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11SCIENTIFIC AND METHODOLOGICAL APPROACH TO DEFINITION THE VALUES OF
PARAMETERS OF WHEELED VEHICLES OF SPECIAL OPERATIONS FORCCES OF THE
ARMED FORCES OF UKRAINE
Sliusarenko O.
Doctoral Student of Hetman Petro Sahaidachnyi National Army Academy, Lviv, Ukraine, Kuprinenko O.
Doctor of Technical Sciences, Senior Research Hief of Department of Armoured Vehicles of Hetman Petro Sahaidachnyi
National Army Academy, Lviv, Ukraine Galchenkova M.
Junior Research Laboratory of Hetman Petro Sahaidachnyi National Army Academy, Lviv, Ukraine,
Bondarev I.
Instructor of Department of Armoured Vehicles of Hetman Petro Sahaidachnyi National Army Academy,
Lviv, Ukraine Stah T.
Instructor of Department of Armoured Vehicles of Hetman Petro Sahaidachnyi National Army Academy,
Lviv, Ukraine.
Abstract
The article analyzes the existing approaches to the formation of wheeled vehicle fleets of special operations forces of the armed forces of the leading countries and the main world trends in their development. There are determined the main parameters of wheeled vehicles that affect the completeness and quality of tasks performed by units of the Special Operations Forces of the Armed Forces of Ukraine. The problems of development of the nomenclature of wheeled machines for the needs of the Special Operations Forces of the Armed Forces of Ukraine in accordance with the specifics of the tasks assigned to them are considered. An analysis of existing scientific and methodological approaches to determining the basic parameters of wheeled machines, the results of which established their imperfection. It is proposed a scientific and methodological approach to determining the basic parameters of wheeled vehicles for the needs of the Special Operations Forces of the Armed Forces of Ukraine, which allows to take into account the ambiguity of their application in modern military conflicts and features of the tasks they actually solve.
Keywords: special operations forces, wheeled vehicles, nomenclature, functional indicators. expert survey, membership function of fuzzy sets.
Formulation of the problem.
The beginning of the XXI century is characterized by an increase in the number of armed conflicts of various nature and intensity, in which non-traditional methods of struggle are prevalent. The need to resolve religious and ethnic conflicts between states and regions, counter the growth of international terrorism and piracy, the possibility of the spread of weapons of mass destruction and crime cause the growing role of special methods of conflict resolution, the evolution of special operations and formations that can solve them. [7].
The experience of developed countries, as well as own national experience shows the importance in resolving modern military conflicts of special operations forces (SOF), which are able to adequately respond to new challenges and threats to national and international security not only in war but also in peacetime, both abroad and on its own territory. Unlike other structures, the main features of the SOF are low visibility, secre-tiveness, secrecy, selectivity, autonomy, and a high level of risk associated with political, diplomatic, military, or economic consequences. This necessitates the equipment of SOF units with modern high-tech models of military equipment that best meet the solution of a wide range of special tasks. [13; 24; 28].
The main means of ensuring the mobility of SSPO units during combat missions are wheeled vehicles (WV) [16-19].
The existing type of WV of SOF of the Armed Forces (AF) of Ukraine is characterized by obsolescence, backwardness and diversity of WV, which do not always correspond to the nature of the tasks that are actually solved. Some types of WV have low tactical and technical characteristics and low ability to perform tasks in difficult road and climatic conditions. There is an urgent need to equip the units of SOF of the Armed Forces of Ukraine with WV, which correspond to the nature of the whole range of tasks actually solved by SOF, take into account trends in armed struggle and achievements in the development and operation of vehicles [25].
The complexity of the development and design of promising models of the WV of SOF lies in the limited possibilities of applying existing scientific and methodological approaches to determining the values of the parameters of the WV and the ambiguity of the description of methods and conditions of their combat application. In such circumstances, there is a need to find and use new approaches that would justify the technical parameters of the WV of SOF depending on the tasks assigned to them.
Analysis of recent research and publications.
To date, the fleet of the WV of SOF of the Armed Forces of Ukraine includes the following groups of vehicles [25]:
- Soviet-made cars, which were inherited during the reform of special units and information and psychological operations (UAZ, ZIL, GAS, Ural, KamAZ, KrAZ);
- the WV on the basis of commercial vehicles provided by volunteers during the anti-terrorist operation in eastern Ukraine;
- wheeled vehicles of domestic and foreign production, which were received in the framework of procurement and military assistance.
