The Relationship between Risk and Expected Return in Europe

Revised: 2006-07

Uncovering Ecosystem Service Bundles through Social Preferences

11 p.

Effect of wavelength of sensitizing light on holographic storage properties in LiNbO3 : Fe : Ni crystal

By sensitizing with 514 nm green light, 488 nm blue light and 390 nm ultraviolet light, respectively, recording with 633 nm red light, effect of wavelength of sensitizing light on holographic storage properties in LiNbO3:Fe:Ni crystal is investigated in detail. It is shown that by shortening the wavelength of sensitizing light gradually, nonvolatile holographic recording properties of oxidized LiNbO3:Fe:Ni crystal is optimized gradually, 390 nm ultraviolet light is the best as the sensitizing light. Considering the absorption of sensitizing light, to obtain the best performance in two-center holographic recording we must choose a sensitizing wavelength that is long enough to prevent unwanted absorptions (band-to-band, etc.) and short enough to result in efficient sensitization from the deep traps. So in practice a trade-off is always needed. Explanation is presented theoretically. (c) 2005 Elsevier GmbH. All rights reserved.

Anisotropic Bragg diffraction of finite-sized volume holographic grating in photorefractive crystals

Anisotropic diffraction of uniform plane wave by finite-sized volume holographic grating in photorefractive crystals is considered. It is found that the anisotropic diffraction can take place when some special conditions are satisfied. The diffracted image is obtained in experiment for the anisotropic Bragg diffraction in Fe:LiNbO3 crystals. A coupled wave analysis is presented to study the properties of anisotropic diffraction. An analytical integral solution for the amplitudes of the diffracted beams is submitted. A trade off between high diffraction efficiency and the deterioration of reconstruction fidelity is analyzed. Numerical evaluations also show that the finite-sized anisotropic volume grating exhibits strong angular and wavelength selectivity. All the results are useful for the optimizing design of VHOE based on finite-sized volume grating structures. (c) 2006 Elsevier GmbH. All rights reserved.

Topology optimization of silicon anode structures for lithium-ion battery applications

This thesis presents a topology optimization methodology for the systematic design of optimal multifunctional silicon anode structures in lithium-ion batteries. In order to develop next generation high performance lithium-ion batteries, key design challenges relating to the silicon anode structure must be addressed, namely the lithiation-induced mechanical degradation and the low intrinsic electrical conductivity of silicon. As such, this work considers two design objectives of minimum compliance under design dependent volume expansion, and maximum electrical conduction through the structure, both of which are subject to a constraint on material volume. Density-based topology optimization methods are employed in conjunction with regularization techniques, a continuation scheme, and mathematical programming methods. The objectives are first considered individually, during which the iteration history, mesh independence, and influence of prescribed volume fraction and minimum length scale are investigated. The methodology is subsequently extended to a bi-objective formulation to simultaneously address both the compliance and conduction design criteria. A weighting method is used to derive the Pareto fronts, which demonstrate a clear trade-off between the competing design objectives. Furthermore, a systematic parameter study is undertaken to determine the influence of the prescribed volume fraction and minimum length scale on the optimal combined topologies. The developments presented in this work provide a foundation for the informed design and development of silicon anode structures for high performance lithium-ion batteries.

From organism to population: the role of life-history theory

The role of life-history theory in population and evolutionary analyses is outlined. In both cases general life histories can be analysed, but simpler life histories need fewer parameters for their description. The simplest case, of semelparous (breed-once-then-die) organisms, needs only three parameters: somatic growth rate, mortality rate and fecundity. This case is analysed in detail. If fecundity is fixed, population growth rate can be calculated direct from mortality rate and somatic growth rate, and isoclines on which population growth rate is constant can be drawn in a ”state space” with axes for mortality rate and somatic growth rate. In this space density-dependence is likely to result in a population trajectory from low density, when mortality rate is low and somatic growth rate is high and the population increases (positive population growth rate) to high density, after which the process reverses to return to low density. Possible effects of pollution on this system are discussed. The state-space approach allows direct population analysis of the twin effects of pollution and density on population growth rate. Evolutionary analysis uses related methods to identify likely evolutionary outcomes when an organism's genetic options are subject to trade-offs. The trade-off considered here is between somatic growth rate and mortality rate. Such a trade-off could arise because of an energy allocation trade-off if resources spent on personal defence (reducing mortality rate) are not available for somatic growth rate. The evolutionary implications of pollution acting on such a trade-off are outlined.

