=Paper=
{{Paper
|id=Vol-1989/paper53
|storemode=property
|title=Application of case-based method to choose scenarios to resolve emergency situations on main gas pipeline
|pdfUrl=https://ceur-ws.org/Vol-1989/paper53.pdf
|volume=Vol-1989
|authors=Artem Kozaev,Dmitry Alexandrov,Hadi Saleh,Ivan Bukhvalov
}}
==Application of case-based method to choose scenarios to resolve emergency situations on main gas pipeline==
https://ceur-ws.org/Vol-1989/paper53.pdf
Application of case-based method to choose scenarios
to resolve emergency situations on main gas pipeline
Kozaev A.T.
MSc in Software Engineering, Vladimir State University named after
Alexander and Nikolay Stoletov (VlSU)
artemkozaev@gmail.com
Saleh H.M.
PhD, Associate Professor of National Research University Higher School of Economics
(NRU HSE), Associate Professor of Vladimir State University named after
Alexander and Nikolay Stoletov
hsalekh@hse.ru
Alexandov D.V.
Dr.Tech.Sci, Professor of National Research University Higher School of Economics,
Professor of Bauman Moscow State Technical University (Bauman MSTU)
dvalexandrov@hse.ru
Buhvalov I.R.
PhD, Federal State Unitary Enterprise Federal Research and Production Center "Scientific-
Research Institute of Measuring Systems named after Y.E. Sedakov" (NIIIS),
irbukhvalov@mail.ru
Abstract. The article is dedicated to application of case-based method in the
problem of choosing correct suitable scenarios to resolve emergency situations
occurring on main gas pipeline. The result of the work is the algorithm for
choosing scenarios with the given level for suitable solutions to resolve emer-
gency situations using base of cases describing emergency situations on main
gas pipeline.
Keywords: main gas pipeline, emergency situation, pipeline rapture, case-
based method
Uninterrupted consumers supply of natural gas depends on effective and safe opera-
tion of Unified Gas Supply System (UGGS) with minimal harmful impact on the
environment and exclusion of accidents and losses associated with them. It is neces-
sary to implement methods to locate and resolve emergency situations on the main
gas pipeline (MGP). [1, 2]
121
In short, gas transportation system consists of linear part, compressor station and
underground gasholders (sometimes).
On the linear part of the main gas pipeline (MGP), some emergency situations (ES)
may occur. Such as [3, 10]:
• drastic change in sensor readings;
• valves malfunction;
• unauthorized rearrangement of valves;
• emergency situations in the management;
• bursting in the linear part of the pipeline;
• ES on the compressor station territory.
Bursting in the linear part of the pipeline is the most dangerous situation. Subsequent
leakage of a large gas volume (millions of cubic meters) can lead to human casualties,
damage natural resources and the environment, and can pose enormous economic
losses. [4, 5]
In the case of bursting of the MGP linear part, it is necessary to determine the loca-
tion of the gas pipeline rupture (the pipe run and the kilometer), before the elimination
of the ES is initiated. Immediately after the rupture detection, it is necessary to start
looking for the solution to this problem and a way to resolve this emergency situation.
Scenario generation algorithms for finding solutions in emergency situations make
scenarios based on the MGP configuration and the location of the main cranes and
jumper cranes, i.e. based only on static data. However, the condition of the MGP
changes over time. Opening or closing of the particular pipeline crane may be impos-
sible at a certain time, because the ability of turning the crane depends on the differ-
ence in pressure in the pipe sections located before and after this crane (the turn of the
crane is impossible if the difference in pressure values exceeds 0.5 kgf / cm2). Solu-
tion or advice to change state of MGP should be proposed to dispatcher as a result of
algorithm. Changes of MGP state should be applied through changes of state of
cranes (open/close). Short scheme of algorithm is presented in the figure 1.
Different sets of main cranes and jumper cranes are available for opening and clos-
ing at different times because of the unstable values of the MGP pressure sensors, in
particular, when the pipe run is bursted. Thus, not all scenarios can be available from
the set of localization and circumvention scenarios obtained by analyzing the MGP
graph.
Turning any crane takes some time. The crane using in specific scenario which is
available for rotation at the moment can become unavailable after a certain time, and
this moment can occur earlier than the dispatcher will finish the crane turning. After
that, this crane can still be unavailable for a certain time (which may be too long in
terms of the required speed of elimination of the ES associated with the rupture). In
this case, the scenario becomes unsuitable for use. In the article, it’s proposed to rep-
resent knowledge in the form of cases as a base of algorithm to form scenarios Case
based methods fits well because emergency situations have common signs and have
the nature of precedents. General case-based method to find precedents for specific
ES was proposed by Buhvalov I.R. and Kokorin A.A. [1]
122
Beginning
Input of
initial data,
including
coordinates
of MGP
rupture
Generation of scenario to
avoid pipe section before and
after pipe rupture
Generation of scenario to
change flow of the gas
through parallel pipes near
localized section with rupture
Generation
of possible
scenarios
to solve
emergency
situation
Ending
Fig. 1. Short scheme of algorithm to generate scenarios to solve emergency situations
It’s necessary to create base of precedents for MGP with specified configuration.
