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Author: Wing Kam Liu
Publisher: Springer Nature
ISBN: 3030878325
Category : Technology & Engineering
Languages : en
Pages : 287
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Book Description
This book introduces Mechanistic Data Science (MDS) as a structured methodology for combining data science tools with mathematical scientific principles (i.e., “mechanistic” principles) to solve intractable problems. Traditional data science methodologies require copious quantities of data to show a reliable pattern, but the amount of required data can be greatly reduced by considering the mathematical science principles. MDS is presented here in six easy-to-follow modules: 1) Multimodal data generation and collection, 2) extraction of mechanistic features, 3) knowledge-driven dimension reduction, 4) reduced order surrogate models, 5) deep learning for regression and classification, and 6) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems as well as real-life problems. This book is written in a spectral style and is ideal as an entry level textbook for engineering and data science undergraduate and graduate students, practicing scientists and engineers, as well as STEM (Science, Technology, Engineering, Mathematics) high school students and teachers.
Author: Wing Kam Liu
Publisher: Springer Nature
ISBN: 3030878325
Category : Technology & Engineering
Languages : en
Pages : 287
Get Book Here
Book Description
This book introduces Mechanistic Data Science (MDS) as a structured methodology for combining data science tools with mathematical scientific principles (i.e., “mechanistic” principles) to solve intractable problems. Traditional data science methodologies require copious quantities of data to show a reliable pattern, but the amount of required data can be greatly reduced by considering the mathematical science principles. MDS is presented here in six easy-to-follow modules: 1) Multimodal data generation and collection, 2) extraction of mechanistic features, 3) knowledge-driven dimension reduction, 4) reduced order surrogate models, 5) deep learning for regression and classification, and 6) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems as well as real-life problems. This book is written in a spectral style and is ideal as an entry level textbook for engineering and data science undergraduate and graduate students, practicing scientists and engineers, as well as STEM (Science, Technology, Engineering, Mathematics) high school students and teachers.
Author:
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Category : Mechanical engineering
Languages : en
Pages : 506
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Book Description
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Category : Engineering
Languages : en
Pages : 696
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Book Description
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Category : Engineering
Languages : en
Pages : 876
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Book Description
Author:
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ISBN:
Category : Engineering
Languages : en
Pages : 500
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Book Description
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Category : Engineering
Languages : en
Pages : 1246
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Book Description
Author: Alex Kenan
Publisher: Alex Kenan
ISBN: 1736060600
Category : Computers
Languages : en
Pages : 210
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Book Description
The traditional computer science courses for engineering focus on the fundamentals of programming without demonstrating the wide array of practical applications for fields outside of computer science. Thus, the mindset of “Java/Python is for computer science people or programmers, and MATLAB is for engineering” develops. MATLAB tends to dominate the engineering space because it is viewed as a batteries-included software kit that is focused on functional programming. Everything in MATLAB is some sort of array, and it lends itself to engineering integration with its toolkits like Simulink and other add-ins. The downside of MATLAB is that it is proprietary software, the license is expensive to purchase, and it is more limited than Python for doing tasks besides calculating or data capturing. This book is about the Python programming language. Specifically, it is about Python in the context of mechanical and aerospace engineering. Did you know that Python can be used to model a satellite orbiting the Earth? You can find the completed programs and a very helpful 595 page NSA Python tutorial at the book’s GitHub page at https://www.github.com/alexkenan/pymae. Read more about the book, including a sample part of Chapter 5, at https://pymae.github.io
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Category : Cement
Languages : en
Pages : 406
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Book Description
Author: José Machado
Publisher: Springer Nature
ISBN: 3030791653
Category : Technology & Engineering
Languages : en
Pages : 486
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Book Description
This book covers a variety of topics in the field of mechanical engineering, with a special focus on methods and technologies for modeling, simulation, and design of mechanical systems. Based on a set of papers presented at the 1st International Conference “Innovation in Engineering”, ICIE, held in Guimarães, Portugal, on June 28–30, 2021, it focuses on innovation in mechanical engineering, spanning from engineering design and testing of medical devices, evaluation of new materials and composites for different industrial applications, fatigue and stress analysis of mechanical structures, and application of new tools such as 3D printing, CAE 3D models, and decision support systems. This book, which belongs to a three-volume set, provides engineering researchers and professionals with extensive and timely information on new technologies and developments in the field of mechanical engineering and materials.
Author: Arpith Siddaiah
Publisher: Academic Press
ISBN: 0128189177
Category : Science
Languages : en
Pages : 234
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Book Description
Tribocorrosion: Fundamentals, Methods, and Materials provides a balanced coverage of recent advancements in both experimental and computational areas of tribocorrosion, covering the basic concepts of tribology and electrochemistry, as well as testing set-ups, protocols, electrochemical methods, and more. It outlines experimental methods, demonstrating the different effects of material loss due to mechanical and electrochemical actions and looks at their effects in applied automotive, aerospace and biomedical settings. Standard testing protocols, tribocorrosion mechanisms in sliding contacts, and modeling and simulation techniques are all covered at length, as is bio-tribocorrosion and the best ways to prevent it. - Provides a complete overview of tribocorrosion testing, experimentation and modeling methods that in turn empower safer, environmentally-friendlier and cost-saving applications - Balances experimental and computational methods, thus encouraging readers to define and develop experimental and investigative techniques specific to their tribo-system of interest - Covers tribocorrosion behavior in passive and non-passive metals and alloys, coatings, modified surfaces, metal matrix composites, and more
