Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy

One of the ways to solve the conditionally ill-posed problem for ranking quality criteria of the multiobjective system, whose regularization is made by applying the fractal formalism, is hereby considered. Ranking quality criteria by their importance is based on the definition of the area of self-si...

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Date:2018
Main Authors: Bolshakov, V.I., Volchuk, V.M., Dubrov, Yu.I.
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Language:English
Published: Інститут металофізики ім. Г.В. Курдюмова НАН України 2018
Series:Металлофизика и новейшие технологии
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Online Access:https://nasplib.isofts.kiev.ua/handle/123456789/151857
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Cite this:Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy / V.I. Bolshakov, V.M. Volchuk, Yu.I. Dubrov // Металлофизика и новейшие технологии. — 2018. — Т. 40, № 9. — С. 1165-1171. — Бібліогр.: 13 назв. — англ.

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spelling nasplib_isofts_kiev_ua-123456789-1518572025-02-09T23:34:43Z Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy Регуляризация одной условно некорректно поставленной задачи металлургического извлечения (металлов из руд) Реґуляризація однієї умовно некоректно поставленої задачі металургійного вилучення (металів з руд) Bolshakov, V.I. Volchuk, V.M. Dubrov, Yu.I. Физико-технические основы эксперимента и диагностики One of the ways to solve the conditionally ill-posed problem for ranking quality criteria of the multiobjective system, whose regularization is made by applying the fractal formalism, is hereby considered. Ranking quality criteria by their importance is based on the definition of the area of self-similarity for partial criteria. Рассматривается один из путей решения условно некорректной задачи ранжирования критериев качества многокритериальной системы, регуляризация которой производится применением фрактального формализма. Ранжирование критериев качества по их значимости базируется на определении области самоподобия частных критериев. Розглядається один із шляхів вирішення умовно некоректної задачі ранжування критеріїв якости багатокритеріяльної системи, реґуляризація якої проводиться застосуванням фрактального формалізму. Ранжування критеріїв якости за значенням базується на визначенні области самоподібности окремих критеріїв. 2018 Article Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy / V.I. Bolshakov, V.M. Volchuk, Yu.I. Dubrov // Металлофизика и новейшие технологии. — 2018. — Т. 40, № 9. — С. 1165-1171. — Бібліогр.: 13 назв. — англ. 1024-1809 PACS: 06.60.Mr, 61.43.Hv, 61.72.Ff, 81.05.Bx, 81.40.Ef, 81.40.Np, 81.70.Bt DOI:10.15407/mfint.40.09.1165 https://nasplib.isofts.kiev.ua/handle/123456789/151857 en Металлофизика и новейшие технологии application/pdf Інститут металофізики ім. Г.В. Курдюмова НАН України
institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
collection DSpace DC
language English
topic Физико-технические основы эксперимента и диагностики
Физико-технические основы эксперимента и диагностики
spellingShingle Физико-технические основы эксперимента и диагностики
Физико-технические основы эксперимента и диагностики
Bolshakov, V.I.
Volchuk, V.M.
Dubrov, Yu.I.
Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy
Металлофизика и новейшие технологии
description One of the ways to solve the conditionally ill-posed problem for ranking quality criteria of the multiobjective system, whose regularization is made by applying the fractal formalism, is hereby considered. Ranking quality criteria by their importance is based on the definition of the area of self-similarity for partial criteria.
format Article
author Bolshakov, V.I.
Volchuk, V.M.
Dubrov, Yu.I.
author_facet Bolshakov, V.I.
Volchuk, V.M.
Dubrov, Yu.I.
author_sort Bolshakov, V.I.
title Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy
title_short Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy
title_full Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy
title_fullStr Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy
title_full_unstemmed Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy
title_sort regularization of one conditionally ill-posed problem of extractive metallurgy
publisher Інститут металофізики ім. Г.В. Курдюмова НАН України
publishDate 2018
topic_facet Физико-технические основы эксперимента и диагностики
url https://nasplib.isofts.kiev.ua/handle/123456789/151857
citation_txt Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy / V.I. Bolshakov, V.M. Volchuk, Yu.I. Dubrov // Металлофизика и новейшие технологии. — 2018. — Т. 40, № 9. — С. 1165-1171. — Бібліогр.: 13 назв. — англ.
