Approaching machine learning problems in computational fluid dynamics and computer aided engineering applications: A Monograph for Beginners
Product ID: 618348455
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This is not a traditional book. This is a monograph; a practical guide and crash- course to enable mechanical and aerospace engineers to complete machine learning projects on simulation data, from start to finish. Read More: 20 reviews on LinkedIn in first 2 weeks of launch: https://tinyurl.com/JustinHodges777 Table of Contents shown on desertcart page in web browser Who this book is for: If you are interested in ML for CFD/FEA/CAE, it's probably a fit for you. This is an abstraction of experiences into a practical guide to get CFD/CAE practitioners more comfortable in machine learning projects. After hundreds of requests for support, I felt the conviction to set aside my nights for 6 months and produce this book as a more scalable means to help. This book has a lot of (easy to understand) code (not shareable on Github). There is an abundance of resources that cover theoretical knowledge of machine learning in ‘the mainstream’, but relatively little by comparison for CAE applications (especially few that are hands-on). My hope is that the reader already has some (very minimal) theoretical knowledge when they pick this book up. There will be some explanation on the algorithms with examples (in Python), and some degree of surveying/summarizing popular ones, but the primary focus is how and what you should do to solve machine learning problems. This is what I refer to as the pipeline of steps from start to finish in a machine learning project, which seems to have a steep learning curve (my motivation for writing this book). This book will also share my recommended learning pathway for CFD/CAE engineers to develop their AI/ML skills and portfolios and is great for beginners. I am a fan of the ‘code along’ approach and take that to heart in this book. I recommend reading the book while logged into a computer where you can code. "As an AI researcher and engineer; this book must be a daily handbook for preparing a fast-changing, data-driven industry innovation for me and my collogues" - Seungkyun Hong, AI Engineering Leader @MZC, PhD in Computer Science "The book is very well structured, containing informative explanations, especially for beginners in the field. It covers the main steps of ML projects for CFD and CEA applications with some helpful examples" - Dr. Charbel Habchi, Mechanics and Thermal Hydraulics Analysis Engineer, R&D, Framatome "I believe that my long time friend and colleague Justin Hodges, PhD has made a significant contribution in this area. No wonder it is already a best seller on desertcart." - Dr. Shinjan Ghosh, Research Scientist, Siemens "This is the perfect guide to integrating AI and ML into your CAE or CFD simulations with Justin Hodges latest book, tailored for CAE engineering looking to expand their skills" - Rajat Walia, CFD Engineer (Aero Thermal), Mercedes-Benz Research and Development About the Author: While I grew up in a turbomachinery lab characterizing heat transfer, fluid mechanics, and turbulence in gas turbine secondary flow systems in graduate school, I fell in love with artificial intelligence in 2017 working on a project that combined computational fluid dynamics simulations and machine learning during an internship with the Siemens Healthineers in Princeton NJ. Ever since, I have sought to maintain my career direction (mechanical and aerospace engineering applications) but incorporate machine learning and data science as a means to augment our numerical methods in engineering. Review: Clear and useful - This book maybe the best one I’ve ever read about how to apply AI/ML techniques to computer aided engineering. Like the author said, it’s not a book about the theory of machine learning, it’s about how. The book explains the process and steps to make machine learning useful for CAE engineers. Highly recommend reading this book! Review: Code along book provides practical know-how to start an AI/ML project for CFD/CAE - The book is good for instructors and students with limited AI/ML experience, offering guidance on applying these techniques to CFD and CAE applications. This is a code-along book that eventually makes it possible for people who have CFD data at their disposal and use it for their projects. I hope that the next edition will provide color images and more improvements.
| Best Sellers Rank | #1,159,937 in Books ( See Top 100 in Books ) #70 in Aerodynamics (Books) #117 in Fluid Dynamics (Books) #147 in Computer Networks |
| Customer Reviews | 4.2 out of 5 stars 82 Reviews |
Y**A
Clear and useful
This book maybe the best one I’ve ever read about how to apply AI/ML techniques to computer aided engineering. Like the author said, it’s not a book about the theory of machine learning, it’s about how. The book explains the process and steps to make machine learning useful for CAE engineers. Highly recommend reading this book!
P**A
Code along book provides practical know-how to start an AI/ML project for CFD/CAE
The book is good for instructors and students with limited AI/ML experience, offering guidance on applying these techniques to CFD and CAE applications. This is a code-along book that eventually makes it possible for people who have CFD data at their disposal and use it for their projects. I hope that the next edition will provide color images and more improvements.
A**I
Very generic
Very generic handbook. There is ton of similar content available for free on the web. Quality of printing is low and font is tiny.
A**R
A good read for new and experienced engineers in aerospace optimization.
The book is a very plainly stated literal description of how ML works in aerospace. It's written in a way that is intentionally easy to grasp. But it is also a window into the authors own understanding of ML. So, if you are just learning, or you want to learn more from other experts in your field, the books is worth the money either way. I had never bought a print on demand book before either, but the book showed up in 2 days, and the printing looks good.
J**F
AI/ML is everwhere - but it doesn't just magically happen for CAE
I've been in the CAE space for 25 years. AI/ML stands to shake up the industry more than any other previous revolution. We hear about it on TV applied to all sorts of things. This book brings it home for CAE/CFD. It's a great resource for anyone in the field wanting to get started with AI/ML. While I'm not technical enough to understand all the coding involved, Hodges does a great job describing the important themes that need to be considered for a successful application of these methods for anyone.
A**Y
perfect gateway introduction to the future of modeling and simulation
An excellent practical introduction to machine learning algorithms, in this case applied to CFD. Essential reading for any modeling and simulation engineer looking to broaden his or her skills for the future. Trust me (as a practicing engineer with almost 20 years of modeling and simulation experience in the medical device industry) these techniques will be vitally important to this field's future. This book is a perfect introduction to this subject.
V**U
Refreshing introduction to the field
The topics are very refreshing. If you are someone who already has a strong background in data science and machine learning, you can skim through the first couple of chapters and focus more on the later ones. The only drawback is that the images are not in color, which makes it difficult to understand certain sections of the book. The explanations and analogies are great, and the resources and references mentioned in this book are extremely valuable.
J**W
Just Technical Enough!
I thought the conceopts were well organized, and the data was presented clearly. There were even code snippets, and other specific details that I did not expect! The reader should already have experience in CFD (in my case, Fluent), as well as an introductory level and understanding of the purpose of incorporating AI/ML into their workflow. It's such a new and exciting topic in our field, I hope there is a sequel soon!
M**Y
A great resource to understand machine learning
The book is a great introduction to the subject of AI for engineers
A**O
Colours are not present in CFD images and plots
Colours are not present in CFD images and plots. It causes misinterpretation of the informations.
R**A
Disapointed
It is a very basic book. Shows some concepts and make some links with CFD.
A**R
At best a draft of a book! not worth the money!
There are some useful information in this book hence why I did not give it a single star. But to me it is absolutely unacceptable the author would think it is at an appropriate standard for publishing. At best this is an unedited first draft! The grammar is terrible, the writing style is hard to follow with lots of long sentences and repetitions. The explanations are vague in many places. The images are of very poor quality, very grainy, many with text that is unreadable. And I mean black and white for a book on CFD? that's laughable, especially when the author specifically mentions colors on the figure. Shame this could have been an interesting book. but I'll be sending it back!
V**N
A great book to learn about ML in CAE
As a CFD engineer, I bought this book to get a deeper understanding on the application of ML to fluid mechanics problems. This book is full of relevant examples and easy to follow, while providing the reader with a lot of references for further research. I recommend it :)
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