Most real-world design problems are complex and multidisciplinary, with almost always more than one objective (cost) function to be extremized simultaneously. The primary goal of this research is to develop a framewor...
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Most real-world design problems are complex and multidisciplinary, with almost always more than one objective (cost) function to be extremized simultaneously. The primary goal of this research is to develop a framework to enable multi-objective optimization of multidisciplinary design applications, wherein each discipline is able to retain substantial autonomous control during the process. To achieve this end, we have extended the capability of the concurrent subspace optimization method to handle multi-objective optimization problems in a multidisciplinary design optimization context. Although the conventional concurrent subspace optimization approach is easily able to deal with multi-objective optimization problems by applying the weighted sum approach, the main disadvantage is that the weighted sum cannot capture Pareto points on any nonconvex part of the Pareto frontier. Moreover, an aggregate objective function simply cannot reflect the true spirit of the concurrent subspace optimization method, which was developed to allow groups of specialists to independently have more control over their own design criteria and goals, even while maintaining system level coordination. In this paper, the multi-objective Pareto concurrent subspace optimization method is proposed in which each discipline has substantial control over its own objective function during the design process, while still ensuring responsibility for constraint satisfaction in coupled subspaces. The proposed approach is particularly useful given the realities of geographical distribution, computational platform variation, and dependence upon legacy codes within individual disciplines that so predominates the design of large-scale products such as aircraft and automobiles. As part of the multi-objective Pareto concurrent subspace optimization method developed here, it is demonstrated that the endpoints of the Pareto frontier can be easily identified, together with an ability to generate Pareto points with
Satellite formation flight has emerged as a method to increase science return and enable missions that had been impossible with a single spacecraft. Formations often must maintain a precise geometry, which complicates...
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Satellite formation flight has emerged as a method to increase science return and enable missions that had been impossible with a single spacecraft. Formations often must maintain a precise geometry, which complicates mission design, given natural orbit dynamics. This paper presents a multi-impulse formation design strategy that is a compromise between active control and drift solutions. This design, formulation is applied to optimize the magnetospheric multiscale tetrahedron mission using two optimization algorithms, a hierarchical strategy, and a particle swarm approach. Results are presented for a variety of multi-impulse problem specifications, including formation attitude, demonstrating that a multi-impulse solution is a viable strategy that can dramatically improve formation accuracy and longevity at minimal fuel cost. The impact of perturbing forces on optimal designs and their costs is also characterized.
In order to slove the large-scale nonlinear programming (NLP) problems efficiently, an efficient optimization algorithm based on reduced sequential quadratic programming (rSQP) and automatic differentiation (AD)...
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In order to slove the large-scale nonlinear programming (NLP) problems efficiently, an efficient optimization algorithm based on reduced sequential quadratic programming (rSQP) and automatic differentiation (AD) is presented in this paper. With the characteristics of sparseness, relatively low degrees of freedom and equality constraints utilized, the nonlinear programming problem is solved by improved rSQP solver. In the solving process, AD technology is used to obtain accurate gradient information. The numerical results show that the combined algorithm, which is suitable for large-scale process optimization problems, can calculate more efficiently than rSQP itself.
In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a singl...
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In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. Using a variety of mutation operators that can be combined during evolution to generate different probability density function could hold the potential for producing better solutions with less computational effort. In view of this, a linear combination mutation operator of Gaussian and Cauchy mutation is presented in this paper, and a novel clonal selection optimization method based on clonal selection principle is proposed also. The simulation results show the combining mutation strategy can obtain the same performance as the best of pure strategies or even better in some cases.
A nondestructive evaluation technique established on the basis of a global minimization method is presented for the system parameters identification of flexibly supported rectangular laminated composite sandwich plate...
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A nondestructive evaluation technique established on the basis of a global minimization method is presented for the system parameters identification of flexibly supported rectangular laminated composite sandwich plates using measured natural frequencies of the sandwich plates. In this study, the first eight natural frequencies extracted from impulsive vibration testing data are used to identify the system parameters of the flexibly supported sandwich plates. In the identification process, the trial system parameters are used in the Rayleigh-Ritz method to predict the theoretical natural frequencies of the sandwich plate, a frequency discrepancy function is established to measure the sum of the squared differences between the experimental and theoretical predictions of the natural frequencies, and the global minimization method is used to search for the best estimates of the system parameters by making the frequency discrepancy function a global minimum. The accuracy and efficiency of the proposed technique in identifying the system parameters of several flexibly supported sandwich plates made of different face and core materials are studied via both theoretical and experimental approaches. The reasonably good results obtained in this study have demonstrated the applicability of the proposed technique.
