油化工股份有限公司 | A kind of marine oil and gas platform fire incident consequence quantitative estimation method |
| CN110570092A (en) * | 2019-08-12 | 2019-12-13 | 武汉理工大学 | LNG ship navigation safety field determining method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113254880A (en) | 2021-08-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113256127B (en) | LNG fuel power ship gate-passing risk assessment method and device and storage medium | |
| CN112966378B (en) | Hydrogen leakage prediction method and system based on safety evaluation model | |
| Miran et al. | Time-dependent reliability analysis of corroded buried pipelines considering external defects | |
| CN113254880B (en) | Method and device for calculating leakage accident probability of LNG fuel power ship and storage medium | |
| Yamada et al. | Development of natural circulation analytical model in Super-COPD code and evaluation of core cooling capability in Monju during a station blackout | |
| Jeong et al. | Calculation of boil-off gas (BOG) generation of KC-1 membrane LNG tank with high density rigid polyurethane foam by numerical analysis | |
| Suzuki et al. | Quantitative risk assessment of a hydrogen refueling station by using a dynamic physical model based on multi-physics system-level modeling | |
| James et al. | Risk assessment and vulnerability analysis of liquefied natural gas (LNG) regasification terminal | |
| Avrithi et al. | Load and resistance factor design (LRFD) of nuclear straight pipes for loads that cause primary stress | |
| CN116596302A (en) | Buried steel gas pipeline inspection period determining method based on dynamic analysis, electronic equipment and storage medium | |
| Shan et al. | A methodology to determine the target reliability of natural gas pipeline systems based on risk acceptance criteria of pipelines | |
| Correa-Jullian et al. | Liquid Hydrogen Storage System FMEA and Data Requirements for Risk Analysis | |
| CN111539110B (en) | Drain valve internal leakage detection method and device, computer equipment and storage medium | |
| Murthy et al. | Selection of failure frequency and its impact on risk assessment–A case study from plot plan optimisation | |
| CN112101797A (en) | Dynamic fault diagnosis method and system for complex industrial system | |
| Yasseri et al. | Remaining useful life (RUL) of corroding pipelines | |
| Iannaccone et al. | LNG tanks exposed to distant pool fires: a CFD study | |
| Cesna et al. | Reactor cavity and ALS thermal-hydraulic evaluation in the case of fuel channels ruptures at Ignalina NPP | |
| Fan et al. | The reliability estimation of simplified natural gas pipeline compressor stations based on statistics principles | |
| Yasseri | Fragility analysis of corroded pipeline | |
| Zheng et al. | Analyzing the risk of the ammonia storage facility using extended FMEA model based on probabilistic linguistic GLDS method with consensus reaching | |
| Lee et al. | Reliability estimation of buried gas pipelines in terms of various types of random variable distribution | |
| Jullian | Data Requirements to Enable PHM for Liquid Hydrogen Storage Systems from a Risk Assessment Perspective | |
| Yang et al. | Intuitionistic fuzzy-MULTIMOORA-FMEA for FPSO oil and gas processing system | |
| Musyafa et al. | HAZOP Study and Layer of Protection Analysis Based Fuzzy System at Oil Distribution Unit, Surabaya-East Java |
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 |