Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy
A technique of quantitative determination of europium by proton-induced X–ray emission (PIXE) using of 1.6 MeV energy and measurement of the characteristic europium Lα–shell X–rays is developed. The possibility of using carbon substrates for the preparation of europium targets to be subjected to 1.6...
Gespeichert in:
| Veröffentlicht in: | Вопросы атомной науки и техники |
|---|---|
| Datum: | 2020 |
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Національний науковий центр «Харківський фізико-технічний інститут» НАН України
2020
|
| Schlagworte: | |
| Online Zugang: | https://nasplib.isofts.kiev.ua/handle/123456789/194759 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy / V.V. Levenets, A.Yu. Lonin, O.P. Omelnik, A.O. Shchur // Problems of atomic science and tecnology. — 2020. — № 1. — С. 121-126. — Бібліогр.: 18 назв. — англ. |
Institution
Digital Library of Periodicals of National Academy of Sciences of Ukraine| id |
nasplib_isofts_kiev_ua-123456789-194759 |
|---|---|
| record_format |
dspace |
| spelling |
Levenets, V.V. Lonin, A.Yu. Omelnik, O.P. Shchur, A.O. 2023-11-29T14:41:27Z 2023-11-29T14:41:27Z 2020 Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy / V.V. Levenets, A.Yu. Lonin, O.P. Omelnik, A.O. Shchur // Problems of atomic science and tecnology. — 2020. — № 1. — С. 121-126. — Бібліогр.: 18 назв. — англ. 1562-6016 https://nasplib.isofts.kiev.ua/handle/123456789/194759 621.039.73:66.081.2 A technique of quantitative determination of europium by proton-induced X–ray emission (PIXE) using of 1.6 MeV energy and measurement of the characteristic europium Lα–shell X–rays is developed. The possibility of using carbon substrates for the preparation of europium targets to be subjected to 1.6 MeV proton irradiat ion was studied. A linear dependence of the quantitative content and the emission intensity of the Lα–shell of europium is obtained. The use of europium as a natural analogue was applied to the study of the americium sorption from aqueous solutions by natural and synthetic zeolites under static conditions. It has been established that the europium sorption coefficient (Ks) for clinoptilolite is 72.7% that is twice as high the Ks for synthetic zeolites NaA Ks– 36.8%) and NaX (Ks – 25.2%). The effect of competing sodium ions on europium sorption by zeolites has been studied. Розроблено методику кількісного визначення європію за допомогою протон–індукованого рентгенівського випромінювання (ХРВ) з використанням енергії 1,6 МеВ і реєстрацією характеристичного рентгенівського випромінювання Lα–оболонки європію. Вивчено можливість використання вуглецевих підкладок для приготування мішеней, що містять європій для опромінення протонами з енергією 1,6 МеВ. Отримана лінійна залежність кількісного вмісту та інтенсивності випромінювання Lα–оболонки європію. Досліджена сорбція європію як імітатора америцію з водних розчинів природним і синтетичними цеолітами в статичних умовах. Встановлено, що коефіцієнт сорбції європію (Ks) для кліноптилоліту становить 72,7%, що в два рази вище Ks для синтетичних цеолітів NaA (Ks – 36,8%) і NaX (Ks – 25,2%). Вивчено вплив конкуруючих іонів натрію на сорбцію європія цеолітами. Разработана методика количественного определения европия с помощью протон–индуцированного рентгеновского излучения (ХРИ) с использованием энергии 1,6 МэВ и регистрацией характеристического рентгеновского излучения Lα–оболочки европия. Изучена возможность использования углеродных подложек для приготовления мишеней, содержащих европий, для облучения протонами с энергией 1,6 МэВ. Получена линейная зависимость количественного содержания и интенсивности излучения Lα–оболочки европия. Исследована сорбция европия как имитатора америция из водных растворов природным и синтетическими цеолитами в статических условиях. Установлено, что коэффициент сорбции европия (Ks) для клиноптилолита составляет 72,7%, что в два раза выше Ks для синтетических цеолитов NaA (Ks – 36,8%) и NaX (Ks – 25,2%). Изучено влияние конкурирующих ионов натрия на сорбцию европия цеолитами en Національний науковий центр «Харківський фізико-технічний інститут» НАН України Вопросы атомной науки и техники Physics and the technology of construction materials Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy Дослідження особливості сорбції європію природним та синтетичними цеолітами для використання в ядерній енергетиці Исследования особенности сорбции европия природным и синтетическими цеолитами для использования в ядерной энергетике Article published earlier |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| collection |
DSpace DC |
| title |
Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy |
| spellingShingle |
Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy Levenets, V.V. Lonin, A.Yu. Omelnik, O.P. Shchur, A.O. Physics and the technology of construction materials |
| title_short |
Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy |
| title_full |
Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy |
| title_fullStr |
Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy |
| title_full_unstemmed |
Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy |
| title_sort |
studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy |
| author |
Levenets, V.V. Lonin, A.Yu. Omelnik, O.P. Shchur, A.O. |
| author_facet |
Levenets, V.V. Lonin, A.Yu. Omelnik, O.P. Shchur, A.O. |
| topic |
Physics and the technology of construction materials |
| topic_facet |
Physics and the technology of construction materials |
| publishDate |
2020 |
| language |
English |
| container_title |
Вопросы атомной науки и техники |
| publisher |
Національний науковий центр «Харківський фізико-технічний інститут» НАН України |
| format |
Article |
| title_alt |
Дослідження особливості сорбції європію природним та синтетичними цеолітами для використання в ядерній енергетиці Исследования особенности сорбции европия природным и синтетическими цеолитами для использования в ядерной энергетике |
| description |
A technique of quantitative determination of europium by proton-induced X–ray emission (PIXE) using of 1.6 MeV energy and measurement of the characteristic europium Lα–shell X–rays is developed. The possibility of using carbon substrates for the preparation of europium targets to be subjected to 1.6 MeV proton irradiat ion was studied. A linear dependence of the quantitative content and the emission intensity of the Lα–shell of europium is obtained. The use of europium as a natural analogue was applied to the study of the americium sorption from aqueous solutions by natural and synthetic zeolites under static conditions. It has been established that the europium sorption coefficient (Ks) for clinoptilolite is 72.7% that is twice as high the Ks for synthetic zeolites NaA Ks– 36.8%) and NaX (Ks – 25.2%). The effect of competing sodium ions on europium sorption by zeolites has been studied.
