The radio-frequency (RF) field mapping and its analysis inside a space vehicle cabin, although of immense importance, represent a complex problem due to their inherent concavity. Further hybrid surface modeling requir...
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The radio-frequency (RF) field mapping and its analysis inside a space vehicle cabin, although of immense importance, represent a complex problem due to their inherent concavity. Further hybrid surface modeling required for such concave enclosures leads to ray proliferation, thereby making the problem computationally intractable. In this paper, space vehicle is modeled as a double-curvatured general paraboloid of revolution (GPOR) frustum, whose aft section is matched to an end-capped right circular cylinder. A 3D ray-tracing package is developed which involves a uniform ray-launching scheme, an intelligent scheme for ray bunching, and an adaptive reception algorithm for obtaining ray-path details inside the concave space vehicle. Due to nonavailability of image method for concave curvatured surfaces, the proposed ray-tracing method is validated with respect to the RF field build-up inside a closed lossy cuboid using image method. The RF field build-up within the space vehicle is determined using the details of ray paths and the material parameters. The results for RF field build-up inside a metal-backed dielectric space vehicle are compared with those of highly metallic one for parallel and perpendicular polarizations. The convergence of RF field within the vehicle is analyzed with respect to the propagation time and the number of bounces a ray undergoes before reaching the receiving point.
Reconstruction of computer generated holograms (CGHs) addressed on a spatial light modulator (SLM) is an effective way to dynamically generate designed light field distributions. Based on the classic Gerchberg-Saxton ...
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Reconstruction of computer generated holograms (CGHs) addressed on a spatial light modulator (SLM) is an effective way to dynamically generate designed light field distributions. Based on the classic Gerchberg-Saxton (GS) algorithm, we proposed a technique, which can greatly reduce the computation cost to about 60 % in calculating CGHs for three-dimensional (3D) structures but with little degradation of reconstructed light field compared with the classic GS algorithm. The CGHs calculated by our method were displayed on a twisted nematic liquid crystal display, working as a phase-only-modulation SLM, and 3D structures of optical fields, e.g., 3D array of optical traps and vortices, were reconstructed with high efficiency and high quality. Besides, the possibility for 3D holographic display or projection was also demonstrated with this algorithm by reconstruction several images simultaneously in distinct axial planes.
The Fleet Assignment Problem (FAP) of aircraft scheduling in airlines is studied, and the optimization model of FAP is proposed. The objective function of this model is revenue maximization, and it considers comprehen...
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The Fleet Assignment Problem (FAP) of aircraft scheduling in airlines is studied, and the optimization model of FAP is proposed. The objective function of this model is revenue maximization, and it considers comprehensively the difference of scheduled flights and aircraft models in flight areas and mean passenger flows. In order to solve the model, a self-adapting genetic algorithm is supposed to solve the model, which uses natural number coding, adjusts dynamically crossover and mutation operator probability, and adopts intelligent heuristic adjusting to quicken optimization pace. The simulation with production data of an airline shows that the model and algorithms suggested in this paper are feasible and have a good application value.
Based on an internal tidal model, the practical performances of the limited-memory BFGS (L-BFGS) method and two gradient descent (GD) methods (the normal one with Wolfe's line search and the simplified one) are in...
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Based on an internal tidal model, the practical performances of the limited-memory BFGS (L-BFGS) method and two gradient descent (GD) methods (the normal one with Wolfe's line search and the simplified one) are investigated computationally through a series of ideal experiments in which the open boundary conditions (OBCs) are inverted by assimilating the interior observations with the adjoint method. In the case that the observations closer to the unknown boundary are included for assimilation, the L-BFGS method performs the best. As compared with the simplified GD method, the normal one really uses less iteration to reach a satisfactory solution, but its advantage over the simplified one is much smaller than expected. In the case that only the observations that are further from the unknown boundary are assimilated, the simplified GD method performs the best instead, whereas the performances of the other two methods are not satisfactory. The advanced L-BFGS algorithm and Wolfe's line search still need to be improved when applied to the practical cases. The simplified GD method, which is controllable and easy to implement, should be regarded seriously as a choice, especially when the classical advanced optimization techniques fail or perform poorly.
An implicit reserve constraint unit commitment (IRCUC) model is presented in this paper. Different from the traditional unit commitment (UC) model, the constraint of spinning reserve is not given explicitly but implic...
