Sebastian K. Crönert presents a new, automated process that makes it possible to obtain all the fuel properties required for combustion simulation. If necessary, these are then transferred - also automatically - into specially created correlation equations through which they are then made available again at simulation runtime. This method makes it possible to represent even more complex correlations and cross-influences on calculation variables in a resource-optimised way (memory requirements and access time) while maintaining the same accuracy. The procedure is validated using test bench measurement data for the pure fuels anisole and cyclopentanone and their blends with regular petrol (RON95E10). Additional validations include more established synthetic fuels and hydrogen. It is shown that an extraordinarily high prediction quality can be achieved for the model class.
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Sebastian K. Crönert completed his doctorate at the Institute of Automotive Engineering Stuttgart (IFS) at the University of Stuttgart and continues to work there as a research assistant. His work focuses on reaction kinetic investigations of synthetic fuels, hydrogen and ammonia as well as software engineering and model development.
Sebastian K. Crönert presents a new, automated process that makes it possible to obtain all the fuel properties required for combustion simulation. If necessary, these are then transferred - also automatically - into specially created correlation equations through which they are then made available again at simulation runtime. This method makes it possible to represent even more complex correlations and cross-influences on calculation variables in a resource-optimised way (memory requirements and access time) while maintaining the same accuracy. The procedure is validated using test bench measurement data for the pure fuels anisole and cyclopentanone and their blends with regular petrol (RON95E10). Additional validations include more established synthetic fuels and hydrogen. It is shown that an extraordinarily high prediction quality can be achieved for the model class.
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Taschenbuch. Zustand: Neu. A Complete Methodology for the Predictive Simulation of Novel, Single- and Multi-Component Fuel Combustion | Sebastian K. Crönert | Taschenbuch | xl | Englisch | 2023 | Springer VS | EAN 9783658430740 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 127659237
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Taschenbuch. Zustand: Neu. Neuware -Sebastian K. Crönert presents a new, automated process that makes it possible to obtain all the fuel properties required for combustion simulation. If necessary, these are then transferred - also automatically - into specially created correlation equations through which they are then made available again at simulation runtime. This method makes it possible to represent even more complex correlations and cross-influences on calculation variables in a resource-optimised way (memory requirements and access time) while maintaining the same accuracy. The procedure is validated using test bench measurement data for the pure fuels anisole and cyclopentanone and their blends with regular petrol (RON95E10). Additional validations include more established synthetic fuels and hydrogen. It is shown that an extraordinarily high prediction quality can be achieved for the model class.Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 228 pp. Englisch. Artikel-Nr. 9783658430740
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Sebastian K. Crönert presents a new, automated process that makes it possible to obtain all the fuel properties required for combustion simulation. If necessary, these are then transferred - also automatically - into specially created correlation equations through which they are then made available again at simulation runtime. This method makes it possible to represent even more complex correlations and cross-influences on calculation variables in a resource-optimised way (memory requirements and access time) while maintaining the same accuracy. The procedure is validated using test bench measurement data for the pure fuels anisole and cyclopentanone and their blends with regular petrol (RON95E10). Additional validations include more established synthetic fuels and hydrogen. It is shown that an extraordinarily high prediction quality can be achieved for the model class. Artikel-Nr. 9783658430740
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