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Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Kantorovich, Lev |
Mathematics for Natural Scientists |
I12528 |
2022 |
Book |
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| 2 |
Barber, J. R |
Elasticity |
I12472 |
2022 |
Book |
|
| 3 |
Steinhauser, Martin Oliver |
Computational Multiscale Modeling of Fluids and Solids |
I12437 |
2022 |
Book |
|
| 4 |
Cacuci, Dan Gabriel |
The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I |
I12435 |
2022 |
Book |
|
| 5 |
Bonamente, Massimiliano |
Statistics and Analysis of Scientific Data |
I12430 |
2022 |
Book |
|
| 6 |
Huerta Cu??llar, Guillermo |
Complex Systems and Their Applications |
I12413 |
2022 |
Book |
|
| 7 |
Volchenkov, Dimitri |
Mathematical Methods in Modern Complexity Science |
I12384 |
2022 |
Book |
|
| 8 |
Tang, Kwong-Tin |
Mathematical Methods for Engineers and Scientists 1 |
I12284 |
2022 |
Book |
|
| 9 |
Milstein, Grigori N |
Stochastic Numerics for Mathematical Physics |
I11924 |
2021 |
eBook |
|
| 10 |
Vasile, Massimiliano |
Optimization Under Uncertainty with Applications to Aerospace Engineering |
I11723 |
2021 |
eBook |
|
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1.
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| Title | Mathematics for Natural Scientists : Fundamentals and Basics |
| Author(s) | Kantorovich, Lev |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XXIII, 768 p. 189 illus., 163 illus. in color : online resource |
| Abstract Note | This book, now in a second revised and enlarged edition, covers a course of mathematics designed primarily for physics and engineering students. It includes all the essential material on mathematical methods, presented in a form accessible to physics students and avoiding unnecessary mathematical jargon and proofs that are comprehensible only to mathematicians. Instead, all proofs are given in a form that is clear and sufficiently convincing for a physicist. Examples, where appropriate, are given from physics contexts. Both solved and unsolved problems are provided in each section of the book. The second edition includes more on advanced algebra, polynomials and algebraic equations in significantly extended first two chapters on elementary mathematics, numerical and functional series and ordinary differential equations. Improvements have been made in all other chapters, with inclusion of additional material, to make the presentation clearer, more rigorous and coherent, and the number of problems has been increased at least twofold. Mathematics for Natural Scientists: Fundamentals and Basics is the first of two volumes. Advanced topics and their applications in physics are covered in the second volume the second edition of which the author is currently being working on |
| ISBN,Price | 9783030912222 |
| Keyword(s) | 1. Applications of Mathematics
2. Chemometrics
3. Diseases
4. EBOOK
5. EBOOK - SPRINGER
6. ENGINEERING MATHEMATICS
7. Engineering???Data processing
8. Mathematical and Computational Engineering Applications
9. Mathematical Applications in Chemistry
10. Mathematical Methods in Physics
11. MATHEMATICAL PHYSICS
12. MATHEMATICS
13. Theoretical, Mathematical and Computational Physics
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12528 |
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On Shelf |
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2.
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| Title | Elasticity |
| Author(s) | Barber, J. R |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XX, 637 p. 131 illus., 2 illus. in color : online resource |
| Abstract Note | This book emphasizes engineering applications of elasticity. This is a first-year graduate textbook in linear elasticity. It is written with the practical engineering reader in mind, dependence on previous knowledge of solid mechanics, continuum mechanics or mathematics being minimized. Examples are generally worked through to final expressions for the stress and displacement fields in order to explore the engineering consequences of the results. This 4th edition presents new and revised material, notably on the Eshelby inclusion problem and anisotropic elasticity. The topics covered are chosen with a view to modern research applications in fracture mechanics, composite materials, tribology and numerical methods. Thus, significant attention is given to crack and contact problems, problems involving interfaces between dissimilar media, thermoelasticity, singular asymptotic stress fields and three-dimensional problems |
| ISBN,Price | 9783031152146 |
| Keyword(s) | 1. Applications of Mathematics
2. Classical and Continuum Physics
3. EBOOK
4. EBOOK - SPRINGER
5. Engineering Fluid Dynamics
6. ENGINEERING MATHEMATICS
7. Engineering???Data processing
8. FLUID MECHANICS
9. Mathematical and Computational Engineering Applications
10. MATHEMATICS
11. MECHANICAL ENGINEERING
12. Mechanics, Applied
13. PHYSICS
14. Solid Mechanics
15. SOLIDS
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12472 |
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On Shelf |
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3.
