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Hydromechanical Analysis of Fluid-Elastomeric Lag Dampers Including Subzero Temperatures

JOURNAL OF AIRCRAFT 2014年第3期51卷 1056-1061页

作者： Ngatu, Grum T. Singh, Harinder J. Wereley, Norman M. Kothera, Curt S. Univ Maryland Dept Aerosp Engn College Pk MD 20742 USA InnoVital Syst Inc Beltsville MD 20705 USA

The article examined the behavior of a snubber-type fluid-elastomeric (FE) lag damper under dynamic load applications at various operating temperatures. Topics discussed include hydromechanical modeling of fluid-elastomeric damper and parameter identification and model performance. Figures that represent the damping force versus velocity cycles at two different operating temperatures are also presented.

关键词： Helicopter Rotor Fluid Density Material Properties Hysteretic Damping optimization algorithm Aerospace Engineering Laminar Flow Elastomers Snubber Temperature Effects

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Comparison of linear models for gas turbine performance

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2014年第8期228卷 1291-1301页

作者： Hu Yu Yang Yuecheng Zhang Shiying Sun Zhensheng Xian Res Inst Hitech Hongqing Town 710025 Shaanxi Provinc Peoples R China

Linearization of turbofan engines is an effective method for performance control and fault diagnosis. In this study, three different linearization techniques, including the partial derivative method, optimized fitting method and equilibrium manifold, are discussed and compared. First, an optimized fitting method is developed based on the least-square method and an optimization algorithm. To avoid trapping in local optimization solution, the initial values used in the optimization approach are obtained through the partial derivative method. Second, to verify the accuracy and effectiveness of the linear model in the flight envelope, the result of linear modeling method based on equilibrium manifold is analyzed in detail. Finally, an overall assessment of the merits or weaknesses of linearization models is provided based on the obtained results.

关键词： Linear model gas turbine least-square method optimization algorithm equilibrium manifold

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Representing Sampled Pareto Frontiers as Parameterized Continuous Manifolds Using Self-Organizing Maps

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AIAA JOURNAL 2014年第11期52卷 2480-2490页

作者： Daskilewicz, Matthew J. German, Brian J. Georgia Inst Technol Sch Aerosp Engn Atlanta GA 30319 USA

This paper describes a method for defining a coordinate system to parameterize a sampled Pareto frontier of a continuous multi-attribute design problem using a modified self-organizing map. By defining such a coordinate system, the design problem may be reformulated from y = f(x) to (y,x) = g(psi), where x is a vector of design variables, y is a vector of attributes, and psi is a vector of barycentric coordinates. Exploration of the design problem using psi as the independent variables has the following desirable properties: 1) Every vector psi corresponds to a Pareto efficient design, and every Pareto efficient design has a corresponding psi. 2) The number of psi coordinates is equal to the number of attributes, regardless of the number of design variables. 3) Each attribute y(i) has a corresponding coordinate psi(i) such that the sign of partial derivative y(i)/partial derivative psi(i) is positive if the objective is to maximize y(i) and negative if the objective is to minimize y(i) (i.e., the attributes improve monotonically as their corresponding coordinates increase). This approach, named the "Pareto simplex self-organizing map" is easily implemented as a postprocessing step to sampling a Pareto frontier with multi-objective optimization. The construction of the coordinates and their use in design space exploration is demonstrated on a conceptual wing design problem.

关键词： Pareto Frontier Space Exploration optimization algorithm Critical Mach Number Bending Moment Artificial Neural Network Evolutionary algorithm Lift to Drag Ratio Transonic Aircraft Genetic algorithm

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A mathematical solution of optimal partition of production loops for subsea wells in the layout of daisy chains

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART M-JOURNAL OF ENGINEERING FOR THE MARITIME ENVIRONMENT 2014年第3期228卷 211-219页

作者： Wang, Yingying Wang, Deguo Duan, Menglan Xu, Minghua Cao, Jing Estefen, Segen F. China Univ Petr Offshore Oil Gas Res Ctr Beijing 102249 Peoples R China Univ Fed Rio de Janeiro COPPE BR-21945 Rio De Janeiro Brazil Changzhou Univ Sch Math & Phys Changzhou Peoples R China CNOOC Res Inst Beijing Peoples R China

