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Link on-off prediction based multipath transfer optimization for aircraft

- , 2017, DOI: 10.16511/j.cnki.qhdxxb.2017.21.021
Abstract: 为各类飞行器提供互联网接入的主要技术方案可以分为卫星通信和地空宽带2种。当飞行器处于两者的重叠覆盖区域,采用多路径进行数据通信将有可能极大改善传输性能。针对上述飞行器多接入场景,该文提出了一种多路径传输优化方案DMPTCP (dynamic multipath transmission control protocol)。针对链路通断情况发现缓慢、数据分配效率低的问题,结合飞行轨迹可预测的特点,设计了一种基于链路通断状态预测的数据分配算法;并针对链路时延和丢包率差异大所导致的接收方乱序情况严重的问题,通过接收方同时在多条子流回复连接层否定确认信息,使得发送方能够快速获得接收方总体乱序情况并对丢包进行重传。仿真实验表明: DMPTCP在聚合带宽和接收方总体乱序情况两方面均明显优于现有多路径传输机制。
Abstract:The two main technologies used for aircraft internet access are satellite and air-to-ground (ATG) communication systems. When an aircraft flies over areas with overlapping signals, communicating with multiple paths may greatly improve transmission performance. This paper presents an optimization scheme for multipath transmissions in such aircraft multiple access scenarios. The slow link state discovery rates and inefficient data scheduling are improved by a link on-off prediction based data scheduling algorithm. The severe out-of-order condition caused by a long link round trip time (RTT) and loss rate differences is improved by transmitting a data level negative acknowledgement with all subflows from the receiver so that the sender can quickly identify and retransmit lost packets. Simulations show that this method is better than existing mechanisms for both the aggregated bandwidth and the average number of out of order packets.
Power Transformer No-Load Loss Prediction with FEM Modeling and Building Factor Optimization  [PDF]
Ehsan Hajipour, Pooya Rezaei, Mehdi Vakilian, Mohsen Ghafouri
Journal of Electromagnetic Analysis and Applications (JEMAA) , 2011, DOI: 10.4236/jemaa.2011.310068
Abstract: Estimation of power transformer no-load loss is a critical issue in the design of distribution transformers. Any deviation in estimation of the core losses during the design stage can lead to a financial penalty for the transformer manufacturer. In this paper an effective and novel method is proposed to determine all components of the iron core losses applying a combination of the empirical and numerical techniques. In this method at the first stage all computable components of the core losses are calculated, using Finite Element Method (FEM) modeling and analysis of the transformer iron core. This method takes into account magnetic sheets anisotropy, joint losses and stacking holes. Next, a Quadratic Programming (QP) optimization technique is employed to estimate the incomputable components of the core losses. This method provides a chance for improvement of the core loss estimation over the time when more measured data become available. The optimization process handles the singular deviations caused by different manufacturing machineries and labor during the transformer manufacturing and overhaul process. Therefore, application of this method enables different companies to obtain different results for the same designs and materials employed, using their historical data. Effectiveness of this method is verified by inspection of 54 full size distribution transformer measurement data.

MA Handong,CUI Erjie,

力学与实践 , 2007,
Abstract: In this paper,the significance of the drag reduction for civil transportation aircraft is briefly illus- trated.Drag prediction techniques for civil transportation aircraft,including Computational Fluid Dynamics (CFD) tools and wind tunnel experiments,are analyzed and evaluated.Then the review is focused on the present state and perspectives of the research on drag reduction techniques,specifically in the fields of drag reduction aerodynamic configurations and devices,induced drag reduction methods and friction drag reduction methods.The related fundamental scientific and technological problems of drag reduction,such as aerody- namic configuration layout,optimization design and flow control,as well as the further improvement in CFD and wind tunnel experiment techniques for drag prediction are discussed,in the light of the development of civil transportation aircraft in China.
Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization  [PDF]
Linhong Zhu,Dong Guo,Junming Yin,Greg Ver Steeg,Aram Galstyan
Computer Science , 2014,
Abstract: We propose a scalable temporal latent space model for link prediction in dynamic social networks, where the goal is to predict links over time based on a sequence of previous graph snapshots. The model assumes that each user lies in an unobserved latent space and interactions are more likely to form between similar users in the latent space representation. In addition, the model allows each user to gradually move its position in the latent space as the network structure evolves over time. We present a global optimization algorithm to effectively infer the temporal latent space, with a quadratic convergence rate. Two alternative optimization algorithms with local and incremental updates are also proposed, allowing the model to scale to larger networks without compromising prediction accuracy. Empirically, we demonstrate that our model, when evaluated on a number of real-world dynamic networks, significantly outperforms existing approaches for temporal link prediction in terms of both scalability and predictive power.
Reengineering Aircraft Structural Life Prediction Using a Digital Twin  [PDF]
Eric J. Tuegel,Anthony R. Ingraffea,Thomas G. Eason,S. Michael Spottswood
International Journal of Aerospace Engineering , 2011, DOI: 10.1155/2011/154798
Abstract: Reengineering of the aircraft structural life prediction process to fully exploit advances in very high performance digital computing is proposed. The proposed process utilizes an ultrahigh fidelity model of individual aircraft by tail number, a Digital Twin, to integrate computation of structural deflections and temperatures in response to flight conditions, with resulting local damage and material state evolution. A conceptual model of how the Digital Twin can be used for predicting the life of aircraft structure and assuring its structural integrity is presented. The technical challenges to developing and deploying a Digital Twin are discussed in detail. 1. Introduction Despite increasing capability to understand relevant physical phenomena and to automate numerical modeling of them, the process for lifing aircraft structure as outlined in Figure 1 has not advanced greatly in fifty years. The external loads on an aircraft (aerodynamic pressures and ground loads) are developed by the loads group using a specialized model and placed in a database. The loads for selected design points are pulled from the database by the structural modeling group who then apply them to the structural finite element model (FEM) to develop the internal loads in the airframe for each design load case. These cases are placed in a second database. The durability and damage tolerance experts use these internal load cases to develop stress transfer functions relating the external loads to local stresses at details such as fastener holes, cutouts, and fillets. The stress transfer functions are applied to the loads in the flight loads database to develop a stress spectrum at each point of interest in the airframe. These stress spectra are used in specialized fatigue software together with an idealized local geometry to predict the fatigue crack nucleation or fatigue crack growth lives of details that have been identified as fatigue sensitive. Meanwhile, the dynamics group uses yet another specialized model to determine the vibration characteristics of the aircraft to address the fatigue of the structure due to low-amplitude, high-frequency dynamic loads such as acoustic and aeroelastic. Figure 1: Schematic of current life prediction process. Increased computational horsepower has enabled each of the individual parts of this process to be performed more efficiently, and so more load cases and fatigue locations can be analyzed. The output files from one model are more readily translated into input files for the next step of the process. However, there has been little effort made to
A Temporal Bayesian Network for Diagnosis and Prediction  [PDF]
Gustavo Arroyo-Figueroa,Luis Enrique Sucar
Computer Science , 2013,
Abstract: Diagnosis and prediction in some domains, like medical and industrial diagnosis, require a representation that combines uncertainty management and temporal reasoning. Based on the fact that in many cases there are few state changes in the temporal range of interest, we propose a novel representation called Temporal Nodes Bayesian Networks (TNBN). In a TNBN each node represents an event or state change of a variable, and an arc corresponds to a causal-temporal relationship. The temporal intervals can differ in number and size for each temporal node, so this allows multiple granularity. Our approach is contrasted with a dynamic Bayesian network for a simple medical example. An empirical evaluation is presented for a more complex problem, a subsystem of a fossil power plant, in which this approach is used for fault diagnosis and prediction with good results.
Optimization of operational aircraft parameters Reducing Noise Emission  [PDF]
Lina Abdallah,Mounir Haddou,Salah Khardi
Mathematics , 2008,
Abstract: The objective of this paper is to develop a model and a minimization method to provide flight path optimums reducing aircraft noise in the vicinity of airports. Optimization algorithm has solved a complex optimal control problem, and generates flight paths minimizing aircraft noise levels. Operational and safety constraints have been considered and their limits satisfied. Results are here presented and discussed.
