Electromagnetic-thermal design optimization of the brushless doubly fed induction generator

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.

Optimization of efficiency-loss figure of merit in carrier-depletion silicon Mach-Zehnder optical modulator.

In this paper we study the optimization of interleaved Mach-Zehnder silicon carrier depletion electro-optic modulator. Following the simulation results we demonstrate a phase shifter with the lowest figure of merit (modulation efficiency multiplied by the loss per unit length) 6.7 V-dB. This result was achieved by reducing the junction width to 200 nm along the phase-shifter and optimizing the doping levels of the PN junction for operation in nearly fully depleted mode. The demonstrated low FOM is the result of both low V(π)L of ~0.78 Vcm (at reverse bias of 1V), and low free carrier loss (~6.6 dB/cm for zero bias). Our simulation results indicate that additional improvement in performance may be achieved by further reducing the junction width followed by increasing the doping levels.

Design optimization and experimental demonstration of low VπL carrier-depletion silicon mach-zehnder modulator

We design, optimize and demonstrate a highly efficient carrier-depletion silicon Mach-Zehnder modulator with very low VπL of ~0.2Vcm. Design consideration, fabrication process and experimental results will be presented. © OSA 2013.

Low-rank optimization with trace norm penalty

The paper addresses the problem of low-rank trace norm minimization. We propose an algorithm that alternates between fixed-rank optimization and rank-one updates. The fixed-rank optimization is characterized by an efficient factorization that makes the trace norm differentiable in the search space and the computation of duality gap numerically tractable. The search space is nonlinear but is equipped with a Riemannian structure that leads to efficient computations. We present a second-order trust-region algorithm with a guaranteed quadratic rate of convergence. Overall, the proposed optimization scheme converges superlinearly to the global solution while maintaining complexity that is linear in the number of rows and columns of the matrix. To compute a set of solutions efficiently for a grid of regularization parameters we propose a predictor-corrector approach that outperforms the naive warm-restart approach on the fixed-rank quotient manifold. The performance of the proposed algorithm is illustrated on problems of low-rank matrix completion and multivariate linear regression. © 2013 Society for Industrial and Applied Mathematics.

Optimization on manifolds: Methods and applications

This paper provides an introduction to the topic of optimization on manifolds. The approach taken uses the language of differential geometry, however,we choose to emphasise the intuition of the concepts and the structures that are important in generating practical numerical algorithms rather than the technical details of the formulation. There are a number of algorithms that can be applied to solve such problems and we discuss the steepest descent and Newton's method in some detail as well as referencing the more important of the other approaches.There are a wide range of potential applications that we are aware of, and we briefly discuss these applications, as well as explaining one or two in more detail. © 2010 Springer -Verlag Berlin Heidelberg.

Multispacecraft refueling optimization considering the J2 perturbation and window constraints

The optimization of a near-circular low-Earth-orbit multispacecraft refueling problem is studied. The refueling sequence, service time, and orbital transfer time are used as design variables, whereas the mean mission completion time and mean propellant consumed by orbital maneuvers are used as design objectives. The J2 term of the Earth's nonspherical gravity perturbation and the constraints of rendezvous time windows are taken into account. A hybridencoding genetic algorithm, which uses normal fitness assignment to find the minimum mean propellant-cost solution and fitness assignment based on the concept of Pareto-optimality to find multi-objective optimal solutions, is presented. The proposed approach is demonstrated for a typical multispacecraft refueling problem. The results show that the proposed approach is effective, and that the J2 perturbation and the time-window constraints have considerable influences on the optimization results. For the problems in which the J2 perturbation is not accounted for, the optimal refueling order can be simply determined as a sequential order or as the order only based on orbitalplane differences. In contrast, for the problems that do consider the J2 perturbation, the optimal solutions obtained have a variety of refueling orders and use the drift of nodes effectively to reduce the propellant cost for eliminating orbital-plane differences. © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Optimization of operational conditions in a submerged membrane bioreactor

In this study, optimization of operational conditions of a submerged membrane bioreactor treating municipal waste-water was studied. Mixed liquid suspended solid (MLSS), membrane flux (J(v)), aeration (Q), ratio of pumping, time to break time (t(p)/t(b)), and ratio of up flow area to down flow area (A Ad) were chosen as the easily manipulable parameters to study their effects on removal efficiency and membrane fouling. Totally, 16 different runs were designed to compare and select the best combination of the 5 parameters. The results showed that the optimal operational conditions were MLSS = 7g(.)L(-1), J(v) = 10L(.)m(-2.)h(-1), Q = 6 m(3.)h(-1), t(p)/t(b)= 4 min/1 min, and A(r)/A(d) = 1.7 m(2)/m(2). Under such conditions, the SMBR could achieve a double win of high removal efficiency and low membrane fouling.

