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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>An Entropy Model of the Aircraft Gas Turbine Engine Blades Restoration Method Choice</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Andriy Goncharenko</string-name>
        </contrib>
      </contrib-group>
      <pub-date>
        <year>2018</year>
      </pub-date>
      <fpage>1</fpage>
      <lpage>3</lpage>
      <abstract>
        <p>The paper goal is to investigate the influence of a few specified methods of the gas-turbine engine blades repair upon a choice of a preferable blades geometry restoration technology. There is a scientific proof for the good blades shape restoration method choice that fits the customer needs, being taking into account the subjective preferences of the available technologies and extremizing the preferences uncertainty.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>I. INTRODUCTION</title>
      <p>
        For an active system economic activity management it is
used the theory of subjective analysis [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. A system governed
by a decision making person (or a group of such persons in a
certain hierarchical structure) is considered as active system
since the system is under the managerial influence of the
individuals (they are deemed to be reckoned with as the
active elements of their own active system). The foundation
stone of the subjective analysis theory (the theory of
individual subjective preferences optimal distribution upon a
certain, taken by an individual into her/his consideration, set
of some attainable alternatives) is the entropy paradigm, the
so-called Subjective Entropy Maximum Principle (SEMP),
which is going to be used in the presented paper as a research
tool, although with the application into an objectively
existing optimum sphere rather than just to the subjectively
preferred matters and only. This creates a background for the
information and analytical support of the economic activity.
      </p>
      <p>
        In aviation industry, in particular, in aeronautical
engineering design and its further operation modes, the
individuals’ subjective preferences play a crucial role. The
same is to the aircraft as a whole, as well as to its power plant
specifically. Definitely, those individuals’ subjective
preferences are intruding the fields of both aircraft and their
powerplants maintenance and repair as that follows the
references [
        <xref ref-type="bibr" rid="ref2 ref3">2, 3</xref>
        ].
      </p>
      <p>
        The other area of subjective preferences application here is
alternatives in technologies. Concerning an aviation
gasturbine engine (AGTE) repair it deals with the techniques
proposed in multiple and developed, described, and discussed
in publications of both directions of practitioners/engineers
and academicians [
        <xref ref-type="bibr" rid="ref4 ref5 ref6">4–6</xref>
        ].
      </p>
      <p>
        The objectives of the presented paper are to demonstrate
the multi-optional optimality doctrine newest developments
applicability initiated in works [
        <xref ref-type="bibr" rid="ref10 ref11 ref7 ref8 ref9">7–11</xref>
        ] to the problems of
aeroengines technical operation.
      </p>
      <p>
        The developed herein concept seems promising to the
variety of adjacent scientific areas applications, for instance,
like for those ones considered and discussed in publications
[
        <xref ref-type="bibr" rid="ref12 ref13 ref14 ref15 ref16 ref17 ref18 ref19">12–19</xref>
        ].
      </p>
      <p>II. MATHEMATICAL MODELING AND DEVELOPED</p>
    </sec>
    <sec id="sec-2">
      <title>METHODS</title>
      <p>A gas-turbine engine (GTE) blades apparatus is designed
on one hand to ensure the required compression of the air
supplied with the necessary parameters to the combustion
chamber by the compressor part of the engine and on the
other hand the blades apparatus of the turbine part allows
getting enough work and gas parameters for the compressor
driving and aircraft propulsion.</p>
      <p>The important thermodynamic parameter here is the
polytropic process index n which magnitude must lie within
the very narrow designed value diapason. In operation the
blades wear out, their geometrical shape distorts, as a result
of this the engine cannot perform the designed work.</p>
      <p>The restoration of the blades geometry form has to be
made.</p>
      <sec id="sec-2-1">
        <title>A. Theoretical Problem Setting</title>
        <p>Polytropic process index n approximate mean value, in
real engines thermodynamic processes (such as, for instance,
expansion of combustion gasses in the cylinder of an internal
combustion engine, or in our case, the other examples are
compression and expansion of gasses in an AGTE)
calculations, can be found from polytropic process equation:
pV n = Const ,
where p is pressure; V is volume; provided the values of
the pressure p1 , p2 and volume V1 , V2 are known at some
points 1 and 2 of the process.</p>
        <p>Indeed</p>
        <p>p1V1n = p2V2n .
ln p1 + n lnV1 = ln p2 + n lnV2 ,
n lnV1 − n lnV2 = ln p2 − ln p1 ,
n = ln p2 − ln p1 .</p>
        <p>lnV1 − lnV2
(1)
(2)
(3)</p>
        <p>This simplest method of (1) – (3) for polytropic process
index n determination can be found from practically any
reference, guidance or study book on either theoretical or
engineering thermodynamics either heat engines.
