Deep learning-based forward modeling and inversion techniques for computational physics problems / Yinpeng Wang, Qiang Ren.
| Author/creator | Wang, Yinpeng, 1999- |
| Other author | Ren, Qiang (Associate professor) |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton : CRC Press, Taylor & Francis Group, 2024. |
| Description | 1 online resource |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Subjects |
| Abstract | "This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems. Pursuing a holistic perspective, the book includes the following areas. The first chapter discusses the basic DL frameworks. Then, the steady heat conduction problem is solved by the classical U-net in Chapter 2, involving both the passive and active cases. Afterwards, the sophisticated heat flux on a curved surface is reconstructed by the presented Conv-LSTM, exhibiting high accuracy and efficiency. Besides, the electromagnetic parameters of complex medium such as the permittivity and conductivity are retrieved by a cascaded framework in Chapter 4. Additionally, a physics-informed DL structure along with a nonlinear mapping module are employed to obtain the space/temperature/time-related thermal conductivity via the transient temperature in Chapter 5. Finally, in Chapter 6, a series of the latest advanced frameworks and the corresponding physics applications are introduced. As deep learning techniques are experiencing vigorous development in computational physics, more people desire related reading materials. This book is intended for graduate students, professional practitioners, and researchers who are interested in DL for computational physics"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Source of description | Description based on print version record and CIP data provided by publisher. |
| Issued in other form | Print version: Wang, Yinpeng, 1999- Deep learning-based forward modeling and inversion techniques for computational physics problems First edition. Boca Raton : CRC Press, Taylor & Francis Group, 2024 9781032502984 |
| Genre/form | Electronic books. |
| LCCN | 2022060812 |
| ISBN | 9781003397830 (ebook) |
| ISBN | (hardcover) |
| ISBN | (paperback) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |