A simulation of aircraft fuel management system

Jiménez, Juan Francisco; Girón-Sierra, José M.; Insaurralde, Carlos C.; Seminario, M.A.

doi:10.1016/j.simpat.2007.01.007

Cited by 29 publications

(11 citation statements)

References 2 publications

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“…Para un determinado plan le corresponderá una carga mínima obligatoria. Básicamente esta carga, además de tener en cuenta la cantidad de combustible que previsiblemente consumirán los motores (más un margen de seguridad), también contiene, o bien la cantidad de combustible necesaria para mantenerse a la espera en hipódromo durante un determinado tiempo antes de tener permiso para aterrizar en el destino, o bien la cantidad necesaria para aterrizar en el aeropuerto alternativo si no es posible hacerlo en el de destino [3].…”

Section: Descripción Del Problemaunclassified

Repostaje en tierra de un avión mediante algoritmos genéticos

Plaza¹,

Santos²

2020

XXXVIII Jornadas De Automática: Gijón, 6, 7, Y 8 De Septiembre De 2017

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aeronave comercial. En concreto se ha abordado el repostaje de la aeronave antes de un vuelo. El repostaje en tierra consiste en decidir la cantidad de combustible que se dispondrá en cada depósito atendiendo a criterios de seguridad, estabilidad del avión y eficiencia energética. Para ello se define un problema de optimización cuya función de coste nace del conocimiento específico de los factores que influyen en una aeronave que tiene relación con el posicionamiento del combustible. Después su resolución se realiza mediante Algoritmos Genéticos. Los resultados obtenidos en simulación mejoran la solución manual estándar que se viene aplicando.

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Section: Descripción Del Problemaunclassified

Repostaje en tierra de un avión mediante algoritmos genéticos

Plaza¹,

Santos²

2020

XXXVIII Jornadas De Automática: Gijón, 6, 7, Y 8 De Septiembre De 2017

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“…We do not want to force modelers to use overly detailed models of physical phenomena that are not central to their design problem, and such discrete models provide adequate abstractions. [31] to construct similar models of aircraft fuel systems.) In this MoC, components (actors) have input and output ports, in contrast to equational modeling tools such as Modelica [23], where ports are neither inputs nor outputs.…”

Section: Modeling Challengesmentioning

confidence: 99%

Addressing Modeling Challenges in Cyber-Physical Systems

Derler¹,

Lee²,

Sangiovanni‐Vincentelli³

2011

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Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. This paper focuses on the challenges of modeling cyber-physical systems that arise from the intrinsic heterogeneity, concurrency, and sensitivity to timing of such systems. It uses a portion of an aircraft vehicle management systems (VMS), specifically the fuel management subsystem, to illustrate the challenges and then discusses technologies that at least partially address the challenges. Specific technologies described include hybrid system modeling and simulation, concurrent and heterogeneous models of computation, the use of domain-specific ontologies to enhance modularity, and the joint modeling of functionality and implementation architectures. Copyright © 2011, by the author(s).All rights reserved.Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. AcknowledgementThis work was supported in part by the Center for Hybrid and Embedded Software Systems (CHESS) at UC Berkeley, which receives support from the National Science Foundation (NSF awards #0720882 (CSR-EHS: PRET), #0931843 (ActionWebs), and #1035672 (CSR-CPS Ptides)), the U. S. Army Research Office (ARO #W911NF-07-2-0019), the U. Abstract This paper focuses on the challenges of modeling cyber-physical systems that arise from the intrinsic heterogeneity, concurrency, and sensitivity to timing of such systems. It uses a portion of an aircraft vehicle management systems (VMS), specifically the fuel management subsystem, to illustrate the challenges, and then discusses technologies that at least partially address the challenges. Specific technologies described include hybrid system modeling and simulation, concurrent and heterogeneous models of computation, the use of domain-specific ontologies to enhance modularity, and the joint modeling of functionality and implementation architectures. 1

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“…It also includes the fuel balance between the tail tank, and the mid tank in order to get a better Center of Gravity (CoG) which improves the fuel consumption [60].…”

Section: Airplane Simulationmentioning

confidence: 99%

Model-Based Development Framework for distributed embedded control of aircraft fuel systems

Insaurralde

Seminario

Jiménez

et al. 2010

29th Digital Avionics Systems Conference

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Model-based approaches for control software architectures reduce risks and costs in the development process of embedded systems. They allow seeing the system-wide analysis impacts of architectural choices, and increases confidence through early verification/validation of the model assumptions. This representation technique is well suitable for a European project named "SmartFuel" which proposes a distributed control strategy for aircraft fuel systems. It is an embedded system with open architecture which allows aircraft-parts manufactures to develop their own commercial offthe-shelf (COTS) fuel components, i.e. networked mechatronic devices. Within the first SmartFuel phase, the verification and validation of the above avionics system has been successfully carried out through prototype-based simulations. The second project phase aims to develop models and tools to analyze, synthesize, and pre-verify/pre-validate by model simulation the avionics system architecture at early development stages. The results expected from the modeling (i.e. prediction of key system features and the automatic code generation for the COTS components) benefit to the development process. This paper presents a Model-Based Development Framework (MBDF) to deal with the avionics system specifications, and the creation of embedded system models. In addition, the experimental outcomes when the MBDF is applied to two case studies (helicopter and airplane fuel systems) are presented.

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A simulation of aircraft fuel management system

Cited by 29 publications

References 2 publications

Repostaje en tierra de un avión mediante algoritmos genéticos

Repostaje en tierra de un avión mediante algoritmos genéticos

Addressing Modeling Challenges in Cyber-Physical Systems

Model-Based Development Framework for distributed embedded control of aircraft fuel systems

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