Data-Driven Evolutionary Modeling in Materials Technology, Nirupam Chakraborti
Автор: V.K. Jain Название: Micromanufacturing Processes ISBN: 1138076422 ISBN-13(EAN): 9781138076426 Издательство: Taylor&Francis Рейтинг: Цена: 64300.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Increased demand for and developments in micromanufacturing have created a need for a resource that covers both the science and technology of this rapidly growing area. With contributions from eminent professors and researchers actively engaged in teaching, research, and development, Micromanufacturing Processes details the basic principles, tools, techniques, and latest advances in micromanufacturing processes. It includes coverage of measurement techniques and research trends as well as a large number of cross-references, making it useful to the students and researchers alike.
The book outlines the challenges faced not only in micromanufacturing but also in meso- and nanomanufacturing, exploring topics such as micromachining, micro welding, microforming, micromolding, nanofinishing and micro-/nano-metrology. It includes examples that demonstrate the capabilities of fabricating micro- / nano-products and micro- / nano-features on the macro and micro products. The text also discusses nanofinishing techniques giving surface finish in the domain of sub-nano level, micro welding techniques, namely, laser beam micro welding, electron beam micro welding, micro / nano patterning in large quantities, and micro / nano metrology principles and equipments. It goes on to describe devices such as nano spring, micro mixer, micro cantilever, to name just a few.
Unique in its level of coverage, the book highlights new challenges in manufacturing and covers several different types of micromanufacturing processes, such as micromachining, microforming, microcasting, microjoining, nanofinishing, and micrometrology. The level of details, extensive references, figures, and diagrams make the book a reference that will become the standard for this field.
Автор: J.-P. Caliste; A. Truyol; Jack H. Westbrook Название: Thermodynamic Modeling and Materials Data Engineering ISBN: 3642722091 ISBN-13(EAN): 9783642722097 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Updated contributions inspired by Symposium discussions and selections from other CODATA workshops concerning material properties data and Computer Aided Design combine to highlight the complexity of material data issues on experimental, theoretical and simulation levels Articles were selected for their pertinence in three areas.
Автор: V. I. Naoumov, V. G. Krioukov, A. L. Abdullin, A. Название: Chemical Kinetics in Combustion and Reactive Flows: Modeling Tools and Applications ISBN: 1108427049 ISBN-13(EAN): 9781108427043 Издательство: Cambridge Academ Рейтинг: Цена: 141510.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduces advanced mathematical tools for the modeling, simulation, and analysis of chemical non-equilibrium phenomena in combustion and flows, following a detailed explanation of the basics of thermodynamics and chemical kinetics of reactive mixtures. Researchers, practitioners, lecturers, and graduate students will find this work valuable.
Автор: Wang, Yan Название: Uncertainty Quantification In Multiscale Materials Modeling ISBN: 0081029411 ISBN-13(EAN): 9780081029411 Издательство: Elsevier Science Рейтинг: Цена: 314410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.
Автор: Daniel Ashlock Название: Evolutionary Computation for Modeling and Optimization ISBN: 1441919694 ISBN-13(EAN): 9781441919694 Издательство: Springer Рейтинг: Цена: 67030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets.
Lots of applications and test problems, including a biotechnology chapter.
Автор: Li, Juan Название: Decomposition-based evolutionary optimization in complex environments / ISBN: 9811218986 ISBN-13(EAN): 9789811218989 Издательство: World Scientific Publishing Рейтинг: Цена: 95040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Multi-objective optimization problems (MOPs) and uncertain optimization problems (UOPs) which widely exist in real life are challengeable problems in the fields of decision making, system designing, and scheduling, amongst others. Decomposition exploits the ideas of aEURO~making things simpleaEURO (TM) and aEURO~divide and conqueraEURO (TM) to transform a complex problem into a series of simple ones with the aim of reducing the computational complexity. In order to tackle the abovementioned two types of complicated optimization problems, this book introduces the decomposition strategy and conducts a systematic study to perfect the usage of decomposition in the field of multi-objective optimization, and extend the usage of decomposition in the field of uncertain optimization.
Автор: Kutz J Nathan Название: Data-Driven Modeling & Scientific Computation ISBN: 0199660344 ISBN-13(EAN): 9780199660346 Издательство: Oxford Academ Рейтинг: Цена: 49620.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies.
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