852 resultados para Multi-Objective Optimization
Resumo:
Diversas das possíveis aplicações da robótica de enxame demandam que cada robô seja capaz de estimar a sua posição. A informação de localização dos robôs é necessária, por exemplo, para que cada elemento do enxame possa se posicionar dentro de uma formatura de robôs pré-definida. Da mesma forma, quando os robôs atuam como sensores móveis, a informação de posição é necessária para que seja possível identificar o local dos eventos medidos. Em virtude do tamanho, custo e energia dos dispositivos, bem como limitações impostas pelo ambiente de operação, a solução mais evidente, i.e. utilizar um Sistema de Posicionamento Global (GPS), torna-se muitas vezes inviável. O método proposto neste trabalho permite que as posições absolutas de um conjunto de nós desconhecidos sejam estimadas, com base nas coordenadas de um conjunto de nós de referência e nas medidas de distância tomadas entre os nós da rede. A solução é obtida por meio de uma estratégia de processamento distribuído, onde cada nó desconhecido estima sua própria posição e ajuda os seus vizinhos a calcular as suas respectivas coordenadas. A solução conta com um novo método denominado Multi-hop Collaborative Min-Max Localization (MCMM), ora proposto com o objetivo de melhorar a qualidade da posição inicial dos nós desconhecidos em caso de falhas durante o reconhecimento dos nós de referência. O refinamento das posições é feito com base nos algoritmos de busca por retrocesso (BSA) e de otimização por enxame de partículas (PSO), cujos desempenhos são comparados. Para compor a função objetivo, é introduzido um novo método para o cálculo do fator de confiança dos nós da rede, o Fator de Confiança pela Área Min-Max (MMA-CF), o qual é comparado com o Fator de Confiança por Saltos às Referências (HTA-CF), previamente existente. Com base no método de localização proposto, foram desenvolvidos quatro algoritmos, os quais são avaliados por meio de simulações realizadas no MATLABr e experimentos conduzidos em enxames de robôs do tipo Kilobot. O desempenho dos algoritmos é avaliado em problemas com diferentes topologias, quantidades de nós e proporção de nós de referência. O desempenho dos algoritmos é também comparado com o de outros algoritmos de localização, tendo apresentado resultados 40% a 51% melhores. Os resultados das simulações e dos experimentos demonstram a eficácia do método proposto.
Resumo:
Optically-fed distributed antenna system (DAS) technology is combined with passive ultra high frequency (UHF) radio frequency identification (RFID). It is shown that RFID signals can be carried on directly modulated radio over fiber links without impacting their performance. It is also shown that a multi-antenna DAS can greatly reduce the number of nulls experienced by RFID in a complex radio environment, increasing the likelihood of successful tag detection. Consequently, optimization of the DAS reduces nulls further. We demonstrate RFID tag reading using a three antenna DAS system over a 20mx6m area, limited by building constraints, where 100% of the test points can be successfully read. The detected signal strength from the tag is also observed to increase by an average of approximately 10dB compared with a conventional switched multi-antenna RFID system. This improvement is achieved at +31dBm equivalent isotropically radiated power (EIRP) from all three antenna units (AUs).
Resumo:
The objective of this study was to examine the operating characteristics of a light duty multi cylinder compression ignition engine with regular gasoline fuel at low engine speed and load. The effects of fuel stratification by means of multiple injections as well as the sensitivity of auto-ignition and burn rate to intake pressure and temperature are presented. The measurements used in this study included gaseous emissions, filter smoke opacity and in-cylinder indicated information. It was found that stable, low emission operation was possible with raised intake manifold pressure and temperature, and that fuel stratification can lead to an increase in stability and a reduced reliance on increased temperature and pressure. It was also found that the auto-ignition delay sensitivity of gasoline to intake temperature and pressure was low within the operating window considered in this study. Nevertheless, the requirement for an increase of pressure, temperature and stratification in order to achieve auto-ignition time scales small enough for combustion in the engine was clear, using pump gasoline. Copyright © 2009 SAE International.