Optimization algorithms and ODE's in MDO

There is a need for a stronger theoretical understanding of Multidisciplinary Design Optimization (MDO) within the field. Having developed a differential geometry framework in response to this need, we consider how standard optimization algorithms can be modeled using systems of ordinary differential equations (ODEs) while also reviewing optimization algorithms which have been derived from ODE solution methods. We then use some of the framework's tools to show how our resultant systems of ODEs can be analyzed and their behaviour quantitatively evaluated. In doing so, we demonstrate the power and scope of our differential geometry framework, we provide new tools for analyzing MDO systems and their behaviour, and we suggest hitherto neglected optimization methods which may prove particularly useful within the MDO context. Copyright © 2013 by ASME.

GPU-accelerated optimization of fuel treatments for mitigating wildfire hazard

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.

Efficient strategies for process design and optimization in ring rolling

Ring rolling is an incremental bulk forming process for the near-net-shape production of seamless rings. This paper shows how nowadays the process design and optimization can be efficiently supported by simulation methods. For reliable predictions of the material flow and the microstructure evolution it's necessary to include a real ring rolling mill's control algorithm into the model. Furthermore an approach for the online measurement of the profile evolution during the process is presented by means of axial profiling in ring rolling. Hence the definition of new ring rolling strategies is possible even for advanced geometries.

Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems. © 2013 IEEE.

Optimization of an effective extraction procedure for the analysis of microcystins in soils and lake sediments

Microcystin analysis in sediments and soils is considered very difficult due to low recovery for extraction. This is the primary limiting factor for understanding the fate of toxins in the interface between water and sediment in both the aquatic ecosystem as well as in soils. In the present study, a wide range of extraction solvents were evaluated over a wide range of pH, extraction approaches and equilibration time to optimize an effective extraction procedure for the analysis of microcystins in soils and lake sediments. The number of extractions required and acids in extraction solutions were also studied. In this procedure, EDTA-sodium pyrophosphate solution was selected as an extraction solvent based on the adsorption mechanism study. The optimized procedure proved to be highly efficient and achieved over 90% recovery. Finally, the developed procedure was applied to field soil and sediment sample collected from Chinese lakes during bloom seasons and microcystins were determined in six of ten samples. (c) 2005 Elsevier Ltd. All rights reserved.

Optimization by orthogonal array design and humoral immunity of the bivalent vaccine against Aeromonas hydrophila and Vibrio fluvialis infection in crucian carp (Carassius auratus L.)

Aeromonas hydrophila and Vibrio fluvialis are the causative agents of a serious haemorrhagic septicaemia that affects a wide range of freshwater fish in China. In order to develop a bivalent anti-A. hydrophila and anti-V. fluvialis formalin-killed vaccine to prevent this disease, an orthogonal array design (OAD) method was used to optimize the production conditions, using three factors, each having three levels. The effects of these factors and levels on the relative per cent survival for crucian carp were quantitatively evaluated by analysis of variance. The final optimized formulation was established. The data showed that inactivation temperature had a significant effect on the potency of vaccine, but formalin concentration did not. The bivalent vaccine could elicit a strong humoral response in crucian carp (Carassius auratus L.) against both A. hydrophila and V. fluvialis simultaneously, which peaked at 3 or 5 weeks respectively. Antibody titres remained high until week 12, the end of the experiment, after a single intraperitoneal injection. The verification experiment confirmed that an optimized preparation could provide protection for fish at least against A. hydrophila infection, and did perform better than the non-optimized vaccine judged by the antibody levels and protection rate, suggesting that OAD is of value in the development of improved vaccine formulations.