As a result, the park of WV SOF is characterized by a large variety of samples, the purpose and tactical and technical characteristics of which are similar and at the same time do not fully meet the needs of SOF.
The problem of substantiation of technical parameters of the WV is actual and is considered in works [1; 6; 9; 10; 21; 22; 27].
The method proposed in [21] is based on the selection and ranking of the main properties of all-wheel drive multi-purpose cars and "dual-use" cars and allows to assess their technical level, as well as to assess the technical level of car families as a whole. At the same time, the proposed method does not allow when choosing and ranking the main properties to take into account the conditions of combat use of the WV and the specifics of the tasks assigned to them, to determine the values of the main parameters.
In works [6; 9; 10; 27] are considered the problem of determining the boundaries (contours) of unified families of combat wheeled vehicles during the substantiation of their rational nomenclature. The use of cluster analysis methods allows determining the boundaries (contours) by forming groups of homogeneous samples of combat wheeled vehicles on the basis of characteristics that characterize their combat properties; and determine the boundaries of each group. At the same time, the above mentioned approaches can be applied only to armored wheeled vehicles and do not take into account the peculiarities of the conditions of use of wheeled vehicles by SOF units and the tasks assigned to them.
To date, considerable experience has been gained in substantiating the types for different equipment, but the closest to the WV are the scientific and methodological approaches and recommendations given in [1; 22].
Recommendations [22] allow to obtain the optimal type of general engineering products using the methods of discrete programming, probability theory and mathematical statistics. The algorithm for solving the problem of creating a type is one of the implementations of the method of branches and boundaries, leads to accurate results and is performed in 2 stages:
at the first stage with the help of a fast quasi-optimal algorithm of multi-step selection determine the solution of this problem, which is approximate and is used as an initial record;
in the second stage, build a tree of options and determine the optimal type.
This approach makes it possible to determine the type that fully satisfies the demand for products with minimal total costs. But it is developed in the conditions of administrative-command system of management of the industry and does not allow considering transition to market conditions of economy, competitiveness of creation of the WV, ambiguity of the description of process of use of the WV.
The method of substantiation of the type of machines has similar shortcomings [1], which provides for the formalization of the uncertainty of estimates of perspective values of machine parameters using the methods of probability theory and mathematical statistics. Methods of self-organizing systems theory (adaptive algorithms) are used to optimize parameter values.
Thus, there is a contradiction between the need to develop the WV for needs of SOF of the Armed Forces of Ukraine and the imperfection of the existing scientific and methodological approaches to substantiate the technical parameters of the WV. To solve this contradiction, it is necessary to develop a scientific and methodological apparatus to substantiate the technical parameters of the WV of SOF of the Armed Forces of Ukraine, which will take into account the shortcomings of existing approaches and allow justifying the technical parameters of the WV of SOF depending on application conditions and tasks that lie on them.
The purpose of the article is to develop a scientific and methodological apparatus that will determine the technical parameters of the WV of SOF depending on the tasks that they actually solve.
Presenting main material
The development of promising samples of the WV is preceded by the definition of the main parameters that generally characterize the WV. The rational number of parameters for the construction of the nomenclature of the WV must be determined from the analysis of the peculiarities of the use of the WV in modern military conflicts.
Peculiarities of the use of the WV of SOF in modern military conflicts are:
1. A large variety of tasks (in terms of volume and number), which are performed with the help of the WV.
2. Uncertainty, incompleteness (insufficient amount) of information on the conditions of tasks and distances of transportation.
3. Increased requirements for secrecy, autonomy, mobility and airworthiness of the WV.
As the main parameters that determine the design and operational properties of the WV, it is advisable to take the load capacity, gross weight, belonging to the group of axial loads and fuel range.
Traditional scientific and methodological approaches to determining the parameters of the WV on the basis of probability theories and statistics in modern conditions, which are characterized by dynamism and instability of events, have limited capabilities [3; 8; 14; 29].
The main reasons for this are the lack of sufficient reliable source statistics for modeling, significant difficulties and limitations in the organization and conduct of field experiments, large resource and time costs to collect the necessary information. In conditions of non-
statistical uncertainty, new approaches are becoming more widespread, which are based on the judgments of experts obtained through specially designed procedures [20].
