The Battin, Gooding, and Sun algorithms are able to converge for nearly 100% of all orbit combinations. Both the Gooding and Sun algorithms have approximately the same performance, whereas the Battin algorithm is cons...
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The Battin, Gooding, and Sun algorithms are able to converge for nearly 100% of all orbit combinations. Both the Gooding and Sun algorithms have approximately the same performance, whereas the Battin algorithm is consistently slower. The performance for each Lambert algorithm, when run on the graphics processing unit (GPU), has been compared. Each Lambert solution algorithm is able to compute tens of millions of solutions per second, with Sun's method having the best performance at nearly 32 million solutions per second. This represents an increase in performance of two orders of magnitude when using GPUs over standard CPU algorithms. Although even the grid search CPU run times are not high when compared with common high-performance computing algorithms, mission optimization algorithms often require run times ranging from hours to multiple days. By offloading computations for solutions to Lambert's problem to GPU(s) and sufficiently parallelizing optimization algorithms, performance increases of up to two orders of magnitude can be realized when compared with standard CPU algorithms. This will allow mission designers to quickly compute complex trajectories when evaluating potential mission architectures.
The paper presents the design of a symmetric, active, gust load alleviation system for a regional transport aircraft, based on a static output feedback with a constrained structure. The design is carried out on a comp...
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The paper presents the design of a symmetric, active, gust load alleviation system for a regional transport aircraft, based on a static output feedback with a constrained structure. The design is carried out on a comprehensive finite state aeroservoelastic model, including sensor units and actuator transfer functions, and verified by taking into account saturated control positions, rates, and hinge moments. The controller is designed within a quadratic optimal framework, through a second-order Hessian-based optimization algorithm, exploiting block diagonal Schur transformations of the closed-loop state equations and performance weightings. An accurately chosen worst discrete gust and a reference flight condition provide a baseline design, which is significantly effective in alleviating continuous turbulence loads. Such a reference design proves itself robust enough to alleviate atmospheric loads over the complete flight envelope and is eventually further improved and robustified through a simple bilinear q-M algebraic scheduling.
Selective laser melting (SLM) is becoming a powerful additive manufacturing technology for different industries: automotive, medical, chemical, aerospace, etc. SLM could dramatically narrow the time frames to optimize...
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Selective laser melting (SLM) is becoming a powerful additive manufacturing technology for different industries: automotive, medical, chemical, aerospace, etc. SLM could dramatically narrow the time frames to optimize production, providing extraordinary freedom to validate design and to develop new materials. The extension of applications requires different materials with specific properties and therefore tailored properties of the final product. In this article, a hierarchical approach including mutual analysis of SLM parameters necessary to control the final product quality on every level - the track, the layer and the final 3D object - is suggested and discussed. Numerical simulation allowed the estimation of temperature distribution during laser melting and predicted final microstructures and properties of a 3D SLM object. A series of single tracks, layers and 3D objects were manufactured from AISI 420 stainless steel to validate a proposed algorithm. The efficiency of the approach was illustrated by the manufacturing of fully dense samples from AISI 420 stainless steel widely used in the plastics-moulding industry. The results show that based on the proposed systematic hierarchical approach, optimal process parameters can be efficiently established for high-quality SLM parts from metal powders. (C) 2014 Elsevier B.V. All rights reserved.
Transportation facility or automotive service enterprise location is an interesting and important *** improve transportation efficient,lots of researchers have addressed traditional facility location allocation(FLA) p...
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ISBN:
(纸本)9781510823808
Transportation facility or automotive service enterprise location is an interesting and important *** improve transportation efficient,lots of researchers have addressed traditional facility location allocation(FLA) problem,e.g.,the FLA problem with the minimum transportation cost or the maximum obtained *** work aims to optimize obsolete vehicle location with the minimum transportation ***,the return center location on obsolete vehicle is influenced by regional ***,the regional constraint should be considered as factors influencing the FLA *** handle this issue via a more practical method,this work proposes an economic optimal model with region constraints for an automotive service *** is,by taking the vehicle return center as a typical automotive service enterprise and an example,this work presents its new economic optimal models considering region and non-region *** artificial fish swarm algorithm is proposed to solve the proposed *** numerical examples are given to illustrate the proposed models and testify the effectiveness of the algorithm.
Minimum miscibility pressure (MMP) is a key parameter determining the feasibility of complete miscibility of oil and gas. Using a slim-tube model, we have experimentally established the MMP for gas and six oil samples...
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Minimum miscibility pressure (MMP) is a key parameter determining the feasibility of complete miscibility of oil and gas. Using a slim-tube model, we have experimentally established the MMP for gas and six oil samples. We propose an improved mathematical model for determining the MMP, designed using 97 groups of MMP data for hydrocarbons (18 groups for lean-gas flooding and 79 groups for rich-gas flooding). The model obtained is universal and is a function of the reservoir temperature, the average molecular weight of the C (7+) oil fraction, and the mole fraction of volatile components (CH (4) and N (2) ) and intermediate components (CO (2) , H (2) S, C (2) -C (6) ) in the crude oil and in the injected gas. We compare our proposed model with widely used empirical models, showing considerable convergence between the experimental data and the calculations;the percentage average absolute relative error (%AARE) is 7.11%.
