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Author | Title | Accn# | Year | Item Type | Claims |
| 11 |
Kitamura, Keiichi |
Advancement of Shock Capturing Computational Fluid Dynamics Methods |
I09025 |
2020 |
eBook |
|
| 12 |
Miller, Karol |
Computational Biomechanics for Medicine |
I09019 |
2020 |
eBook |
|
| 13 |
McClarren, Ryan G |
Uncertainty Quantification and Predictive Computational Science |
I08959 |
2018 |
eBook |
|
| 14 |
Im, Chang-Hwan |
Computational EEG Analysis |
I08859 |
2018 |
eBook |
|
| 15 |
Lookman, Turab |
Materials Discovery and Design |
I08650 |
2018 |
eBook |
|
| 16 |
Mbiock, Aristide |
Radiation in Enclosures |
I11457 |
2000 |
eBook |
|
| 17 |
Milstein, Grigori Noah |
Stochastic Numerics for Mathematical Physics |
I11424 |
2004 |
eBook |
|
| 18 |
Emmerich, Heike |
The Diffuse Interface Approach in Materials Science |
I11360 |
2003 |
eBook |
|
| 19 |
Krizek, Michal |
Conjugate Gradient Algorithms and Finite Element Methods |
I11205 |
2004 |
eBook |
|
| 20 |
Armfield, Steve |
Computational Fluid Dynamics 2002 |
I11088 |
2003 |
eBook |
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11.
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| Title | Advancement of Shock Capturing Computational Fluid Dynamics Methods : Numerical Flux Functions in Finite Volume Method |
| Author(s) | Kitamura, Keiichi |
| Publication | Singapore, Springer Singapore, 2020. |
| Description | XI, 136 p. 52 illus., 13 illus. in color : online resource |
| Abstract Note | This book offers a compact primer on advanced numerical flux functions in computational fluid dynamics (CFD). It comprehensively introduces readers to methods used at the forefront of compressible flow simulation research. Further, it provides a comparative evaluation of the methods discussed, helping readers select the best numerical flux function for their specific needs. The first two chapters of the book reviews finite volume methods and numerical functions, before discussing issues commonly encountered in connection with each. The third and fourth chapter, respectively, address numerical flux functions for ideal gases and more complex fluid flow cases??? multiphase flows, supercritical fluids and magnetohydrodynamics. In closing, the book highlights methods that provide high levels of accuracy. The concise content provides an overview of recent advances in CFD methods for shockwaves. Further, it presents the author???s insights into the advantages and disadvantages of each method, helping readers implement the numerical methods in their own research |
| ISBN,Price | 9789811590115 |
| Keyword(s) | 1. CLASSICAL MECHANICS
2. Computational Science and Engineering
3. Computer mathematics
4. EBOOK
5. EBOOK - SPRINGER
6. Engineering Fluid Dynamics
7. FLUID MECHANICS
8. Fluid- and Aerodynamics
9. FLUIDS
10. MECHANICS
11. NUMERICAL ANALYSIS
12. Numerical and Computational Physics, Simulation
13. PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I09025 |
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On Shelf |
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12.
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| Title | Computational Biomechanics for Medicine : Solid and Fluid Mechanics for the Benefit of Patients |
| Author(s) | Miller, Karol;Wittek, Adam;Joldes, Grand;Nash, Martyn P;Nielsen, Poul M. F |
| Publication | Cham, Springer International Publishing, 2020. |
| Description | VIII, 200 p. 108 illus., 60 illus. in color : online resource |
| Abstract Note | Computational Biomechanics for Medicine: Solid and fluid mechanics for the benefit of patients contributions and papers from the MICCAI Computational Biomechanics for Medicine Workshop help in conjunction with Medical Image Computing and Computer Assisted Intervention conference (MICCAI 2019) in Shenzhen, China. The content is dedicated to research in the field of methods and applications of computational biomechanics to medical image analysis, image-guided surgery, surgical simulation, surgical intervention planning, disease prognosis and diagnostics, analysis of injury mechanisms, implant and prostheses design, as well as artificial organ design and medical robotics. These proceedings appeal to researchers, students and professionals in the field. |
| ISBN,Price | 9783030424282 |
| Keyword(s) | 1. AUTOMATION
2. Biological systems
3. Biomedical engineering
4. Biomedical Engineering and Bioengineering
5. Computational Science and Engineering
6. Computer mathematics
7. EBOOK
8. EBOOK - SPRINGER
9. Imaging / Radiology
10. Medical and Radiation Physics
11. Medical physics
12. RADIATION
13. Radiology
14. ROBOTICS
15. Robotics and Automation
16. Systems biology
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I09019 |
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On Shelf |
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13.
