Final Report of Optimization Algorithms for Hierarchical Problems, with Applications to Nanoporous Materials

Energy Technology Data Exchange (ETDEWEB)

Nash, Stephen G.

2013-11-11

The research focuses on the modeling and optimization of nanoporous materials. In systems with hierarchical structure that we consider, the physics changes as the scale of the problem is reduced and it can be important to account for physics at the fine level to obtain accurate approximations at coarser levels. For example, nanoporous materials hold promise for energy production and storage. A significant issue is the fabrication of channels within these materials to allow rapid diffusion through the material. One goal of our research is to apply optimization methods to the design of nanoporous materials. Such problems are large and challenging, with hierarchical structure that we believe can be exploited, and with a large range of important scales, down to atomistic. This requires research on large-scale optimization for systems that exhibit different physics at different scales, and the development of algorithms applicable to designing nanoporous materials for many important applications in energy production, storage, distribution, and use. Our research has two major research thrusts. The first is hierarchical modeling. We plan to develop and study hierarchical optimization models for nanoporous materials. The models have hierarchical structure, and attempt to balance the conflicting aims of model fidelity and computational tractability. In addition, we analyze the general hierarchical model, as well as the specific application models, to determine their properties, particularly those properties that are relevant to the hierarchical optimization algorithms. The second thrust was to develop, analyze, and implement a class of hierarchical optimization algorithms, and apply them to the hierarchical models we have developed. We adapted and extended the optimization-based multigrid algorithms of Lewis and Nash to the optimization models exemplified by the hierarchical optimization model. This class of multigrid algorithms has been shown to be a powerful tool for

CENTRAL PLATEAU REMEDIATION OPTIMIZATION STUDY

Energy Technology Data Exchange (ETDEWEB)

BERGMAN, T. B.; STEFANSKI, L. D.; SEELEY, P. N.; ZINSLI, L. C.; CUSACK, L. J.

2012-09-19

THE CENTRAL PLATEAU REMEDIATION OPTIMIZATION STUDY WAS CONDUCTED TO DEVELOP AN OPTIMAL SEQUENCE OF REMEDIATION ACTIVITIES IMPLEMENTING THE CERCLA DECISION ON THE CENTRAL PLATEAU. THE STUDY DEFINES A SEQUENCE OF ACTIVITIES THAT RESULT IN AN EFFECTIVE USE OF RESOURCES FROM A STRATEGIC PERSPECTIVE WHEN CONSIDERING EQUIPMENT PROCUREMENT AND STAGING, WORKFORCE MOBILIZATION/DEMOBILIZATION, WORKFORCE LEVELING, WORKFORCE SKILL-MIX, AND OTHER REMEDIATION/DISPOSITION PROJECT EXECUTION PARAMETERS.

Optimization of the gas chromatographic separations

International Nuclear Information System (INIS)

Gasco Sanchez, L.

1973-01-01

A review and a critical study on the optimization of the gas chromatographic separations are made. After dealing with the fundamental gas chromatographic equations, some methods of expressing column performances are discussed: performance indices, performance parameters, resolution and effective plate number per unit time. This is completed with a comparative study on performances of various types of columns. Moreover, optimization methods for operating chromatographic conditions are extensively dealt with: as resolution optimization, separation time, and normalization techniques for the time of analysis in order to achieve the maximum resolution at constant time. Finally, some others non operating parameters such as: selectivity of stationary phases, column preparation and optimization methods by means of computers are studied. (Author) 68 refs

DESIGN OPTIMIZATION METHOD USED IN MECHANICAL ENGINEERING

Directory of Open Access Journals (Sweden)

SCURTU Iacob Liviu

2016-11-01

Full Text Available This paper presents an optimization study in mechanical engineering. First part of the research describe the structural optimization method used, followed by the presentation of several optimization studies conducted in recent years. The second part of the paper presents the CAD modelling of an agricultural plough component. The beam of the plough is analysed using finite element method. The plough component is meshed in solid elements, and the load case which mimics the working conditions of agricultural equipment of this are created. The model is prepared to find the optimal structural design, after the FEA study of the model is done. The mass reduction of part is the criterion applied for this optimization study. The end of this research presents the final results and the model optimized shape.

Schedule optimization study implementation plan

International Nuclear Information System (INIS)

1993-11-01

This Implementation Plan is intended to provide a basis for improvements in the conduct of the Environmental Restoration (ER) Program at Hanford. The Plan is based on the findings of the Schedule Optimization Study (SOS) team which was convened for two weeks in September 1992 at the request of the U.S. Department of Energy (DOE) Richland Operations Office (RL). The need for the study arose out of a schedule dispute regarding the submission of the 1100-EM-1 Operable Unit (OU) Remedial Investigation/Feasibility Study (RI/FS) Work Plan. The SOS team was comprised of independent professionals from other federal agencies and the private sector experienced in environmental restoration within the federal system. The objective of the team was to examine reasons for the lengthy RI/FS process and recommend ways to expedite it. The SOS team issued their Final Report in December 1992. The report found the most serious impediments to cleanup relate to a series of management and policy issues which are within the control of the three parties managing and monitoring Hanford -- the DOE, U.S. Environmental Protection Agency (EPA), and the State of Washington Department of Ecology (Ecology). The SOS Report identified the following eight cross-cutting issues as the root of major impediments to the Hanford Site cleanup. Each of these eight issues is quoted from the SOS Report followed by a brief, general description of the proposed approach being developed

Optimization study of ultracold neutron sources at TRIGA reactors using MCNP

International Nuclear Information System (INIS)

Pokotilovskij, Yu.N.; Rogov, A.D.

1997-01-01

Monte Carlo simulation for the optimization of ultracold and very cold neutron sources for TRIGA reactors is performed. The calculations of thermal and cold neutron fluxes from the TRIGA reactor for different positions and configurations of a very cold solid methane moderator were performed with using the MCNP program. The production of neutrons in the ultracold and very cold energy range was calculated for the most promising final moderators (converters): very cold solid deuterium and heavy methane. The radiation energy deposition was calculated for the optimized solid methane-heavy methane cold neutron moderator

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

Science.gov (United States)

Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

2011-01-01

Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

Following an Optimal Batch Bioreactor Operations Model

DEFF Research Database (Denmark)

Ibarra-Junquera, V.; Jørgensen, Sten Bay; Virgen-Ortíz, J.J.

2012-01-01

The problem of following an optimal batch operation model for a bioreactor in the presence of uncertainties is studied. The optimal batch bioreactor operation model (OBBOM) refers to the bioreactor trajectory for nominal cultivation to be optimal. A multiple-variable dynamic optimization of fed...... as the master system which includes the optimal cultivation trajectory for the feed flow rate and the substrate concentration. The “real” bioreactor, the one with unknown dynamics and perturbations, is considered as the slave system. Finally, the controller is designed such that the real bioreactor...

Comparative Study of the Tuning Performances of the Nominal and Long L* CLIC Final Focus System at √s = 380 GeV

CERN Document Server

Plassard, F; Marin, E; Tomás, R

2017-01-01

Mitigation of static imperfections for emittance preservation is one of the most important and challenging tasks faced by the Compact Linear Collider (CLIC) beam delivery system. A simulation campaign has been performed to recover the nominal luminosity by means of different alignment procedures. The state of the art of the tuning studies is drawn up. Comparative studies of the tuning performances and a tuning-based final focus system design optimization for two L options are presented. The effectiveness of the tuning techniques applied to these different lattices will be decisive for the final layout of the CLIC final focus system at √s = 380 GeV.

Back to the future: nostalgia increases optimism.

Science.gov (United States)

Cheung, Wing-Yee; Wildschut, Tim; Sedikides, Constantine; Hepper, Erica G; Arndt, Jamie; Vingerhoets, Ad J J M

2013-11-01

This research examined the proposition that nostalgia is not simply a past-oriented emotion, but its scope extends into the future, and, in particular, a positive future. We adopted a convergent validation approach, using multiple methods to assess the relation between nostalgia and optimism. Study 1 tested whether nostalgic narratives entail traces of optimism; indeed, nostalgic (compared with ordinary) narratives contained more expressions of optimism. Study 2 manipulated nostalgia through the recollection of nostalgic (vs. ordinary) events, and showed that nostalgia boosts optimism. Study 3 demonstrated that the effect of nostalgia (induced with nomothetically relevant songs) on optimism is mediated by self-esteem. Finally, Study 4 established that nostalgia (induced with idiographically relevant lyrics) fosters social connectedness, which subsequently increases self-esteem, which then boosts optimism. The nostalgic experience is inherently optimistic and paints a subjectively rosier future.