series Металлофизика и новейшие технологии
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fulltext PACS numbers: 06.60.Mr, 61.43.Hv, 61.72.Ff, 81.05.Bx, 81.40.Ef, 81.40.Np, 81.70.Bt Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy V. I. Bolshakov, V. M. Volchuk, and Yu. I. Dubrov Prydniprovs’ka State Academy of Civil Engineering and Architecture, 24a Chernyshevs’ky Str., 49600 Dnipro, Ukraine One of the ways to solve the conditionally ill-posed problem for ranking quality criteria of the multiobjective system, whose regularization is made by applying the fractal formalism, is hereby considered. Ranking quality criteria by their importance is based on the definition of the area of self-similarity for partial criteria. At the first stage of research, the key parameter is identified under the defined initial conditions by ranking quality criteria with the use of the fractal formalism. Ranking the criteria by importance is based on the estima- tion of the comparative value of areas of their self-similarity. The self- similarity coefficients of these areas appear as the regularization parameter at this stage of research. These areas are estimated by means of definitions of their relative values as the ratio of the range for existence of each partial crite- rion referred to its upper boundary. The second stage of research is initiated by the need to determine the optimal combinations of the target product proper- ties in the working area, depending on the customer conditions. For this pur- pose, the sub-compromise regions are defined in the working area of partial criteria under consideration (compromise criteria). The sub-compromise par- tial regions are regions of the optimal combinations of properties. Thus, the regularization at the second stage is made in co-ordination with the require- ments of the customer. In this connection, the example of solving the condi- tionally ill-posed problem for optimizing the multicriteria and multiparamet- ric technologies of fabrication of cast iron rolls is given. Key words: multiparametric technologies, regularization parameter, self- similarity area, compromise criteria, mechanical properties, fractal formalism. Corresponding author: Volodymyr Mykolayovych Volchuk E-mail: volchuky@gmail.com Citation: V. I. Bolshakov, V. M. Volchuk, and Yu. I. Dubrov, Regularization of One Conditionally Ill-Posed Problem of Extractive Metallurgy, Metallofiz. Noveishie Tekhnol., 40, No. 9: 1165–1171 (2018), DOI: 10.15407/mfint.40.09.1165. Ìåòàëëîôèç. íîâåéøèå òåõíîë. / Metallofiz. Noveishie Tekhnol. 2018, т. 40, № 9, сс. 1165–1171 / DOI: 10.15407/mfint.40.09.1165 Îттèсêè äîстóïíû íåïîсðåäстâåííî îт èçäàтåëÿ Ôîтîêîïèðîâàíèå ðàçðåøåíî тîëüêî â сîîтâåтстâèè с ëèöåíçèåé  2018 ÈÌÔ (Èíстèтóт ìåтàëëîôèçèêè èì. Ã. Â. Êóðäþìîâà ÍÀÍ Óêðàèíû) Íàïå÷àтàíî â Óêðàèíå. 1165 https://doi.org/10.15407/mfint.40.09.1165 https://doi.org/10.15407/mfint.40.09.1165 1166 V. I. BOLSHAKOV, V. M. VOLCHUK, and Yu. I. DUBROV Рîçгëÿäàєтüсÿ îäèí іç øëÿхіâ âèðіøåííÿ óìîâíî íåêîðåêтíîї çàäà÷і ðàí- жóâàííÿ êðèтåðіїâ ÿêîстè бàгàтîêðèтåðіÿëüíîї сèстåìè, ðåґóëÿðèçàöіÿ ÿêîї ïðîâîäèтüсÿ çàстîсóâàííÿì ôðàêтàëüíîгî ôîðìàëіçìó. Рàíжóâàííÿ êðèтåðіїâ ÿêîстè çà çíà÷åííÿì бàçóєтüсÿ íà âèçíà÷åííі îбëàстè сàìîïîäі- бíîстè îêðåìèх êðèтåðіїâ. Ключові слова: бàгàтîïàðàìåтðè÷íà тåхíîëîгіÿ, ïàðàìåтåð ðåґóëÿðèçà- öії, îбëàстü сàìîïîäібíîстè, îбëàстü êîìïðîìісó êðèтåðіїâ, ìåхàíі÷íі âëàстèâîсті, ôðàêтàëüíèé ôîðìàëіçì. Рàссìàтðèâàåтсÿ îäèí èç ïóтåé ðåøåíèÿ óсëîâíî íåêîððåêтíîé çàäà÷è ðàíжèðîâàíèÿ êðèтåðèåâ êà÷åстâà ìíîгîêðèтåðèàëüíîé сèстåìû, ðåгó- ëÿðèçàöèÿ êîтîðîé ïðîèçâîäèтсÿ ïðèìåíåíèåì ôðàêтàëüíîгî ôîðìàëèç- ìà. Рàíжèðîâàíèå êðèтåðèåâ êà÷åстâà ïî èх çíà÷èìîстè бàçèðóåтсÿ íà îïðåäåëåíèè îбëàстè сàìîïîäîбèÿ ÷àстíûх êðèтåðèåâ. Ключевые слова: ìíîгîïàðàìåтðè÷åсêàÿ тåхíîëîгèÿ, ïàðàìåтð ðåгóëÿ- ðèçàöèè, îбëàстü сàìîïîäîбèÿ, îбëàстü êîìïðîìèссà êðèтåðèåâ, ìåхàíè- ÷åсêèå сâîéстâà, ôðàêтàëüíûé ôîðìàëèçì. (Received March 13, 2018) 1. PROBLEM FORMULATION The ranking of criteria by their importance for the multi-criteria sys- tem should ensure