Multi-criteria material selection in engineering design

Almost all material selection problems require that a compromise be sought between some metric of performance and cost. Trade-off methods using utility functions allow optimal solutions to be found for two objective, but for three it is harder. This paper develops and demonstrates a method for dealing with three objectives.

Otimização multi-objetivo de projetos de redes de transporte dutoviário de gás natural

Dutos de transmissão são tubulações especialmente desenvolvidas para transportar produtos diversos a longas distâncias e representam a forma mais segura e econômica de transporte para grandes quantidades de fluidos. Os dutos de gás natural, denominados gasodutos, são usados para transportar o gás desde os campos de produção até os centros consumidores, onde o gás é inserido em redes de distribuição para entrega aos consumidores finais. Os gasodutos de transporte apresentam diversas características de monopólio natural, que são o principal argumento econômico para sua regulação. A regulação visa garantir que esta atividade seja explorada de maneira eficiente, refletindo em tarifas de transporte justas para os consumidores e que proporcionem o retorno adequado aos investidores, levando-se em consideração a quantidade de gás transportado. Neste contexto, o presente trabalho tem como objetivo propor metodologias de otimização multi-objetivo de projetos de redes de gasodutos de transporte, envolvendo métodos a posteriori. O problema de otimização formulado contempla restrições associadas ao escoamento do gás e o comportamento das estações de compressão. A solução do problema fornece um conjunto de projetos ótimos de redes de transporte em função da maximização da quantidade de gás natural transportado e da minimização da tarifa associada a esse serviço. A ferramenta foi aplicada a diversos estudos de caso com configurações típicas da indústria de transporte de gás natural. Os resultados mostraram que as metodologias propostas são capazes de fornecer subsídios que permitem ao tomador de decisão do ponto de vista regulatório realizar uma análise de trade-off entre a quantidade de gás transportado e a tarifa, buscando assim atender ao interesse da sociedade em relação à exploração do serviço de transporte

Muitiobjective pressurized water reactor reload core design by nondominated genetic algorithm search

The design of pressurized water reactor reload cores is not only a formidable optimization problem but also, in many instances, a multiobjective problem. A genetic algorithm (GA) designed to perform true multiobjective optimization on such problems is described. Genetic algorithms simulate natural evolution. They differ from most optimization techniques by searching from one group of solutions to another, rather than from one solution to another. New solutions are generated by breeding from existing solutions. By selecting better (in a multiobjective sense) solutions as parents more often, the population can be evolved to reveal the trade-off surface between the competing objectives. An example illustrating the effectiveness of this novel method is presented and analyzed. It is found that in solving a reload design problem the algorithm evaluates a similar number of loading patterns to other state-of-the-art methods, but in the process reveals much more information about the nature of the problem being solved. The actual computational cost incurred depends: on the core simulator used; the GA itself is code independent.

Efficient sampling of atomic configurational spaces.

We describe a method to explore the configurational phase space of chemical systems. It is based on the nested sampling algorithm recently proposed by Skilling (AIP Conf. Proc. 2004, 395; J. Bayesian Anal. 2006, 1, 833) and allows us to explore the entire potential energy surface (PES) efficiently in an unbiased way. The algorithm has two parameters which directly control the trade-off between the resolution with which the space is explored and the computational cost. We demonstrate the use of nested sampling on Lennard-Jones (LJ) clusters. Nested sampling provides a straightforward approximation for the partition function; thus, evaluating expectation values of arbitrary smooth operators at arbitrary temperatures becomes a simple postprocessing step. Access to absolute free energies allows us to determine the temperature-density phase diagram for LJ cluster stability. Even for relatively small clusters, the efficiency gain over parallel tempering in calculating the heat capacity is an order of magnitude or more. Furthermore, by analyzing the topology of the resulting samples, we are able to visualize the PES in a new and illuminating way. We identify a discretely valued order parameter with basins and suprabasins of the PES, allowing a straightforward and unambiguous definition of macroscopic states of an atomistic system and the evaluation of the associated free energies.

