Design, analysis and implementation of a versatile low level radio frequency system for accelerating cavities

179 p.

High Order Multi-Moment Constrained Finite Volume Method. Part I: Basic Formulation

A new high-order finite volume method based on local reconstruction is presented in this paper. The method, so-called the multi-moment constrained finite volume (MCV) method, uses the point values defined within single cell at equally spaced points as the model variables (or unknowns). The time evolution equations used to update the unknowns are derived from a set of constraint conditions imposed on multi kinds of moments, i.e. the cell-averaged value and the point-wise value of the state variable and its derivatives. The finite volume constraint on the cell-average guarantees the numerical conservativeness of the method. Most constraint conditions are imposed on the cell boundaries, where the numerical flux and its derivatives are solved as general Riemann problems. A multi-moment constrained Lagrange interpolation reconstruction for the demanded order of accuracy is constructed over single cell and converts the evolution equations of the moments to those of the unknowns. The presented method provides a general framework to construct efficient schemes of high orders. The basic formulations for hyperbolic conservation laws in 1- and 2D structured grids are detailed with the numerical results of widely used benchmark tests. (C) 2009 Elsevier Inc. All rights reserved.

MODIFIED ENGAGEMENT METHOD FOR MATRIX OPERATION

We describe a modified engagement method for matrix operation based on a two-dimensional crossed-ring interconnection network, Our method incorporates fewer steps than that reported by Bocker et al. [Appl. Opt. 22, 804 (1983)], and its performance is found to be the most efficient (minimum steps) in comparison with other systolic and/or engagement methods for matrix operation. Thus, it may be helpful for other optical and electronic implementations of matrix operations. One compact optoelectronic integrity approach for implementing the modified engagement method is briefly described. (C) 1995 Optical Society of America

Optical two-dimensional SW-banyan network: Optical implementation, routing control, and determination of permissible permutations

A 2-D SW-banyan network is introduced by properly folding the 1-D SW-banyan network, and its corresponding optical setup is proposed by means of polarizing beamsplitters and 2-D phase spatial light modulators. Then, based on the characteristics and the proposed optical setup, the control for the routing path between any source-destination pair is given, and the method to determine whether a given permutation is permissible or not is discussed. Because the proposed optical setup consists of only optical polarization elements, it is compact in structure, its corresponding energy loss and crosstalk are low, and its corresponding available number of channels is high. (C) 1996 Society of Photo-Optical Instrumentation Engineers.

A fully-nonlocal energy-based formulation and high-performance realization of the quasicontinuum method

The quasicontinuum (QC) method was introduced to coarse-grain crystalline atomic ensembles in order to bridge the scales from individual atoms to the micro- and mesoscales. Though many QC formulations have been proposed with varying characteristics and capabilities, a crucial cornerstone of all QC techniques is the concept of summation rules, which attempt to efficiently approximate the total Hamiltonian of a crystalline atomic ensemble by a weighted sum over a small subset of atoms. In this work we propose a novel, fully-nonlocal, energy-based formulation of the QC method with support for legacy and new summation rules through a general energy-sampling scheme. Our formulation does not conceptually differentiate between atomistic and coarse-grained regions and thus allows for seamless bridging without domain-coupling interfaces. Within this structure, we introduce a new class of summation rules which leverage the affine kinematics of this QC formulation to most accurately integrate thermodynamic quantities of interest. By comparing this new class of summation rules to commonly-employed rules through analysis of energy and spurious force errors, we find that the new rules produce no residual or spurious force artifacts in the large-element limit under arbitrary affine deformation, while allowing us to seamlessly bridge to full atomistics. We verify that the new summation rules exhibit significantly smaller force artifacts and energy approximation errors than all comparable previous summation rules through a comprehensive suite of examples with spatially non-uniform QC discretizations in two and three dimensions. Due to the unique structure of these summation rules, we also use the new formulation to study scenarios with large regions of free surface, a class of problems previously out of reach of the QC method. Lastly, we present the key components of a high-performance, distributed-memory realization of the new method, including a novel algorithm for supporting unparalleled levels of deformation. Overall, this new formulation and implementation allows us to efficiently perform simulations containing an unprecedented number of degrees of freedom with low approximation error.

