Zobrazeno 1 - 10
of 1 461
pro vyhledávání: '"physics informed neural network"'
Publikováno v:
Nuclear Engineering and Technology, Vol 56, Iss 12, Pp 5396-5404 (2024)
For decades, plasma transport simulations in tokamaks have used the finite difference method (FDM), a relatively simple scheme to solve the transport equations, a coupled set of time-dependent partial differential equations. In this FDM approach, typ
Externí odkaz:
https://doaj.org/article/ca50dadc3cbb4d9499251b52ed18d4ec
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract To achieve the desired superheat of molten steel during the continuous casting process, optimization of process parameters such as molten steel temperature in ladle furnace, casting speed, and baking temperature is necessary. Therefore, obta
Externí odkaz:
https://doaj.org/article/c99fe18c972441aaad37aa17967ebe74
Autor:
Hanwen Bi, Thushara D. Abhayapala
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-14 (2024)
Abstract Machine learning and neural networks have advanced numerous research domains, but challenges such as large training data requirements and inconsistent model performance hinder their application in certain scientific problems. To overcome the
Externí odkaz:
https://doaj.org/article/a80b8f4e9c81417d8b5370fa8592f3ba
Publikováno v:
Geothermal Energy, Vol 12, Iss 1, Pp 1-25 (2024)
Abstract Deep learning has gained attention as a potentially powerful technique for modeling natural-state geothermal systems; however, its physical validity and prediction inaccuracy at extrapolation ranges are limiting. This study proposes the use
Externí odkaz:
https://doaj.org/article/98dec23e81004fc1a283719de796a275
Publikováno v:
International Journal of Numerical Methods for Heat & Fluid Flow, 2024, Vol. 34, Issue 8, pp. 2963-2985.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/HFF-11-2023-0709
Publikováno v:
Metrology, Vol 4, Iss 3, Pp 489-505 (2024)
As modern systems become more complex, their control strategy no longer relies only on measurement data from probes; it also requires information from mathematical models for non-measurable places. On the other hand, those mathematical models can lea
Externí odkaz:
https://doaj.org/article/a2e62ec8a78342b7b2e3d0e8561e7325
Autor:
Marco Olivieri, Xenofon Karakonstantis, Mirco Pezzoli, Fabio Antonacci, Augusto Sarti, Efren Fernandez-Grande
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-14 (2024)
Abstract Recent developments in acoustic signal processing have seen the integration of deep learning methodologies, alongside the continued prominence of classical wave expansion-based approaches, particularly in sound field reconstruction. Physics-
Externí odkaz:
https://doaj.org/article/6005aa4b95014b97842bd29c0d30c324
Publikováno v:
Progress in Earth and Planetary Science, Vol 11, Iss 1, Pp 1-9 (2024)
Abstract Earthquake-induced crustal deformation provides valuable insights into the mechanisms of tectonic processes. Dislocation models offer a fundamental framework for comprehending such deformation, and two-dimensional antiplane dislocations are
Externí odkaz:
https://doaj.org/article/be1eacef7ad94ed3af7116247b9dd632
Publikováno v:
Water Research X, Vol 25, Iss , Pp 100266- (2024)
Transitions between free-surface and pressurized flows, known as transient mixed flows, have posed significant challenges in urban drainage systems (UDS), e.g., pipe bursts, road collapses, and geysers. However, traditional mechanistic modeling for m
Externí odkaz:
https://doaj.org/article/59a0f82da1e64f46913c1ba0a604d21d
Publikováno v:
International Journal of Strategic Property Management, Vol 28, Iss 5 (2024)
Effective pricing is important for on-street parking management and proactive parking pricing is an innovative strategy to achieve optimal parking utilization. For proactive parking pricing, accurately predicting parking occupancy and deriving the pr
Externí odkaz:
https://doaj.org/article/59b383a9fec246f5aad8b7801caaf67b