- Opin vísindi
- →
- Browsing by Author
JavaScript is disabled for your browser. Some features of this site may not work without it.
Browsing by Author "Riedel, Morris"
Now showing items 1-8 of 8
-
The capability of recurrent neural networks to predict turbulence flow via spatiotemporal features (IEEE, 2022-07-06)This study presents a deep learning (DL) neural network hybrid data-driven method that is able to predict turbulence flow velocity field. Recently many studies have reported the application of recurrent neural network (RNN) methods, particularly the ... -
(Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag, 2022-01-22)
-
(MDPI AG, 2022-02-21)This paper evaluates the photovoltaic (PV) module operating temperature’s relation to efficiency via a numerical heat transfer model. The literature reports that higher PV module operating temperatures impact PV module efficiency. There are dozens of ...
-
(ParCFD2022, 2022-05-25)This study aimed to employ artificial intelligence capability and computing scalability to predict the velocity field of the straining turbulence flow. Rotating impellers in a box have generated the turbulence, subsequently subjected to an axisymmetric ...
-
(MDPI AG, 2023-05-19)Since the stagnation point is subject to straining motion, this 3D experiment is an effort to simulate the stagnation plane, which applies to studying the particle erosion in rotary machine blades, such as wind turbines, gas turbines, and compressors. ...
-
(2021-11-24)In this study, recorded empirical data were applied with a practical approach to investigate the optimal tilt angle of the flat plate collectors facing south for a long period in Tehran, Iran. The data included 20 years of recorded average total radiation ...
-
(Crimson Publishers, 2022-02-23)This study aims to consider the Nominal Operating Cell Temperature (NOCT) model for the photovoltaic (PV) module by adding the wind effect via experiment equation. The resulting model presents a linear wind convection heat transfer equation; the PV ...
-
(2024-01-01)In plant science, it is an established method to obtain structural parameters of crops using image analysis. In recent years, deep learning techniques have improved the underlying processes significantly. However, since data acquisition is time and ...
Now showing items 1-8 of 8