| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Neural network-based prediction and control of air flow in a data center |
| Autor/-in: | De Lorenzi, Flavio Vömel, Christof |
| DOI: | 10.1115/1.4005605 |
| Erschienen in: | Journal of Thermal Science and Engineering Applications |
| Band(Heft): | 4 |
| Heft: | 2 |
| Seite(n): | 021005 |
| Erscheinungsdatum: | 2012 |
| Verlag / Hrsg. Institution: | The American Society of Mechanical Engineers |
| ISSN: | 1948-5085 1948-5093 |
| Sprache: | Englisch |
| Fachgebiet (DDC): | 690: Hausbau und Bauhandwerk |
| Zusammenfassung: | As modern data centers continue to grow in power, size, and numbers, there is an urgent need to reduce energy consumption by optimized cooling strategies. In this paper, we present a neural network-based prediction of air flow in a data center that is cooled through perforated floor tiles. With a significantly smaller execution time than computational fluid dynamics, it predicts in real-time server inlet temperatures and can detect whether prevalent air flow cools the servers sufficiently to guarantee safe operation. Combined with a cooling system model, we obtain a temperature and air flow control algorithm that is fast and accurate enough to find an optimal operating point of the data center cooling system in real-time. We also demonstrate the performance of our algorithm on a reference data center and show that energy consumption can be reduced by up to 30%. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/13434 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Angewandte Mathematik und Physik (IAMP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
Es gibt keine Dateien zu dieser Ressource.
Zur Langanzeige
De Lorenzi, F., & Vömel, C. (2012). Neural network-based prediction and control of air flow in a data center. Journal of Thermal Science and Engineering Applications, 4(2), 21005. https://doi.org/10.1115/1.4005605
De Lorenzi, F. and Vömel, C. (2012) ‘Neural network-based prediction and control of air flow in a data center’, Journal of Thermal Science and Engineering Applications, 4(2), p. 021005. Available at: https://doi.org/10.1115/1.4005605.
F. De Lorenzi and C. Vömel, “Neural network-based prediction and control of air flow in a data center,” Journal of Thermal Science and Engineering Applications, vol. 4, no. 2, p. 021005, 2012, doi: 10.1115/1.4005605.
DE LORENZI, Flavio und Christof VÖMEL, 2012. Neural network-based prediction and control of air flow in a data center. Journal of Thermal Science and Engineering Applications. 2012. Bd. 4, Nr. 2, S. 021005. DOI 10.1115/1.4005605
De Lorenzi, Flavio, and Christof Vömel. 2012. “Neural Network-Based Prediction and Control of Air Flow in a Data Center.” Journal of Thermal Science and Engineering Applications 4 (2): 21005. https://doi.org/10.1115/1.4005605.
De Lorenzi, Flavio, and Christof Vömel. “Neural Network-Based Prediction and Control of Air Flow in a Data Center.” Journal of Thermal Science and Engineering Applications, vol. 4, no. 2, 2012, p. 21005, https://doi.org/10.1115/1.4005605.
Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.