Optimal Reference Strain Structure for Studying Dynamic Responses of Flexible Rockets

Science.gov (United States)

Tsushima, Natsuki; Su, Weihua; Wolf, Michael G.; Griffin, Edwin D.; Dumoulin, Marie P.

2017-01-01

In the proposed paper, the optimal design of reference strain structures (RSS) will be performed targeting for the accurate observation of the dynamic bending and torsion deformation of a flexible rocket. It will provide the detailed description of the finite-element (FE) model of a notional flexible rocket created in MSC.Patran. The RSS will be attached longitudinally along the side of the rocket and to track the deformation of the thin-walled structure under external loads. An integrated surrogate-based multi-objective optimization approach will be developed to find the optimal design of the RSS using the FE model. The Kriging method will be used to construct the surrogate model. For the data sampling and the performance evaluation, static/transient analyses will be performed with MSC.Natran/Patran. The multi-objective optimization will be solved with NSGA-II to minimize the difference between the strains of the launch vehicle and RSS. Finally, the performance of the optimal RSS will be evaluated by checking its strain-tracking capability in different numerical simulations of the flexible rocket.

Optimization and management of materials in earthwork construction : final report, April 2010.

Science.gov (United States)

2010-04-01

As a result of forensic investigations of problems across Iowa, a research study was developed aimed at providing solutions to identified : problems through better management and optimization of the available pavement geotechnical materials and throu...

Pareto-Ranking Based Quantum-Behaved Particle Swarm Optimization for Multiobjective Optimization

Directory of Open Access Journals (Sweden)

Na Tian

2015-01-01

Full Text Available A study on pareto-ranking based quantum-behaved particle swarm optimization (QPSO for multiobjective optimization problems is presented in this paper. During the iteration, an external repository is maintained to remember the nondominated solutions, from which the global best position is chosen. The comparison between different elitist selection strategies (preference order, sigma value, and random selection is performed on four benchmark functions and two metrics. The results demonstrate that QPSO with preference order has comparative performance with sigma value according to different number of objectives. Finally, QPSO with sigma value is applied to solve multiobjective flexible job-shop scheduling problems.

Optimal perturbations for nonlinear systems using graph-based optimal transport

Science.gov (United States)

Grover, Piyush; Elamvazhuthi, Karthik

2018-06-01

We formulate and solve a class of finite-time transport and mixing problems in the set-oriented framework. The aim is to obtain optimal discrete-time perturbations in nonlinear dynamical systems to transport a specified initial measure on the phase space to a final measure in finite time. The measure is propagated under system dynamics in between the perturbations via the associated transfer operator. Each perturbation is described by a deterministic map in the measure space that implements a version of Monge-Kantorovich optimal transport with quadratic cost. Hence, the optimal solution minimizes a sum of quadratic costs on phase space transport due to the perturbations applied at specified times. The action of the transport map is approximated by a continuous pseudo-time flow on a graph, resulting in a tractable convex optimization problem. This problem is solved via state-of-the-art solvers to global optimality. We apply this algorithm to a problem of transport between measures supported on two disjoint almost-invariant sets in a chaotic fluid system, and to a finite-time optimal mixing problem by choosing the final measure to be uniform. In both cases, the optimal perturbations are found to exploit the phase space structures, such as lobe dynamics, leading to efficient global transport. As the time-horizon of the problem is increased, the optimal perturbations become increasingly localized. Hence, by combining the transfer operator approach with ideas from the theory of optimal mass transportation, we obtain a discrete-time graph-based algorithm for optimal transport and mixing in nonlinear systems.

Design Optimization of Mechanical Components Using an Enhanced Teaching-Learning Based Optimization Algorithm with Differential Operator

Directory of Open Access Journals (Sweden)

B. Thamaraikannan

2014-01-01

Full Text Available This paper studies in detail the background and implementation of a teaching-learning based optimization (TLBO algorithm with differential operator for optimization task of a few mechanical components, which are essential for most of the mechanical engineering applications. Like most of the other heuristic techniques, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. A differential operator is incorporated into the TLBO for effective search of better solutions. To validate the effectiveness of the proposed method, three typical optimization problems are considered in this research: firstly, to optimize the weight in a belt-pulley drive, secondly, to optimize the volume in a closed coil helical spring, and finally to optimize the weight in a hollow shaft. have been demonstrated. Simulation result on the optimization (mechanical components problems reveals the ability of the proposed methodology to find better optimal solutions compared to other optimization algorithms.

Educational Optimism among Parents: A Pilot Study

Science.gov (United States)

Räty, Hannu; Kasanen, Kati

2016-01-01

This study explored parents' (N = 351) educational optimism in terms of their trust in the possibilities of school to develop children's intelligence. It was found that educational optimism could be depicted as a bipolar factor with optimism and pessimism on the opposing ends of the same dimension. Optimistic parents indicated more satisfaction…

A Two-Stage Robust Optimization for Centralized-Optimal Dispatch of Photovoltaic Inverters in Active Distribution Networks

DEFF Research Database (Denmark)

Ding, Tao; Li, Cheng; Yang, Yongheng

2017-01-01

Optimally dispatching Photovoltaic (PV) inverters is an efficient way to avoid overvoltage in active distribution networks, which may occur in the case of PV generation surplus load demand. Typically, the dispatching optimization objective is to identify critical PV inverters that have the most...... nature of solar PV energy may affect the selection of the critical PV inverters and also the final optimal objective value. In order to address this issue, a two-stage robust optimization model is proposed in this paper to achieve a robust optimal solution to the PV inverter dispatch, which can hedge...... against any possible realization within the uncertain PV outputs. In addition, the conic relaxation-based branch flow formulation and second-order cone programming based column-and-constraint generation algorithm are employed to deal with the proposed robust optimization model. Case studies on a 33-bus...

Optimization under Uncertainty

KAUST Repository

Lopez, Rafael H.

2016-01-06

The goal of this poster is to present the main approaches to optimization of engineering systems in the presence of uncertainties. We begin by giving an insight about robust optimization. Next, we detail how to deal with probabilistic constraints in optimization, the so called the reliability based design. Subsequently, we present the risk optimization approach, which includes the expected costs of failure in the objective function. After that the basic description of each approach is given, the projects developed by CORE are presented. Finally, the main current topic of research of CORE is described.

Optimal observables and phase-space ambiguities

International Nuclear Information System (INIS)

Nachtmann, O.; Nagel, F.

2005-01-01

Optimal observables are known to lead to minimal statistical errors on parameters for a given normalised event distribution of a physics reaction. Thereby all statistical correlations are taken into account. Therefore, on the one hand they are a useful tool to extract values on a set of parameters from measured data. On the other hand one can calculate the minimal constraints on these parameters achievable by any data-analysis method for the specific reaction. In case the final states can be reconstructed without ambiguities optimal observables have a particularly simple form. We give explicit formulae for the optimal observables for generic reactions in case of ambiguities in the reconstruction of the final state and for general parameterisation of the final-state phase space. (orig.)

Study on Electricity Purchase Optimization in Coordination of Electricity and Carbon Trading

Science.gov (United States)

Liu, Dunnan; Meng, Yaru; Zhang, Shuo

2017-07-01

With the establishment of carbon emissions trading market in China, the power industry has become an important part of the market participants. The power grid enterprises need to optimize their own strategies in the new environment of electricity market and carbon market coordination. First, the influence of electricity and carbon trading coordination on electricity purchase strategy for grid enterprises was analysed in the paper. Then a power purchase optimization model was presented, which used the minimum cost of low carbon, energy saving and environment protection as the goal, the power generation capacity, installed capacity and pollutant emission as the constraints. Finally, a provincial power grid was taken as an example to analyse the model, and the optimization order of power purchase was obtained, which provided a new idea for the low carbon development of power grid enterprises.

An optimal generic model for multi-parameters and big data optimizing: a laboratory experimental study

Science.gov (United States)

Utama, D. N.; Ani, N.; Iqbal, M. M.

2018-03-01

Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

Science.gov (United States)

Jin, Junchen

2016-01-01

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Jiaxi Wang

2016-01-01

Full Text Available The shunting schedule of electric multiple units depot (SSED is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality.