its stable operation within the specified limits, ac- cording to statutory documents [1]. The defined limits determine the working area of parameters. When identifying the operation of such systems, one often has to deal with complexities dictated by the influ- ence of a number of factors that guarantee their stability. As a rule, such problems are often solved by methods of applied mathematics [2– 4]. At the same time, the majority of the applied problems of extractive metallurgy can be considered as conditionally ill-posed ones [5] that initiate the introduction of additional stipulations for their more ade- quate representation. Such stipulations may include the definition of the ways to optimize the multicriteria and multiparameter technolo- gies in the working area by finding areas with the best combination of partial indicators (criteria). From this point of view, the problem of ranking quality criteria of the multiparameter technologies, examined earlier [6], taking into account the fractal formalism [7–9], seems to be incomplete and can be transformed as the conditionally ill-posed one, whose solution, depending on various initial conditions, can vary. Ac- cording to J. Hadamard [10], the problem is deemed to be ill-posed, if: it has no solution (in our concerned class), it has many solutions (from two or more), and the procedure for finding the solution is unstable (i.e. with the smallest measurement error or small perturbations of the ini- tial data [11], the solution obtained can substantially differ from the REGULARIZATION OF ILL-POSED PROBLEM OF EXTRACTIVE METALLURGY 1167 exact one). Failure to fulfil, at least, one of the above-listed stipulations for the problem under consideration confirms its ill-posedness. In spite of the fact that the first item of stipulations is fulfilled, which points to the existence of the solution for the problem of ranking quality criteria, the second and third items are not fulfilled for this problem. The second item cannot be fulfilled subject to possible chang- es in the customer’s requirements as for the significance of partial cri- teria. In this regard, the ranking of criteria can be carried out accord- ing to the customer’s requirements, by the degree of influence of the chemical composition elements, and by the detectable value of the area of self-similarity for each of partial criteria [6] determining the stabil- ity of the technology operation. The third item of ill-posedness stipula- tions cannot be fulfilled as well, since the procedure for finding one or another solution of this conditionally ill-posed problem can vary de- pending on periodically changing parameters in the working area (chemical composition, cooling conditions, etc.). Proceeding from the peculiarities of the above-formulated stipula- tions, the solution of this conditionally ill-posed problem concerning the optimization of the multiparameter technologies is proposed to be carried out in two stages. At the first stage of the research, the key pa- rameter is identified under the defined initial conditions by ranking quality criteria with the use of the fractal formalism. The ranking of criteria by importance is based on the estimation of the comparative value of areas of their self-similarity. The self-similarity coefficients of these areas appear as the regularization parameter at this stage of the research. These areas are estimated by means of definitions of their relative values as the ratio of the range for existence of each partial criterion referred to its upper boundary. The second stage of research is initiated by the need to determine the optimal combinations of the target product properties in the working area, depending on the customer conditions. For this purpose, the sub- compromise regions are defined in the working area of partial criteria under consideration (compromise criteria). The sub-compromise partial regions are regions of the optimal combinations of properties [12]. Thus, the regularization at the second stage is made in co-ordination with the requirements of the customer. In this connection, the example of solving the conditionally ill-posed problem for optimizing the multicriteria and multiparameter technol- ogies of production of cast iron rolls is given below. 