Розроблено методику кількісного визначення європію за допомогою протон–індукованого рентгенівського випромінювання (ХРВ) з використанням енергії 1,6 МеВ і реєстрацією характеристичного рентгенівського випромінювання Lα–оболонки європію. Вивчено можливість використання вуглецевих підкладок для приготування мішеней, що містять європій для опромінення протонами з енергією 1,6 МеВ. Отримана лінійна залежність кількісного вмісту та інтенсивності випромінювання Lα–оболонки європію. Досліджена сорбція європію як імітатора америцію з водних розчинів природним і синтетичними цеолітами в статичних умовах. Встановлено, що коефіцієнт сорбції європію (Ks) для кліноптилоліту становить 72,7%, що в два рази вище Ks для синтетичних цеолітів NaA (Ks – 36,8%) і NaX (Ks – 25,2%). Вивчено вплив конкуруючих іонів натрію на сорбцію європія цеолітами.
Разработана методика количественного определения европия с помощью протон–индуцированного рентгеновского излучения (ХРИ) с использованием энергии 1,6 МэВ и регистрацией характеристического рентгеновского излучения Lα–оболочки европия. Изучена возможность использования углеродных подложек для приготовления мишеней, содержащих европий, для облучения протонами с энергией 1,6 МэВ. Получена линейная зависимость количественного содержания и интенсивности излучения Lα–оболочки европия. Исследована сорбция европия как имитатора америция из водных растворов природным и синтетическими цеолитами в статических условиях. Установлено, что коэффициент сорбции европия (Ks) для клиноптилолита составляет 72,7%, что в два раза выше Ks для синтетических цеолитов NaA (Ks – 36,8%) и NaX (Ks – 25,2%). Изучено влияние конкурирующих ионов натрия на сорбцию европия цеолитами
|
| issn |
1562-6016 |
| url |
https://nasplib.isofts.kiev.ua/handle/123456789/194759 |
| citation_txt |
Studies of the features of the sorption of an europium by natural and synthetic zeolites for using it in the nuclear energy / V.V. Levenets, A.Yu. Lonin, O.P. Omelnik, A.O. Shchur // Problems of atomic science and tecnology. — 2020. — № 1. — С. 121-126. — Бібліогр.: 18 назв. — англ. |
| work_keys_str_mv |
AT levenetsvv studiesofthefeaturesofthesorptionofaneuropiumbynaturalandsyntheticzeolitesforusingitinthenuclearenergy AT loninayu studiesofthefeaturesofthesorptionofaneuropiumbynaturalandsyntheticzeolitesforusingitinthenuclearenergy AT omelnikop studiesofthefeaturesofthesorptionofaneuropiumbynaturalandsyntheticzeolitesforusingitinthenuclearenergy AT shchurao studiesofthefeaturesofthesorptionofaneuropiumbynaturalandsyntheticzeolitesforusingitinthenuclearenergy AT levenetsvv doslídžennâosoblivostísorbcííêvropíûprirodnimtasintetičnimiceolítamidlâvikoristannâvâderníienergeticí AT loninayu doslídžennâosoblivostísorbcííêvropíûprirodnimtasintetičnimiceolítamidlâvikoristannâvâderníienergeticí AT omelnikop doslídžennâosoblivostísorbcííêvropíûprirodnimtasintetičnimiceolítamidlâvikoristannâvâderníienergeticí AT shchurao doslídžennâosoblivostísorbcííêvropíûprirodnimtasintetičnimiceolítamidlâvikoristannâvâderníienergeticí AT levenetsvv issledovaniâosobennostisorbciievropiâprirodnymisintetičeskimiceolitamidlâispolʹzovaniâvâdernoiénergetike AT loninayu issledovaniâosobennostisorbciievropiâprirodnymisintetičeskimiceolitamidlâispolʹzovaniâvâdernoiénergetike AT omelnikop issledovaniâosobennostisorbciievropiâprirodnymisintetičeskimiceolitamidlâispolʹzovaniâvâdernoiénergetike AT shchurao issledovaniâosobennostisorbciievropiâprirodnymisintetičeskimiceolitamidlâispolʹzovaniâvâdernoiénergetike |
| first_indexed |
2025-11-24T15:54:11Z |
| last_indexed |
2025-11-24T15:54:11Z |
| _version_ |
1850849312477544448 |
| fulltext |
ISSN 1562-6016. ВАНТ. 2020. №1(125) 127
UDC 621.039.5
COMPONENTS OF AUTOMATED INTELLECTUAL SYSTEMS
SUPPORTING DECISIONS AT THE STAGE OF OPERATION
AND EQUIPMENT DIAGNOSTICS OF NUCLEAR POWER UNITS
О.V. Yefimov
1
, М.М. Pylypenko
2
, Т.V. Potanina
1
, Т.О. Yesypenko
1
,
V.L. Kavertsev
1
, Т.А. Harkusha
1
1
National Technical University “Kharkiv Polytechnic Institute”, Kharkiv, Ukraine
E-mail: AVEfimov@kpi.kharkov.ua;
2
National Science Center “Kharkov Institute of Physics and Technology”, Kharkiv, Ukraine
The results of studies of parameters, characteristics and performance of NPP units by mathematical modeling
methods using computer-integrated technologies for their implementation, which allow to simulate many functional
states of systems and equipment of NPP units during the simulation experiment are presented. The general structure
of interaction of blocks of software complex for analysis of efficiency of work and parametric diagnostics of NPP
units with WWER is developed. The structure of the block of programs of parametric diagnostics of equipment of
NPP units is presented. The essence of methods and approaches of parametric diagnostics of power unit equipment
is considered.