To determine the parameters of WV, it is proposed to use heuristic methods using fuzzy set theory, which on the basis of approximate, fuzzy verbal concepts of experts allow to take into account uncertainties and all factors relevant to this problem and can not be accurately quantified [4; 5; 11; 30].
Mathematical formulation of the problem of determining the initial standard size range of the WV looks like [2]:
D ={°n }= {"«1 ^Un2 ^Unm }, (1)
where D - a set of compromise estimates of the parameters of the WV;
These questions allow us to determine the main indicators of the WV of SOF load capacity, gross weight, belonging to the group of axial loads and fuel range. Estimates provided by experts may be, for example, as follows: a) the range of fuel on dirt roads is approximately equal to 200 kilometers; b) the number of personnel to be moved by the sample of the WV, from 5 to 7. These approximately point and approximately interval estimates of experts should be processed using fuzzy set theory, namely through the construction of membership functions of fuzzy sets.
According to the chosen method, when constructing membership functions of a fuzzy set of numbers that are approximately equal to some number K, a function of the form is used [23]:
Vk (u )
_-a(K—u)2
(2)
eter;
Dn - compromise assessment of the WV param- where JUK (u) - the membership function of
n — number of the WV;
u
nm
■ expert assessments of the WV parameters;
m — number of expert assessments;
" O " - a symbol of intersection of membership functions of fuzzy sets, built on the basis of expert estimates.
To conduct an expert questioning in relation to research, that is conducted, it is advisable to use a consistent, iterative procedure, based on the alternate inclusion in the survey of an increasing number of experts until the stabilization of their assessments.
For each sample of the WV, a survey of experts in the field of combat use of SOF units will be conducted.
Experts are asked to answer the following questions:
1. Determine the number of personnel to be moved by the sample of the WV.
2. Identify the weapons and ammunition that must be installed on this sample of the WV.
3. Determine the type and level of ballistic and mine protection of the WV sample.
4. Identify additional special equipment and facilities that need to be installed such as KM.
5. Determine the range of fuel on dirt roads.
the numbers u of the real axis to the fuzzy set, which is approximately equal to the number K; 41« 0 5
a =__l_ and depends on the required deP
gree of ambiguity L K (u);
P - the distance between the points at which the function ¡LIk (u) takes the value of 0.5.
The task of constructing a membership function for a number is to determine the parameters corresponding to this number (points at which the membership function takes the value of 0.5).
In order to determine the set of the form "numbers that are approximately equal to K", it is necessary to find out how people imagine the boundaries of classes of numbers that are approximately equal to some given.
When constructing membership functions, there was used an improved method of processing expert assessments of A.V. Skofenko [15], which allows to increase the adequacy of the results of processing fuzzy quantitative expert assessments of physical quantities (Fig. 1).
-1—-=4-- a b H--R»-1-.
0,5 ■
[
K1,
1000 1050 1100 1150 1200 1200 1300 1350
1000
1100
1200
1250
M
0
u
a) 6)
Fig. 1 Construction of membership functions offuzzy sets:
a - an example of the expert's answer: "... the load capacity of the WV should be approximately 1200 kg.";
b - an example of the expert's answer: "... load capacity of the WV should be from about 1160 to 1240 kg."
The use of the MATLAB application package allows formalizing the expert estimates of the load capacity of the WV of SOF by constructing the membership functions for each class of the WV and compromise estimates.
In order to determine trade-off estimates, convolution based on the operation of intersection of fuzzy sets is used. The operation of intersection of fuzzy sets corresponds to the operation min, which is performed with their membership functions:
Md (xi ) = min Ma, j = m
D = ux n«2 o.
o u„
(3)
where — the membership function of the compromise assessment of the parameter of the WV X, that is under consideration;
D — a compromise estimate of the parameter of the WV, which is determined by the operation of the intersection of the membership functions of fuzzy sets,
which are built on the basis of expert estimates Um
(shaded area in Figure 2);
m - number of expert assessments; " O" - a symbol of intersection of membership functions, built on the basis of expert assessments.
0.8
0.6
0.4
0.2
1000
1100
1200
1300
Fig. 2. An example of a compromise assessment of the load capacity of the sample of the WV, which is determined by the operation of the intersection offuzzy sets and is represented as a rectangle
To determine the values of the main parameters of the samples of WV, it is necessary to additionally defasify the obtained compromise estimates by the method described in [12].