Resumo:
This paper reports on fuel design optimization of a PWR operating in a self sustainable Th-233U fuel cycle. Monte Carlo simulated annealing method was used in order to identify the fuel assembly configuration with the most attractive breeding performance. In previous studies, it was shown that breeding may be achieved by employing heterogeneous Seed-Blanket fuel geometry. The arrangement of seed and blanket pins within the assemblies may be determined by varying the designed parameters based on basic reactor physics phenomena which affect breeding. However, the amount of free parameters may still prove to be prohibitively large in order to systematically explore the design space for optimal solution. Therefore, the Monte Carlo annealing algorithm for neutronic optimization is applied in order to identify the most favorable design. The objective of simulated annealing optimization is to find a set of design parameters, which maximizes some given performance function (such as relative period of net breeding) under specified constraints (such as fuel cycle length). The first objective of the study was to demonstrate that the simulated annealing optimization algorithm will lead to the same fuel pins arrangement as was obtained in the previous studies which used only basic physics phenomena as guidance for optimization. In the second part of this work, the simulated annealing method was used to optimize fuel pins arrangement in much larger fuel assembly, where the basic physics intuition does not yield clearly optimal configuration. The simulated annealing method was found to be very efficient in selecting the optimal design in both cases. In the future, this method will be used for optimization of fuel assembly design with larger number of free parameters in order to determine the most favorable trade-off between the breeding performance and core average power density.
Resumo:
The design challenges of the fertile-free based fuel (FFF) can be addressed by careful and elaborate use of burnable poisons (BP). Practical fully FFF core design for PWR reactor has been reported in the past [1]. However, the burnable poison option used in the design resulted in significant end of cycle reactivity penalty due to incomplete BP depletion. Consequently, excessive Pu loading were required to maintain the target fuel cycle length, which in turn decreased the Pu burning efficiency. A systematic evaluation of commercially available BP materials in all configurations currently used in PWRs is the main objective of this work. The BP materials considered are Boron, Gd, Er, and Hf. The BP geometries were based on Wet Annular Burnable Absorber (WABA), Integral Fuel Burnable Absorber (IFBA), and Homogeneous poison/fuel mixtures. Several most promising combinations of BP designs were selected for the full core 3D simulation. All major core performance parameters for the analyzed cases are very close to those of a standard PWR with conventional UO2 fuel including possibility of reactivity control, power peaking factors, and cycle length. The MTC of all FFF cores was found at the full power conditions at all times and very close to that of the UO2 core. The Doppler coefficient of the FFF cores is also negative but somewhat lower in magnitude compared to UO2 core. The soluble boron worth of the FFF cores was calculated to be lower than that of the UO2 core by about a factor of two, which still allows the core reactivity control with acceptable soluble boron concentrations. The main conclusion of this work is that judicial application of burnable poisons for fertile free fuel has a potential to produce a core design with performance characteristics close to those of the reference PWR core with conventional UO2 fuel.
Resumo:
In view of its special features, the brushless doubly fed induction generator (BDFIG) shows high potentials to be employed as a variable-speed drive or wind generator. However, the machine suffers from low efficiency and power factor and also high level of noise and vibration due to spatial harmonics. These harmonics arise mainly from rotor winding configuration, slotting effects, and saturation. In this paper, analytical equations are derived for spatial harmonics and their effects on leakage flux, additional loss, noise, and vibration. Using the derived equations and an electromagnetic-thermal model, a simple design procedure is presented, while the design variables are selected based on sensitivity analyses. A multiobjective optimization method using an imperialist competitive algorithm as the solver is established to maximize efficiency, power factor, and power-to-weight ratio, as well as to reduce rotor spatial harmonic distortion and voltage regulation simultaneously. Several constraints on dimensions, magnetic flux densities, temperatures, vibration level, and converter voltage and rating are imposed to ensure feasibility of the designed machine. The results show a significant improvement in the objective function. Finally, the analytical results of the optimized structure are validated using finite-element method and are compared to the experimental results of the D180 frame size prototype BDFIG. © 1982-2012 IEEE.