2. RESEARCH MATERIAL Investigated were the section-mill cast iron rolls with the globular shape of graphite, chromium and nickel alloyed. The rolls were not 1168 V. I. BOLSHAKOV, V. M. VOLCHUK, and Yu. I. DUBROV subjected to the heat treatment and had the smooth surface of barrels. The structure of the rolls in the working area (up to ≅ 50 mm) had the following shape (Fig. 1). Dimensions of the globular graphite inclusions (their diameter) on the grinding surface varied from 35 µm to 59 µm, which corresponds to point 6 according to the standard ISO 945-75. The globular graphite in the working layer of the barrel at the depth of ≅ 5–15 mm is much less common to find in comparison with carbides, including ledeburite, which is explained by its content up to ≅ 3% (the standard is ШÃ4 ac- cording to ÃÎСТ 3443). The globular shape of graphite is caused by the addition of a small amount of magnesium—up to 0.054% by weight. Pearlite has the different dispersion (average distance between two ad- jacent cementite plates): from 0.79 µm to 2.2 µm. The area occupied by cementite averaged 20–30% according to calculations with the use of the linear method of A. Rosival, which corresponds to the score of Ц25. Mechanical properties of the roll-foundry iron (ultimate strength σВ, ultimate bending strength σ, impact strength KС, Shore hardness HSD) were determined according to ÃÎСТ 27208-87 with the use of standard techniques. The billets, from which samples were prepared for full-scale tests, have been selected from the cast samples. Samples were cut from the working area of smooth metal barrels of rolls in the tangential direction, as well as manufactured from the samples sepa- rately cast in castings. The impact strength of cast iron was deter- mined without the notch on the samples of 10×10×55 mm size. To as- sess the ultimate bending strength, the samples of 10×10×90 mm were used, and in tensile tests—the samples of 25 mm diameter, with the gauge length of 50 mm. To improve the reliability of the results obtained, the data on the a b Fig. 1. Structure of the working layer of cast iron roll barrels: globular graph- ite (a), colonies of ledeburite, graphite eutectic, pearlite matrix, HNO3 etch- ing (b). REGULARIZATION OF ILL-POSED PROBLEM OF EXTRACTIVE METALLURGY 1169 full-scale tests of tangential samples were used (the sampling for 283 metal fusions of the gross weight of ≅ 800 tons) [4]. 3. EXPERIMENTAL RESULTS AND DISCUSSION To implement the first stage of the research, the working area of cast iron quality criteria (compromise criteria), depending on their chemical composition, is determined according to the current ТÓÓ 14-2-1188-97 within the following limits: σВ ≈ 240–460 MPa, σ ≈ 330–940 MPa, KС ≈ 9–33 kJ/m2, HSD ≈ 40–60, taking into account the whole range of applicable cooling conditions for rolls in the metal shape. In order to determine the working area of stable indicators for quali- ty criteria of the multiparameter technologies, their ranking by im- portance was carried out. The criteria ranking methodology is more par- ticularly described in the paper [6]. The criteria ranking procedure was carried out on the basis of the analysis concerning their area of self- similarity. In this case, the regularization parameter for the stable oper- ation of the technology is represented by the self-similarity coefficient. The area of self-similarity of the normalized quality criteria for the ultimate strength varied from 240 to 460 MPa, i.e., by 220 units (with- in the limits of (220/460)⋅100% ≈ 48%). We therewith assume that the self-similarity coefficient B Kσ is equal to 0.48. The self-similarity in- dicators for the remaining partial criteria were similarly calculated and made up for Kσ = 0.65, KKС = 0.73 and KHSD = 0.33. The key parameter among quality criteria under consideration is the impact strength having