The multi-objective optimization of linearized impulsive rendezvous is investigated in this paper and this optimization includes the minimum characteristic velocity, the minimum time of flight, and the maximum safety ...
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The multi-objective optimization of linearized impulsive rendezvous is investigated in this paper and this optimization includes the minimum characteristic velocity, the minimum time of flight, and the maximum safety performance index, of which the trajectory safety performance index is defined as the minimum relative distance between a chaser and a target in the chaser's free-flying path. A theoretical model for calculating this safety performance index is provided. The three-objective optimization model is proposed based on the Clohessy-Wiltshire system. wherein a generalized inverse matrix solution for linear equations is applied to avoid handling the terminal equality constraints. The multi-objective nondominated sorting genetic algorithm is employed to obtain the Pareto solution set. The proposed approach is evaluated using the -V-bar homing and +V-bar homing rendezvous missions. It is shown that tradeoffs between time of flight, fuel cost, and passive trajectory safety for rendezvous trajectory is quickly demonstrated by the approach. By identifying multiple solutions, the approach can produce a variety of missions to meet different needs.
This paper proposes a new methodology for the automatic characterization of the influent wastewater in WWTP. With this methodology, model components are automatically estimated by means of optimization algorithms comb...
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ISBN:
(纸本)1843391481
This paper proposes a new methodology for the automatic characterization of the influent wastewater in WWTP. With this methodology, model components are automatically estimated by means of optimization algorithms combining a-priori knowledge of the expected wastewater composition with experimental information from the available measurement data. The characterization is carried out based on an extended model components list in which components are described by means their elemental mass fractions. This allows an easy establishment of relationships between model components with experimental data and also, to obtain a general methodology applicable to any model used for wastewater biological treatments. The characterization of the wastewater influent of Galindo-Bilbao according this methodology has demonstrated its validity and the easy application to the ASM1 model influent characterization.
An important source of uncertainty in finite element models used for static and fatigue analysis is due to inaccuracy in estimating both the magnitude and distribution of loads. Furthermore, it is often assumed in the...
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An important source of uncertainty in finite element models used for static and fatigue analysis is due to inaccuracy in estimating both the magnitude and distribution of loads. Furthermore, it is often assumed in the models that the structure is rigidly supported even though there may be significant compliance at the support. It is often difficult to accurately estimate the compliance as well as the actual distribution of the load. Recent improvements in experimental techniques enable full-field strain measurement with relative ease for structural components. A method for using these measurements to compute the applied load and distribution, as well as compliances at the supported boundaries, is presented in this paper. Accurately determining the loads and boundary conditions can significantly improve the ability to predict fatigue life and the likely location of failure for structures.
A novel approach for optical beam distribution into two-dimensional (2D) fibre arrays using 2D Dammann gratings is investigated. We report for the first time experimental results of a 2D optical power distribution int...
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A novel approach for optical beam distribution into two-dimensional (2D) fibre arrays using 2D Dammann gratings is investigated. We report for the first time experimental results of a 2D optical power distribution into 2 x 2 polymer optical fibre arrays using a Dammann grating. This paper focuses on the design and fabrication of the diffractive optical element (DOE) along with investigating the coupling performance of the system. This grating may be applicable to a fibre to the home (FTTH) network as it can support sufficient channels with good output uniformity together with low polarization-dependent loss (PDL). Using an appropriate optimization algorithm, the optimum profile for the Dammann gratings can be calculated. The gratings are then fabricated on indium-doped tin oxide (ITO) glass using electron-beam lithography. This method shows that it can achieve low PDL and good uniformity together with acceptable insertion loss.
An adjoint-based optimization procedure is proposed for improving the robustness and extending the range of linear-elasticity-based mesh deformation techniques. Using the values of the modulus of elasticity E defined ...
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An adjoint-based optimization procedure is proposed for improving the robustness and extending the range of linear-elasticity-based mesh deformation techniques. Using the values of the modulus of elasticity E defined in each mesh cell as the design variables, the procedure seeks to determine an optimum distribution of E throughout the mesh, to minimize a global objective function that reflects the skewness or lack of quality of the deformed mesh. The technique is applied to highly stretched mixed element meshes in two and three dimensions on complex geometries and is shown to be capable of recovering a valid mesh in a small number of optimization cycles for cases in which the nonoptimized linear-elasticity approach fails. However, the solution of the optimization problem remains relatively costly in terms of CPU time, compared with a nonoptimized mesh deformation calculation, making this technique best suited for precomputing improved E distributions before the simulation or for use as a plug-in module to be invoked in cases in which the nonoptimized procedure fails.
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