Emulation of Complex Fluid Flows: Projection-Based Reduced-Order Modeling and Machine Learning (Machine Learning in Science, Technology, Engineering and Mathematics, 1)
Language: English
Published by De Gruyter, 2025
- Hardcover
- New
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
AbeBooks seller since January 19, 2007
Condition: New
£ 172.84
Quantity: 3 available
Add to basketSeller Inventory # 409666986
- Title
- Emulation of Complex Fluid Flows: Projection-Based Reduced-Order Modeling and Machine Learning (Machine Learning in Science, Technology, Engineering and Mathematics, 1)
- Author
- Wang, Xingjian; Yang, Vigor
- Publisher
- De Gruyter
- Publication year
- 2025
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3111631354
- ISBN 13
- 9783111631356
While artificial intelligence has made significant strides in imaging and natural language processing, its utilization in engineering science remains relatively new. This book aims to introduce machine learning techniques to facilitate the emulation of complex fluid flows. The work focuses on projection-based reduced-order models (ROMs) that condense high-dimensional data into a low-dimensional subspace by leveraging principal components. Techniques like proper orthogonal decomposition (POD) and convolutional autoencoder (CAE) are utilized to configure this subspace, establishing a functional mapping between input parameters and solution fields. The applicability of POD-based ROMs for spatial and spatiotemporal problems are explored across various engineering scenarios, including flow past a cylinder, supercritical turbulent flows, and hydrogen-blended combustion. To capture intricate dynamics, common POD, kernel-smoothed POD, and common kernel-smoothed POD methods are developed in sequence. Additionally, the effectiveness of POD and CAE in capturing nonlinear features are compared. This book is designed to benefit graduate students and researchers interested in the intersection of data and engineering sciences.
"Synopsis" may belong to another edition of this title.
About the Author
Prof. Xingjian Wang received his Ph.D. from the Georgia Institute of Technology in 2016 and is currently associate professor in the Department of Energy and Power at Tsinghua University. He previously served as assistant professor in the Department of Mechanical and Civil Engineering at the Florida Institute of Technology. His research focuses on the interdisciplinary study of engineering science and machine learning, particularly in developing reduced-order models and analyzing complex fluid flows and combustion under extreme conditions. Dr. Wang has received multiple awards, including the 2020 iLASS Asia Best Paper Award and the 2019 SPES Award from the American Statistical Society. His contributions to the field are well-recognized, with several articles featured as Editor’s Picks and highlighted on the front cover of Physics of Fluids.
Prof. Vigor Yang is professor of aerospace engineering and a faculty member of the Machine Learning PhD Program at the Georgia Institute of Technology. He is also the founding director of Georgia Tech‘s James C. Wu Laboratory of Artificial Intelligence in Technology, Engineering, and Computing (ArTEC). Prof. Yang's research lies at the interface between engineering and data sciences, driving forward the integration of artificial intelligence and engineering disciplines for cutting-edge solutions. His extensive body of work includes advancements in thermal-fluid dynamics and propulsion, with a strong emphasis on leveraging machine learning to enhance these areas. He is a member of the U.S. National Academy of Engineering, an academician of the Academia Sinica, and a foreign member of the Chinese Academy of Engineering and the Indian National Academy of Engineering
"About the title" may belong to another edition of this title.
Majestic Books
Hounslow, United Kingdom
AbeBooks seller since January 19, 2007
Shipping rates from United Kingdom to U.S.A.
| Item | 14 to 45 business days | 5 to 10 business days |
|---|---|---|
| First item | £ 6.50 | £ 9.85 |
Payment methods
Store description
Specialty
Art, Economics, Buddhism, Religion, Sociology, PaintingSeller's business information
BOOKS AND PERIODICALS AGENCY LTD
90 Barnet Gate Lane
Barnet, United Kingdom EN5 2AX
Terms of sale
Returns accepted if you are not satisfied with the Service or Book.
Right of withdrawal
If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.
Information regarding the right of withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).
We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.
We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.
We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.
We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.
You shall send back the goods or hand them over to Majestic Books, Hounslow, United Kingdom, without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.
Exceptions to the right of withdrawal
The right of withdrawal does not apply to:
- The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
- The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.
Shipping terms
Best packaging and fast delivery