A novel method to design flexible URAs

Aperture patterns play a vital role in coded aperture imaging ( CAI) applications. In recent years, many approaches were presented to design optimum or near-optimum aperture patterns. Uniformly redundant arrays (URAs) are, undoubtedly, the most successful for constant sidelobe of their periodic autocorrelation function. Unfortunately, the existing methods can only be used to design URAs with a limited number of array sizes and fixed autocorrelation sidelobe-to-peak ratios. In this paper, we present a novel method to design more flexible URAs. Our approach is based on a searching program driven by DIRECT, a global optimization algorithm. We transform the design question to a mathematical model, based on the DIRECT algorithm, which is advantageous for computer implementation. By changing determinative conditions, we obtain two kinds of types of URAs, including the filled URAs which can be constructed by existing methods and the sparse URAs which have never been mentioned by other authors as far as we know. Finally, we carry out an experiment to demonstrate the imaging performance of the sparse URAs.

Implementation of the nursing process in a health area: models and assessment structures used

Objective: to analyze what nursing models and nursing assessment structures have been used in the implementation of the nursing process at the public and private centers in the health area Gipuzkoa (Basque Country). Method: a retrospective study was undertaken, based on the analysis of the nursing records used at the 158 centers studied. Results: the Henderson model, Carpenito's bifocal structure, Gordon's assessment structure and the Resident Assessment Instrument Nursing Home 2.0 have been used as nursing models and assessment structures to implement the nursing process. At some centers, the selected model or assessment structure has varied over time. Conclusion: Henderson's model has been the most used to implement the nursing process. Furthermore, the trend is observed to complement or replace Henderson's model by nursing assessment structures.

A working guide to the assessment, implementation and post project monitoring of fisheries habitat improvement schemes in South Cumbria

Due to changes in land use over the last century, the physical nature of many streams and rivers in the British Isles has probably changed. In some cases this change may be large for example as a result of flood defence schemes and is easily observed, whilst in other cases altered land use, farming, forestry or urbanization may have resulted in more subtle changes to river features. This working guide draws together a way of assessing habitat in any stream or river and determine sites or reaches on the assessed watercourse that may benefit from habitat improvement schemes. It will determine a method of measuring existing habitat in a broad sense, whilst referring to R and D studies currently being undertaken in this area. A method of prioritising any proposed habitat restoration work will be suggested. The limitations of fisheries improvement schemes in terms of cross functional acceptance (flood defence and conservation) will be examined along with suggested proposals for some example watercourses. The need for pre and post enhancement monitoring will be discussed as will the requirement for maintenance programs on schemes. Finally methods for determining the cost benefits of small schemes will be examined, compared to other currently used enhancement strategies. This will allow small scale revenue schemes to be used to back up pre project cost benefit analysis as required in future capital submissions.

Learning from implementation of community selection in Zambia, Solomon Islands, and Bangladesh AAS hubs

The CGIAR Research Program on Aquatic Agricultural Systems (AAS) is a research in development program which aims to foster innovation to respond to community needs, and through networking and social learning to bring about development outcomes and impact at scale. It aims to reach the poorest and most vulnerable communities that are dependent upon aquatic agricultural systems. AAS uses monitoring and evaluation to track progress along identified impact pathways for accountability and learning. This report presents an evaluation of the recommended method for selecting communities during the participatory planning process, referred to as AAS “hub rollout,” in the first year of program implementation.

Application of the fixed point method for solution in time stepping finite element analysis using the inverse vector Jiles-Atherton model

An implementation of the inverse vector Jiles-Atherton model for the solution of non-linear hysteretic finite element problems is presented. The implementation applies the fixed point method with differential reluctivity values obtained from the Jiles-Atherton model. Differential reluctivities are usually computed using numerical differentiation, which is ill-posed and amplifies small perturbations causing large sudden increases or decreases of differential reluctivity values, which may cause numerical problems. A rule based algorithm for conditioning differential reluctivity values is presented. Unwanted perturbations on the computed differential reluctivity values are eliminated or reduced with the aim to guarantee convergence. Details of the algorithm are presented together with an evaluation of the algorithm by a numerical example. The algorithm is shown to guarantee convergence, although the rate of convergence depends on the choice of algorithm parameters. © 2011 IEEE.