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An implicit reserve constraint unit commitment (IRCUC) model is presented in this paper. Different from the traditional unit commitment (UC) model, the constraint of spinning reserve is not given explicitly but implicitly in a trade-off between the production cost and the outage loss. An analytical method is applied to evaluate the reliability of UC solutions and to estimate the outage loss. The stochastic failures of generating units and uncertainties of load demands are considered while assessing the reliability. The artificial fish swarm algorithm(AFSA) is employed to solve this proposed model. In addition to the regular operation, a mutation operator (MO) is designed to enhance the searching performance of the algorithm. The feasibility of the proposed method is demonstrated from 10 to 100 units system, and the testing results are compared with those obtained by genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) in terms of total production cost and computational time. The simulation results show that the proposed method is capable of obtaining higher quality solutions.
We prove that the problem of recognition of the existence of solutions as rational functions for linear homogeneous partial differential or difference equations with polynomial coefficients is algorithmically undecida...
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We prove that the problem of recognition of the existence of solutions as rational functions for linear homogeneous partial differential or difference equations with polynomial coefficients is algorithmically undecidable.
Finite element analysis (FEA) refers to simulating real system by using limited number of unknowns to appraisal an approximate real system with infinite number. To overcome the shortcomings of FM in stand-alone Ansys,...
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Finite element analysis (FEA) refers to simulating real system by using limited number of unknowns to appraisal an approximate real system with infinite number. To overcome the shortcomings of FM in stand-alone Ansys, a collaborative computing system over multiple virtual machines (CCSMVM) is proposed to convert stand-alone Ansys into multi-machines. We present the architecture and workflow of CCSMVM, and then focus on key technologies of task construction and scheduling. A FEA application related to FPBS is developed to verify the prototype of CCSMVM integrated Ansys. The experiments show that: (1) the feasibility of key technologies has been verified since load balancing among virtual machines is achieved. (2) CCSMVM can complete the tasks in short completion time with high resource unitization. (3) Our task scheduling algorithm can complete the tasks in shorter time than other algorithms. It is concluded that CCSMVM can accelerate the execution of tasks by exchanging the running speed with resources. (C) 2013 Elsevier Ltd. All rights reserved.
Based on the correlation and ranging methods, we developed an algorithm determining the coordinates of moving sources of wideband noise. The main advantage of this algorithm is the ability to eliminate the ambiguities...
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Based on the correlation and ranging methods, we developed an algorithm determining the coordinates of moving sources of wideband noise. The main advantage of this algorithm is the ability to eliminate the ambiguities of determining the target coordinates arising in the multistatic systems. To test the proposed algorithm, a laboratory passive multistatic radar system was designed and assembled. This paper describes the parameters of the experiment conducted using this system. The obtained results are discussed and analyzed.
Using cellular floating vehicle data is a crucial technique for measuring and forecasting real-time traffic information based on anonymously sampling mobile phone positions for intelligent transportation systems (ITSs...
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Using cellular floating vehicle data is a crucial technique for measuring and forecasting real-time traffic information based on anonymously sampling mobile phone positions for intelligent transportation systems (ITSs). However, a high sampling frequency generates a substantial load for ITS servers, and traffic information cannot be provided instantly when the sampling period is long. In this paper, two analytical models are proposed to analyze the optimal sampling period based on communication behaviors, traffic conditions, and two consecutive fingerprint positioning locations from the same call and estimate vehicle speed. The experimental results show that the optimal sampling period is 41.589 seconds when the average call holding time was 60 s, and the average speed error rate was only 2.87%. ITSs can provide accurate and real-time speed information under lighter loads and within the optimal sampling period. Therefore, the optimal sampling period of a fingerprint positioning algorithm is suitable for estimating speed information immediately for ITSs.
Aimed at the multidimensional and complex characteristic of airport competitiveness, a new algorithm is proposed in which BP neural network is optimized by improved double chains quantum genetic algorithm (IDCQGA-BP)....
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Aimed at the multidimensional and complex characteristic of airport competitiveness, a new algorithm is proposed in which BP neural network is optimized by improved double chains quantum genetic algorithm (IDCQGA-BP). The new algorithm is better than existing algorithms in convergence and the diversity of quantumchromosomes. The empirical data of eight airports in Yangtze River Delta in 2011 and 2012 is applied to verify the feasibility of the new algorithm, and then the competitiveness of the eight airports from 2013 to 2015 is gotten through the algorithm. The results show the following. (1) The new algorithm is better than the existing optimization algorithms in the aspects of error accuracy and run time. (2) The gaps of the airports in Yangtze River Delta are narrowing;the competition and cooperation are getting stronger and stronger. (3) The main increase reason of airport competitiveness is the increase of own investment.
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