Symbiotic Optimization of Behavior

Science.gov (United States)

2015-05-01

SYMBIOTIC OPTIMIZATION OF BEHAVIOR UNIVERSITY OF WASHINGTON MAY 2015 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED...2014 4. TITLE AND SUBTITLE SYMBIOTIC OPTIMIZATION OF BEHAVIOR 5a. CONTRACT NUMBER FA8750-12-1-0304 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT

A New Hybrid Nelder-Mead Particle Swarm Optimization for Coordination Optimization of Directional Overcurrent Relays

Directory of Open Access Journals (Sweden)

An Liu

2012-01-01

Full Text Available Coordination optimization of directional overcurrent relays (DOCRs is an important part of an efficient distribution system. This optimization problem involves obtaining the time dial setting (TDS and pickup current (Ip values of each DOCR. The optimal results should have the shortest primary relay operating time for all fault lines. Recently, the particle swarm optimization (PSO algorithm has been considered an effective tool for linear/nonlinear optimization problems with application in the protection and coordination of power systems. With a limited runtime period, the conventional PSO considers the optimal solution as the final solution, and an early convergence of PSO results in decreased overall performance and an increase in the risk of mistaking local optima for global optima. Therefore, this study proposes a new hybrid Nelder-Mead simplex search method and particle swarm optimization (proposed NM-PSO algorithm to solve the DOCR coordination optimization problem. PSO is the main optimizer, and the Nelder-Mead simplex search method is used to improve the efficiency of PSO due to its potential for rapid convergence. To validate the proposal, this study compared the performance of the proposed algorithm with that of PSO and original NM-PSO. The findings demonstrate the outstanding performance of the proposed NM-PSO in terms of computation speed, rate of convergence, and feasibility.

Final Report---Optimization Under Nonconvexity and Uncertainty: Algorithms and Software

Energy Technology Data Exchange (ETDEWEB)

Jeff Linderoth

2011-11-06

the goal of this work was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems. The focus of the work done in the continuation was on Mixed Integer Nonlinear Programs (MINLP)s and Mixed Integer Linear Programs (MILP)s, especially those containing a great deal of symmetry.

Solid Rocket Motor Design Using Hybrid Optimization

Directory of Open Access Journals (Sweden)

Kevin Albarado

2012-01-01

Full Text Available A particle swarm/pattern search hybrid optimizer was used to drive a solid rocket motor modeling code to an optimal solution. The solid motor code models tapered motor geometries using analytical burn back methods by slicing the grain into thin sections along the axial direction. Grains with circular perforated stars, wagon wheels, and dog bones can be considered and multiple tapered sections can be constructed. The hybrid approach to optimization is capable of exploring large areas of the solution space through particle swarming, but is also able to climb “hills” of optimality through gradient based pattern searching. A preliminary method for designing tapered internal geometry as well as tapered outer mold-line geometry is presented. A total of four optimization cases were performed. The first two case studies examines designing motors to match a given regressive-progressive-regressive burn profile. The third case study studies designing a neutrally burning right circular perforated grain (utilizing inner and external geometry tapering. The final case study studies designing a linearly regressive burning profile for right circular perforated (tapered grains.

Study on poloidal field coil optimization and equilibrium control of ITER

International Nuclear Information System (INIS)

Shinya, Kichiro; Sugihara, Masayoshi; Nishio, Satoshi

1989-03-01

The purpose of this report is to present general features of the poloidal field coil optimization for the ITER plasma, flexibility analysis for various plasma options and some other aspect of the equilibrium control which is required for understanding plasma operation in more detail. Double null divertor plasma was selected as a main object of the optimization. Single null divertor plasma was assumed to be an alternative, because single null divertor plasma can be operational within the amounts of the total stored energy and ampere-turns of the double null divertor plasma, if it is shaped appropriately. Plasma parameters used in the present analysis are mainly those employed in the preliminary study by the Basic Device Engineering group of the ITER design team. The most part of the optimization study, however, utilizes the parameters proposed for discussion by the Japan team before starting joint design work at Garching. Plasma shape, and solenoid coil shape and size, which maximize available flux swing with reasonable amounts of the stored energy and ampere-turns, are discussed. Location and minimum number of the poloidal field coils with adequate shaping controllability were also discussed for various plasma options. Some other aspect of the equilibrium control, such as separatrix swing, moving null point operation during plasma heating and possible range of li, were evaluated and the guideline for the engineering design was proposed. Finally, fusion power output was estimated for the different pressure profiles and combinations of the average density and temperature, and the magnetic quantities of the scrape-off region was calculated to be available for the future divertor analysis. (author)

Final Report A Multi-Language Environment For Programmable Code Optimization and Empirical Tuning

Energy Technology Data Exchange (ETDEWEB)

Yi, Qing [Univ. of Colorado, Colorado Springs, CO (United States); Whaley, Richard Clint [Univ. of Texas, San Antonio, TX (United States); Qasem, Apan [Texas State Univ., San Marcos, TX (United States); Quinlan, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2013-11-23

This report summarizes our effort and results of building an integrated optimization environment to effectively combine the programmable control and the empirical tuning of source-to-source compiler optimizations within the framework of multiple existing languages, specifically C, C++, and Fortran. The environment contains two main components: the ROSE analysis engine, which is based on the ROSE C/C++/Fortran2003 source-to-source compiler developed by Co-PI Dr.Quinlan et. al at DOE/LLNL, and the POET transformation engine, which is based on an interpreted program transformation language developed by Dr. Yi at University of Texas at San Antonio (UTSA). The ROSE analysis engine performs advanced compiler analysis, identifies profitable code transformations, and then produces output in POET, a language designed to provide programmable control of compiler optimizations to application developers and to support the parameterization of architecture-sensitive optimizations so that their configurations can be empirically tuned later. This POET output can then be ported to different machines together with the user application, where a POET-based search engine empirically reconfigures the parameterized optimizations until satisfactory performance is found. Computational specialists can write POET scripts to directly control the optimization of their code. Application developers can interact with ROSE to obtain optimization feedback as well as provide domain-specific knowledge and high-level optimization strategies. The optimization environment is expected to support different levels of automation and programmer intervention, from fully-automated tuning to semi-automated development and to manual programmable control.

Advanced commercial Tokamak optimization studies

International Nuclear Information System (INIS)

Whitley, R.H.; Berwald, D.H.; Gordon, J.D.

1985-01-01

Our recent studies have concentrated on developing optimal high beta (bean-shaped plasma) commercial tokamak configurations using TRW's Tokamak Reactor Systems Code (TRSC) with special emphasis on lower net electric power reactors that are more easily deployable. A wide range of issues were investigated in the search for the most economic configuration: fusion power, reactor size, wall load, magnet type, inboard blanket and shield thickness, plasma aspect ratio, and operational β value. The costs and configurations of both steady-state and pulsed reactors were also investigated. Optimal small and large reactor concepts were developed and compared by studying the cost of electricity from single units and from multiplexed units. Multiplexed units appear to have advantages because they share some plant equipment and have lower initial capital investment as compared to larger single units

Systematic study of source mask optimization and verification flows

Science.gov (United States)

Ben, Yu; Latypov, Azat; Chua, Gek Soon; Zou, Yi

2012-06-01

Source mask optimization (SMO) emerged as powerful resolution enhancement technique (RET) for advanced technology nodes. However, there is a plethora of flow and verification metrics in the field, confounding the end user of the technique. Systemic study of different flows and the possible unification thereof is missing. This contribution is intended to reveal the pros and cons of different SMO approaches and verification metrics, understand the commonality and difference, and provide a generic guideline for RET selection via SMO. The paper discusses 3 different type of variations commonly arise in SMO, namely pattern preparation & selection, availability of relevant OPC recipe for freeform source and finally the metrics used in source verification. Several pattern selection algorithms are compared and advantages of systematic pattern selection algorithms are discussed. In the absence of a full resist model for SMO, alternative SMO flow without full resist model is reviewed. Preferred verification flow with quality metrics of DOF and MEEF is examined.

Optimal Control and Optimization of Stochastic Supply Chain Systems

CERN Document Server

Song, Dong-Ping

2013-01-01

Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject in the context of the presence of a variety of uncertainties. Numerous examples with intuitive illustrations and tables are provided, to demonstrate the structural characteristics of the optimal control policies in various stochastic supply chains and to show how to make use of these characteristics to construct easy-to-operate sub-optimal policies.                 In Part I, a general introduction to stochastic supply chain systems is provided. Analytical models for various stochastic supply chain systems are formulated and analysed in Part II. In Part III the structural knowledge of the optimal control policies obtained in Part II is utilized to construct easy-to-operate sub-optimal control policies for various stochastic supply chain systems accordingly. Finally, Part IV discusses the optimisation of threshold-type control policies and their robustness. A key feature of the book is its tying together of ...