INTRODUCTION
It is known that nuclear power plant units, which are
complex technical systems, are characterized by a large
number of parameters, multifunctional links between
them, a variety of equipment for various technological
purposes and physic-chemical processes occurring in it,
as well as operation under the influence of external
random processes, etc.
To study the parameters, characteristics and
performance of NPP units as complex technical systems
methods of mathematical modeling using computer-
integrated technologies for their implementation are
now widely used. They make it possible to simulate the
set of functional states of both systems and equipment
of power units in a simulation experiment [1–19].
Technological processes occurring in the equipment
of NPP units at various modes of their operation,
including dynamic (transient), are generally described
by complex systems of nonlinear differential equations
in partial derivatives. For the description of
technological processes at stationary (quasi-stationary)
modes of operation of power units non-linear equations
are used, which have their own peculiarities. Numerical
methods are used to solve them in the process of
simulation, and sometimes their linearization, which
makes it possible to obtain an approximate solution with
sufficient accuracy for engineering practice [1–3].
LITERATURE DATA ANALYSIS
AND PROBLEM STATEMENT
Functional state modeling and diagnostics of power
equipment on the example of turbines are presented in
[1]. Optimization of models, processes, structures and
modes of operation of NPP power equipment and
mathematical modeling of technological processes
occurring in reactors and steam generators of NPP units
are described in [2, 3]. In order to solve the problems of
analysis, control and diagnostics in the articles [4, 5],
the authors proposed a simulation model of NPP units
with WWER-1000. And the automated decision support
system for nuclear power plant operators is described in
[6, 7]. Studies [8–11] are devoted to the development of
new generation nuclear reactor structures and their
elements using simulation methods. Methods of
constructing diagnostic models of power equipment are
described in detail in [12–14]. The application of
mathematical modeling methods to calculate various
performance indicators for power plants is presented in
studies [15–20]. Articles [21–23] formulate the
conceptual foundations of the theory of simulation
modeling and construction of integrated automated
systemof operation of power plants. The issue of
optimal load distribution between power units of
nuclear power plants based on modern methods of
mathematical modeling is considered in [24, 25].
The main component of the approaches presented in
these works are mathematical (simulation models),
which adequately describe the technological processes,
both in individual elements and in the unit as a whole,
and their computer implementation in the form of an
automated set of programs that can serve as a basis for
creating automated intellectual decision supporting
system (ADSS) by operating and repair personnel of
NPP units.
ADSS allows to solve the following tasks:
– calculation of the parameters of technological
processes in the elements, nodes and systems of the
power unit;
– parametric diagnostics of the technical state of
power unit equipment;
– calculation of indicators of reliability and safety
indicators of systems and equipment of the power unit;
– calculation of the projected electricity and heat
generated by the power unit in a given period of
operation;
– calculation of the technical and economic
indicators of the unit’s efficiency;
– calculation of the performance indicators of repair
work (repair cycles) at the power unit.
The effectiveness of using such ADSS in the process
of operation of NPP units as parts of their automated
system of operation, the accuracy and number of
decision-making options offered by the system
mailto:AVEfimov@kpi.kharkov.ua_
128 ISSN 1562-6016. ВАНТ. 2020. №1(125)
significantly depend on the level of the unit simulation
model detailing and the accuracy of the mathematical
methods used in the computer programs of the above-
mentioned calculations to describe the technological
processes in the equipment of the units.
The purpose of this article is to describe the results
of the research aimed at developing computer-integrated
components of one of the ADSS variants for operational
and maintenance personnel of NPP units according to
the criterion of technical and economic efficiency,
taking into account the diagnostics of the technical
equipment state based on the simulation model
describing by means of up-to-date mathematical
methods the technological processes in the main and
auxiliary equipment of power units using up-to-date
mathematical methods at the level of detailing,
corresponding to their principle and deployed thermal
schemes. This simulation model, methods and
approaches to its creation based on the graph theory are
described in sufficient detail in [1, 3–6] and several
others.