Resumo:
A multi-functional 1 × 9 wavelength selective switch based on liquid crystal on silicon (LCOS) spatial light modulator technology and anamorphic optics was tested at a channel spacing of 100 and 200 GHz, including dynamic data measurements on both single beam deflection and multi-casting to two ports. The multi-casting holograms were optimized using a modified Gerchberg-Saxton routine to design the core hologram, followed by a simulated annealing routine to reduce crosstalk at non-switched ports. The effect of clamping the magnitude of phase changes between neighboring pixels during optimization was investigated, with experimental results for multi-casting to two ports resulting in a signal insertion loss of-7.6 dB normalized to single port deflection, a uniformity of ±0.6%, and a worst case crosstalk of-19.4 dB, which can all be improved further by using a better anti-reflection coating on the LCOS SLM coverplate and other measures. © 2013 IEEE.
Resumo:
Fuel treatment is considered a suitable way to mitigate the hazard related to potential wildfires on a landscape. However, designing an optimal spatial layout of treatment units represents a difficult optimization problem. In fact, budget constraints, the probabilistic nature of fire spread and interactions among the different area units composing the whole treatment, give rise to challenging search spaces on typical landscapes. In this paper we formulate such optimization problem with the objective of minimizing the extension of land characterized by high fire hazard. Then, we propose a computational approach that leads to a spatially-optimized treatment layout exploiting Tabu Search and General-Purpose computing on Graphics Processing Units (GPGPU). Using an application example, we also show that the proposed methodology can provide high-quality design solutions in low computing time. © 2013 The Authors. Published by Elsevier B.V.
Resumo:
A 2.5-D and 3-D multi-fold GPR survey was carried out in the Archaeological Park of Aquileia (northern Italy). The primary objective of the study was the identification of targets of potential archaeological interest in an area designated by local archaeological authorities. The second geophysical objective was to test 2-D and 3-D multi-fold methods and to study localised targets of unknown shape and dimensions in hostile soil conditions. Several portions of the acquisition grid were processed in common offset (CO), common shot (CSG) and common mid point (CMP) geometry. An 8×8 m area was studied with orthogonal CMPs thus achieving a 3-D subsurface coverage with azimuthal range limited to two normal components. Coherent noise components were identified in the pre-stack domain and removed by means of FK filtering of CMP records. Stack velocities were obtained from conventional velocity analysis and azimuthal velocity analysis of 3-D pre-stack gathers. Two major discontinuities were identified in the area of study. The deeper one most probably coincides with the paleosol at the base of the layer associated with activities of man in the area in the last 2500 years. This interpretation is in agreement with the results obtained from nearby cores and excavations. The shallow discontinuity is observed in a part of the investigated area and it shows local interruptions with a linear distribution on the grid. Such interruptions may correspond to buried targets of archaeological interest. The prominent enhancement of the subsurface images obtained by means of multi-fold techniques, compared with the relatively poor quality of the conventional single-fold georadar sections, indicates that multi-fold methods are well suited for the application to high resolution studies in archaeology.
Resumo:
基于螺旋理论和空间模型理论绘制了Stewart平台型六维力传感器的性能图谱,总结了结构参数对传感器各性能指标的影响规律;在此基础上对大型Stewart平台六维力传感器的结构进行了非线性单目标、多目标优化设计,为具有普通球形铰链大型Stewart平台六维力传感器的设计和优化提供了依据。
Resumo:
分析了制造系统与制造过程之间的关系;论证了从过程的角度对制造进行建模更恰当;结合Agent和π演算的特点,给出Agent制造系统描述模型及基于π演算的单个Agent的BDI模型,并指出Agent和π演算结合的制造过程模型有利于进行优化目标在不同制造过程层次的分解,不论从方法的角度还是实现的角度,都适合复杂系统建模。Agent和π演算相结合可以有效分析并解决离散事件的建模与仿真中的问题。
Resumo:
The primary approaches for people to understand the inner properties of the earth and the distribution of the mineral resources are mainly coming from surface geology survey and geophysical/geochemical data inversion and interpretation. The purpose of seismic inversion is to extract information of the subsurface stratum geometrical structures and the distribution of material properties from seismic wave which is used for resource prospecting, exploitation and the study for inner structure of the earth and its dynamic process. Although the study of seismic parameter inversion has achieved a lot since 1950s, some problems are still persisting when applying in real data due to their nonlinearity and ill-posedness. Most inversion methods we use to invert geophysical parameters are based on iterative inversion which depends largely on the initial model and constraint conditions. It would be difficult to obtain a