National Computational Infrastructure for Lattice Gauge Theory: Final Report

International Nuclear Information System (INIS)

Richard Brower; Norman Christ; Michael Creutz; Paul Mackenzie; John Negele; Claudio Rebbi; David Richards; Stephen Sharpe; Robert Sugar

2006-01-01

This is the final report of Department of Energy SciDAC Grant ''National Computational Infrastructure for Lattice Gauge Theory''. It describes the software developed under this grant, which enables the effective use of a wide variety of supercomputers for the study of lattice quantum chromodynamics (lattice QCD). It also describes the research on and development of commodity clusters optimized for the study of QCD. Finally, it provides some high lights of research enabled by the infrastructure created under this grant, as well as a full list of the papers resulting from research that made use of this infrastructure

Design and optimization of food processing conditions

OpenAIRE

Silva, C. L. M.

1996-01-01

The main research objectives of the group are the design and optimization of food processing conditions. Most of the work already developed is on the use of mathematical modeling of transport phenomena and quantification of degradation kinetics as two tools to optimize the final quality of thermally processed food products. Recently, we initiated a project with the main goal of studying the effects of freezing and frozen storage on orange and melon juice pectinesterase activity and q...

DESIGN OPTIMIZATION OF A FOOT VALVE BY USING ANSYS®

Directory of Open Access Journals (Sweden)

Serdar KARAOĞLU

2008-02-01

Full Text Available In this study, main components of a foot valve, being produced by casting, were optimized for minimum weight. The study was focused on the minimization of casting costs by reducing the volumes of two main parts of the foot valve. ANSYS® finite elements package was used in the study. In the optimization stage, parametrical dimensions were determined according to manufacturer's design criteria and related standards. Final design of the foot valve was completed by using the calculated values of optimum dimensions of the main components. Design optimization procedure gave about 8.5% of weight reductions in the main foot valve components.

Optimal Set-Point Synthesis in HVAC Systems

DEFF Research Database (Denmark)

Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

2007-01-01

This paper presents optimal set-point synthesis for a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger and a water-to-air heat exchanger. The objective function is composed of the electrical power for different...... components, encompassing fans, primary/secondary pump, tertiary pump, and air-to-air heat exchanger wheel; and a fraction of thermal power used by the HVAC system. The goals that have to be achieved by the HVAC system appear as constraints in the optimization problem. To solve the optimization problem......, a steady state model of the HVAC system is derived while different supplying hydronic circuits are studied for the water-to-air heat exchanger. Finally, the optimal set-points and the optimal supplying hydronic circuit are resulted....

Interactive Topology Optimization

DEFF Research Database (Denmark)

Nobel-Jørgensen, Morten

Interactivity is the continuous interaction between the user and the application to solve a task. Topology optimization is the optimization of structures in order to improve stiffness or other objectives. The goal of the thesis is to explore how topology optimization can be used in applications...... on theory of from human-computer interaction which is described in Chapter 2. Followed by a description of the foundations of topology optimization in Chapter 3. Our applications for topology optimization in 2D and 3D are described in Chapter 4 and a game which trains the human intuition of topology...... optimization is presented in Chapter 5. Topology optimization can also be used as an interactive modeling tool with local control which is presented in Chapter 6. Finally, Chapter 7 contains a summary of the findings and concludes the dissertation. Most of the presented applications of the thesis are available...

Optimal processing of reversible quantum channels

Energy Technology Data Exchange (ETDEWEB)

Bisio, Alessandro, E-mail: alessandro.bisio@unipv.it [QUIT Group, Dipartimento di Fisica, INFN Sezione di Pavia, via Bassi 6, 27100 Pavia (Italy); D' Ariano, Giacomo Mauro; Perinotti, Paolo [QUIT Group, Dipartimento di Fisica, INFN Sezione di Pavia, via Bassi 6, 27100 Pavia (Italy); Sedlák, Michal [Department of Optics, Palacký University, 17. Listopadu 1192/12, CZ-771 46 Olomouc (Czech Republic); Institute of Physics, Slovak Academy of Sciences, Dúbravská Cesta 9, 845 11 Bratislava (Slovakia)

2014-05-01

We consider the general problem of the optimal transformation of N uses of (possibly different) unitary channels to a single use of another unitary channel in any finite dimension. We show how the optimal transformation can be fully parallelized, consisting in a preprocessing channel followed by a parallel action of all the N unitaries and a final postprocessing channel. Our techniques allow to achieve an exponential reduction in the number of the free parameters of the optimization problem making it amenable to an efficient numerical treatment. Finally, we apply our general results to find the analytical solution for special cases of interest like the cloning of qubit phase gates.

Expanded studies of linear collider final focus systems at the Final Focus Test Beam

International Nuclear Information System (INIS)

Tenenbaum, P.G.

1995-12-01

In order to meet their luminosity goals, linear colliders operating in the center-of-mass energy range from 3,50 to 1,500 GeV will need to deliver beams which are as small as a few Manometers tall, with x:y aspect ratios as large as 100. The Final Focus Test Beam (FFTB) is a prototype for the final focus demanded by these colliders: its purpose is to provide demagnification equivalent to those in the future linear collider, which corresponds to a focused spot size in the FFTB of 1.7 microns (horizontal) by 60 manometers (vertical). In order to achieve the desired spot sizes, the FFTB beam optics must be tuned to eliminate aberrations and other errors, and to ensure that the optics conform to the desired final conditions and the measured initial conditions of the beam. Using a combination of incoming-beam diagnostics. beam-based local diagnostics, and global tuning algorithms, the FFTB beam size has been reduced to a stable final size of 1.7 microns by 70 manometers. In addition, the chromatic properties of the FFTB have been studied using two techniques and found to be acceptable. Descriptions of the hardware and techniques used in these studies are presented, along with results and suggestions for future research

Expanded studies of linear collider final focus systems at the Final Focus Test Beam

Energy Technology Data Exchange (ETDEWEB)

Tenenbaum, Peter Gregory [Stanford Univ., CA (United States)

1995-12-01

In order to meet their luminosity goals, linear colliders operating in the center-of-mass energy range from 3,50 to 1,500 GeV will need to deliver beams which are as small as a few Manometers tall, with x:y aspect ratios as large as 100. The Final Focus Test Beam (FFTB) is a prototype for the final focus demanded by these colliders: its purpose is to provide demagnification equivalent to those in the future linear collider, which corresponds to a focused spot size in the FFTB of 1.7 microns (horizontal) by 60 manometers (vertical). In order to achieve the desired spot sizes, the FFTB beam optics must be tuned to eliminate aberrations and other errors, and to ensure that the optics conform to the desired final conditions and the measured initial conditions of the beam. Using a combination of incoming-beam diagnostics. beam-based local diagnostics, and global tuning algorithms, the FFTB beam size has been reduced to a stable final size of 1.7 microns by 70 manometers. In addition, the chromatic properties of the FFTB have been studied using two techniques and found to be acceptable. Descriptions of the hardware and techniques used in these studies are presented, along with results and suggestions for future research.

Study on high-speed cutting parameters optimization of AlMn1Cu based on neural network and genetic algorithm

Directory of Open Access Journals (Sweden)

Zhenhua Wang

2016-04-01

Full Text Available In this article, the cutting parameters optimization method for aluminum alloy AlMn1Cu in high-speed milling was studied in order to properly select the high-speed cutting parameters. First, a back propagation neural network model for predicting surface roughness of AlMn1Cu was proposed. The prediction model can improve the prediction accuracy and well work out the higher-order nonlinear relationship between surface roughness and cutting parameters. Second, considering the constraints of technical requirements on surface roughness, a mathematical model for optimizing cutting parameters based on the Bayesian neural network prediction model of surface roughness was established so as to obtain the maximum machining efficiency. The genetic algorithm adopting the homogeneous design to initialize population as well as steady-state reproduction without duplicates was also presented. The application indicates that the algorithm can effectively avoid precocity, strengthen global optimization, and increase the calculation efficiency. Finally, a case was presented on the application of the proposed cutting parameters optimization algorithm to optimize the cutting parameters.