COMPUTER-INTEGRATED COMPONENTS
AND THE MATHEMATICAL METHODS OF
THE IR IMPLEMENTATION
Based on the simulation model of the NPP power
unit with WWER-1000, computer-integrated
components of ADSS were developed as a set of
computer programs for analyzing technical and
economic efficiency of operation and parameter
diagnosing the technical state of two-loop cycle NPP
unit equipment.
These components are used for a new, more
advanced version of the automated complex of
programs for analyzing the operation of two-loop cycle
NPP units [6], expanded by developing programs for
computing diagnostic parameters of the main and
auxiliary equipment of power units.
The structure of individual components (blocks) of
the automated computer program complex for analyzing
technical and economic efficiency of operation and
parameter diagnosing NPP power units with WWER is
shown in Fig. 1.
This set of programs, which is controlled by the
MAIN file (see Fig. 1), can be divided into two parts:
conservative and operational, which is quite typical for
automated decision-making support systems for
operational personnel of power facilities as complex
technical systems [6].
The conservative part of the program complex,
which provides the adequate description of the
technological processes in the systems and equipment of
the NPP power unit at different operation modes,
includes:
– a database operation block, which is used to store
the information accumulating during the operation of
the power unit (see Fig. 1);
– a block for processing information about the
values of the parameters and characteristics of
technological processes in the power equipment
received from the instrumentation of the power unit (see
Fig. 1);
– a block for identifying the simulation model with
the actual technical state of the power unit equipment
(see Fig. 1);
– a block of the modification of the structure and
parameters of thermal power unit scheme (TS) that
provides for connecting, disconnecting, switching,
replacing, eliminating and including equipment into the
TS, as well as entering and correcting the initial data
necessary to compute the parameters of the
technological processes in the power unit equipment
(see Fig. 1).
The operational part of the program complex, which
provides the computation of parameters in the power
unit systems and equipment, contains the following
program blocks:
– a block of programs for computing parameters,
characteristics and indicators in the reactor plant
equipment by means of the corresponding algorithms
given in [2, 3], including programs for computing
thermal and hydraulic parameters and characteristics of
the heating agent in the primary loop equipment, in
particular, in main circulation pumps, as well as
working substance in steam generators;
– blocks of programs for computing the parameters,
characteristics and indicators of the turbine installation
by means of the corresponding algorithms given in [2,
3], including: a block of programs for computing the
parameters, characteristics and indicators in the flow
sections of the main turbine and the turbo drive of the
feed pump; blocks of programs for computing the
parameters, characteristics and indicators in the systems
of condensation and regenerative heating of the main
condensate and feed water; a block of programs for
computing the parameters, characteristics and indicators
in the system for heating the network water (heating
system);
– a block of programs for the parameter diagnostics
of the main and auxiliary equipment in the power unit,
created on the basis of the approaches, methods and
models described in detail in [1–3].
Let's consider the essence of methods and
approaches for parameter diagnostics of power unit
equipment.
Technical state of the unit equipment during its
operation is determined by the values of the set of
diagnostic features (functions) , which are
measures of the quality of its functioning at the moment
. Automated diagnostics of the technical
condition of the NPP unit equipment can be performed
with the help of mathematical models of technological
processes that occur in the equipment and which are
integrated into the simulation model of the unit [1, 2,
26]. The simulation model of the power unit, which is
organized in the form of logical and numerical operators
of the calculation of technological process parameters,
allows to determine technical and economic
performance of the unit and mutual influence of the
equipment parameters. The analysis of these data in
specific operating conditions allows us to determine the
most significant constant and changing parameters and
to form the characteristics of the predicted background.
WD
,, 0jj
ISSN 1562-6016. ВАНТ. 2020. №1(125) 129
Among the criteria which are crucial in making a
decision on the repair because of the technical condition
of systems and equipment, an important indicator is the
impact of changes in equipment parameters and its
failure on the efficiency of the production of electrical
and thermal energy. Determining the rate of decline
(relative to the average level) of the performance
indicators of systems and equipment on the basis of the
data of the integrated operation characteristics of power
units [1, 25], it is possible to find out the optimal service
life, predict the duration of the inter-repair periods and
the term of their economically justified removal for the
repair. In the case of forecasting the technical and
economic level of the unit equipment, the analysis of its
behavior in specific operating conditions allows to
select the most essential (informative) steels and
variables, to form the characteristics of the forecast
background and, in such a way, to obtain a sufficient
amount of diagnostic features. With the help of
operational characteristics it is possible to arrange
parameters according to their influence on the status of
systems and equipment of power units [1, 5].
The process of the automated diagnostics of the
technical state of the equipment of NPP units can be
represented by the following procedure:
– planning and organizing a series of inspections
, which are experiments
with the power unit simulation model for all the
equipment to be diagnosed;
– determining in the course of operation the input
impact value on the basis of indicators of control-
measuring devices of the system of thermal automatics
and measurements of the power unit – the
initial data coming into the simulation model of the
power unit, and the model response to that influence, as
the value of the diagnostic function (test
result). To do this, the task of optimizing the selection
of inspections that determine the technical state of the
unit equipment is pre-solved. The total number of
inspections should be minimal and each
inspection should contain the maximum amount of
information ;
– comparing the values of diagnostic functions
, obtained as a result of the simulation
experiment on the power unit simulation model with
their measured and normative values in order to make a
diagnostic conclusion about the causes and factors of
changes in the technical equipment condition and
determine the time remaining before its failure.
