Geometric optimization methods for independent component analysis applied on gene expression data

DNA microarrays provide a huge amount of data and require therefore dimensionality reduction methods to extract meaningful biological information. Independent Component Analysis (ICA) was proposed by several authors as an interesting means. Unfortunately, experimental data are usually of poor quality- because of noise, outliers and lack of samples. Robustness to these hurdles will thus be a key feature for an ICA algorithm. This paper identifies a robust contrast function and proposes a new ICA algorithm. © 2007 IEEE.

Collective optimization over average quantities

This paper addresses the design of algorithms for the collective optimization of a cost function defined over average quantities in the presence of limited communication. We argue that several meaningful collective optimization problems can be formulated in this way. As an application of the proposed approach, we propose a novel algorithm that achieves synchronization or balancing in phase models of coupled oscillators under mild connectedness assumptions on the (possibly time-varying and unidirectional) communication graphs. © 2006 IEEE.

Continuous dynamical systems that realize discrete optimization on the hypercube

We study the problem of finding a local minimum of a multilinear function E over the discrete set {0,1}n. The search is achieved by a gradient-like system in [0,1]n with cost function E. Under mild restrictions on the metric, the stable attractors of the gradient-like system are shown to produce solutions of the problem, even when they are not in the vicinity of the discrete set {0,1}n. Moreover, the gradient-like system connects with interior point methods for linear programming and with the analog neural network studied by Vidyasagar (IEEE Trans. Automat. Control 40 (8) (1995) 1359), in the same context. © 2004 Elsevier B.V. All rights reserved.

Neutronic optimization in high conversion Th-233U fuel assembly with simulated annealing

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.

Optimization of burnable poison design for Pu incineration in fully fertile free PWR core

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.

Minimum maneuver time calculation using convex optimization

The problem of calculating the minimum lap or maneuver time of a nonlinear vehicle, which is linearized at each time step, is formulated as a convex optimization problem. The formulation provides an alternative to previously used quasi-steady-state analysis or nonlinear optimization. Key steps are: the use of model predictive control; expressing the minimum time problem as one of maximizing distance traveled along the track centerline; and linearizing the track and vehicle trajectories by expressing them as small displacements from a fixed reference. A consequence of linearizing the vehicle dynamics is that nonoptimal steering control action can be generated, but attention to the constraints and the cost function minimizes the effect. Optimal control actions and vehicle responses for a 90 deg bend are presented and compared to the nonconvex nonlinear programming solution. Copyright © 2013 by ASME.

Sensitivity analysis and optimization of the nuclear fuel cycle

A sensitivity study has been conducted to assess the robustness of the conclusions presented in the MIT Fuel Cycle Study. The Once Through Cycle (OTC) is considered as the base-line case, while advanced technologies with fuel recycling characterize the alternative fuel cycles. The options include limited recycling in LWRs and full recycling in fast reactors and in high conversion LWRs. Fast reactor technologies studied include both oxide and metal fueled reactors. The analysis allowed optimization of the fast reactor conversion ratio with respect to desired fuel cycle performance characteristics. The following parameters were found to significantly affect the performance of recycling technologies and their penetration over time: Capacity Factors of the fuel cycle facilities, Spent Fuel Cooling Time, Thermal Reprocessing Introduction Date, and incore and Out-of-core TRU Inventory Requirements for recycling technology. An optimization scheme of the nuclear fuel cycle is proposed. Optimization criteria and metrics of interest for different stakeholders in the fuel cycle (economics, waste management, environmental impact, etc.) are utilized for two different optimization techniques (linear and stochastic). Preliminary results covering single and multi-variable and single and multi-objective optimization demonstrate the viability of the optimization scheme.

Design and optimization of planar mesa termination for diamond Schottky barrier diodes

In this paper, we present planar mesa termination structure with high k dielectric Al2O3 for high-voltage diamond Schottky barrier diode. Analysis, design, and optimization are carried out by simulations using finite element technology computer-aided design (TCAD) Sentaurus Device software. The performances of planar mesa termination structure are compared to those of conventional field plate termination structure. It is found that optimum geometry of planar mesa terminated diode requires shorter metal plate extension (1/3 of the field plate terminated diode). Consequently, planar mesa terminated diode can be designed with bigger Schottky contact to increase its current carrying capability. Breakdown performance of field plate termination structure is limited at 1480 V due to peak electric field at the corner of Schottky contact (no oxide breakdown occurs). In contrast, peak electric field in planar mesa termination structure only occurs in the field oxide such that its breakdown performance is highly dependent on the oxide material. Due to Al2O3 breakdown, planar mesa termination structure suffers premature breakdown at 1440 V. Considering no oxide breakdown occurs, planar mesa termination structure can realize higher breakdown voltage of 1751 V. Therefore, to fully realize the potential of planar mesa terminated diode, it is important to choose suitable high k dielectric material with sufficient breakdown electric field for the field oxide. © 2013 Elsevier B.V.

Optimization Algorithms on Matrix Manifolds

This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms.

Multi-objective optimization of a fluid structure interaction benchmarking

The integration and application of a new multi-objective tabu search optimization algorithm for Fluid Structure Interaction (FSI) problems are presented. The aim is to enhance the computational design process for real world applications and to achieve higher performance of the whole system for the four considered objectives. The described system combines the optimizer with a well established FSI solver which is based on the fully implicit, monolithic formuFlation of the problem in the Arbitrary Lagrangian-Eulerian FEM approach. The proposed solver resolves the proposed uid-structure interaction benchmark which describes the self-induced elastic deformation of a beam attached to a cylinder in laminar channel ow. The optimized ow characteristics of the aforementioned geometrical arrangement illustrate the performance of the system in two dimensions. Special emphasis is given to the analysis of the simulation package, which is of high accuracy and is the core of application. The design process identifies the best combination of ow features for optimal system behavior and the most important objectives. In addition, the presented methodology has the potential to run in parallel, which will significantly speed-up the elapsed time. Finite Element Method (FEM), Fluid-Structure Interaction (FSI), Multi-Ojective Tabu search (MOTS2). Copyright © 2013 Tech Science Press.

An approach to multi-fidelity optimization of aeroengine compression systems

The aerodynamic design of turbomachinery presents the design optimisation community with a number of exquisite challenges. Chief among these are the size of the design space and the extent of discontinuity therein. This discontinuity can serve to limit the full exploitation of high-fidelity computational fluid dynamics (CFD): such codes require detailed geometric information often available only sometime after the basic configuration of the machine has been set by other means. The premise of this paper is that it should be possible to produce higher performing designs in less time by exploiting multi-fidelity techniques to effectively harness CFD earlier in the design process, specifically by facilitating its participation in configuration selection. The adopted strategy of local multi-fidelity correction, generated on demand, combined with a global search algorithm via an adaptive trust region is first tested on a modest, smooth external aerodynamic problem. Speed-up of an order of magnitude is demonstrated, comparable to established techniques applied to smooth problems. A number of enhancements aimed principally at effectively evaluating a wide range of configurations quickly is then applied to the basic strategy, and the emerging technique is tested on a generic aeroengine core compression system. A similar order of magnitude speed-up is achieved on this relatively large and highly discontinuous problem. A five-fold increase in the number of configurations assessed with CFD is observed. As the technique places constraints neither on the underlying physical modelling of the constituent analysis codes nor on first-order agreement between those codes, it has potential applicability to a range of multidisciplinary design challenges. © 2012 by Jerome Jarrett and Tiziano Ghisu.