Topology optimized permanent magnet systems

DEFF Research Database (Denmark)

Bjørk, Rasmus; Bahl, Christian; Insinga, Andrea Roberto

2017-01-01

Topology optimization of permanent magnet systems consisting of permanent magnets, high permeability iron and air is presented. An implementation of topology optimization for magnetostatics is discussed and three examples are considered. The Halbach cylinder is topology optimized with iron...... and an increase of 15% in magnetic efficiency is shown. A topology optimized structure to concentrate a homogeneous field is shown to increase the magnitude of the field by 111%. Finally, a permanent magnet with alternating high and low field regions is topology optimized and a ΛcoolΛcool figure of merit of 0...

Asymptotic Normality of the Optimal Solution in Multiresponse Surface Mathematical Programming

OpenAIRE

Díaz-García, José A.; Caro-Lopera, Francisco J.

2015-01-01

An explicit form for the perturbation effect on the matrix of regression coeffi- cients on the optimal solution in multiresponse surface methodology is obtained in this paper. Then, the sensitivity analysis of the optimal solution is studied and the critical point characterisation of the convex program, associated with the optimum of a multiresponse surface, is also analysed. Finally, the asymptotic normality of the optimal solution is derived by the standard methods.

A Novel Optimal Control Method for Impulsive-Correction Projectile Based on Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Ruisheng Sun

2016-01-01

Full Text Available This paper presents a new parametric optimization approach based on a modified particle swarm optimization (PSO to design a class of impulsive-correction projectiles with discrete, flexible-time interval, and finite-energy control. In terms of optimal control theory, the task is described as the formulation of minimum working number of impulses and minimum control error, which involves reference model linearization, boundary conditions, and discontinuous objective function. These result in difficulties in finding the global optimum solution by directly utilizing any other optimization approaches, for example, Hp-adaptive pseudospectral method. Consequently, PSO mechanism is employed for optimal setting of impulsive control by considering the time intervals between two neighboring lateral impulses as design variables, which makes the briefness of the optimization process. A modification on basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. In addition, a suboptimal control and guidance law based on PSO technique are put forward for the real-time consideration of the online design in practice. Finally, a simulation case coupled with a nonlinear flight dynamic model is applied to validate the modified PSO control algorithm. The results of comparative study illustrate that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately and provides a reference approach to handling such impulsive-correction problem.

Final Report on Pilot Studies / Final Report on Classroom Research with STEM and TESL Assessment

DEFF Research Database (Denmark)

Biel, Carmen; Wake, Jo Dugstad; Hesse, Friedrich

This Deliverable is the final report on pilot studies within the NEXT-TELL project (D6.7) and furthermore comprises the Deliverable on Classroom Research with STEM and TESL Assessment (D2.9) in order to avoid redundancies between those two Deliverables.......This Deliverable is the final report on pilot studies within the NEXT-TELL project (D6.7) and furthermore comprises the Deliverable on Classroom Research with STEM and TESL Assessment (D2.9) in order to avoid redundancies between those two Deliverables....

Optimization studies on the calorimetric second level tau trigger of the ATLAS experiment at the Large Hadron Collider

CERN Document Server

Perez Codina, Estel

2008-01-01

Moving to the high energy regime of LHC, the identification of tau leptons will become an important and very powerful tool, allowing the discovery of physics beyond the Standard Model. Many models, light SM Higgs and various SUSY models among them, predict an abundant production of taus with respect to other leptons. The ATLAS collaboration has developed tools to efficiently identify tau at trigger level, based on the advanced calorimetry and tracking capabilities. The work presented in this Master Thesis is focused on the optimization of the first trigger level energy thresholds and the second trigger level calorimetric variables. A systematic optimization is designed, which allows us to study the robustness of the trigger selection. The improvements achieved by using a sampling energy calibration are discussed. Finally, an optimization on the size of the calorimeter region used to calculate the trigger variables is performed.

Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

Directory of Open Access Journals (Sweden)

Yan Sun

2015-09-01

Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

Topology optimized permanent magnet systems

Science.gov (United States)

Bjørk, R.; Bahl, C. R. H.; Insinga, A. R.

2017-09-01

Topology optimization of permanent magnet systems consisting of permanent magnets, high permeability iron and air is presented. An implementation of topology optimization for magnetostatics is discussed and three examples are considered. The Halbach cylinder is topology optimized with iron and an increase of 15% in magnetic efficiency is shown. A topology optimized structure to concentrate a homogeneous field is shown to increase the magnitude of the field by 111%. Finally, a permanent magnet with alternating high and low field regions is topology optimized and a Λcool figure of merit of 0.472 is reached, which is an increase of 100% compared to a previous optimized design.

Space engineering modeling and optimization with case studies

CERN Document Server

Pintér, János

2016-01-01

This book presents a selection of advanced case studies that cover a substantial range of issues and real-world challenges and applications in space engineering. Vital mathematical modeling, optimization methodologies and numerical solution aspects of each application case study are presented in detail, with discussions of a range of advanced model development and solution techniques and tools. Space engineering challenges are discussed in the following contexts: •Advanced Space Vehicle Design •Computation of Optimal Low Thrust Transfers •Indirect Optimization of Spacecraft Trajectories •Resource-Constrained Scheduling, •Packing Problems in Space •Design of Complex Interplanetary Trajectories •Satellite Constellation Image Acquisition •Re-entry Test Vehicle Configuration Selection •Collision Risk Assessment on Perturbed Orbits •Optimal Robust Design of Hybrid Rocket Engines •Nonlinear Regression Analysis in Space Engineering< •Regression-Based Sensitivity Analysis and Robust Design ...

Optimization of a fuel bundle within a CANDU supercritical water reactor

International Nuclear Information System (INIS)

Schofield, M.E.

2009-01-01

The supercritical water reactor is one of six nuclear reactor concepts being studied under the Generation IV International Forum. Generation IV nuclear reactors will improve the metrics of economics, sustainability, safety and reliability, and physical protection and proliferation resistance over current nuclear reactor designs. The supercritical water reactor has specific benefits in the areas of economics, safety and reliability, and physical protection. This work optimizes the fuel composition and bundle geometry to maximize the fuel burnup, and minimize the surface heat flux and the form factor. In optimizing these factors, improvements can be achieved in the areas of economics, safety and reliability of the supercritical water reactor. The WIMS-AECL software was used to model a fuel bundle within a CANDU supercritical water reactor. The Gauss' steepest descent method was used to optimize the above mentioned factors. Initially the fresh fuel composition was optimized within a 43-rod CANFLEX bundle and a 61-rod bundle. In both the 43-rod and 61-rod bundle scenarios an online refuelling scheme and non-refuelling scheme were studied. The geometry of the fuel bundles was then optimized. Finally, a homogeneous mixture of thorium and uranium fuel was studied in a 60-rod bundle. Each optimization process showed definitive improvements in the factors being studied, with the most significant improvement being an increase in the fuel burnup. The 43-rod CANFLEX bundle was the most successful at being optimized. There was little difference in the final fresh fuel content when comparing an online refuelling scheme and non-refuelling scheme. Through each optimization scenario the ratio of the fresh fuel content between the annuli was a significant determining cause in the improvements in the factors being optimized. The geometry optimization showed that improvement in the design of a fuel bundle is indeed possible, although it would be more advantageous to pursue it

Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach.

Science.gov (United States)

Zhang, Huaguang; Feng, Tao; Yang, Guang-Hong; Liang, Hongjing

2015-07-01

In this paper, the inverse optimal approach is employed to design distributed consensus protocols that guarantee consensus and global optimality with respect to some quadratic performance indexes for identical linear systems on a directed graph. The inverse optimal theory is developed by introducing the notion of partial stability. As a result, the necessary and sufficient conditions for inverse optimality are proposed. By means of the developed inverse optimal theory, the necessary and sufficient conditions are established for globally optimal cooperative control problems on directed graphs. Basic optimal cooperative design procedures are given based on asymptotic properties of the resulting optimal distributed consensus protocols, and the multiagent systems can reach desired consensus performance (convergence rate and damping rate) asymptotically. Finally, two examples are given to illustrate the effectiveness of the proposed methods.