Optimal control predicts human performance on objects with internal degrees of freedom.

On a daily basis, humans interact with a vast range of objects and tools. A class of tasks, which can pose a serious challenge to our motor skills, are those that involve manipulating objects with internal degrees of freedom, such as when folding laundry or using a lasso. Here, we use the framework of optimal feedback control to make predictions of how humans should interact with such objects. We confirm the predictions experimentally in a two-dimensional object manipulation task, in which subjects learned to control six different objects with complex dynamics. We show that the non-intuitive behavior observed when controlling objects with internal degrees of freedom can be accounted for by a simple cost function representing a trade-off between effort and accuracy. In addition to using a simple linear, point-mass optimal control model, we also used an optimal control model, which considers the non-linear dynamics of the human arm. We find that the more realistic optimal control model captures aspects of the data that cannot be accounted for by the linear model or other previous theories of motor control. The results suggest that our everyday interactions with objects can be understood by optimality principles and advocate the use of more realistic optimal control models for the study of human motor neuroscience.

Theoretical and numerical investigation of SiC JFET and MOSFET at 6.5 kV

This paper presents a preliminary theoretical and numerical investigation of 4H-SiC JFET and MOSFET at 6.5 kV. To improve the on-state/breakdown performance of the JFET, buried layers in conjunction with a highly doped buffer layer have been used. Trench technology has been employed for the MOSFET. The devices were simulated and optimized using MEDICI[I] simulator. From the comparison between the two devices, it turns out that the JFET offers a better on-state/breakdown trade-off, while the trench MOSFET has the advantage of MOS-control.

An experimental semi-active anti-roll system

The use of anti-roll bars to provide additional roll stiffness and therefore to reduce the trade-off between ride and rollover performance has previously been studied. However, little work has been carried out to investigate the benefits of a switchable roll stiffness. Such a semi-active anti-roll system has the ability to have a low roll stiffness during straight-ahead driving for improved ride performance and high roll stiffness during cornering for improved roll performance. Modelling of such a system is conducted and the model is validated against a semi-active anti-roll system fitted to an experimental vehicle. Experimental and theoretical investigations are used to investigate the performance of such a system with several different strategies employed to switch to the high-stiffness state. The use of an air suspension on the vehicle to roll into corners is also investigated, as is the possibility of exploiting the road layout by allowing the vehicle to be in a low-roll-stiffness configuration during a corner, and then to switch to the high-roll-stiffness configuration midcorner, hence 'locking in' a roll angle. The best rollover performance improvement that was achieved was 12.5 per cent. © IMechE 2008.

The evolution of intermediate castration virulence and ant coexistence in a spatially structured environment

Theory suggests that spatial structuring should select for intermediate levels of virulence in parasites, but empirical tests are rare and have never been conducted with castration (sterilizing) parasites. To test this theory in a natural landscape, we co

Hybrid model predictive control applied to switching control of burner load for a compact marine boi

This paper discusses the application of hybrid model predictive control to control switching between different burner modes in a novel compact marine boiler design. A further purpose of the present work is to point out problems with finite horizon model predictive control applied to systems for which the optimal solution is a limit cycle. Regarding the marine boiler control the aim is to find an optimal control strategy which minimizes a trade-off between deviations in boiler pressure and water level from their respective setpoints while limiting burner switches.The approach taken is based on the Mixed Logic Dynamical framework. The whole boiler systems is modelled in this framework and a model predictive controller is designed. However to facilitate on-line implementation only a small part of the search tree in the mixed integer optimization is evaluated to find out whether a switch should occur or not. The strategy is verified on a simulation model of the compact marine boiler for control of low/high burner load switches. It is shown that even though performance is adequate for some disturbance levels it becomes deteriorated when the optimal solution is a limit cycle. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.