Binary particle swarm optimization (BPSO) algorithm was used to generate the binary gold nano bi-domes for getting higher absorption coefficient spectrum. The simulation results show that absorption coefficient strong...
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Binary particle swarm optimization (BPSO) algorithm was used to generate the binary gold nano bi-domes for getting higher absorption coefficient spectrum. The simulation results show that absorption coefficient strongly depends on the localized position of nano particles and non-periodic structures have more appropriate response in term of absorption coefficient. This approach can be useful in optical applications such as solar cell and plasmonic nano antenna.
This paper proposed an improved Stud Genetic algorithm using the Opposition-based strategy(SGAO) to improve the performance of the traditional SGA and accelerate its convergence *** SGAO,we use opposition-based approa...
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ISBN:
(纸本)9781510823808
This paper proposed an improved Stud Genetic algorithm using the Opposition-based strategy(SGAO) to improve the performance of the traditional SGA and accelerate its convergence *** SGAO,we use opposition-based approach to initialize the population and to perform mutation with the aim to improve the quality of *** experiments,we use some benchmark functions to the show the performance of the proposed approach and compare it with other algorithms such as genetic algorithm,different evolutionary,particle swarm optimization and stud genetic *** show that SGAO has faster convergence speed and higher solution precision.
Transportation facility or automotive service enterprise location is an interesting and important issue. To improve transportation efficiency, many researchers have addressed the traditional facility location allocati...
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Transportation facility or automotive service enterprise location is an interesting and important issue. To improve transportation efficiency, many researchers have addressed the traditional facility location allocation (FLA) problem, e.g., the FLA problem with the minimum transportation cost or the maximum obtained profit. However, with the improvement of saving energy awareness and the enhancement of environmental concerns, energy efficient and low carbon emission should be considered as key factors influencing the FLA problem. To handle this issue via a more practical method, this work proposes a sustainable location issue for an automotive service enterprise. That is, by taking the vehicle inspection station as a typical automotive service enterprise and an example, this work presents new energy-efficient models of its sustainable location with carbon constraints. An artificial fish swarm algorithm is proposed to solve the proposed models. Some numerical examples are given to illustrate the proposed models and testify the effectiveness of the algorithm. Note to Practitioners-This work concerns the sustainable management problem for locating an automotive service enterprise. To deal with such an issue, this work proposes a novel sustainable analysis method. The previous research handles such a problem through a methodology based on the traditional economical method, which is not enough without considering sustainable factors, e.g., energy consumption and carbon emission. The goal of this work is to establish the energy-efficient models for locating an automotive service enterprise with carbon emission constraint, i.e., to meet the specific requirement of carbon emission assuredly while minimizing the transportation energy/fuel consumption of service customers. Both theoretical and simulated results demonstrate that the proposed approach is effective and feasible. Such results can help decision makers perform better judgments when a practical automotive service en
The optical switch based on the dimer plasmonic nano-tubes on the silicon waveguide has been numerically analysed. In the proposed switch, the optical switch has been excited by two monochromatic incident plan-waves w...
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The optical switch based on the dimer plasmonic nano-tubes on the silicon waveguide has been numerically analysed. In the proposed switch, the optical switch has been excited by two monochromatic incident plan-waves with the same frequency and two polar angles "theta = 0" and "theta = pi/2". If the signal with theta = 0 applies, the incident wave will be transmitted, and on the other hand coherent perfect absorption (CPA) will occur and the two incident waves will be suppressed, if we apply both signals to the switch at the same time. Therefore, the signal with theta = pi/2 acts as control signal. Since the CPA efficiency depends strongly on the number of plasmonic nano-tubes and its location, a new efficient binary optimization method based on the Teaching-Learning-Based optimization (TLBO) algorithm is proposed to design an optimized array of the plasmonic nano-tubes in order to achieve the maximum absorption coefficient in the 'off' state and the minimum absorption coefficient in the 'on' state. In Binary TLBO, a group of learners consists of a matrix with binary entries, control the presence ('1') or the absence ('0') of nano tubes in the array.
Trajectory optimization has been identified as an important way to reduce flight costs and polluting emissions. Due to the power capacity limitations in airborne devices such as the flight management system, a fast me...
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Trajectory optimization has been identified as an important way to reduce flight costs and polluting emissions. Due to the power capacity limitations in airborne devices such as the flight management system, a fast method should be implemented to calculate the full trajectory cost. Many flight management systems use a set of lookup tables with experimental data for each flight phase, and they are called performance databases. In this paper, the trajectory flight cost is calculated using a performance database instead of using classical equations of motion. The trajectory to be calculated is composed of climb, acceleration, cruise, descent, and deceleration. The influence of the crossover altitude during climb and descent, as well as step climbs in cruise, was considered. Lagrange linear interpolations were performed within the performance database discrete values to calculate the required values. By providing a takeoff weight, the initial and final coordinates, and the desired flight plan, the trajectory model provides the top-of-climb coordinates, the top-of-descent coordinates, the fuel burned, and the flight time needed to follow the given flight plan. The accuracy of the trajectory costs calculated with the proposed method was validated with an aerodynamic model in FlightSIM (R), which is software developed by Presagis (R), and with the trajectory cost given by the flight management system benchmark of reference. Results showed that, for the same reference trajectories and for the same inputs, the cost computed by the method proposed in this paper is close to the costs provided by FlightSIM and by the flight management system benchmark or reference.
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