N-Springs pump and treat system optimization study

International Nuclear Information System (INIS)

1997-03-01

This letter report describes and presents the results of a system optimization study conducted to evaluate the N-Springs pump and treat system. The N-Springs pump and treat is designed to remove strontium-90 (90Sr) found in the groundwater in the 100-NR-2 Operable Unit near the Columbia River. The goal of the system optimization study was to assess and quantify what conditions and operating parameters could be employed to enhance the operating and cost effectiveness of the recently upgraded pump and treat system.This report provides the results of the system optimization study, reports the cost effectiveness of operating the pump and treat at various operating modes and 90Sr removal goals, and provides recommendations for operating the pump and treat

Optimal Sensor Placement for Latticed Shell Structure Based on an Improved Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Xun Zhang

2014-01-01

Full Text Available Optimal sensor placement is a key issue in the structural health monitoring of large-scale structures. However, some aspects in existing approaches require improvement, such as the empirical and unreliable selection of mode and sensor numbers and time-consuming computation. A novel improved particle swarm optimization (IPSO algorithm is proposed to address these problems. The approach firstly employs the cumulative effective modal mass participation ratio to select mode number. Three strategies are then adopted to improve the PSO algorithm. Finally, the IPSO algorithm is utilized to determine the optimal sensors number and configurations. A case study of a latticed shell model is implemented to verify the feasibility of the proposed algorithm and four different PSO algorithms. The effective independence method is also taken as a contrast experiment. The comparison results show that the optimal placement schemes obtained by the PSO algorithms are valid, and the proposed IPSO algorithm has better enhancement in convergence speed and precision.

A study of optical design and optimization of laser optics

Science.gov (United States)

Tsai, C.-M.; Fang, Yi-Chin

2013-09-01

This paper propose a study of optical design of laser beam shaping optics with aspheric surface and application of genetic algorithm (GA) to find the optimal results. Nd: YAG 355 waveband laser flat-top optical system, this study employed the Light tools LDS (least damped square) and the GA of artificial intelligence optimization method to determine the optimal aspheric coefficient and obtain the optimal solution. This study applied the aspheric lens with GA for the flattening of laser beams using collimated laser beam light, aspheric lenses in order to achieve best results.

Optimizing Bus Frequencies under Uncertain Demand: Case Study of the Transit Network in a Developing City

Directory of Open Access Journals (Sweden)

Zhengfeng Huang

2013-01-01

Full Text Available Various factors can make predicting bus passenger demand uncertain. In this study, a bilevel programming model for optimizing bus frequencies based on uncertain bus passenger demand is formulated. There are two terms constituting the upper-level objective. The first is transit network cost, consisting of the passengers’ expected travel time and operating costs, and the second is transit network robustness performance, indicated by the variance in passenger travel time. The second term reflects the risk aversion of decision maker, and it can make the most uncertain demand be met by the bus operation with the optimal transit frequency. With transit link’s proportional flow eigenvalues (mean and covariance obtained from the lower-level model, the upper-level objective is formulated by the analytical method. In the lower-level model, the above two eigenvalues are calculated by analyzing the propagation of mean transit trips and their variation in the optimal strategy transit assignment process. The genetic algorithm (GA used to solve the model is tested in an example network. Finally, the model is applied to determining optimal bus frequencies in the city of Liupanshui, China. The total cost of the transit system in Liupanshui can be reduced by about 6% via this method.

Characterization and validation of the thorax phantom Lungman for dose assessment in chest radiography optimization studies.

Science.gov (United States)

Rodríguez Pérez, Sunay; Marshall, Nicholas William; Struelens, Lara; Bosmans, Hilde

2018-01-01

This work concerns the validation of the Kyoto-Kagaku thorax anthropomorphic phantom Lungman for use in chest radiography optimization. The equivalence in terms of polymethyl methacrylate (PMMA) was established for the lung and mediastinum regions of the phantom. Patient chest examination data acquired under automatic exposure control were collated over a 2-year period for a standard x-ray room. Parameters surveyed included exposure index, air kerma area product, and exposure time, which were compared with Lungman values. Finally, a voxel model was developed by segmenting computed tomography images of the phantom and implemented in PENELOPE/penEasy Monte Carlo code to compare phantom tissue-equivalent materials with materials from ICRP Publication 89 in terms of organ dose. PMMA equivalence varied depending on tube voltage, from 9.5 to 10.0 cm and from 13.5 to 13.7 cm, for the lungs and mediastinum regions, respectively. For the survey, close agreement was found between the phantom and the patients' median values (deviations lay between 8% and 14%). Differences in lung doses, an important organ for optimization in chest radiography, were below 13% when comparing the use of phantom tissue-equivalent materials versus ICRP materials. The study confirms the value of the Lungman for chest optimization studies.

Bayesian optimization for materials science

CERN Document Server

Packwood, Daniel

2017-01-01

This book provides a short and concise introduction to Bayesian optimization specifically for experimental and computational materials scientists. After explaining the basic idea behind Bayesian optimization and some applications to materials science in Chapter 1, the mathematical theory of Bayesian optimization is outlined in Chapter 2. Finally, Chapter 3 discusses an application of Bayesian optimization to a complicated structure optimization problem in computational surface science. Bayesian optimization is a promising global optimization technique that originates in the field of machine learning and is starting to gain attention in materials science. For the purpose of materials design, Bayesian optimization can be used to predict new materials with novel properties without extensive screening of candidate materials. For the purpose of computational materials science, Bayesian optimization can be incorporated into first-principles calculations to perform efficient, global structure optimizations. While re...

Topology Optimization - Engineering Contribution to Architectural Design

Science.gov (United States)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

The idea of the topology optimization is to find within a considered design domain the distribution of material that is optimal in some sense. Material, during optimization process, is redistributed and parts that are not necessary from objective point of view are removed. The result is a solid/void structure, for which an objective function is minimized. This paper presents an application of topology optimization to multi-material structures. The design domain defined by shape of a structure is divided into sub-regions, for which different materials are assigned. During design process material is relocated, but only within selected region. The proposed idea has been inspired by architectural designs like multi-material facades of buildings. The effectiveness of topology optimization is determined by proper choice of numerical optimization algorithm. This paper utilises very efficient heuristic method called Cellular Automata. Cellular Automata are mathematical, discrete idealization of a physical systems. Engineering implementation of Cellular Automata requires decomposition of the design domain into a uniform lattice of cells. It is assumed, that the interaction between cells takes place only within the neighbouring cells. The interaction is governed by simple, local update rules, which are based on heuristics or physical laws. The numerical studies show, that this method can be attractive alternative to traditional gradient-based algorithms. The proposed approach is evaluated by selected numerical examples of multi-material bridge structures, for which various material configurations are examined. The numerical studies demonstrated a significant influence the material sub-regions location on the final topologies. The influence of assumed volume fraction on final topologies for multi-material structures is also observed and discussed. The results of numerical calculations show, that this approach produces different results as compared with classical one

Optimal Design of Porous Materials

DEFF Research Database (Denmark)

Andreassen, Erik

The focus of this thesis is topology optimization of material microstructures. That is, creating new materials, with attractive properties, by combining classic materials in periodic patterns. First, large-scale topology optimization is used to design complicated three-dimensional materials......, throughout the thesis extra attention is given to obtain structures that can be manufactured. That is also the case in the final part, where a simple multiscale method for the optimization of structural damping is presented. The method can be used to obtain an optimized component with structural details...

Procedure and methodology of Radiation Protection optimization

International Nuclear Information System (INIS)

Wang Hengde

1995-01-01

Optimization of Radiation Protection is one of the most important principles in the system of radiation protection. The paper introduces the basic principles of radiation protection optimization in general, and the procedure of implementing radiation protection optimization and methods of selecting the optimized radiation protection option in details, in accordance with ICRP 55. Finally, some economic concepts relating to estimation of costs are discussed briefly

Optimization of Enzymatic Hydrolysis of Waste Bread before Fermentation

OpenAIRE

Hudečková, Helena; Šupinová, Petra; Ing. Mgr. Libor Babák, Ph.D., MBA

2017-01-01

Finding of optimal hydrolysis conditions is important for increasing the yield of saccharides. The higher yield of saccharides is usable for increase of the following fermentation effectivity. In this study optimal conditions (pH and temperature) for amylolytic enzymes were searched. As raw material was used waste bread. Two analytical methods for analysis were used. Efficiency and process of hydrolysis was analysed spectrophotometrically by Somogyi-Nelson method. Final yields of glucose were...