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| Title | Uncertainty Quantification and Predictive Computational Science : A Foundation for Physical Scientists and Engineers |
| Author(s) | McClarren, Ryan G |
| Publication | Cham, Springer International Publishing, 2018. |
| Description | XVII, 345 p. 141 illus., 99 illus. in color : online resource |
| Abstract Note | This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences.Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying local sensitivity analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in R and python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and first year graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform. Organizes interdisciplinary topics of uncertainty quantification into a single teaching text Reviews the fundamentals of probability and statistics Guides the transition from merely performing calculations to making confident predictions Builds readers??? confidence in the validity of their simulations Illustrates concepts with real-world examples and models from the physical sciences and engineering Includes R and python code, enabling readers to perform the analysis |
| ISBN,Price | 9783319995250 |
| Keyword(s) | 1. APPLIED MATHEMATICS
2. Computational Science and Engineering
3. Computer mathematics
4. COMPUTER SIMULATION
5. EBOOK
6. EBOOK - SPRINGER
7. ENGINEERING MATHEMATICS
8. Mathematical and Computational Engineering
9. Mathematical Applications in the Physical Sciences
10. MATHEMATICAL PHYSICS
11. Numerical and Computational Physics, Simulation
12. PHYSICS
13. Simulation and Modeling
14. Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
15. Statistics??
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I08959 |
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On Shelf |
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14.
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| Title | Computational EEG Analysis : Methods and Applications |
| Author(s) | Im, Chang-Hwan |
| Publication | Singapore, Springer Singapore, 2018. |
| Description | XII, 228 p. 59 illus., 36 illus. in color : online resource |
| Abstract Note | This book introduces and reviews all of the currently available methods being used for computational electroencephalogram (EEG) analysis, from the fundamentals through to the state-of-the-art. The aim of the book is to help biomedical engineers and medical doctors who use EEG to better understand the methods and applications of computational EEG analysis from a single, well-organized resource. Following a brief introduction to the principles of EEG and acquisition techniques, the book is divided into two main sections. The first of these covers analysis methods, beginning with preprocessing, and then describing EEG spectral analysis, event-related potential analysis, source imaging and multimodal neuroimaging, and functional connectivity analysis. The following section covers application of EEG analysis to specific fields, including the diagnosis of psychiatric diseases and neurological disorders, brain-computer interfacing, and social neuroscience. Aimed at practicing medical specialists, engineers, researchers and advanced students, the book features contributions from world-renowned biomedical engineers working across a broad spectrum of computational EEG analysis techniques and EEG applications |
| ISBN,Price | 9789811309083 |
| Keyword(s) | 1. Biomedical engineering
2. Biomedical Engineering and Bioengineering
3. Computational Science and Engineering
4. Computer mathematics
5. EBOOK
6. EBOOK - SPRINGER
7. Imaging / Radiology
8. Medical and Radiation Physics
9. Medical physics
10. Neurology
11. Neurology??
12. RADIATION
13. Radiology
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I08859 |
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On Shelf |
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15.
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| Title | Materials Discovery and Design : By Means of Data Science and Optimal Learning |
| Author(s) | Lookman, Turab;Eidenbenz, Stephan;Alexander, Frank;Barnes, Cris |
| Publication | Cham, Springer International Publishing, 2018. |
| Description | XVI, 256 p. 98 illus., 88 illus. in color : online resource |
| Abstract Note | This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the application of data science to materials problems are sketched. Computational and experimental facilities today generate vast amounts of data at an unprecedented rate. The book gives guidance to discover new knowledge that enables materials innovation to address grand challenges in energy, environment and security, the clearer link needed between the data from these facilities and the theory and underlying science. The role of inference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key to achieving the desired goals of real time analysis and feedback. Thus, the importance of this book lies in emphasizing that the full value of knowledge driven discovery using data can only be realized by integrating statistical and information sciences with materials science, which is increasingly dependent on high throughput and large scale computational and experimental data gathering efforts. This is especially the case as we enter a new era of big data in materials science with the planning of future experimental facilities such as the Linac Coherent Light Source at Stanford (LCLS-II), the European X-ray Free Electron Laser (EXFEL) and MaRIE (Matter Radiation in Extremes), the signature concept facility from Los Alamos National Laboratory. These facilities are expected to generate hundreds of terabytes to several petabytes of in situ spatially and temporally resolved data per sample. The questions that then arise include how we can learn from the data to accelerate the processing and analysis of reconstructed microstructure, rapidly map spatially resolved properties from high throughput data, devise diagnostics for pattern detection, and guide experiments towards desired targeted properties. The authors are an interdisciplinary group of leading experts who bring the excitement of the nascent and rapidly emerging field of materials informatics to the reader. |
| ISBN,Price | 9783319994659 |
| Keyword(s) | 1. Characterization and Evaluation of Materials
2. Computational Science and Engineering
3. Computer mathematics
4. DATA MINING
5. Data Mining and Knowledge Discovery
6. EBOOK
7. EBOOK - SPRINGER
8. Engineering???Materials
9. Materials Engineering
10. MATERIALS SCIENCE
11. NUMERICAL ANALYSIS
12. Numerical and Computational Physics, Simulation
13. PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I08650 |
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On Shelf |
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17.