l ,...,1 lkAk ,1,
lkYk ,1,
kYWD
lkk ,1,
maxk
I
kYWD
Block of programs for
modifying the structure of
thermal power unit scheme
Block of programs for
computing the parameters
of the power unit
Block of programs for modifying the
parameters of thermal power unit
scheme
Control program MAIN
Database
operation
block
Identifi-
cation
program
block
Block of programs for
information processing
from power unit
instrumentation (reactor
and steam
turbine))section)
Block of
simulation
experiment
control
programs
Block of programs for
analyzing the results of the
computation of the power
unit operation parameters
and diagnosing the
equipment state
Block of
programs for
computing
steam
generators
Block of
programs for
computing
main
circulation
pumps
Block of
programs for
computing
the
steam turbin
e
Block of
programs
for compu-
ting the
condenser
Block of
programs for
computing
the system of
regenerative
feed water
heating
Block of
programs for
computing the
heating network
installation
Block of programs for computing
the parameters of the systems and
equipment of the reactor plant
Block of programs for computing the parameters of the
systems and equipment of the turbo-mount
Parameter diagnostics program block
Fig. 1. The structure of the interaction of components (blocks) of the automated system performance
analysis
and parameter diagnostics of NPP power units with WWER
130 ISSN 1562-6016. ВАНТ. 2020. №1(125)
In the general case, in the diagnostics of the
technical state of the power unit equipment by means of
a simulation model, the multi-parameter function
is a diagnostic function. It characterizes
the effect of changes over time t on the equipment
parameter vector , which reflect the
deterioration in performance during the inter-repair
period, on the efficiency of the unit operation. The
power unit simulation model allows us to obtain
dependencies that predict the effect of changes in each
of the parameters on W over time t:
, .
Since the predicted processes of changes in the
power unit equipment operation characteristics during
the repair period are random functions of time
, the apparatus of the theory of random
processes can be applied to their image. In this case, for
a fixed point of time , the random process
is the random variable, characterized by one-
dimensional density of distribution .
The result of the probabilistic forecasting of changes
in the power unit equipment parameters is the calculated
probability for its working state
, ,
where is the known probability density of a
random process section at the moment ; is a valid
value of .
The simulation model of the power unit allows to
determine the cumulative effect of changes over time k
of the power unit equipment parameters on its
performance indicators: .
The probability of such an impact is .
The measurement of technological parameters by
means of control and measuring devices in the course of
the power unit operation is carried out, as a rule, in the
conditions of various random obstacles and errors.
Taking this into account, the measurement results of the
multivariable diagnostic function W at a fixed point of
time on the operating equipment can be regarded as
interval estimation, that is, the interval between
statistics containing with certain probability a true value
of W.
Thus, the measured function W can be considered a
random variable from the sampling of n measurements
with unknown mean µ. In probabilistic theory of
mathematical statistics, a sampling is a set of
independent randomly distributed in a similar way
variables. However, careful analysis of most real-world
practical problems shows that what is known is not
sampling but quantities , where –
certain errors in measurements, observations, analysis,
experiments, and studies (e. g. instrumental errors).
One reason is to record the results of observations
with a finite number of significant figures. And, thus, it
is important to build the statistics on which the
statistical conclusions are based and which is used to
evaluate the parameters and characteristics of the
distribution and test of hypotheses according to the
principle, that the value of statistics from variable ,
but not is known. If the errors meet the condition
, then the initial data are presented in the
form of intervals , and the restriction on
the errors can be set in different ways in addition to
absolute, relative, as well as other indicators of the
difference between and can be used.
Based on the rules of classical statistics, we can state
the following. The minimum and maximum values of
function W in the sampling can be taken as the lower
and upper bounds of the confidence interval
and the value can be
considered as the confidence probability ( – the
accepted level of significance). If it is known that the
distribution w is normal, then the value is
to go through Student’s – distribution with
degrees of freedom. Here is the sampling mean of
the results of measurements of multivariable function
W, that is , and S is the sampling variance
. It should be added that, with a
small number of observations, normality cannot be
reliably established, and as the sampling size increases,
the Student's quantile of the distribution becomes closer
to the quantile of the normal distribution.
Then the percentage confidence interval for the
diagnostic function W takes the form
, where – the quantile of
t-Student’s distribution with number of degrees
of level freedom .
This statement is used to construct, based on
measurement results, a series of confidence intervals of
the diagnostic function w that differ from each other by
the probability of determining the values of this function
in each of the intervals
.
The application of interval statistics methods
determines another confidence interval for mathematical
expectation for a given confidence probability
W W X
1, , mX X X
rX
r r rW W X 1,r m
0, ,j j
0, ,j j
r
,r jf x
max
min
work ,
r
r
x
r
r j r r j r
x
P g f x dx 1,r m
,r jf x
j rg
rx
1
,
k
i i j
i
W W X k m
work
1
k
i
i
P P
j
l
iW ll
i
l
i WW
l
iW
iW
iW
ll :
l
i
l
i WW ;
iW iW
min maxW W W 1
W n
S
t 1n
W
1
1 n
W W
n
2
2
1
1
1
n
S W W
n
21
1n
SW t
n
21
1nt
1n
1
2
2 21 1
1 1 1W n n
W n
P t t
S
ISSN 1562-6016. ВАНТ. 2020. №1(125) 131
: ,
where – is the quantile of order of the
standard normal distribution with zero mathematical
expectation and single variance. That is, as the sampling
size increases, the length of the confidence interval
cannot be less than , where С is a constant note
estimation (the note is the value of the maximum
deviation caused by the observations errors :
φ – statistics).