Well pattern optimization in a low permeability sandstone reservoir: a case study from Erlian Basin in China

Science.gov (United States)

Wang, Xia; Fu, Lixia; Yan, Aihua; Guo, Fajun; Wu, Cong; Chen, Hong; Wang, Xinying; Lu, Ming

2018-02-01

Study on optimization of development well patterns is the core content of oilfield development and is a prerequisite for rational and effective development of oilfield. The study on well pattern optimization mainly includes types of well patterns and density of well patterns. This paper takes the Aer-3 fault block as an example. Firstly, models were built for diamond-shaped inverted 9-spot patterns, rectangular 5-spot patterns, square inverted 9-spot patterns and inverted 7-spot patterns under the same well pattern density to correlate the effect of different well patterns on development; secondly, comprehensive analysis was conducted to well pattern density in terms of economy and technology using such methods as oil reservoir engineering, numerical simulation, economic limits and economic rationality. Finally, the development mode of vertical well + horizontal well was presented according to the characteristics of oil reservoirs in some well blocks, which has realized efficient development of this fault block.

Implementing of the multi-objective particle swarm optimizer and fuzzy decision-maker in exergetic, exergoeconomic and environmental optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn; Babaie, Meisam; Farmani, Mohammad Reza

2011-01-01

Multi-objective optimization for design of a benchmark cogeneration system namely as the CGAM cogeneration system is performed. In optimization approach, Exergetic, Exergoeconomic and Environmental objectives are considered, simultaneously. In this regard, the set of Pareto optimal solutions known as the Pareto frontier is obtained using the MOPSO (multi-objective particle swarm optimizer). The exergetic efficiency as an exergetic objective is maximized while the unit cost of the system product and the cost of the environmental impact respectively as exergoeconomic and environmental objectives are minimized. Economic model which is utilized in the exergoeconomic analysis is built based on both simple model (used in original researches of the CGAM system) and the comprehensive modeling namely as TTR (total revenue requirement) method (used in sophisticated exergoeconomic analysis). Finally, a final optimal solution from optimal set of the Pareto frontier is selected using a fuzzy decision-making process based on the Bellman-Zadeh approach and results are compared with corresponding results obtained in a traditional decision-making process. Further, results are compared with the corresponding performance of the base case CGAM system and optimal designs of previous works and discussed. -- Highlights: → A multi-objective optimization approach has been implemented in optimization of a benchmark cogeneration system. → Objective functions based on the environmental impact evaluation, thermodynamic and economic analysis are obtained and optimized. → Particle swarm optimizer implemented and its robustness is compared with NSGA-II. → A final optimal configuration is found using various decision-making approaches. → Results compared with previous works in the field.

Technical Design and Optimization Study for the FERMI at Elettra FEL Photoinjector

International Nuclear Information System (INIS)

Lidia, Steven M.; Penco, Giuseppe; Trovo', Mauro

2006-01-01

The FERMI (at) Elettra FEL project will provide a novel, x-ray free electron laser user facility at Sincrotrone Trieste based on seeded and cascade FEL techniques. The electron beam source and injector systems play a crucial role in the success of the facility by providing the highest quality electron beams to the linac and FEL undulators. This Technical Note examines the critical technology components that make up the injector system, and demonstrates optimum beam dynamics solutions to achieve the required high quality electron beams. Section 2 provides an overview of the various systems and subsystems that comprise the photoinjector. The different operating modes of the injector are described as they pertain to the different linac configurations driven by the FEL and experimental design. For each mode, the required electron beam parameters are given. Sections 3 and 4 describe the critical beamline elements in the injector complex: the photocathode and drive laser, and the RF gun. The required drive laser parameters are given at the end of Section 3. Additional details on the design of the photoinjector drive laser systems are presented in a separate Technical Note. Design considerations for the RF gun are extensively presented in Section 4. There, we describe the variation of the cavity geometry to optimize the efficiency of the energy transfer to the electron beam. A study of the power coupling into the various cavity modes that interact within the bandwidth of the RF drive pulse is presented, followed by a study of the transient cavity response under several models and, finally, the effects on extracted beam quality. Section 5 describes the initial design for the low energy, off-axis diagnostic beamline. Beam dynamics simulations using ASTRA, elegant, and MAD are presented. Section 6 presents the optimization studies for the beam dynamics in the various operating modes. The optimized baseline configurations for the beamline and incident drive laser pulse are

An experimental and multi-objective optimization study of a forced draft cooling tower with different fills

International Nuclear Information System (INIS)

Singh, Kuljeet; Das, Ranjan

2016-01-01

Highlights: • Experimental and optimization study on forced draft cooling tower is done. • New correlations for splash, trickle and film type fills are proposed. • Multi-objective performance optimization study has been done using NSGA-II. • Weighted decision making criterion is proposed depending upon user priority. • Proposed generalized methodology can be implemented in industrial cooling towers. - Abstract: In the present study, a forced draft mechanical cooling tower has been experimentally investigated using trickle, film and splash fills. Various performance parameters such as range, tower characteristic ratio, effectiveness and water evaporation rate are first analyzed for each fill. Thereafter, based upon the experimental data, pertinent correlations have been developed for performance parameters by considering mass flow rates of water and air as design variables. Each of the performance parameters is considered to be an individual objective function and all objectives are then simultaneously optimized for maximizing the performance of the cooling tower using elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II). The multi-objective optimization algorithm gives a set of possible combinations of design variables, which is referred as the optimal Pareto-front, out of which a unique combination is selected based upon a decision making criterion. The proposed decision making procedure evaluates a Decision Making Score (DMS) based on assigned performance priorities for each point of the Pareto-front. Depending on DMS a unique combination of design variables is then selected for each type of fill that maximizes the tower’s performance. These optimal points and the corresponding objective function are finally compared and based upon the highest DMS value, the wire-mesh (trickle) fill is found to be the most efficient fill under the present experimental conditions. The methodology presented in this work has been made more generalized, so that it

Optimal debulking targets in women with advanced stage ovarian cancer: a retrospective study of immediate versus interval debulking surgery.

Science.gov (United States)

Altman, Alon D; Nelson, Gregg; Chu, Pamela; Nation, Jill; Ghatage, Prafull

2012-06-01

The objective of this study was to examine both overall and disease-free survival of patients with advanced stage ovarian cancer after immediate or interval debulking surgery based on residual disease. We performed a retrospective chart review at the Tom Baker Cancer Centre in Calgary, Alberta of patients with pathologically confirmed stage III or IV ovarian cancer, fallopian tube cancer, or primary peritoneal cancer between 2003 and 2007. We collected data on the dates of diagnosis, recurrence, and death; cancer stage and grade, patients' age, surgery performed, and residual disease. One hundred ninety-two patients were included in the final analysis. The optimal debulking rate with immediate surgery was 64.8%, and with interval surgery it was 85.9%. There were improved overall and disease-free survival rates for optimally debulked disease (advanced stage ovarian cancer, the goal of surgery should be resection of disease to microscopic residual at the initial procedure. This results in improved overall survival than lesser degrees of resection. Further studies are required to determine optimal surgical management.

On Implementation of Dynamic Programming for Optimal Control Problems with Final State Constraints À propos de l’implémentation de la programmation dynamique pour des problèmes de contrôle optimal avec des contraintes sur l’état final

Directory of Open Access Journals (Sweden)

Sundström O.

2009-09-01

Full Text Available In this paper we present issues related to the implementation of dynamic programming for optimal control of a one-dimensional dynamic model, such as the hybrid electric vehicle energy management problem. A study on the resolution of the discretized state space emphasizes the need for careful implementation. A new method is presented to treat numerical issues appropriately. In particular, the method deals with numerical problems that arise due to high gradients in the optimal cost-to-go function. These gradients mainly occur on the border of the feasible state region. The proposed method not only enhances the accuracy of the final global optimum but also allows for a reduction of the state-space resolution with maintained accuracy. The latter substantially reduces the computational effort to calculate the global optimum. This allows for further applications of dynamic programming for hybrid electric vehicles such as extensive parameter studies. Cette publication présente certains problèmes concernant l’implémentation de la programmation dynamique pour le contrôle optimal d’un modèle dynamique scalaire, comme par exemple la gestion énergétique d’un véhicule hybride électrique. Une étude sur la résolution de l’espace d’état discrétisé souligne le besoin d’une implémentation minutieuse. Une nouvelle méthode qui permet de traiter des problèmes numériques d’une façon adéquate est présentée. Cette méthode permet particulièrement de résoudre des problèmes numériques engendrés par de forts gradients dans la fonction coût optimale. Ces gradients se situent surtout aux bornes de l’ensemble d’états atteignables. La méthode proposée améliore non seulement la précision de l’optimum global, mais permet aussi de réduire la résolution de l’espace d’état en conservant la précision. Le nombre de calculs nécessaire pour évaluer l’optimum global est ainsi considérablement réduit. Cela permet des

Optimization of multi-stage dynamic treatment regimes utilizing accumulated data.