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| Title | Computational Multiscale Modeling of Fluids and Solids : Theory and Applications |
| Author(s) | Steinhauser, Martin Oliver |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XXVII, 432 p. 145 illus., 55 illus. in color : online resource |
| Abstract Note | The expanded 3rd edition of this established textbook offers an updated overview and review of the computational physics techniques used in materials modelling over different length and time scales. It describes in detail the theory and application of some of the most important methods used to simulate materials across the various levels of spatial and temporal resolution. Quantum mechanical methods such as the Hartree-Fock approximation for solving the Schr??dinger equation at the smallest spatial resolution are discussed as well as the Molecular Dynamics and Monte-Carlo methods on the micro- and meso-scale up to macroscopic methods used predominantly in the Engineering world such as Finite Elements (FE) or Smoothed Particle Hydrodynamics (SPH). Extensively updated throughout, this new edition includes additional sections on polymer theory, statistical physics and continuum theory, the latter being the basis of FE methods and SPH. Each chapter now first provides an overview of the key topics covered, with a new ???key points??? section at the end. The book is aimed at beginning or advanced graduate students who want to enter the field of computational science on multi-scales. It provides an in-depth overview of the basic physical, mathematical and numerical principles for modelling solids and fluids on the micro-, meso-, and macro-scale. With a set of exercises, selected solutions and several case studies, it is a suitable book for students in physics, engineering, and materials science, and a practical reference resource for those already using materials modelling and computational methods in their research |
| ISBN,Price | 9783030989545 |
| Keyword(s) | 1. Characterization and Analytical Technique
2. Computational Mathematics and Numerical Analysis
3. EBOOK
4. EBOOK - SPRINGER
5. ENGINEERING MATHEMATICS
6. Engineering???Data processing
7. GEOLOGY
8. Materials???Analysis
9. Mathematical and Computational Engineering Applications
10. MATHEMATICAL PHYSICS
11. Mathematics???Data processing
12. Theoretical, Mathematical and Computational Physics
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12437 |
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On Shelf |
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4.
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| Title | The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I : Overcoming the Curse of Dimensionality: Linear Systems |
| Author(s) | Cacuci, Dan Gabriel |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XII, 362 p : online resource |
| Abstract Note | The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties underlying the respective model. The functional derivatives (also called ???sensitivities???) of results (also called ???responses???) produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing ???reduced-order modeling??? by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing ???model validation,??? by comparing computations to experiments to address the question ???does the model represent reality???? (v) prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward ???predictive modeling??? to obtain best-estimate predicted results with reduced predicted uncertainties; (vii) performing inverse ???predictive modeling???; (viii) designing and optimizing the system. This 3-Volume monograph describes a comprehensive adjoint sensitivity analysis methodology, developed by the author, which enables the efficient and exact computation of arbitrarily high-order sensitivities of model responses in large-scale systems comprising many model parameters. The qualifier ???comprehensive??? is employed to highlight that the model parameters considered within the framework of this methodology also include the system???s uncertain boundaries and internal interfaces in phase-space. The model???s responses can be either scalar-valued functionals of the model???s parameters and state variables (e.g., as customarily encountered in optimization problems) or general function-valued responses. Since linear operators admit bona-fide adjoint operators, responses of models that are linear in the state functions (i.e., dependent variables) can depend simultaneously on both the forward and the adjoint state functions. Hence, the sensitivity analysis of such responses warrants the treatment of linear systems in their own right, rather than treating them as particular cases of nonlinear systems. This is in contradistinction to responses for nonlinear systems, which can depend only on the forward state functions, since nonlinear operators do not admit bona-fide adjoint operators (only a linearized form of a nonlinear operator may admit an adjoint operator). Thus, Volume 1 of this book presents the mathematical framework of the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as ???nth-CASAM-L???), which is conceived for the most efficient computation of exactly obtained mathematical expressions of arbitrarily-high-order (nth-order) sensitivities of a generic system response with respect to all of the parameters underlying the respective forward/adjoint systems. Volume 2 of this book presents the application of the nth-CASAM-L to perform a fourth-order sensitivity and uncertainty analysis of an OECD/NEA reactor physics benchmark which is representative of a large-scale model comprises many (21,976) uncertain parameters, thereby amply illustrating the unique potential of the nth-CASAM-L to enable the exact and efficient computation of chosen high-order response sensitivities to model parameters. Volume 3 of this book presents the ???nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems??? (abbreviation: nth-CASAM-N) for the practical, efficient, and exact computation of arbitrarily-high order sensitivities of responses to model parameters for systems that are also nonlinear in their underlying state functions. Such computations are not feasible with any other methodology. The application of the nth-CASAM-L and the nth-CASAM-N overcomes the so-called ???curse of dimensionality??? in sensitivity and uncertainty analysis, thus revolutionizing all of the fields of activities which require accurate computation of response sensitivities. Since this monograph includes many illustrative, fully worked-out, paradigm problems, it can serve as a textbook or as supplementary reading for graduate courses in academic departments in the natural sciences and engineering |
| ISBN,Price | 9783030963644 |
| Keyword(s) | 1. Computational Physics and Simulations
2. COMPUTER SIMULATION
3. EBOOK
4. EBOOK - SPRINGER
5. Energy and state
6. Energy policy
7. Energy Policy, Economics and Management
8. ENGINEERING MATHEMATICS
9. Engineering???Data processing
10. Mathematical and Computational Engineering Applications
11. Mathematical Modeling and Industrial Mathematics
12. MATHEMATICAL MODELS
13. MATHEMATICAL PHYSICS
14. NUCLEAR PHYSICS
15. Statistical Theory and Methods
16. Statistics??
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12435 |
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On Shelf |
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5.
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| Title | Statistics and Analysis of Scientific Data |
| Author(s) | Bonamente, Massimiliano |
| Publication | Singapore, 1. Imprint: Springer
2. Springer Nature Singapore, 2022. |
| Description | XXIII, 488 p. 58 illus., 48 illus. in color : online resource |
| Abstract Note | This book is the third edition of a successful textbook for upper-undergraduate and early graduate students, which offers a solid foundation in probability theory and statistics and their application to physical sciences, engineering, biomedical sciences and related disciplines. It provides broad coverage ranging from conventional textbook content of probability theory, random variables, and their statistics, regression, and parameter estimation, to modern methods including Monte-Carlo Markov chains, resampling methods and low-count statistics. In addition to minor corrections and adjusting structure of the content, particular features in this new edition include: Python codes and machine-readable data for all examples, classic experiments, and exercises, which are now more accessible to students and instructors New chapters on low-count statistics including the Poisson-based Cash statistic for regression in the low-count regime, and on contingency tables and diagnostic testing. An additional example of classic experiments based on testing data for SARS-COV-2 to demonstrate practical applications of the described statistical methods. This edition inherits the main pedagogical method of earlier versions???a theory-then-application approach???where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the materials. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data as well as exercises and examples to aid the readers' understanding of the topic |
| ISBN,Price | 9789811903656 |
| Keyword(s) | 1. Applied Statistics
2. Data Analysis and Big Data
3. EBOOK
4. EBOOK - SPRINGER
5. ENGINEERING MATHEMATICS
6. Engineering???Data processing
7. Mathematical and Computational Engineering Applications
8. Mathematical Methods in Physics
9. MATHEMATICAL PHYSICS
10. Mathematical statistics???Data processing
11. Quantitative research
12. Statistical Theory and Methods
13. Statistics and Computing
14. Statistics??
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12430 |
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On Shelf |
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6.