The daisy chain is one of the main layout types of the subsea production system in the development of deepwater oil and gas fields. The number of production loops, length of subsea pipelines, and partition of subsea wells are the main concerns in pigging loop design, pipeline laying, and flow assurance, which become important factors for the capital and operating expenditures and the risk management of deepwater fields. This article focuses on the basic optimal partition problem of production loops for subsea wells in the layout of daisy chains. It proposes to find the optimal partition method at the lowest layout cost, where a mathematical model is proposed and its dedicated algorithm is developed. Numerical simulations are conducted to evaluate the validity of the proposed model and the performance of the algorithm. The results show that the model can accurately describe the optimal partition problem of daisy chains in practice, and a mathematical solution to the optimal partition can be obtained by the algorithm programmed in MATLAB, which can provide the engineers a quantitative reference for the layout of daisy chains in engineering.

关键词： Subsea production system daisy chain layout optimal partition mathematical model optimization algorithm

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Random filtering structure-based compressive sensing radar

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2014年第1期2014卷 1-11页

作者： Zhang, Jindong Ban, YangYang Zhu, Daiyin Zhang, Gong Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210016 Peoples R China

Recently with an emerging theory of 'compressive sensing' (CS), a radically new concept of compressive sensing radar (CSR) has been proposed in which the time-frequency plane is discretized into a grid. Random filtering is an interesting technique for efficiently acquiring signals in CS theory and can be seen as a linear time-invariant filter followed by decimation. In this paper, random filtering structure-based CSR system is investigated. Note that the sparse representation and sensing matrices are required to be as incoherent as possible;the methods for optimizing the transmit waveform and the FIR filter in the sensing matrix separately and simultaneously are presented to decrease the coherence between different target responses. Simulation results show that our optimized results lead to smaller coherence, with higher sparsity and better recovery accuracy observed in the CSR system than the nonoptimized transmit waveform and sensing matrix.

关键词： Compressive sensing radar Random filtering Cross-correlation optimization algorithm

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Generalizing Movements with Information-Theoretic Stochastic Optimal Control

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2014年第9期11卷 579-595页

作者： Lioutikov, Rudolf Paraschos, Alexandros Peters, Jan Neumann, Gerhard Tech Univ Darmstadt Intelligent Autonomous Syst Grp D-64283 Darmstadt Germany Max Planck Inst Intelligent Syst Dept Empir Inference D-72076 Tubingen Germany

Stochastic optimal control is typically used to plan a movement for a specific situation. Although most stochastic optimal control methods fail to generalize this movement plan to a new situation without replanning, a stochastic optimal control method is presented that allows reuse of the obtained policy in a new situation, as the policy is more robust to slight deviations from the initial movement plan. To improve the robustness of the policy, we employ information-theoretic policy updates that explicitly operate on trajectory distributions instead of single trajectories. To ensure a stable and smooth policy update, the "distance" is limited between the trajectory distributions of the old and the new control policies. The introduced bound offers a closed-form solution for the resulting policy and extends results from recent developments in stochastic optimal control. In contrast to many standard stochastic optimal control algorithms, the current approach can directly infer the system dynamics from data points, and hence can also be used for model-based reinforcement learning. This paper represents an extension of the paper by Lioutikov et al. ("Sample-Based Information-Theoretic Stochastic Optimal Control," Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Piscataway, NJ, 2014, pp. 3896-3902). In addition to revisiting the content, an extensive theoretical comparison is presented of the approach with related work, additional aspects of the implementation are discussed, and further evaluations are introduced.

关键词： Theoretic Stochastic Optimal Control Reinforcement Learning Robotics Linear Quadratic Gaussian Robots Markov Decision Process Kullback Leibler Divergence Search algorithm optimization algorithm Control algorithm

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Enhancement of loading capacity of distribution system through distributed generator placement considering techno-economic benefits with load growth

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年第Jan.期54卷 505-515页

作者： Mistry, Khyati D. Roy, Ranjit SV Natl Inst Technol Dept Elect Engn Surat 395007 Gujarat India