However, the important advantage of estimating in
this way is not only the spread of the interval and taking
into account the errors of observations, but also the fact
that the distributions of the results of observations in
many practical problems are often different from the
normal ones.
In the process of diagnostics, the comparison of the
mean of the diagnostic function ̅ and the value of
the same function , calculated by the simulation
model of the power unit, which is the sum of the effects
of individual possible causes (positive test result ) at
the time , corresponding to the measurements is
performed. This is done by using the statistical theory of
testing alternative hypotheses
{
̅
̅
The hypothesis is rejected if the absolute value
of statistics | | |
( ̅ )
√ ⁄
|
⁄ .
In this case, in the process of diagnostics it can be
concluded that ̅ , and the value |
̅ | is used to make decisions about the
reasons that have affected the technical condition of the
equipment. The lower , the higher the probability
of the fact that these causes have changed the condition
of the equipment. Those reasons for which is within
the confidence interval
⁄
√
⁄ , where the
probability of a possible error is minimal, are most
probable. The probability of making a decision as a
result of diagnostics is equal to . If
the hypothesis , is fulfilled, that is, if the probability
of ̅ , the decision making probability will be
maximal (because the probability of error is zero):
.
The approach of interval data statistics to
determining the “true” threshold value in hypothesis
testing, which meets the criterion actually applied, is
within the interval of two notes. It is advisable to
replace the threshold value with the value which is one
note bigger. This ensures that the probability of
rejecting the null hypothesis, if it is true, is not more
than .
To determine the dependencies that describe the
change in the technical condition and reliability of the
equipment, as well as the time remaining before its
failure, the following approach is proposed to plan the
timing and duration of repairs and calculate the unit
availability factor.
Within the predicted time interval of the unit
operation, the parameters of its equipment are to be
modernized as a result of changing the technical
condition of the equipment. Due to the stability of
physicochemical processes that cause these changes, the
parameters are continuous and monotonic functions of
time t, which can be considered as semi-Markov
dependencies with known approximations of their
realizations. These approximations are represented by
different functions. In the practice of operation of the
equipment of NPP units, linear and exponential
functions are most frequently found. They can be
presented as and
respectively, where .
With the beginning of the equipment operation at the
moment of time 00 , with the help of the regular or
special system of measuring instruments of the unit and
its simulation model, technical condition of the
equipment is diagnosed within the whole operation time
interval 0 and, thus, the realization of
functions mrxr ,1,
is observed consistently until
the end of the predicted interval of operation . From
the discrete realization values obtained in the process of
observations in points ,, 0jj the best
extrapolation curves mrxr ,1, are selected, that is,
the coefficients rr , or rrc ,
of approximation
dependencies are calculated, with each new value of the
observed realizations specify the forecast curves
mrxr ,1, . The point of intersection of function
mrxr ,1, , that describes the change in the technical
condition of the diagnosed equipment with the set limit
mrgr ,1, , which determines the limit value of this
function, based on the technical and economic
indicators of the unit or its reliability, is interpreted as
the equipment to failure. This allows you to determine
the time j
, remaining to the necessary repair
of the equipment (to its failure)
from the moment of
the technical condition diagnostics j .
The dependencies mrxr ,1, , that are built for
the entire set of equipment in operation constitute the
parameter evolution database of the state and reliability
of the equipment for specific types of NPP units and
their operating conditions. Such database can be applied
at different stages of the life cycle of power units,
including for planning the duration of power plant repair
work and determining the installed capacity utilization
rate or the availability factor.
1
n
S
u
n
S
u 1;1
1u
1
2
2C
iii WWWN
sup
W
k
j
0H
W
W
work
1
1
k
i
i
P P
0H
work
1
k
i
i
P P
C
rrrx recx rr
mr ,1
132 ISSN 1562-6016. ВАНТ. 2020. №1(125)
The structure of the parameter diagnostics program
block is presented in Fig. 2. The factors causing the
deviation of diagnostic parameters (functions) from
standard values for various dimensions of the power
equipment of NPP power units with WWER are
summarized, systematized and entered into the database
of the program complex.
Computer-integrated components in the form of a
program complex allow to solve the following types of
problems arising during the operation of NPP power
units with WWER:
– problems of analyzing the influence of the
equipment parameters, the structure of thermal schemes
and external operating conditions on the performance of
power units;
– problems of structural and parameter optimization
of the performance indicators of power units;
– problems of optimal distribution of electrical and
heating loads in time t between n power plant units
depending on the technical state of their equipment
under various external operating conditions in order to
achieve optimal performance indicators of the entire
NPP;
– the problems of evaluating the performance of
power units during the forecast period of their operation
t based on the analysis of reliability indicators R(t) (for
example, probability of failure-free operation) of their
thermal schemes and equipment obtained by means of
technical state parameter diagnostics.
DISCUSSION OF THE RESEARCH
RESULTS
The analysis of the results of computing a number of
specific problems of the above-mentioned types using
the described complex of programs showed that their
values in terms of the initial data error, caused by errors
in measuring technological process parameters by
means of standard instrumentation, as well as errors in
formula which were used in the computation algorithms,
do not exceed the limits acceptable for assessing
technical and economic efficiency, reliability and safety
of NPP power units.