Conclusions
1. Given the complexity of the description of the process of combat use of the WV, to determine the basic parameters of the sample of the WV, it is advisable to use vague verbal concepts and statements based on experience and imaginary language models of experts on combat use units of SOF.
2. The proposed scientific and methodological approach allows during the design of the WV of SOF to ensure their maximum compliance with the typical conditions of use and features of the tasks that are actually solved.
References
1. Antipenko, V., Kats, G. and Petrushev, V. (1990), "Modeli i metody optimizatsii parametrich-eskikh ryadov mashin" [Models and methods of optimization parametric series of machines], Mashi-nostroyeniye, Moscow, 176 p.
2. Bellman, R. and Zadeh, L. (1970), "Decision-Making in a Fuzzy Environment", Management Science, Vol. 17, No. 4, pp.141-164.
3. Blitzstein, J. and Hwang, J. (2014), "Introduction to Probability", CRC Press, 596 p.
4. Borisov, A., Alekseev, A., Merkurieva, H. and other (1989), "Obrabotka niechetkoi informatsyi v sis-tiemakh priniatiia reshenii" [Processing of fuzzy information in decision-making systems], Radio and communication, Moscow, 304 p.
5. Borisov, A., Krumberg, O. and Fedorov, I. (1990), "Prinyatie resheniy na osnove nechetkih mod-eley: Primeryi ispolzovaniya" [Decision making based on fuzzy models: Examples of use], Zinatne, Riga, 184 p.
6. Chornyy, M., Kuprinenko, O. and Holub, V. (2010), "Obhruntuvannya propozytsiy shchodo vyznachennya neobkhidnoho rivnya zakhystu avtomobiliv bahatotsilovoho pryznachennya v zalezhnosti vid kharakteru ta mistsya yikh vykorystannya" [Justification of proposals for determining the required level of multipurpose vehicle protection depending on the nature and location of their use], Systems of Arms and Military Equipment, No2(22), pp.182-187.
7. Galushko, S. (2011), "Nekotoryye voprosy pod-gotovki i provedeniya spetsialnykh operatsiy v period posle Vtoroy Mirovoy voyny" [Some issues of prepa-
l
0
ration and carrying out of special operations in the period after World War II], Tsentr strategicheskih otsenok i prognozov, Moscow, 73 p.
8. Hogg R., Tanis E., Zimmerman D. (2015), "Probability and Statistical Inference", Pearson, 556 p.
9. Holub, V., Chepkov, I., Kuprinenko, O., Chechenkova, O. and Hulyayev A. (2013), "Obgruntu-vannya typazhu boyovykh kolisnykh mashyn iz vykorystannyam metodiv klasternoho analizu" [Justification of the type of combat vehicles using cluster analysis methods.], Avtoshliakhovyk Ukrayiny, No5, pp.510.
10. Holub, V., Chepkov, I., Kuprinenko, O., Chechenkova, O. and Hulyayev A. (2011), "Kla-syfikatsiya boyovykh kolisnykh mashyn metodamy nechitkoho klasternoho analizu" [Classification of combat vehicles by indistinct cluster analysis methods], Scientific Works of Central research Institute of weapons and military equipment of armed forces of Ukraine, No20, pp.201-209.
11. Kofman, A. (1982), "Vvedenie v teoriyu nechetkih mnozhestv " [Introduction to the theory of fuzzy sets], Radio and communication, Moscow, 432p.
12. Kuprinenko, O. and Holub, V. (2007), "Metod defazyfikatsii nechitkykh mnozhyn" [Method of dephasing of fuzzy sets], Information processing systems, No. 2(60), pp. 107-108.
13. Lutsenko, A. (2010), "Analiz dosvidu stvoren-nia, tendentsii rozvytku ta osoblyvostei pidhotovky syl spetsialnykh operatsii" [Analysis of experience of creation, tendencies of development and features of preparation of Special Operations forces], Systems of Weapons and Military Equipment, No. 1(21), pp. 2730.
14. Martyshchenko, L. and Panov, V. (1981), "Mietody voienno-nauchnykh issliedovanii v zadachakh razrabotki i yspytaniia vooruzheniia. Ch.1" [Methods of military research in the problems of development and testing of weapons. Vol. 1], MoD, Moscow, 280 p.