Load growth in a system is a natural phenomenon. With the increase in load demand, system power loss and voltage drop increases. Distributed generators (DGs) are one of the best solutions to cope up with the load growth if they are allocated appropriately in the distribution system. In this work, optimal size and location of multiple DGs are found to cater the incremental load on the system and minimization of power loss without violating system constraints. For this a predetermined annual load growth up to five years is considered with voltage regulation as a constraint. The particle swarm optimization with constriction factor approach is applied to determine the optimum size and location with multiple DGs. To see the effect of load growth on system, 33-node IEEE standard test case is considered. It is observed that with the penetration of multiple number of DGs in distribution system, there is great improvement in several distribution system parameters. Moreover, the loading capacity of distribution system is enhanced through DG placement and its techno-economic benefits are also established. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Distributed generators Load growth optimization algorithm Radial distribution system Voltage stability index Voltage profile

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Nonlinear Proportional-Derivative Control Incorporating Closed-Loop Control Allocation for Spacecraft

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2014年第3期37卷 799-812页

作者： Hu, Qinglei Li, Bo Zhang, Youmin Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Heilongjiang Peoples R China Concordia Univ Dept Mech & Ind Engn Montreal PQ H3G 1M8 Canada

A novel saturated proportional-derivative control law incorporated with closed-loop control allocation is proposed for spacecraft attitude stabilization in this paper. More specifically, a saturated proportional-derivative-based baseline nonlinear controller is designed to guarantee the globally asymptotic stability under control input/signal constraints. Then, a closed-loop constrained optimal control allocation scheme is employed to distribute the moments synthesized by the baseline controller over the redundant actuators in the presence of constraints due to actuator amplitude and rate constraints. The optimal control solution is to be found by penalizing the control allocation errors and rates using optimal quadratic programming algorithms. A significant feature of this work is that the asymptotic stability with the closed-loop control allocation is guaranteed theoretically. Simulation results are presented to illustrate the performance of the proposed scheme.

关键词： Proportional Derivative Spacecraft Models Actuator Torque Attitude Control System Optimal Control optimization algorithm Spacecraft Attitude Energy Consumption Singular Value Decomposition Nonlinear Control

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Kernel density estimation of three-parameter Weibull distribution with neural network and genetic algorithm

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APPLIED MATHEMATICS AND COMPUTATION 2014年 247卷 803-814页

作者： Yang, Fan Yue, Zhufeng Northwestern Polytech Univ Dept Engn Mech Xian 710072 Peoples R China

Three-parameter Weibull distribution is widely employed as a model in reliability and lifetime studies due to its good fit to data. It is important to estimate the unknown parameters exactly for modeling. There are many methods to estimate the parameters of three-parameter Weibull distribution and the kernel density estimation method is one of them. The smoothing parameter has a significant influence on the estimation accuracy. In this paper, the neural network and genetic algorithm were used to get the best smoothing parameter and the result was compared with other methods. The Monte Carlo simulations were carried out to show the feasibility of our approach for estimation of three-parameter Weibull distribution. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Neural network model Genetic algorithm Weibull distribution optimization algorithm Maximum likelihood method Grey model

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Routing and spectrum allocation algorithms for elastic optical networks with dedicated path protection

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OPTICAL SWITCHING AND NETWORKING 2014年 13卷 63-75页

作者： Walkowiak, Krzysztof Klinkowski, Miroslaw Rabiega, Bartosz Goscien, Roza Dept Syst & Comp Networks Wroclaw Poland Inst Natl Telecommun Warsaw Poland

Elastic optical network (EON) architectures have been recently proposed as a candidate solution for provisioning of both huge bandwidth and flexible connections in next generation optical networks. In this paper, we focus on survivable EON scenarios and, in particular, we address an offline problem of routing and spectrum allocation (RSA) with dedicated path protection (DPP) in EON. We formulate RSA/DPP as an Integer Linear Programming (ILP) problem. Since RSA is a difficult problem itself, we propose to apply a metaheuristic approach to provide near-optimal solutions to RSA/DPP. Namely, we develop a Tabu Search-based algorithm (TS), and a hybrid Adaptive Frequency Assignment-TS (AFA/TS) algorithm. We investigate the efficiency of the algorithms for a set of network and DPP scenarios and we show that the proposed algorithms outperform other reference algorithms. Eventually, we present some comparative results for different path protection scenarios. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Elastic optical network Routing and spectrum allocation Dedicated path protection optimization algorithm

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