believable result when taking into consideration different factors such as environmental and equipment noise that exist in seismic wave excitation, propagation and acquisition. The seismic inversion based on real data is a typical nonlinear problem, which means most of their objective functions are multi-minimum. It makes them formidable to be solved using commonly used methods such as general-linearization and quasi-linearization inversion because of local convergence. Global nonlinear search methods which do not rely heavily on the initial model seem more promising, but the amount of computation required for real data process is unacceptable. In order to solve those problems mentioned above, this paper addresses a kind of global nonlinear inversion method which brings Quantum Monte Carlo (QMC) method into geophysical inverse problems. QMC has been used as an effective numerical method to study quantum many-body system which is often governed by Schrödinger equation. This method can be categorized into zero temperature method and finite temperature method. This paper is subdivided into four parts. In the first one, we briefly review the theory of QMC method and find out the connections with geophysical nonlinear inversion, and then give the flow chart of the algorithm. In the second part, we apply four QMC inverse methods in 1D wave equation impedance inversion and generally compare their results with convergence rate and accuracy. The feasibility, stability, and anti-noise capacity of the algorithms are also discussed within this chapter. Numerical results demonstrate that it is possible to solve geophysical nonlinear inversion and other nonlinear optimization problems by means of QMC method. They are also showing that Green’s function Monte Carlo (GFMC) and diffusion Monte Carlo (DMC) are more applicable than Path Integral Monte Carlo (PIMC) and Variational Monte Carlo (VMC) in real data. The third part provides the parallel version of serial QMC algorithms which are applied in a 2D acoustic velocity inversion and real seismic data processing and further discusses these algorithms’ globality and anti-noise capacity. The inverted results show the robustness of these algorithms which make them feasible to be used in 2D inversion and real data processing. The parallel inversion algorithms in this chapter are also applicable in other optimization. Finally, some useful conclusions are obtained in the last section. The analysis and comparison of the results indicate that it is successful to bring QMC into geophysical inversion. QMC is a kind of nonlinear inversion method which guarantees stability, efficiency and anti-noise. The most appealing property is that it does not rely heavily on the initial model and can be suited to nonlinear and multi-minimum geophysical inverse problems. This method can also be used in other filed regarding nonlinear optimization.
Resumo:
Seismic exploration is the main method of seeking oil and gas. With the development of seismic exploration, the target becomes more and more complex, which leads to a higher demand for the accuracy and efficiency in seismic exploration. Fourier finite-difference (FFD) method is one of the most valuable methods in complex structure exploration, which has obtained good effect. However, in complex media with wider angles, the effect of FFD method is not satisfactory. Based on the FFD operator, we extend the two coefficients to be optimized to four coefficients, then optimize them globally using simulated annealing algorithm. Our optimization method select the solution of one-way wave equation as the objective function. Except the velocity contrast, we consider the effects of both frequency and depth interval. The proposed method can improve the angle of FFD method without additional computation time, which can reach 75° in complex media with large lateral velocity contrasts and wider propagation angles. In this thesis, combinating the FFD method and alternative-direction-implicit plus interpolation(ADIPI) method, we obtain 3D FFD with higher accuracy. On the premise of keeping the efficiency of the FFD method, this method not only removes the azimuthal anisotropy but also optimizes the FFD mehod, which is helpful to 3D seismic exploration. We use the multi-parameter global optimization method to optimize the high order term of FFD method. Using lower-order equation to obtain the approximation effect of higher-order equation, not only decreases the computational cost result from higher-order term, but also obviously improves the accuracy of FFD method. We compare the FFD, SAFFD(multi-parameter simulated annealing globally optimized FFD), PFFD, phase-shift method(PS), globally optimized FFD (GOFFD), and higher-order term optimized FFD method. The theoretical analyses and the impulse responses demonstrate that higher-order term optimized FFD method significantly extends the accurate propagation angle of the FFD method, which is useful to complex media with wider propagation angles.