B. Optional Functions Entropy Problem Setting</p>
        <p>
          The other concept also proposed in references [
          <xref ref-type="bibr" rid="ref10 ref11 ref7 ref8 ref9">7–11</xref>
          ] and
hereinafter is based upon an optimization principle close to
SEMP [
          <xref ref-type="bibr" rid="ref1">1</xref>
          ] application in the context close to the described in
papers [
          <xref ref-type="bibr" rid="ref10 ref9">9, 10</xref>
          ].
        </p>
        <p>Let us consider the thermodynamic states 1 and 2 of a gas
in polytropic process as some optional states in a certain
respect. Thus we come to a multi-optional problem.</p>
        <p>Now, the other sub-problem of the polytropic process
given description is to discover the options’ objective
effectiveness functions related to those two optional states.
Let us presuppose the objective effectiveness functions for
the considered two-optional problem of the polytropic
process considered description are lnV1 and lnV2 . This
might be reasonably natural with regards to apparent
perception of the obvious quantitative characteristic of the
existing reality.</p>
        <p>
          With the use of the supposed multi-optional optimality,
likewise in subjective analysis [
          <xref ref-type="bibr" rid="ref1 ref10">1, 10</xref>
          ] conditional optimality
of the individual’s subjective preferences distribution, with
extremizing subjective entropy, that is applying the doctrine
analogous to SEMP concept, we have the right to write down
the postulated functional in the view of:
        </p>
        <p>2 2
Φh = −∑ hi (Vi )ln hi (Vi ) + n∑ hi (Vi )lnVi
i=1 i=1 (4)</p>
        <p>
           2 
+γ∑ hi (Vi ) − 1 ,
 i=1 
where hi (Vi ) are specific hybrid-optional effectiveness
functions, similar to the preferences functions of [
          <xref ref-type="bibr" rid="ref1 ref10">1, 10</xref>
          ],
however in this problem setting the assumed specific
hybridoptional effectiveness functions hi (Vi ) are not relating with
anybody’s preferences or choice; γ is normalizing
coefficient (function).
        </p>
        <p>The first member of expression (4) is the hybrid-optional
effectiveness functions entropy (like subjective entropy of the
preferences).</p>
        <p>The necessary conditions for the functional (4) extremum
existence:
∂Φh = 0 ,
∂hi (Vi )
yield
∂Φh = − ln hi (Vi ) −1 + n lnVi + γ = 0 , ∀i = 1, 2
∂hi (Vi )
This inevitably means in turn</p>
        <p>ln h1(V1) − n lnV1 = γ −1 = ln h2 (V2 ) − n lnV2 .</p>
        <p>From where</p>
        <p>ln h1(V1) − ln h2 (V2 ) = n(lnV1 − lnV2 ) .</p>
        <p>And
n = ln h1(V1 ) − ln h2 (V2 ) .</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>III. ANALYSIS</title>
      <sec id="sec-3-1">
        <title>A. Polytropic Equation Setting</title>
        <p>Thus, we have got a parallel result to the law of subjective
conservatism if the values of parameters n , V1 , and V2 are
given.</p>
        <p>
          In case as in work [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ]:
        </p>
        <p>h1(V1 ) = xp2 , h2 (V2 ) = xp1 , (10)
where x is unknown, uncertain multiplier in type of the
Lagrange one, we obtain with the help of the procedure
considered through (4) – (10) the needed polytropic process
index (3).</p>
        <p>Indeed, substituting equations (10) for their values into
expression (9) it yields
(11)
(12)
(13)
(14)
n =
ln xp2</p>
        <p>xp1
.
finally, formula (3).</p>
        <p>The sense of the uncertain multiplier x becomes obvious
with the use of the normalizing condition of the initial
functional (4). That is</p>
        <p>Hence,</p>
        <p>p1 + p2</p>
        <p>Remarkable here is that the multi-optional hybrid function
has the view of
n i=1
2
∑ pi lnVi
2
∑ pi lnVi
or n i=1
2 2
∑ pi ∑ pi
i=1 i=1
where subscript i means: “pertaining not to the i th but to
the other option of the two-optional situation”.</p>
        <p>Moreover, in case expressed with (4) – (14) the sought
polytropic process index n has been got for the given values
of hybrid-optional effectiveness functions hi (Vi ) and at this
the found value of n can make the hybrid-optional
effectiveness functions of hi (Vi ) also be optimal for the
objective functional (4).</p>
        <p>B. Aeroengine blades alternative restoration technique
problem solution on the subjective entropy paradigm
basis</p>
        <p>Now, in order to retain polytropic process index within the
required designed value interval, so that to ensure the desired
engine performance, periodical restoration of the specified
GTE blades apparatus geometry has to be executed.</p>
        <p>Supposedly, there are competing methods. These are, for
example, plasma (Pl), laser (La), and electro-arc (El). Each of
which are the alternatives for a GTE repair plant to
implement. Here we have a three-alternative problem. Then,
there are corresponding subjective effectiveness functions:
Pl(·), La(·), and El(·) that have relations to each of the being
considered alternatives.