Precedents describe emergency situations and actions necessary to resolve that situa-
tion.
Specification of precedent p contains:
1. array of emergency situations;
2. array of scenarios (advices) describing possible solutions to resolve emergency sit-
uations;
3. array of results of applied scenarios.
Specific emergency situation and array of possible scenarios to solve that emer-
gency situation correspond to each precedent p.
= , (С , ) ,1 ≤ ≤ с,
с – number of possible solutions to resolve scenario.
123
Base of cases stores known scenarios to solve emergency situations that occured
before. The data in base of cases can contain historical data about the results of apply-
ing these scenarios as well. The solution proposed in the scenario is considered ac-
ceptable if the emergency situation is significantly similar to the precedent.
If emergency situation does not have an acceptable solution in the use case base, it
should be eliminated using known algorithms to solve emergency situations. [12, 14]
Descriptions of ES includes information about coordinates of MGP rupture and
state of MGP in that moment. State of MGP includes information about state of
cranes [7, 11].
It was described algorithm to find acceptable scenarios among a variety of different
combinations. The algorithm determines the applicability of scenarios in the condi-
tions of a given ES taking into account various combinations of states on the MGP.
Since it is difficult to determine full compliance of the precedent to this ES, it is
necessary to establish following:
1. criteria on which it is possible to determine the coefficient of conformity of a giv-
en ES to a particular precedent
2. weights, which determine the degree of significance of the individual elements
included in the description of the individual ES
3. the necessary degree of conformity of the ES to the precedent for the correct deci-
sion-making on the elimination of the ES
State of the four-way couplings of the MPG determine the signs of an ES. [8] It is
necessary to generate a comparison matrix for signs of ES. The number of signs is
defined as n. The matrix has the size n x n.
One element of this matix eij is defined as:
= ,( ≠ )∧( ≠ )
= 0, ( = )⋁( = )
– four-way coupling on which rupture occurred, and – distance from four-
way coupling i and j to four-way coupling .
To calculate the weight that determines the degree of significance of the elements,
the following formula is used:
∑
= ,
−1
N – count of four-way couplings, j – number of the element.
When choosing a certain precedent, it is necessary that the four-way coupling in-
dicated in the description of the use case correspond to the four-way coupling corre-
sponding to the rupture given in the description of the specific ES. It is also necessary
124
that the states of the cranes on the MGP match states defined in the description of the
use case.
It is necessary to define coefficient kc (0 ≤ kc ≤1) which determines the required
degree of correspondence of the ES to the precedent.
After determining the coefficient of compliance, the matrix elements of the MPG
and a set of use cases and ES – tests are conducted to determine the most appropriate
precedent for each given ES. [9, 13] For each of the test results it is necessary to
check that the degree of compliance is above the minimum of specified degree of
compliance.
The correspondence of an element to a use case is defined as
1, ℎ
=
0, ℎ
The degree of applicability of the precedent is calculated using the following
formula:
∑
= , ≠ ,
∑
– value of element i, – weight of the element, N – count of elements – four-
way couplings.
The degree of applicability of the use case base is calculated as:
∑
̅= ,
– count of ES, – degree of applicability of the precedent for ES i.
Additional restrictions are:
̅≥ с
̅− ∗ ( )≥ ̅
a – coefficient determined from the results of the experiment; ( ) – standard de-
viation.
∑ ( ̅− )
( )=
To choose precedent applicable to specific ES from the precedents database it is
necessary to perform steps:
1. Set initial value of degree of applicability p = 0
2. Pick precedent from the database.
125
3. Check if precedent fully correspond to ES or is last in database then go to step 6, if
not – go to step 4.
4. Calculate degree of compliance of current precedent to specific ES
5. Check if calculated value is more than current value of p, then assign calculated
value to p and go to step 2
6. If found precedent correspond to ES fully, then result is that precedent. If some
precedents was found then result is a set of precedents. If no precedents found dis-
patcher should be notified that solutions should be found using other algorithms.
After all calculations have been performed, it is necessary to rank the found suitable
precedents by the degree of compliance for a specific ES.
Experiments were performed using the scheme of the existing MGP to test the al-
gorithm. Figure 2 shows the graph of the dependency of degree of compliance of use-
case database to the number of precedents.
1
0,8
Degree of compliance
0,6
0,4
0,2
0
0 1000 2000 3000 4000 5000 6000
Number of precedents
Fig. 2. Graph of the dependency of degree of compliance of use-case database to the number of
precedents
Figure 3 shows a graph of the dependence of the root-mean-square deviation to
the number of precedents.
0,9
0,8
0,7
0,6
Deviation
0,5
0,4
0,3
0,2
0,1
0
0 1000 2000 3000 4000 5000 6000
Number of precedents
Fig. 3. Graph of the dependence of the root-mean-square deviation to the number of precedents
126
The graphs show that with the increase in the number of precedents defined in the
database the value of the degree of correspondence increases, and the scatter of values
for various ES decreases.
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