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| Title | Stochastic Numerics for Mathematical Physics |
| Author(s) | Milstein, Grigori Noah;Tretyakov, Michael V |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 2004. |
| Description | XIX, 596 p : online resource |
| Abstract Note | Stochastic differential equations have many applications in the natural sciences. Besides, the employment of probabilistic representations together with the Monte Carlo technique allows us to reduce solution of multi-dimensional problems for partial differential equations to integration of stochastic equations. This approach leads to powerful computational mathematics that is presented in the treatise. The authors propose many new special schemes, some published here for the first time. In the second part of the book they construct numerical methods for solving complicated problems for partial differential equations occurring in practical applications, both linear and nonlinear. 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, physics, chemistry, and engineering as well as mathematical biology and financial mathematics |
| ISBN,Price | 9783662100639 |
| Keyword(s) | 1. Computational Science and Engineering
2. Computer mathematics
3. EBOOK
4. EBOOK - SPRINGER
5. MATHEMATICAL PHYSICS
6. NUMERICAL ANALYSIS
7. Numerical and Computational Physics, Simulation
8. PHYSICS
9. Physics, general
10. PROBABILITIES
11. Probability Theory and Stochastic Processes
12. Theoretical, Mathematical and Computational Physics
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11424 |
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On Shelf |
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19.
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| Title | Conjugate Gradient Algorithms and Finite Element Methods |
| Author(s) | Krizek, Michal;Neittaanm??ki, Pekka;Glowinski, Roland;Korotov, Sergey |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 2004. |
| Description | XV, 384 p : online resource |
| Abstract Note | The position taken in this collection of pedagogically written essays is that conjugate gradient algorithms and finite element methods complement each other extremely well. Via their combinations practitioners have been able to solve differential equations and multidimensional problems modeled by ordinary or partial differential equations and inequalities, not necessarily linear, optimal control and optimal design being part of these problems. The aim of this book is to present both methods in the context of complicated problems modeled by linear and nonlinear partial differential equations, to provide an in-depth discussion on their implementation aspects. The authors show that conjugate gradient methods and finite element methods apply to the solution of real-life problems. They address graduate students as well as experts in scientific computing |
| ISBN,Price | 9783642185601 |
| Keyword(s) | 1. Computational Intelligence
2. Computational Science and Engineering
3. Computer mathematics
4. EBOOK
5. EBOOK - SPRINGER
6. Fluid- and Aerodynamics
7. FLUIDS
8. Numerical and Computational Physics, Simulation
9. PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11205 |
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On Shelf |
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20.
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| Title | Computational Fluid Dynamics 2002 : Proceedings of the Second International Conference on Computational Fluid Dynamics, ICCFD, Sydney, Australia, 15???19 July 2002 |
| Author(s) | Armfield, Steve;Morgan, P;Srinivas, Karkenahalli |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 2003. |
| Description | XXII, 826 p : online resource |
| Abstract Note | The International Conference on Computational Fluid Dynamics (ICCFD) is the merger of the International Conference on Numerical Methods in Fluid Dynamics (ICNMFD) and the International Symposium on Computational Fluid Dynamics (ISCFD). It is held every two years and brings together physicists, mathematicians and engineers to review and share recent advances in mathematical and computational techniques for modeling fluid dynamics. The proceedings of the 2002 conference held in Sydney, Australia, contain a selection of refereed contributions and are meant to serve as a source of reference for all those interested in the state of the art in computational fluid dynamics |
| ISBN,Price | 9783642593345 |
| Keyword(s) | 1. Computational Science and Engineering
2. Computer mathematics
3. EBOOK
4. EBOOK - SPRINGER
5. Engineering Fluid Dynamics
6. FLUID MECHANICS
7. Fluid- and Aerodynamics
8. FLUIDS
9. Numerical and Computational Physics, Simulation
10. PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11088 |
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On Shelf |
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