Details

Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications 1


Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications 1


1. Aufl.

von: Dmitri Koroliouk, Sergiy Lyashko, Nikolaos Limnios

142,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 16.04.2024
ISBN/EAN: 9781394284337
Sprache: englisch
Anzahl Seiten: 448

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

<p>Mathematical methods in engineering are characterized by a wide range of techniques for approaching various problems. Moreover, completely different analysis techniques can be applied to the same problem, which is justified by the difference in specific applications. Therefore, the study of the analyses and solutions of specific problems leads the researcher to generate their own techniques for the analysis of similar problems continuously arising in the process of technical development.</p> <p><i>Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications</i> contains solutions to specific problems in current areas of computational engineering and cyberphysics.</p>
<p>Preface xi<br /><i>Dmitri KOROLIOUK</i></p> <p><b>Chapter 1 The Hydrodynamic-type Equations and the Solitary Solutions 1</b><br /><i>Sergiy LYASHKO, Valerii SAMOILENKO, Yuliia SAMOILENKO and Ihor GAPYAK</i></p> <p>1.1 Introduction 1</p> <p>1.2 The Korteweg-de Vries equation and the soliton solutions 3</p> <p>1.3 The Korteweg-de Vries equation with a small perturbation 4</p> <p>1.4 The linear WKB technique and its generalization 7</p> <p>1.5 Acknowledgments 11</p> <p>1.6 References 11</p> <p><b>Chapter 2 The Nonlinear WKB Technique and Asymptotic Soliton-like Solutions to the Korteweg-de Vries Equation with Variable Coefficients and Singular Perturbation 15</b><br /><i>Sergiy LYASHKO, Valerii SAMOILENKO, Yuliia SAMOILENKO and Evgen VAKAL</i></p> <p>2.1 Introduction 16</p> <p>2.2 Main notations and definitions 18</p> <p>2.3 The structure of the asymptotic one-phase soliton-like solution 19</p> <p>2.4 The KdV equation with quadratic singularity 20</p> <p>2.5 Equations for the regular part of the asymptotics and their analysis 22</p> <p>2.6 Equations for the singular part of the asymptotics and their analysis 24</p> <p>2.6.1 The main term of the singular part 25</p> <p>2.6.2 The higher terms of the singular part and the orthogonality condition 26</p> <p>2.6.3 The orthogonality condition and the discontinuity curve 29</p> <p>2.6.4 Prolongation of the singular terms from the discontinuity curve 34</p> <p>2.7 Justification of the algorithm 38</p> <p>2.8 Discussion and conclusion 44</p> <p>2.9 Acknowledgments 45</p> <p>2.10 References 45</p> <p><b>Chapter 3 Asymptotic Analysis of the vcKdV Equation with Weak Singularity 49</b><br /><i>Sergiy LYASHKO, Valerii SAMOILENKO, Yuliia SAMOILENKO and Nataliia LYASHKO</i></p> <p>3.1 Introduction 50</p> <p>3.2 The asymptotic soliton-like solutions 51</p> <p>3.3 The examples of the asymptotic soliton-like solutions 56</p> <p>3.3.1 The asymptotic step-wise solutions 57</p> <p>3.3.2 The asymptotic solutions of soliton type 61</p> <p>3.4 Discussion and conclusion 66</p> <p>3.5 Acknowledgments 66</p> <p>3.6 References 66</p> <p><b>Chapter 4 Modeling of Heterogeneous Fluid Dynamics with Phase Transitions and Porous Media 69</b><br /><i>Gennadiy V SANDRAKOV</i></p> <p>4.1 Introduction 69</p> <p>4.2 The large particle method 72</p> <p>4.3 The particle-in-cell method 79</p> <p>4.4 Modeling of heterogeneous fluid dynamics 83</p> <p>4.5 Modeling of heterogeneous fluid dynamics with phase transitions 88</p> <p>4.6 Modeling of viscous fluid dynamics and porous media 94</p> <p>4.7 References 98</p> <p><b>Chapter 5 Mathematical Models and Control of Functionally Stable Technological Process 101</b><br /><i>Volodymyr PICHKUR, Valentyn SOBCHUK and Dmytro CHERNIY</i></p> <p>5.1 Introduction 101</p> <p>5.2 Analysis of production process planning procedure 104</p> <p>5.3 Mathematical model of the production process management system of an industrial enterprise 108</p> <p>5.4 Control design 111</p> <p>5.5 Algorithm of control of production process 115</p> <p>5.6 Conclusion 116</p> <p>5.7 Acknowledgments 117</p> <p>5.8 References 118</p> <p><b>Chapter 6 Alternative Direction Multiblock