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| Title | Complex Systems and Their Applications : Second International Conference (EDIESCA 2021) |
| Author(s) | Huerta Cu??llar, Guillermo;Campos Cant??n, Eric;Tlelo-Cuautle, Esteban |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | X, 269 p. 149 illus., 129 illus. in color : online resource |
| Abstract Note | This book is a compilation of scientific articles written by recognized researchers, and select students, participating in the Second Conference on the Study of Complex Systems and their Applications (EDIESCA 2021). EDIESCA 2021 arose from the need for academic and research groups that carry out this scientific research to disseminate their results internationally. The study and characterization of systems with non-linear and/or chaotic behavior has been of great interest to researchers around the world, for which many important results have been obtained with various applications. The dynamic study of chaotic oscillators of different models, such as R??ssler, Lorenz, and Chua, has generated important advances in understanding of chemical reactions, meteorological behavior, design of electronic devices, and other applications. Topics at the event included applications for communications systems by masking techniques, financial behavior, networks analysis, nonlinear lasers, numerical modeling, electronic design, and other interesting topics in the area of complex systems. Additionally, there are results on numerical simulation and electronic designs to generate complex dynamic behaviors |
| ISBN,Price | 9783031024726 |
| Keyword(s) | 1. Applied Dynamical Systems
2. COMPLEX SYSTEMS
3. DYNAMICS
4. EBOOK
5. EBOOK - SPRINGER
6. ELECTRONIC CIRCUIT DESIGN
7. Electronics Design and Verification
8. ENGINEERING DESIGN
9. ENGINEERING MATHEMATICS
10. Engineering???Data processing
11. Mathematical and Computational Engineering Applications
12. Mechanics, Applied
13. Multibody systems
14. Multibody Systems and Mechanical Vibrations
15. NONLINEAR THEORIES
16. SYSTEM THEORY
17. VIBRATION
|
| Item Type | Book |
Multi-Media Links
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Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12413 |
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On Shelf |
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7.
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| Title | Mathematical Methods in Modern Complexity Science |
| Author(s) | Volchenkov, Dimitri;Tenreiro Machado, J. A |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | X, 197 p. 94 illus., 69 illus. in color : online resource |
| Abstract Note | This book presents recent developments in nonlinear and complex systems. It provides recent theoretic developments and new techniques based on a nonlinear dynamical systems approach that can be used to model and understand complex behavior in nonlinear dynamical systems. It covers information theory, relativistic chaotic dynamics, data analysis, relativistic chaotic dynamics, solvability issues in integro-differential equations, and inverse problems for parabolic differential equations, synchronization and chaotic transient. Presents new concepts for understanding and modeling complex systems |
| ISBN,Price | 9783030794125 |
| Keyword(s) | 1. Applied Dynamical Systems
2. Computational Intelligence
3. DYNAMICS
4. EBOOK
5. EBOOK - SPRINGER
6. ENGINEERING MATHEMATICS
7. Engineering???Data processing
8. Mathematical and Computational Engineering Applications
9. MATHEMATICAL PHYSICS
10. NONLINEAR THEORIES
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12384 |
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On Shelf |
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8.
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| Title | Mathematical Methods for Engineers and Scientists 1 : Complex Analysis and Linear Algebra |
| Author(s) | Tang, Kwong-Tin |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XV, 492 p. 129 illus : online resource |
| Abstract Note | Part 1 of this popular graduate-level textbook focuses on mathematical methods involving complex analysis, determinants, and matrices, including updated and additional material covering conformal mapping. The second edition comes with extensive updates and additions, making them a more complete reference for graduate science and engineering students while imparting comfort and confidence in using advanced mathematical tools in both upper-level undergraduate and beginning graduate courses. This set of student-centered textbooks presents topics such as complex analysis, matrix theory, vector and tensor analysis, Fourier analysis, integral transformations, and ordinary and partial differential equations in a discursive style that is clear, engaging, and easy to follow. Replete with pedagogical insights from an author with more than 30 years of experience in teaching applied mathematics, this indispensable set of books features numerous clearly stated and completely worked out examples together with carefully selected problems and answers that enhance students' understanding and analytical skills |
| ISBN,Price | 9783031056789 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. ENGINEERING MATHEMATICS
4. Engineering???Data processing
5. Mathematical and Computational Engineering Applications
6. Mathematical Methods in Physics
7. MATHEMATICAL PHYSICS
8. PROJECTIVE GEOMETRY
9. Theoretical, Mathematical and Computational Physics
|
| Item Type | Book |
Multi-Media Links
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| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12284 |
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On Shelf |
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9.
