Mechanical Engineering News
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Total Pages | : 182 |
Release | : 1994 |
Genre | : Mechanical engineering |
ISBN | : |
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Author | : |
Publisher | : |
Total Pages | : 182 |
Release | : 1994 |
Genre | : Mechanical engineering |
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Total Pages | : 506 |
Release | : 1974 |
Genre | : Mechanical engineering |
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Author | : American Society of Mechanical Engineers |
Publisher | : |
Total Pages | : 1252 |
Release | : 1904 |
Genre | : Mechanical engineering |
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Vols. 2, 4-11, 62-68 include the Society's Membership list; v. 55-80 include the Journal of applied mechanics (also issued separately) as contributions from the Society's Applied Mechanics Division.
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Total Pages | : 940 |
Release | : 1906 |
Genre | : Engineering |
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Total Pages | : |
Release | : 1987 |
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Author | : Wing Kam Liu |
Publisher | : Springer Nature |
Total Pages | : 287 |
Release | : 2022-01-01 |
Genre | : Technology & Engineering |
ISBN | : 3030878325 |
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.
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Total Pages | : 876 |
Release | : 1892 |
Genre | : Engineering |
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Total Pages | : 500 |
Release | : 1907 |
Genre | : Engineering |
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Total Pages | : |
Release | : 1985 |
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Author | : Alex Kenan |
Publisher | : Alex Kenan |
Total Pages | : 210 |
Release | : 2021-01-01 |
Genre | : Computers |
ISBN | : 1736060600 |
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