18 resultados para Flow control
Resumo:
Como apoyo al Subsistema ECM tradicional de los sistemas de Guerra Electrónica, surge el Equipo de Seguimiento en Elevación cuyo fin es la búsqueda de la amenaza en elevación. Ante la necesidad de un mayor número de líneas entre los bloques internos de este Equipo de Seguimiento, se hace necesario el diseño de una Tarjeta de Interfaz y Control. La tarjeta se ocupará de realizar el control de datos y flujo de señales de módulos RF que componen el Equipo, haciendo de interfaz entre las Tarjetas Procesadoras y Digitalizadoras, así como entre la Tarjeta de Proceso y el Bloque de Recepción. Una vez que se haya realizado el análisis de la necesidad de controlar estas señales, estudiado las especificaciones y los requisitos funcionales del Sistema, se procederá a implementar el diseño hardware y desarrollo firmware de la Tarjeta de Interfaz y Control de un Equipo de Seguimiento en Elevación para un Subsistema ECM, que constituye el objetivo de este PFC. ABSTRACT. In order to find a threat on elevation, and as a support on the basic ECM subsystems of E-war systems, the Elevation Tracking Equipment appears. To the need of a bigger number of lines between inside blocks of this Tracking Equipment, the design of an Interface and Control Board is needed. This board will deal with the data control and with the flow of RF modules signals that set up the Equipment, and will also work as an interface between the Processing and Digitalizing Board, as well as between the Process Board and the Reception Block. Once the signal control necessity analysis has been made, and once the specifications and functional System requirements have been studied, the hardware design and the firmware development will be ran as a target of PFC.
Resumo:
Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs.
Resumo:
We explore the recently developed snapshot-based dynamic mode decomposition (DMD) technique, a matrix-free Arnoldi type method, to predict 3D linear global flow instabilities. We apply the DMD technique to flows confined in an L-shaped cavity and compare the resulting modes to their counterparts issued from classic, matrix forming, linear instability analysis (i.e. BiGlobal approach) and direct numerical simulations. Results show that the DMD technique, which uses snapshots generated by a 3D non-linear incompressible discontinuous Galerkin Navier?Stokes solver, provides very similar results to classical linear instability analysis techniques. In addition, we compare DMD results issued from non-linear and linearised Navier?Stokes solvers, showing that linearisation is not necessary (i.e. base flow not required) to obtain linear modes, as long as the analysis is restricted to the exponential growth regime, that is, flow regime governed by the linearised Navier?Stokes equations, and showing the potential of this type of analysis based on snapshots to general purpose CFD codes, without need of modifications. Finally, this work shows that the DMD technique can provide three-dimensional direct and adjoint modes through snapshots provided by the linearised and adjoint linearised Navier?Stokes equations advanced in time. Subsequently, these modes are used to provide structural sensitivity maps and sensitivity to base flow modification information for 3D flows and complex geometries, at an affordable computational cost. The information provided by the sensitivity study is used to modify the L-shaped geometry and control the most unstable 3D mode.