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| Title | Stochastic Numerics for Mathematical Physics |
| Author(s) | Milstein, Grigori N;Tretyakov, Michael V |
| Publication | Cham, Springer International Publishing, 2021. |
| Description | XXV, 736 p. 33 illus : online resource |
| Abstract Note | This book is a substantially revised and expanded edition reflecting major developments in stochastic numerics since the first edition was published in 2004. The new topics, in particular, include mean-square and weak approximations in the case of nonglobally Lipschitz coefficients of Stochastic Differential Equations (SDEs) including the concept of rejecting trajectories; conditional probabilistic representations and their application to practical variance reduction using regression methods; multi-level Monte Carlo method; computing ergodic limits and additional classes of geometric integrators used in molecular dynamics; numerical methods for FBSDEs; approximation of parabolic SPDEs and nonlinear filtering problem based on the method of characteristics. SDEs have many applications in the natural sciences and in finance. Besides, the employment of probabilistic representations together with the Monte Carlo technique allows us to reduce the solution of multi-dimensional problems for partial differential equations to the integration of stochastic equations. This approach leads to powerful computational mathematics that is presented in the treatise. Many special schemes for SDEs are presented. In the second part of the book numerical methods for solving complicated problems for partial differential equations occurring in practical applications, both linear and nonlinear, are constructed. All the methods are presented with proofs and hence founded on rigorous reasoning, thus giving the book textbook potential. An overwhelming majority of the methods are accompanied by the corresponding numerical algorithms which are ready for implementation in practice. The book addresses researchers and graduate students in numerical analysis, applied probability, physics, chemistry, and engineering as well as mathematical biology and financial mathematics |
| ISBN,Price | 9783030820404 |
| Keyword(s) | 1. BIOMATHEMATICS
2. Chemometrics
3. Computational Science and Engineering
4. EBOOK
5. EBOOK - SPRINGER
6. ENGINEERING MATHEMATICS
7. Engineering???Data processing
8. Mathematical and Computational Biology
9. Mathematical and Computational Engineering Applications
10. Mathematical Applications in Chemistry
11. MATHEMATICAL PHYSICS
12. Mathematics in Business, Economics and Finance
13. Mathematics???Data processing
14. Social sciences???Mathematics
15. Theoretical, Mathematical and Computational Physics
|
| Item Type | eBook |
Multi-Media Links
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Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11924 |
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On Shelf |
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10.
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| Title | Optimization Under Uncertainty with Applications to Aerospace Engineering |
| Author(s) | Vasile, Massimiliano |
| Publication | Cham, Springer International Publishing, 2021. |
| Description | VI, 573 p. 155 illus., 108 illus. in color : online resource |
| Abstract Note | In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students |
| ISBN,Price | 9783030601669 |
| Keyword(s) | 1. Aerospace engineering
2. Aerospace Technology and Astronautics
3. ASTRONAUTICS
4. ASTRONOMY
5. Astronomy, Cosmology and Space Sciences
6. Computational Science and Engineering
7. EBOOK
8. EBOOK - SPRINGER
9. ENGINEERING MATHEMATICS
10. Engineering???Data processing
11. Mathematical and Computational Engineering Applications
12. MATHEMATICAL OPTIMIZATION
13. Mathematics???Data processing
14. OPTIMIZATION
|
| Item Type | eBook |
Multi-Media Links
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| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11723 |
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On Shelf |
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