Let us apply although simplified, rough, however possible
model for the objective effectiveness functions Pl(·), La(·),
and El(·).</p>
        <p>The results of the numerical modeling (in conditional
units) are shown in Fig. 1–3.</p>
        <p>In the considered example the objective effectiveness
functions Pl(·), La(·), and El(·) have five independent
variables. But in actual result presented in Fig. 1 only one:
# 4 (productivity of the alternative technology: P) is being
variated. The rest of the parameters are the corresponding
constant values accepted for the: 1) thickness of the metal
layer welded onto the blades prepared surface; 2) thickness of
the metal layer removed out from the blades bodies down to
the nominal size; 3) number of blades undergoing the
treatment; and 5) is the number of the laborers supposed to be
involved into the alternative technological process.</p>
        <p>For the available three alternatives: plasma, laser, and
electro-arc, all the described approach variables may also be
functions of their arguments. Even with the simplified set of
the independent variables the situation depending upon the
arguments combination remains uncertain. The
interinfluence of the parameters can lead to variants when at some
circumstances it is hard to give the preference to a specific
alternative.</p>
        <p>The preferences obtained by the objective functional
treatment like (4) – (6) are visible in Fig. 2.</p>
        <p>From Fig. 3 it is visible that there are areas with respect to
the productivity P of the blades restoration methods from
approximately 1.5 up to 6.5 kg/h where it is almost
impossible to make a decision concerning which technology
is better to apply (see and compare multi-alternativeness
knots of the individual subjective preferences, noticeable in
Fig. 2 at P = 1.8 and 5.2 kg/h, with the subjective entropy
climaxes appeared in Fig. 3). It might be suspected because
of the effectiveness functions positioning (also see Fig. 1 at
those values).</p>
        <p>The additional information is required to decrease the
subjective entropy. In the framework of the presented model
and developed doctrine the mathematical expressions
constructed and the major parameters being considered will
undoubtedly lead to factual realizations. This process of the
modifications creation is a challenging task; and it is
absolutely clear that the necessary additional information
needed to decrease the uncertainty of the alternative AGTE
blades restoration technologies (subjective entropy of the
available preferences) lies in the sphere of the technological
processes intrinsic values selected each time by the
researcher to compare the alternatives. Therefore, the
essential parameters of the processes models, as well as the
models’ own plausible mathematical constructions, for every
stated problem setting, embody the significant information
that finally decreases the entropy value.</p>
        <p>Thus, if we suppose existence of the different thresholds of
the entropy: 0.5; 0.6; 0.7 (see Fig. 3) for the corresponding
choice, then the subjective entropy as the measure of
uncertainty will be higher or lower than mentioned
thresholds. More to the point, there are two extremums at</p>
        <p>
          In Fig. 2 it is depicted, with the Pr characters, the
subjective preferences functions distributed optimally,
accordingly with the procedures of (4) – (6) [
          <xref ref-type="bibr" rid="ref1">1</xref>
          ], upon the set
of the alternative AGTE blades restoration technologies:
Pl(·), La(·), and El(·), correspondingly.
        </p>
        <p>For the preferences, their four arguments out of the five
introduced are fixed exactly as for the corresponding
effectiveness functions (see designations in Fig.1 and 2).</p>
        <p>Subjective entropy of preferences is presented in Fig. 3.
1.8
5.2
P = 1.8 and 5.2 kg/h; the latter says of practically
twoalternative situation since the uncertainty almost coincides
with the two-alternative situation uncertainty maximal value
ln2 (see Fig. 3).</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>IV. CONCLUSION</title>
      <p>In view of the stated problem, the developed doctrine
allows formulating the following new scientific results.</p>
      <p>The proposed approach gives a possibility of the
alternative aviation gas-turbine engine blades restoration
technologies comparison based upon the application of the
entropy extremization principle. The doctrine implementation
reflects the results of the goal achieving for both objectively
existing and subjectively preferable optimums, as well as for
their combinations.</p>
      <p>Thus, for the absolutely objectively existing polytropic
process, the pressure in polytropic process is the optimal
hybrid-optional function, measured with certain units, of the
“logarithmic measureless volume”. Furthermore the
polytropic process index is obtained on the basis of the
multioptional entropy conditional optimality doctrine rather than
on the absolutely thermodynamic derivations.</p>
      <p>For the subjective component the preferences functions
allow the alternatives assessing with the uncertainty measure.</p>
      <p>In further research it should be considered some other
effectiveness functions and their variables, as well as found
more theoretical results and applicable areas of the
hybridoptional optimality doctrine.</p>
    </sec>
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