Database of the
measurement results
of technological process
parameters
Selection of the equipment
being diagnosed from the
technological power unit scheme
Statistical processing of the
measurement results of
technological process parameters
Program for computing the parameters of
technological power unit processes
Database of power unit
dimensions
Database of power unit equipment
dimensions
Database of inspections and audits
during the operation of the
equipment and expert assumptions
Database of the computed values
of diagnostic functions
Program complex for computing the
parameters of the equipment being
diagnosed
Program for probabilistic determining the
causes of technological equipment
malfunctions
Recommendation block for
operational personnel
Program for identifying the measurements of the diagnosed
equipment parameters with possible causes of faults
Program for determining the deviations of
the calculated, measured and standard
values of diagnostic functions
Database of the normative values
of diagnostic functions
Database of the measured values
of diagnostic functions
Fig. 2. Block of programs for parameter diagnostics of NPP power unit equipment with WWER
ISSN 1562-6016. ВАНТ. 2020. №1(125) 133
CONCLUSIONS
Developed on the basis of the described computer-
integrated components, the automated decision-making
support system for the operational and maintenance
personnel of NPP power units can be used to solve a
wide range of problems arising in the practice of short-,
medium- and long-term control of the operation modes
of power unit systems andoptimizing operation modes
and parameters, diagnosing and forecasting technical
state of power equipment, predicting the amount of
electrical and thermal energy generated by a power unit,
as well as optimizing NPP repair cycles.
REFERENCES
1. A.A. Палагин, A.В. Ефимов, E.Д. Меньшикова.
Моделирование функционального состояния и
диагностика турбоустановок. Киев: «Наукова
думка», 1991, 192 с.
2. А.В. Ефимов, Л.В. Гончаренко, Т.В. Потанина,
В.Л. Каверцев, Е.Д. Меньшикова, А.Л. Гончаренко,
Т.А. Гаркуша, Т.А. Есипенко, Л.С. Молль, А.М. Аль-
Тувайни. Совершенствование и оптимизация
моделей, процессов, конструкций и режимов работы
энергетического оборудования АЭС, ТЭС и
отопительных котельных. Харьков: «Підручник»
НТУ «ХПІ», 2013, 376 с.
3. О.В. Єфімов, М.М. Пилипенко, Т.В. Потаніна,
В.Л. Каверцев, Т.А. Гаркуша. Реактори і
парогенератори енергоблоків АЕС: схеми, процеси,
матеріали, конструкції, моделі. Харків: ТОВ «В
справі», 2017, 420 с.
4. T.V. Potanina, A.V. Yefimov. Development of
WWER-1000 nuclear power plant generating unit
imitation model for solution of analysis, control and
diagnostics tasks // Transactions of Modeling-2006
Conference. Pukhov Power Engineering Modeling
Problems Institute, National Academy of Science of
Ukraine. 2006, p. 217-220.
5. T.V. Potanina, A.V. Yefimov. Symulacyjne mo-
delowanie funkcjonowania energobloku elektro-
wniatomowej z reaktorem WWER-1000 // Nauka i
studia. 2009, N 2(14), p. 59-69 (in Russian).
6. А. Yefimov, D. Kukhtin, T. Potanina, Т. Harkusha,
В. Kavertsev. Operationeal personnel decision-making
support automatic system at nuclear power plant
generating units by criterion of technical ecjnjmic
efficiency with due consideration of reliability factors //
Nuclear and Radiation Safety. 2018, N 2(78), p. 3-11.
7. A.Н. Анохин. Адаптивный человеко-машин-
ный интерфейс для операторов атомных станций //
Сб. научн. работ СНУЯЕ и П. 2013, №2(46), с. 16-24.
8. G.H. Marcus, A.E. Levin. New designs for
nuclear renaissance // Physics Today. 2002,v. 55, N 4,
р. 54-60.
9. J.M. Hoffman. Nuclear’s new are // Machine
Design. 2001, v. 73, N 18, р. 93-98.
10. A technical roadmap for generation IV nuclear
systems: Technical roadmap report. Washington:
NERAC, 2002, 112 p.
11. Generation IV roadmap: Crosscutting fuels and
materials R&D scope report. Issued by the Nuclear
energy research advisory committee and the generation
IV international forum. 2002, 76 p.
12. A. Gardzilewicz, A. Jefimow. The heat and flow
diagnostic procedure leading to a steam turbine repair
Plan // Proc. 10
th
Conf. on Steam and Gas Turbines for
Power and Cogeneration Plants. Karlovy Vary (Czech.
Rep.). 1994, р. 87-93.
13. A. Gardzilewicz, A. Jefimow. Thermal
Diagnostics of Thermal Cycle Components on an
Example of a Regenerative Heat Exchanger Rep. //
IFFM-PAS 256/94, Gdansk, 1994, р. 34-40.
14. J. Gluch, A. Gardzilewicz. The analysis of
performance of the turbine condenser with the prognosis
of repair // Proc. of the International Joint Power
Generation Conf. Baltimore, Maryland (USA), 1998,
v. 2, р. 179-190.
15. G. Dudek. Ekonomiczny rozdzial obciążenia
stosowanie algorytmów ewolucyjnych: Rozprawa
doktorska. Tom 1. Czestochowa, 2002, 199 p.