Method with Nesterov Acceleration and Its Applications 121</b><br /><i>Vladislav HRYHORENKO, Nataliia LYASHKO, Sergiy LYASHKO and Dmytro KLYUSHIN</i></p> <p>6.1 Introduction 121</p> <p>6.2 Proximal operators 122</p> <p>6.3 ADMM (alternating direction method of multipliers) 128</p> <p>6.4 Bregman iteration 131</p> <p>6.5 Forward-backward envelope (FBE) 132</p> <p>6.6 Douglas-Rachford envelope (DRE) 133</p> <p>6.7 Proximal algorithms for complex functions 134</p> <p>6.8 Fast alternative directions methods 137</p> <p>6.9 Numerical experiments 142</p> <p>6.9.1 Exchange problem 142</p> <p>6.9.2 Basis pursuit problem 143</p> <p>6.9.3 Constrained LASSO problem 144</p> <p>6.10 Conclusion 145</p> <p>6.11 References 145</p> <p><b>Chapter 7 Modified Extragradient Algorithms for Variational Inequalities 149</b><br /><i>Vladimir V SEMENOV and Sergey V DENISOV</i></p> <p>7.1 Introduction 149</p> <p>7.2 Preliminaries 149</p> <p>7.3 Overview of the main algorithms for solving variational inequalities and approximations of fixed points 156</p> <p>7.4 Modified extragradient algorithm for variational inequalities 164</p> <p>7.5 Modified extragradient algorithm for variational inequalities and operator equations with a priori information 173</p> <p>7.6 Strongly convergent modified extragradient algorithm 177</p> <p>7.6.1 Algorithm variant for variational inequalities 178</p> <p>7.6.2 Variant for problems with a priori information 193</p> <p>7.7 References 199</p> <p><b>Chapter 8 On Multivariate Algorithms of Digital Signatures on Secure El Gamal-Type Mode 205</b><br /><i>Vasyl USTIMENKO</i></p> <p>8.1 On post-quantum, multivariate and non-commutative cryptography 206</p> <p>8.2 On stable subgroups of formal Cremona group and privatization of multivariate public keys based on maps of bounded degree 208</p> <p>8.3 Multivariate Tahoma protocol for stable Cremona generators and its usage for multivariate encryption algorithms 211</p> <p>8.4 On multivariate digital signature algorithms and their privatization scheme 214</p> <p>8.5 Examples of stable cubical groups 216</p> <p>8.5.1 Simplest graph-based example 216</p> <p>8.5.2 Other stable subgroups defined via linguistic graphs 219</p> <p>8.5.3 Special homomorphisms of linguistic graphs and corresponding semigroups 222</p> <p>8.5.4 Example of stable subsemigroups of arbitrary degree 223</p> <p>8.6 Conclusion 225</p> <p>8.7 References 227</p> <p><b>Chapter 9 Metasurface Model of Geographic Baric Field Formation 231</b><br /><i>Dmitri KOROLIOUK, Maksym ZOZIUK, Pavlo KRYSENKO and Yuriy YAKYMENKO</i></p> <p>9.1 Introduction 231</p> <p>9.2 The parametric scalar field model principle 233</p> <p>9.3 Local isobaric scalar field model 234</p> <p>9.4 Modeling Chladni figures based on the proposed model 235</p> <p>9.5 The frequency of forcing influences and the problem of its detection 237</p> <p>9.6 Conclusion 239</p> <p>9.7 References 241</p> <p><b>Chapter 10 Simulation of the Electron-Hole Plasma State by Perturbation Theory Methods 245</b><br /><i>Andrii BOMBA, Sergiy LYASHKO and Ihor MOROZ</i></p> <p>10.1 Introduction Nonlinear boundary value problems of the p-i-n diodes theory 245</p> <p>10.2 Construction of an asymptotic solution of a boundary value problem for the system of the charge carrier current continuity equations and the Poisson equation 249</p> <p>10.3 Simulation of the charge carriers’ stationary distribution in the electron-hole plasma of the p-i-n diode assembly elements 262</p> <p>10.4 Modeling the charge carriers stationary distribution in the active region of the integrated surface-oriented p-i-n structures 264</p> <p>10.5 Final considerations 270</p> <p>10.6 References 271</p> <p><b>Chapter 11 Diffusion Perturbations in Models of the Dynamics of Infectious Diseases Taking into Account the Concentrated Effects 273</b><br /><i>Serhii BARANOVSKY, Andrii BOMBA, Sergiy LYASHKO and Oksana PRYSHCHEPA</i></p> <p>11.1 Introduction 273</p> <p>11.2 Model problem of infectious disease dynamics taking into account diffusion perturbation and asymptotics of the solution 277</p> <p>11.3 Modeling of diffusion perturbations of infectious disease process taking into account the concentrated effects and immunotherapy 282</p> <p>11.4 