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A continuous multicomponent fuel flame propagation and chemical kinetics model has been developed. In the multicomponent fuel model, the theory of continuous thermodynamics was used to model the properties and composition of fuels such as gasoline. The difference between the current continuous multicomponent fuel model and previous similar models in the literature is that the source terms contributed by chemistry in the mean and the second moment transport equations have been considered. This new model was validated using results from a discrete multicomponent fuel model. In the flame propagation and chemical kinetics model, five improved combustion submodels were also integrated with the new continuous multicomponent fuel model. To consider the change in local fuel vapor mixture composition, a 'primary reference fuel (PRF) adaptive' method is proposed that formulates a relationship between the fuel vapor mixture PRF number (or research octane number) and the fuel vapor mixture composition based on the mean molecular weight and/or variance of the fuel vapor mixture composition in each cell. Simulations of single droplet vaporization with a single-component fuel (iso-octane ) were compared with multicomponent fuel cases. [DOI: 10.1115/1.4000267] Keywords: continuous multicomponent fuel model, flame propagation, G-equation, detailed chemical kinetics

The support vector machine (SVM) is proposed as a response surface model to accelerate the solution speed of metaheuristic algorithms in solving inverse problems. The detail formulations of the SVM regression model using [epsilon]-insensitive loss function are derived. Primary numerical results are reported to demonstrate the feasibility, performance, and robustness of the proposed SVM based response surface model for solving both mathematical functions and engineering design problems. Index Terms--Inverse problem, metaheuristic algorithm, response surface model, support vector machine (SVM).

A tabu search algorithm having robust solution searching power is proposed. To avoid excessive computation burdens which are needed for the expected fitness evaluations in tabu searches, it is proposed that the Gaussian distributed neighborhood vector, the strategy for assigning expected fitness only to promising solutions, and the utilization of neighborhood solutions to determine the fitness values of the potential solutions are to be used. A new distance-weighted formula for the expected fitness assignments is also proposed. Two case studies are reported to validate and demonstrate the feasibility and advantages of using the proposed algorithm in finding the robust solution of an optimal design problem. Index Terms--Expected fitness, optimal design, robust solution, tabu search method.

To incorporate the knowledge or preference of a decision maker or domain expert into a vector optimizer in the search for a series of subsets of the entire Pareto optimal solutions, a vector particle swarm optimization (PSO) algorithm that implements the reference point-based approach together with a desirability function is proposed. The fitness assignment strategy and the neighborhood relationship of the PSO algorithm are redefined to facilitate the realization of the aforementioned objective. To validate and demonstrate the advantages of the proposed algorithm, its applications on two different multiobjective problems are reported. Index Terms--Desirability function, multiobjective design, particle swarm optimization (PSO) algorithm, reference point.

An efficient vector optimizer is proposed based on the hybridization of an ant colony optimization method and a novel exploiting search mechanism. To inherit the learning and searching power of an ant colony algorithm while excluding the usage of a tedious and awkward pheromone updating scheme, it is proposed that an algorithm that models the foraging strategy of pachycodyla apicalis ants is employed and modified. In order to yield better Pareto solutions, the gradient balance concept is used to design the exploitation search process in which some a priori information about the characteristics of the objective functions is used in the selection of nests for subsequent intensifying searches. Numerical experiments are reported to validate the merits and advantages of the proposed vector optimizer for solving practical engineering design problems. Index Terms--Ant colony optimization (ACO), evolutionary computation, multiobjective optimization, optimal design.

A combined method is presented to deal with the practical engineering problems of multiobjective optimization. The Nondominated Sorting Genetic Algorithm II (NSGA-II) is adopted as a searching tool for the Pareto-optimal solutions, which is improved by using a new crossover operator. The response surface model (RSM) based on the radial basis function is used to reduce the computational effort. The application of the method to the shape optimization process of a permanent magnet assembly for magnetic resonance imaging devices is described, and the numerical results show that the method is feasible and efficient for the engineering shape optimization. Index Terms--Genetic algorithm, main magnet of MRI, multiobjective optimization, shape optimization.

This paper presents a new 3-D finite-element method for taking account of vector hysteresis and anisotropy. The proposed method combines the improved scalar Preisach model with the lagging angle between magnetic flux density and magnetic field intensity to solve vector hysteresis problem. Magnetic material's B - H curves with any other directions to rolling direction are obtained by interpolating the measured B - H curves to solve anisotropy problem. The method enables us to solve vector hysteresis and anisotropy problem simply. In order to validate the algorithm presented, TEAM problem32 has been analyzed using 3-D FEM as an example. Index Terms--Anisotropy, lagging angle, Preisach hysteresis model, vector hysteresis.

A new surrogate objective function is suggested for the global optimization of electromagnetic devices. The surrogate objective function is constructed using a [C.sup.1] piecewise response surface incorporated with the design sensitivities computed by using the finite-element method. The sampling data points used for constructing the response surface are adaptively inserted during the optimization process. After the surrogate objective function is constructed, the global optimum point is obtained by using a genetic algorithm. Applications to benchmark problems and the optimum design of a permanent magnet system show the effectiveness of the proposed algorithm. Index Terms--Design sensitivity, finite-element analysis, global optimization, response surface patches.