Development of a tool for rapidly assessing the implementation difficulty and emissions benefits of innovations

Consumer goods manufacturers aiming to reduce the environmental impact associated with their products commonly pursue incremental change strategies, but more radical approaches may be required if we are to address the challenges of sustainable consumption. One strategy to realize step change reductions is to prepare a portfolio of innovations providing different levels of impact reduction in exchange for different levels of organizational resource commitment. In this research a tool is developed to support this strategy, starting with the assumption that through brainstorming or other eco-innovation approaches, a long-list of candidate innovations has been created. The tool assesses the potential greenhouse gas benefit of an innovative option against the difficulty of its implementation. A simple greenhouse gas benefit assessment method based on streamlined LCA was used to analyze impact reduction potential, and a novel measure of implementation difficulty was developed. The predictions of implementation difficulty were compared against expert opinion, and showed similar results indicating the measure can be used sensibly to predict implementation difficulty. The assessment of the environmental gain versus implementation difficulty is visualized in a matrix, showing the trade-offs of several options. The tool is deliberately simple with scalar measures of CO 2 emissions benefits and implementation difficulty so tool users must remain aware of other potential environmental burdens besides greenhouse gases (e.g. water, waste). In addition, although relative life cycle emissions benefits of an option may be low, the absolute impact of an option can be high and there may be other co-benefits, which could justify higher levels of implementation difficulty. Different types of consumer products (e.g. household, personal care, foods) have been evaluated using the tool. Initial trials of the tool within Unilever demonstrate that the tool facilitates rapid evaluation of low-carbon innovations. © 2011 Elsevier Ltd. All rights reserved.

Parallel implementation of Multilevel BDDC

In application of the Balancing Domain Decomposition by Constraints (BDDC) to a case with many substructures, solving the coarse problem exactly becomes the bottleneck which spoils scalability of the solver. However, it is straightforward for BDDC to substitute the exact solution of the coarse problem by another step of BDDC method with subdomains playing the role of elements. In this way, the algorithm of three-level BDDC method is obtained. If this approach is applied recursively, multilevel BDDC method is derived. We present a detailed description of a recently developed parallel implementation of this algorithm. The implementation is applied to an engineering problem of linear elasticity and a benchmark problem of Stokes flow in a cavity. Results by the multilevel approach are compared to those by the standard (two-level) BDDC method.

High order schemes on three-dimensional general polyhedral meshes - Application to the level set method

In this article, we detail the methodology developed to construct arbitrarily high order schemes - linear and WENO - on 3D mixed-element unstructured meshes made up of general convex polyhedral elements. The approach is tailored specifically for the solution of scalar level set equations for application to incompressible two-phase flow problems. The construction of WENO schemes on 3D unstructured meshes is notoriously difficult, as it involves a much higher level of complexity than 2D approaches. This due to the multiplicity of geometrical considerations introduced by the extra dimension, especially on mixed-element meshes. Therefore, we have specifically developed a number of algorithms to handle mixed-element meshes composed of convex polyhedra with convex polygonal faces. The contribution of this work concerns several areas of interest: the formulation of an improved methodology in 3D, the minimisation of computational runtime in the implementation through the maximum use of pre-processing operations, the generation of novel methods to handle complex 3D mixed-element meshes and finally the application of the method to the transport of a scalar level set. © 2012 Global-Science Press.

Advanced applications of a computational design synthesis method

From modelling to manufacturing, computers have increasingly become partners in the design process, helping automate many phases once carried out by hand. In the creative phase, computational synthesis methods aim at facilitating designers' task through the automated generation of optimally directed design alternatives. Nevertheless, applications of these techniques are mainly academic and industrial design practice is still far from applying them routinely. This is due to the complex nature of many design tasks and to the difficulty of developing synthesis methods that can be easily adapted to multiple case studies and automated simulation. This work stems from the analysis of implementation issues and obstacles to the widespread use of these tools. The research investigates the possibility to remove these obstacles through the application of a novel technique to complex design tasks. The ability of this technique to scale-up without sacrificing accuracy is demonstrated. The successful results confirm the possibility to use synthesis methods in complex design tasks and spread their commercial and industrial application.

Active control of high-frequency vibration: Optimisation using the hybrid modelling method

This work presents active control of high-frequency vibration using skyhook dampers. The choice of the damper gain and its optimal location is crucial for the effective implementation of active vibration control. In vibration control, certain sensor/actuator locations are preferable for reducing structural vibration while using minimum control effort. In order to perform optimisation on a general built-up structure to control vibration, it is necessary to have a good modelling technique to predict the performance of the controller. The present work exploits the hybrid modelling approach, which combines the finite element method (FEM) and statistical energy analysis (SEA) to provide efficient response predictions at medium to high frequencies. The hybrid method is implemented here for a general network of plates, coupled via springs, to allow study of a variety of generic control design problems. By combining the hybrid method with numerical optimisation using a genetic algorithm, optimal skyhook damper gains and locations are obtained. The optimal controller gain and location found from the hybrid method are compared with results from a deterministic modelling method. Good agreement between the results is observed, whereas results from the hybrid method are found in a significantly reduced amount of time. © 2012 Elsevier Ltd. All rights reserved.