Modeling the influence of diffusion perturbations on development of infectious diseases under convection 288</p> <p>11.5 Numerical experiment results 292</p> <p>11.6 Conclusion 300</p> <p>11.7 References 301</p> <p><b>Chapter 12 Solitary Waves in the "Shallow Water" Environments 305</b><br /><i>Yurii TURBAL, Mariana TURBAL and Andrii BOMBA</i></p> <p>12.1 Introduction 305</p> <p>12.2 T-forms for the solitary wave approximation 307</p> <p>12.3 Existence of the solution of the gas dynamics equations in the form of solitary waves 313</p> <p>12.4 Analysis of the localized wave trajectories 332</p> <p>12.5 Numerical results 338</p> <p>12.6 Conclusion 341</p> <p>12.7 References 342</p> <p><b>Chapter 13 Instrument Element and Grid Middleware in Metrology Problems 345</b><br /><i>Pavlo NEYEZHMAKOV, Stanislav ZUB, Sergiy LYASHKO, Irina YALOVEGA and Nataliia LYASHKO</i></p> <p>13.1 Introduction 345</p> <p>13.2 Security in the grid 347</p> <p>13.3 Grid element for measuring instruments 347</p> <p>13.4 Grid and some problems of metrology 350</p> <p>13.5 Discussion and conclusion 352</p> <p>13.6 References 352</p> <p><b>Chapter 14 Differential Evolution for Best Uniform Spline Approximation 355</b><br /><i>Larysa VAKAL and Evgen VAKAL</i></p> <p>14.1 Introduction 356</p> <p>14.2 Problem statement 356</p> <p>14.3 Review of methods for spline approximation 357</p> <p>14.4 Algorithm 359</p> <p>14.5 Experimental results and discussion 362</p> <p>14.6 Conclusion 364</p> <p>14.7 References 365</p> <p><b>Chapter 15 Finding a Nearest Pair of Points Between Two Smooth Curves in Euclidean Space 367</b><br /><i>Vladimir V SEMENOV, Nataliia LYASHKO, Stanislav ZUB and Yevhen HAVRYLKO</i></p> <p>15.1 Introduction 367</p> <p>15.2 Define the problem and notations 368</p> <p>15.3 Lagrange function with energy dissipation 369</p> <p>15.4 Lagrange equation 370</p> <p>15.5 Hamiltonian equations 372</p> <p>15.6 Numerical experiments 376</p> <p>15.7 Concluding remarks 378</p> <p>15.8 References 379</p> <p><b>Chapter 16 Constrained Markov Decision Process for the Industry 381</b><br /><i>Michel BOUSSEMART and Nikolaos LIMNIOS</i></p> <p>16.1 Introduction 381</p> <p>16.2 Introduction to constrained Markov decision processes 382</p> <p>16.2.1 Introduction 382</p> <p>16.2.2 Model 383</p> <p>16.2.3 Economic criteria 384</p> <p>16.2.4 Infinite horizon expected discounted reward 386</p> <p>16.2.5 Infinite horizon expected average reward 392</p> <p>16.3 Markov decision process with a constraint on the asymptotic availability 396</p> <p>16.3.1 Introduction 396</p> <p>16.3.2 Model 397</p> <p>16.3.3 Algorithm 399</p> <p>16.3.4 Application 399</p> <p>16.4 Markov decision process with a constraint on the asymptotic failure rate 408</p> <p>16.4.1 Introduction 408</p> <p>16.4.2 Model 409</p> <p>16.4.3 Algorithm 413</p> <p>16.4.4 Application 413</p> <p>16.5 Conclusion 418</p> <p>16.6 References 419</p> <p>List of Authors 423</p> <p>Index 427</p>
<p><b>Dmitri Koroliouk</b> is a Doctor of Sciences, Professor at the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", and leading researcher at the Institute of Mathematics, and at the Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine. He is also Head of the Digital Innovation Laboratory at UNESCO Interdisciplinary Chair in Biotechnology and Bioethics at the University of Rome Tor Vergata, Italy.</p> <p><b>Sergiy Lyashko</b> is Head of the Department of Computational Mathematics at the Faculty of Computer Sciences and Cybernetics, Taras Shevchenko National University of Kyiv, and a professor at the National Academy of Sciences of Ukraine. His research interests concern problems of singular optimal control of linear systems.</p> <p><b>Nikolaos Limnios</b> is a professor at the Laboratoire de Mathématiques Appliquées, Université de Technologie de Compiègne, France. His research interests concern statistical inference for stochastic processes and semi-Markov processes.</p>

Diese Produkte könnten Sie auch interessieren:

Reliability and Six Sigma
Reliability and Six Sigma
von: U Dinesh Kumar, John Crocker, T. Chitra, Haritha Saranga
PDF ebook
106,99 €
Life Distributions
Life Distributions
von: Albert W. Marshall, Ingram Olkin
PDF ebook
181,89 €