This paper presents a novel strategy to model the full three-dimensional structures of end region of huge turbine-generators with power level up to 1000 MW. The 3-D nonlinear anisotropic magnetic field including the eddy current losses is calculated by utilizing the reduced magnetic vector potential formulation. With the help of Biot-Savart's law, the magnetic field caused by currents in the stator and rotor windings, which are very complex in geometric shapes, can be calculated in a far easy way. The flux density distribution in the end region and the eddy current distribution in the structural parts under different operating conditions are presented. Index Terms--Eddy current, end region, modeling, three dimensions, turbogenerator.

An improved compactly supported radial basis function is proposed as a response surface model in the study of computationally heavy design problems. A new interpolation formula is introduced to enhance the interpolation accuracy on boundary derivatives and the proposed response surface model is then combined with stochastic algorithms in the design of a fast global optimizer. Numerical results are reported to demonstrate the generality and the robustness of the proposed works. Index Terms--Compact support, global optimization, inverse problem, radial basis function, response surface model.

An earlier model underlying the foraging strategy of a pachycodyla apicalis ant is modified. The proposed algorithm incorporates key features of the tabu-search method in the development of a relatively simple but robust global ant colony optimization algorithm. Numerical results are reported to validate and demonstrate the feasibility and effectiveness of the proposed algorithm in solving electromagnetic (EM) design problems. Index Terms--Ant colony optimization (ACO), design optimization, foraging behavior, tabu search method.

Based on the refinement successes to particle swarm optimization (PSO) methods, which include, namely, the introduction of an age variable, the proposal of new selection strategies to find the best solutions of the particle as well as for its neighbors, the design of a novel formula for velocity updating, the incorporation of an intensification search phase, and so on, an improved PSO method is presented. The experimental results reported indicate that the refined pinpointing search ability and the global search ability of the proposed method are significantly improved when compared to those of conventional PSOs. Index Terms--Global optimization, metaheuristic algorithm, particle swarm optimization (PSO), stochastic method.

The dynamic-Q optimization method is combined with an interpolating moving least-squares approximation-based response surface model to design an efficient adaptive strategy for solving computationally heavy design problems. The proposed optimal strategy is validated by comparing its performances in finding the solutions of other common optimal methods on two different kinds of problems. Index Terms--Dynamic-Q method, global optimization, optimal design, response surface methodology.

A particle swarm optimization (PSO) based algorithm for finding the Pareto solutions of multiobjective design problems is proposed. To enhance the global searching ability of the available PSOs, a novel formula for updating the particles' velocity and position, as well as the introduction of craziness, are reported. To handle a muitiobjective design problem using the improved PSO, a new fitness assignment mechanism is proposed. Moreover, two repositories, together with the age variables for their members, are introduced for storing and selecting the previous best positions of the particle as well as that of its companions. Besides, the use of age variables to enhance the diversity of the solutions is also described. The proposed method is tested on two numerical examples with promising results. Index Terms--Inverse problem, multiobjective optimal algorithm, optimal design, particle swarm optimization (PSO).

Based on the success in the design of a new global search procedure on the development of a novel trail updating mechanism and the introduction of an elitist strategy to available ant colony optimization (ACO) methods, an improved ACO algorithm is proposed. In order to facilitate the implementation of the search procedure, the available local search phase is simplified also. The algorithm is tested on a mathematical function and an inverse problem, and its performances are compared with those of other well designed methods. Index Terms--Ant colony optimization (ACO) method, heuristic algorithm, inverse problem, optimal design.

The emigration genetic algorithm, which is a genetic-based algorithm, is proposed to obtain the Pareto optimal solution of vector optimal designs of electromagnetic devices. The proposed algorithm differs from the traditional ones in its design of an emigration operator as well as the inclusion of some useful approaches such as the fitness sharing, clustering, and elitism strategy. Detailed numerical results on three different multiobjective design problems are reported to demonstrate the effectiveness and advantages of the proposed algorithm for solving practical engineering multiobjective optimal design problems. Index Terms--Emigration operator, genetic algorithm (GA), numerical method, vector optimization.

To alleviate the difficulties encountered in the generation of meshes for the finite element method for solving thin skin depth problems involving three-dimensional (3-D) eddy-currents, particularly in cases in which the eddy-current region is only a fraction of the entire domain, a new technique based on the combination of finite element and meshless methods is proposed. The use of numerical approach to uphold the mathematical properties of the combined shape functions in terms of consistency and linear independence is also investigated. It is shown that a very coarse mesh is already sufficient to give accurate numerical results with the proposed algorithm. To validate and demonstrate the advantages of the proposed method, typical numerical results on studies of high-frequency 3-D eddy-current problems are reported. Index Terms--Eddy-current, finite element method, meshless method, thin skin depth.

A meshless method based on collocation with radial basis functions (RBFs) and wavelets is proposed. It is shown that the proposed method takes full advantage of both RBFs and wavelets. The bridging scales are employed to preserve the mathematical properties of the entire bases in terms of consistency and linear independence. A numerical example that is used to validate the proposed method is reported. Index Terms--Collocation, meshless method, radial basis function, wavelet.

A tabu search algorithm is proposed for finding the Pareto solutions of multiobjective optimal design problems. In this paper, the contact theorem is used to evaluate the Pareto solutions. The ranking selecting approach and the fitness sharing function are also introduced to identify new current points to begin every iteration cycle. Detailed numerical results are reported in this paper to demonstrate the power of the proposed algorithm in ensuring uniform sampling and obtaining the Pareto optimal front of the multiobjective design problems. The most efficient method of implementing the proposed algorithm is also discussed. Index Terms--Fitness sharing, multiobjective optimization, ranking, tabu search, vector optimization.