the highest self-similarity coefficient KKС = 0.73. Accordingly, indicators of the impact strength for cast iron with the structure of the globular graphite are more sensitive to changes in the in-house technology than other properties of σВ, σ and HSD are. Since it is assumed that, for the regularization of the tech- nology operation with respect to the key parameter KС, it is necessary to maintain indicators of the chemical composition and conditions for cooling of rolls within the limits prescribed by statutory documents. In case of violating the in-house technology, changes in the areas of self- similarity of partial criteria are possible, and consequently—changes in their ranking. To implement the second stage of the research, the compromise cri- teria (Fig. 2), consisting in the normalized representation of variables, whose value is given in percentage [12, 13], were determined. Since this stage is aimed at finding the ways to optimize the multiparameter technologies by identifying areas with the best combination of criteria, from the point of view of the customer, the working areas of criteria represent, from these positions, their compromise criteria. According- ly, the regularization of the technology at this stage will be to identify areas with the best combination of criteria. Regarding the key parame- 1170 V. I. BOLSHAKOV, V. M. VOLCHUK, and Yu. I. DUBROV ter, the following segments are obtained: 1 (KС–HSD–σ), 2 (KС–σ), 3 (KС–HSD), 4 (KС–σВ) (Fig. 2), which makes it possible to consider these segments from the perspective of optimizing the multi- parameter technologies. Based on the customer preference, combinations of partial criteria are selected from the compromise criteria with the possibility to forecast the range of the chemical composition of the roll, which gives the oppor- tunity for the regularization of the technology to produce cast iron rolls. 4. CONCLUSIONS Therefore, the given regularization of the conditionally ill-posed prob- lem using the fractal formalism contributes to optimization of the multiparameter technologies by choosing combinations of partial qual- ity criteria according to the customer’s preference under different ini- tial conditions. REFERENCES 1. Yu. Dubrov, V. Bol’shakov, and V. Volchuk, Puti Identifikatsii Periodicheskikh Mnogokriterialnykh Tekhnologiy [Paths to Identification of Periodic Multicriteria Technologies] (Saarbrucken: Palmarium Academic Publishing: 2015) (in Russian). 2. V. I. Bol’shakov, Substrukturnoe Uprochnenie Konstruktsionnykh Staley [Substructural Hardening of Structural Steels] (Toronto: Basilian Press: 1998) (in Russian). Fig. 2. The compromise criteria of the mechanical properties of cast iron as function of the chemical composition. REGULARIZATION OF ILL-POSED PROBLEM OF EXTRACTIVE METALLURGY 1171 3. T. S. Skoblo, N. M. Vorontsov, S. I. Rudyuk, N. A. Budag’yants, and V. A. Voronina, Prokatnye Valki iz Vysokouglerodistykh Splavov [Forming Rolls from High-Carbon Alloys] (Moscow: Metallurgiya: 1994) (in Russian). 4. A. Ye. Krivosheyev, Litye Valki [Cast Rolls] (Moscow: Metallurgizdat: 1957) (in Russian). 5. A. N. Tikhonov and V. Y. Arsenin, Solutions of Ill-Posed Problems (New York: Winston: 1977). 6. V. M. Volchuk, Metallofiz. Noveishie Tekhnol., 39, No. 7: 949 (2017) (in Russian). 7. B. B. Mandelbrot, The Fractal Geometry of Nature (New York–San Francisco: Freeman: 1982). 8. O. Eh. Zasimchuk, Yu. G. Gordienko, and R. G. Gontareva, Metallofiz. Noveishie Tekhnol., 22, No. 4: 71 (2000) (in Russian). 9. V. Bolshakov, V. Volchuk, and Yu. Dubrov, Fractals and Properties of Materials (Saarbrucken: Lambert Academic Publishing: 2016). 10. J. Hadamard, Princeton University Bulletin, 13: 49 (1902) (in French). 11. S. I. Kabanikhin, Inverse and Ill-Posed Problems. Theory and Applications (De Gruyter: 2011). 12. V. I. Bol’shakov, V. M. Volchuk, and Yu. I. Dubrov, Visn. Nac. Akad. Nauk Ukr., No. 8: 66 (2013) (in Ukrainian). 13. V. I. Bol’shakov, V. N. Volchuk, and Yu. I. Dubrov, Dopov. Nac. Akad. 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