15. Myronchuk, Y. and Kuprinenko, O. (2017), "Pobudova funktsii nalezhnosti nechitkykh mnozhyn, yaki vidpovidaiut kilkisnym ekspertnym otsinkam fizychnykh velychyn" [Constructing a functions of fuzzy sets based on the quantitative expert assessments of natural values], Information processing systems, No. 1(147), pp. 93-97.
16. Neville, L. (2008), "Special Operations Forces
in Afghanistan (Elite)", Osprey Publishing, Oxford, 64 p.
17. Neville, L. (2011), "Special Operations Forces in Iraq", Osprey Publishing, Oxford, 64 p.
18. Neville, L. (2011), "Special Operations Patrol Vehicles: Afghanistan and Iraq", Osprey Publishing, Oxford, 48 p.
19.Neville, L. (2018), "Technicals: Non-Standard Tactical Vehicles from the Great Toyota War to modern Special Forces", Osprey Publishing, Oxford, 48 p.
20. Pankova, L., Pietrovskii, A. and Shneiderman, N. (1984), "Orhanizatsiia ekspiertizy i analiz ek-spiertnoi informatsyi", Science, Moscow, 120p.
21. Pliyev, I. (2010), "Otsenka tekhnicheskogo urovnya semeystva avtomobiley mnogotselevogo naznacheniya na osnove metoda analiza iyerarkhiy" [Evaluation of the technical level of the multipurpose car family based on the hierarchy analysis method], Magazine of Automotive Engineers, No3(62), pp.4649, No5(64), pp.50-54.
22. Razrabotka tipazhey na izdeliya obshchey tekhniki. Rekomendatsii: RV 50-60-51-88" [Development of types for general engineering products. Recommendations: RV 50-60-51-88], (1988), State Committee of the USSR on Standards, Moscow, 13 p.
23. Skofenko, A. (1981), "O postroenii funktsiy prinadlezhnosti nechetkih mnozhestv, sootvetstvuyu-schih kolichestvennyim ekspertnyim otsenkam" [On the construction of membership functions of fuzzy sets corresponding to quantitative expert estimates], Nau-kovedenie i informatika, No. 22, pp. 70-79.
24. Sliusarenko, A. (2017), "Dosvid stvorennia ta struktura syl spetsialnykh operatsii providnykh krain svitu" [Experience of creation and structure of Special Operations forces of the leading countries of the world], Military Scientific Journal, No. 29, pp. 170-181. DOI: https://doi.org/10.33577/2313-5603.29.2018.170-181.
25. Sliusarenko, O. (2018), "Stan ta osnash-chennya Syl spetsialnykh operatsiy Zbroynykh Syl Ukrayiny kolisnymy mashynamy" [Condition and equipment of Special Operations Forces of the Armed Forces of Ukraine by wheeled vehicles], Military technical collection, No18, pp.93-98.
26. Sliusarenko, O. (2019), "Analiz isnuiuchykh naukovo-metodychnykh pidkhodiv obgruntuvannia tekhnichnykh parametriv kolisnykh mashyn Syl spetsi-alnykh operatsii Zbroinykh Syl Ukrainy" [Analysis of existing scientific and methodological approaches for the justification of technical parameters of wheeled vehicles Special Operations Forces of the Armed Forces of Ukraine], Systems of Arms and Military Equipment, No. 1(57), pp. 128-134.
27. Sliusarenko, O. and Kuprinenko, O., (2010), "Mistse i rol bronovanykh avtomobiliv u vyrishenni zavdan Sukhoputnykh viysk" [The place and role of armored vehicles in solving the tasks of Land Forces], Systems of Arms and Military Equipment, No1(21), pp.81-84.
28. Vedeneev, D. and Sliusarenko, A. (2018), "Formuvannya kontseptualno-pravovykh zasad ta struktury rozbudovy syl spetsial'nykh operatsiy Zbroynykh Syl Ukrayiny" [Formation of conceptual and legal principles and structure building up of Special Operations Forces of the Armed Forces of Ukraine], Challenges and risks, No11(98), pp.22-37.
29. Venttsel, Ye. (1972), "Issliedovaniie opi-eratsyi" [Operations research], Soviet radio, Moscow, 552 p.
30. Zadeh, L. (1976), "Poniatyie linhvistichieskoi pieriemiennoi y yeio primienieniie k priniatiiu prib-lizhennykh rieshenii" [The Concept of a Linguistic Variable and its Application to Approximate Reasoning], World, Moscow, 165 p.