16. G. da Costa, C. Costa, A. de Souza. Comparative
Studies of Optimization Methods for the Optimal Power
Flow Problem // Electric Power Systems Research.
2000, v. 56, p. 249-254.
17. H. Wei. An Interior Point Nonlinear
Programming for Optimal Power Flow Problems with a
Novel Data Structure // IEEE Trans. on Power Systems.
1998, v. 13, N 3, p. 870-877.
18. V. Miranda, D. Srinivasan, L. Proenca.
Evolutionary Computationin Power Systems //
Electrical Power and Energy Systems. 1998, v. 20, N 2,
p. 89-98.
19. G. Dudek. Algorytm genetyczny jako metoda
optymalizacji doboru składu jednostek wytwórczych w
systemie elektroenergetycznym // Materiały
konferencyjne: “Algorytmy Ewolucyjne i Optymalizacja
Globalna”. Lądek Zdrój, Warszawa. 2000, p. 51-58.
20. L. Shi, G. Xu. Self-Adaptive Evolutionary
Programming and Its Applications to Multi-Objective
Optimal Operation of Power Systems // Electric Power
Systems Research. 2001, v. 57, p. 181-187.
21. В. Девид Кельтон, Аверилл М. Лоу. Имита-
ционное моделирование. Классика CS. С-Пб.:
«Питер»; К.: Изд. Группа ВНР, 2004, 847 с.
22. В.В. Zeigler, H. Praehofer, T.G. Kim. Theory of
Modeling and Simulation. Academic Press, 2000, 510 p.
23. М.А. Дуэль. Концептуальные основы постро-
ения интегрированной АСУ электростанций //
Енергетика та електрифікація. 2007, №8, с. 16-24.
24.С.Н. Пелых, В.Е. Баскаков, Т.В. Цисельская.
Комплексный критерий эффективности алгоритма
маневрирования мощностью РУ с ВВЭР-1000 в
переменном режиме // Труды Одес. политехн. ун-та.
2009, в. 2(32), с. 53-58.
25. T. Potanina, A. Efimov. Problem of optimalload
distribution between power units on the power stations
// MOTROL. Lublin, 2009, v. 11A, р. 25-30.
26. D.I. Kukhtin, A.V. Yefimov, T.V. Potanina,
T.A. Garkusha. Mathematical models of power plant
generating unit systems and equipments for automatic
mode and operation control // Vestnik NTU KPI. 2015,
N 45(1154), p. 96-104.
Статья поступила в редакцию 11.07.2019 г.
http://scholar.google.com/scholar?cluster=1808241997161171418&hl=en&oi=scholarr
http://scholar.google.com/scholar?cluster=1808241997161171418&hl=en&oi=scholarr
http://scholar.google.com/scholar?cluster=1808241997161171418&hl=en&oi=scholarr
134 ISSN 1562-6016. ВАНТ. 2020. №1(125)
КОМПОНЕНТЫ АВТОМАТИЗИРОВАННЫХ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ
ПОДДЕРЖКИ ПРИНЯТИЯ РЕШЕНИЙ НА ЭТАПЕ ЭКСПЛУАТАЦИИ
И ДИАГНОСТИКИ ОБОРУДОВАНИЯ ЯДЕРНЫХ ЭНЕРГОБЛОКОВ АЭС
А.В. Ефимов, Н.Н. Пилипенко, Т.В. Потанина, Т.А. Есипенко, В.Л. Каверцев, Т.А. Гаркуша
Представлены результаты исследований параметров, характеристик и показателей работы энергоблоков
АЭС методами математического моделирования с использованием компьютерно-интегрированных
технологий их реализации, которые позволяют имитировать в процессе имитационного эксперимента
множество функциональных состояний систем и оборудования энергоблоков АЭС. Разработана общая
структура взаимодействия блоков программного комплекса для анализа эффективности работы и
параметрической диагностики энергоблоков АЭС с ВВЭР. Представлена структура блока программ
параметрической диагностики оборудования энергоблоков АЭС. Рассмотрена сущность методов и подходов
параметрической диагностики оборудования энергоблоков.
КОМПОНЕНТИ АВТОМАТИЗОВАНИХ ІНТЕЛЕКТУАЛЬНИХ СИСТЕМ ПІДТРИМКИ
ПРИЙНЯТТЯ РІШЕНЬ НА ЕТАПІ ЕКСПЛУАТАЦІЇ І ДІАГНОСТИКИ УСТАТКУВАННЯ
ЯДЕРНИХ ЕНЕРГОБЛОКІВ АЕС
О.В. Єфімов, М.М. Пилипенко, Т.В. Потаніна, Т.О. Єсипенко, В.Л. Каверцев, Т.А. Гаркуша
Представлено результати досліджень параметрів, характеристик та показників роботи енергоблоків АЕС
методами математичного моделювання з використанням комп'ютерно-інтегрованих технологій їх реалізації,
які дозволяють імітувати в процесі імітаційного експерименту множину функціональних станів систем та
устаткування енергоблоків АЕС. Розроблено загальну структуру взаємодії блоків програмного комплексу
для аналізу ефективності роботи і параметричної діагностики енергоблоків АЕС з ВВЕР. Представлено
структуру блоку програм параметричної діагностики устаткування енергоблоків АЕС. Розглянуто сутність
методів та підходів параметричної діагностики устаткування енергоблоків.
|