Exergy analyses of aircraft flight systems

Exergy ◽  
2021 ◽  
pp. 515-526
Author(s):  
Ibrahim Dincer ◽  
Marc A. Rosen
2021 ◽  
Author(s):  
Oleg Ivanovich Zavalishin ◽  
Anatoly Nikolaevich Korotonoshko ◽  
Dmitry Alexandrovich Zatuchny ◽  
Yury Grigorievich Shatrakov

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Marcos Paulo Gabriel da Costa e Silva ◽  
Júlio Cesar de Carvalho Miranda

Abstract This work presents exergy analyses applied in four different conceptual second-generation ethanol production processes through a thermochemical route using catalysts based on Molybdenum (P-1), Copper (P-2), and Rhodium (P-3 and P-4), aiming to assess their exergetic efficiencies. The results show that the conceptual processes have satisfactory exergy efficiencies in both cases, when compared among themselves and when compared with other processes reported in literature. The processes’ efficiency for P-1, P-2, P-3 and P-4 were, respectively, 52.4%, 41.4%, 43.7% and 48.9%. The reactors were the sections in which exergy destruction was more significant, due to the exothermic reactions and mixing points (where streams with different temperatures were mixed). Such results show the potential of thermochemical ethanol production, besides opening the possibilities of process improvement. Graphic abstract


Author(s):  
Giorgia Lallai ◽  
Giovanni Loi Zedda ◽  
Célia Martinie ◽  
Philippe Palanque ◽  
Mauro Pisano ◽  
...  

Abstract Training operators to efficiently operate critical systems is a cumbersome and costly activity. A training program aims at modifying operators’ knowledge and skills about the system they will operate. The design, implementation and evaluation of a ‘good’ training program is a complex activity that requires involving multi-disciplinary work from multiple stakeholders. This paper proposes the combined use of task descriptions and augmented reality (AR) technologies to support training activities both for trainees and instructors. AR interactions offer the unique benefit of bringing together the cyber and the physical aspects of an aircraft cockpit, thus providing support to training in this context that cannot be achieved by software tutoring systems. On the instructor side, the LeaFT-MixeR system supports the systematic coverage of planed tasks as well as the constant monitoring of trainee performance. On the trainee side, LeaFT-MixeR provides real-time AR information supporting the identification of objects with which to interact, in order to perform the planned task. The paper presents the engineering principles and their implementation to bring together AR technologies and tool-supported task models. We show how these principles are embedded in LeaFT-MixeR system as well as its application to the training of flight procedures in aircraft cockpits.


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