Image Optimization and Prediction  [PDF]
Shweta Jain,Urmila Shrawankar
Computer Science , 2013,
Abstract: Image Processing, Optimization and Prediction of an Image play a key role in Computer Science. Image processing provides a way to analyze and identify an image .Many areas like medical image processing, Satellite images, natural images and artificial images requires lots of analysis and research on optimization. In Image Optimization and Prediction we are combining the features of Query Optimization, Image Processing and Prediction . Image optimization is used in Pattern analysis, object recognition, in medical Image processing to predict the type of diseases, in satellite images for predicting weather forecast, availability of water or mineral etc. Image Processing, Optimization and analysis is a wide open area for research .Lots of research has been conducted in the area of Image analysis and many techniques are available for image analysis but, a single technique is not yet identified for image analysis and prediction .our research is focused on identifying a global technique for image analysis and Prediction.
Structured Depth Prediction in Challenging Monocular Video Sequences  [PDF]
Miaomiao Liu,Mathieu Salzmann,Xuming He
Computer Science , 2015,
Abstract: In this paper, we tackle the problem of estimating the depth of a scene from a monocular video sequence. In particular, we handle challenging scenarios, such as non-translational camera motion and dynamic scenes, where traditional structure from motion and motion stereo methods do not apply. To this end, we first study the problem of depth estimation from a single image. In this context, we exploit the availability of a pool of images for which the depth is known, and formulate monocular depth estimation as a discrete-continuous optimization problem, where the continuous variables encode the depth of the superpixels in the input image, and the discrete ones represent relationships between neighboring superpixels. The solution to this discrete-continuous optimization problem is obtained by performing inference in a graphical model using particle belief propagation. To handle video sequences, we then extend our single image model to a two-frame one that naturally encodes short-range temporal consistency and inherently handles dynamic objects. Based on the prediction of this model, we then introduce a fully-connected pairwise CRF that accounts for longer range spatio-temporal interactions throughout a video. We demonstrate the effectiveness of our model in both the indoor and outdoor scenarios.
Actuator and Sensor Positioning Optimization in Control Design for a Large BWB Passenger Aircraft  [PDF]
A. Schirrer,C. Westermayer,M. Hemedi,M. Kozek
ISRN Mechanical Engineering , 2011, DOI: 10.5402/2011/635815
Abstract: This paper states an approach to actuator and sensor positioning optimization and design in the control system design of a large blended wing body (BWB) passenger aircraft. Numerous objectives have to be achieved by the control system: loads alleviation, vibration attenuation, and the fulfillment of handling quality requirements. Exploiting the system structure and existing system knowledge (excitation, comfort, and load formulations), evaluation criteria are designed to assess actuator and sensor effectiveness and efficiency for the aircraft dynamic range of interest. The tasks of optimal actuator and sensor positioning, actuator sizing, and actuator bandwidth requirements are investigated, whereby solutions that are robust are sought with respect to parameter variations. The results are shown on a BWB passenger aircraft model and verified using a normalized closed-loop performance assessment approach. 1. Introduction The high complexity of a large-scale system design procedure, such as the control system design of a passenger aircraft, is challenging. The modeling issues are manifold, also involving the interdependence of design decisions and the lack of perfect model information in the design process. In this work, a part of control system design performed within the predesign stage of a large blended wing body (BWB) passenger aircraft (see Figure 1) is reported: the robust optimal selection of inputs and outputs for a vibration control system. Also the related evaluation and system design methods are proposed. This task is comprised of gathering and formulating control design objectives, defining the scope and methods of optimization, choosing appropriate design weights to incorporate excitations and performance objectives, and finally computing optimization results and interpreting them with respect to the system design tasks. The flexible aircraft model under study stems from the ACFA 2020 EU FP7 research project [1]. Figure 1: Large-scale blended wing body (BWB) passenger aircraft. The special properties of flexible structure systems are described in detail in [2]. Fundamental properties of multi-input multi-output (MIMO) control systems and state space system calculus are presented in [3]. Many methods of control system input/output evaluation and selection exist nowadays, and an excellent survey is given by [4]. More recent sources are given by [2, 5, 6]. The evaluation criteria proposed in [2, 6] assess state controllability and observability in a weighted sense. They are combined into a recently proposed criterion to exploit their individual
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