Science.gov (United States)

Huang, Xuelin; Choi, Sangbum; Wang, Lu; Thall, Peter F

2015-11-20

In medical therapies involving multiple stages, a physician's choice of a subject's treatment at each stage depends on the subject's history of previous treatments and outcomes. The sequence of decisions is known as a dynamic treatment regime or treatment policy. We consider dynamic treatment regimes in settings where each subject's final outcome can be defined as the sum of longitudinally observed values, each corresponding to a stage of the regime. Q-learning, which is a backward induction method, is used to first optimize the last stage treatment then sequentially optimize each previous stage treatment until the first stage treatment is optimized. During this process, model-based expectations of outcomes of late stages are used in the optimization of earlier stages. When the outcome models are misspecified, bias can accumulate from stage to stage and become severe, especially when the number of treatment stages is large. We demonstrate that a modification of standard Q-learning can help reduce the accumulated bias. We provide a computational algorithm, estimators, and closed-form variance formulas. Simulation studies show that the modified Q-learning method has a higher probability of identifying the optimal treatment regime even in settings with misspecified models for outcomes. It is applied to identify optimal treatment regimes in a study for advanced prostate cancer and to estimate and compare the final mean rewards of all the possible discrete two-stage treatment sequences. Copyright © 2015 John Wiley & Sons, Ltd.

Optimization of Calcine Blending During Retrieval from Binsets

International Nuclear Information System (INIS)

Nelson, Lee Orville; Mohr, Charles Milton; Taylor, Dean Dalton

2000-01-01

This report documents a study performed during advanced feasibility studies for the INTEC Technology Development Facility (ITDF). The study was commissioned to provide information about functional requirements for the ITDF related to development of equipment and procedures for retrieving radioactive calcine from binset storage at the Idaho Nuclear Technology and Engineering Center (INTEC) at the Idaho National Engineering and Environmental Laboratory (INEEL). Calcine will be retrieved prior to treating it for permanent disposal in a national repository for high level waste. The objective this study was to estimate the degree of homogenization of the calcine that might be achieved through optimized retrieval and subsequent blending. Such homogenization has the potential of reducing the costs for treatment of the calcine and for qualifying of the final waste forms for acceptance at the repository. Results from the study indicate that optimized retrieval and blending can reduce the peak concentration variations of key components (Al, Zr, F) in blended batches of retrieved calcine. During un-optimized retrieval these variations are likely to be 81-138% while optimized retrieval can reduce them to the 5-10% range

Optimal carbon tax with a dirty backstop: Oil, coal, or renewables?

OpenAIRE

van der Ploeg, Frederick; Withagen, Cees A.

2011-01-01

Optimal climate policy is studied. Coal, the abundant resource, contributes more CO2 per unit of energy than the exhaustible resource, oil. We characterize the optimal sequencing oil and coal and departures from the Herfindahl rule. "Preference reversal" can take place. If coal is very dirty compared to oil, there is no simultaneous use. Else, the optimal outcome starts with oil, before using oil and coal together, and finally coal on its own. The "laissez-faire" outcome uses coal forever or ...

Self-adaptive multimethod optimization applied to a tailored heating forging process

Science.gov (United States)

Baldan, M.; Steinberg, T.; Baake, E.

2018-05-01

The presented paper describes an innovative self-adaptive multi-objective optimization code. Investigation goals concern proving the superiority of this code compared to NGSA-II and applying it to an inductor’s design case study addressed to a “tailored” heating forging application. The choice of the frequency and the heating time are followed by the determination of the turns number and their positions. Finally, a straightforward optimization is performed in order to minimize energy consumption using “optimal control”.

Core optimization studies at JEN-Spain

International Nuclear Information System (INIS)

Gomez Alonso, M.

1983-01-01

The JEN-1 is a 3-MW reactor which uses flat-plate fuel elements. It was originally fueled with 20%-enriched uranium but more recently with 90%-enriched fuel. It now appears that it will have to be converted back to using 20%- enriched fuel. Progress is presently being made in fuel fabrication. Plates with meat thicknesses of up to 1.5 mm have been fabricated. Plates are being tested with 40 wt % uranium in the fuel meat. Progress is also being made in reactor design in collaboration with atomic energy commissions of other countries for swimming pool reactors being designed or under construction in Chile, Ecuador, and Spain itself. The design studies address core optimization, safety analysis report updating, irradiation facilities, etc. Core optimization is specifically addressed in this paper. A common swimming-pool-type reactor such as the JEN-1 served as an example. The philosophy adopted in this study is not to try to match the high enrichment core, but rather to treat the design as new and try to optimize it using simplified neutronic/thermal hydraulic/economic models. This philosophy appears to be somewhat original. As many as possible of the fuel parameters are constrained to remain constant

Taking Stock of Unrealistic Optimism.

Science.gov (United States)

Shepperd, James A; Klein, William M P; Waters, Erika A; Weinstein, Neil D

2013-07-01

Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type-the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention.

Taking Stock of Unrealistic Optimism

Science.gov (United States)

Shepperd, James A.; Klein, William M. P.; Waters, Erika A.; Weinstein, Neil D.

2015-01-01

Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type—the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention. PMID:26045714

A Study on the Optimal Welding Condition for Root-Pass in Horizontal Butt-Joint TIG Welding

Energy Technology Data Exchange (ETDEWEB)

Jung, Sung Hun; Kim, Jae-Woong [Yeungnam Univ., Gyeongsan (Korea, Republic of)

2017-04-15

In this study, to investigate the shape of the back bead as a weld quality parameter and to select the optimal condition of the root-pass TIG welding of a horizontal butt-joint, an experimental design and the response surface method (RSM) have been employed. Three parameters are used as input variables, which include the base current, peak current, and welding speed. The back bead width is selected as an output variable representing the weld quality, the target value of the width is 5.4 mm. Conducting the experiments according to the Box-Behnken experimental design, a 2nd regression model for the back bead width was made, and the validation of the model was confirmed by using the F-test. The desirability function was designed through the nominal-the-best formula for the appropriate back bead width. Finally, the following optimal condition for welding was selected using the RSM: base current of 0.9204, peak current of 0.8676, and welding speed of 0.3776 in coded values. For verification, a test welding process under the optimal condition was executed and the result showed the back bead width of 5.38 mm that matched the target value well.

A Study on the Optimal Welding Condition for Root-Pass in Horizontal Butt-Joint TIG Welding

International Nuclear Information System (INIS)

Jung, Sung Hun; Kim, Jae-Woong

2017-01-01

In this study, to investigate the shape of the back bead as a weld quality parameter and to select the optimal condition of the root-pass TIG welding of a horizontal butt-joint, an experimental design and the response surface method (RSM) have been employed. Three parameters are used as input variables, which include the base current, peak current, and welding speed. The back bead width is selected as an output variable representing the weld quality, the target value of the width is 5.4 mm. Conducting the experiments according to the Box-Behnken experimental design, a 2nd regression model for the back bead width was made, and the validation of the model was confirmed by using the F-test. The desirability function was designed through the nominal-the-best formula for the appropriate back bead width. Finally, the following optimal condition for welding was selected using the RSM: base current of 0.9204, peak current of 0.8676, and welding speed of 0.3776 in coded values. For verification, a test welding process under the optimal condition was executed and the result showed the back bead width of 5.38 mm that matched the target value well.

Portfolio optimization and performance evaluation

DEFF Research Database (Denmark)

Juhl, Hans Jørn; Christensen, Michael

2013-01-01

Based on an exclusive business-to-business database comprising nearly 1,000 customers, the applicability of portfolio analysis is documented, and it is examined how such an optimization analysis can be used to explore the growth potential of a company. As opposed to any previous analyses, optimal...... customer portfolios are determined, and it is shown how marketing decision-makers can use this information in their marketing strategies to optimize the revenue growth of the company. Finally, our analysis is the first analysis which applies portfolio based methods to measure customer performance......, and it is shown how these performance measures complement the optimization analysis....

Optimal reconstruction angles

International Nuclear Information System (INIS)

Cook, G.O. Jr.; Knight, L.

1979-07-01

The question of optimal projection angles has recently become of interest in the field of reconstruction from projections. Here, studies are concentrated on the n x n pixel space, where literative algorithms such as ART and direct matrix techniques due to Katz are considered. The best angles are determined in a Gauss--Markov statistical sense as well as with respect to a function-theoretical error bound. The possibility of making photon intensity a function of angle is also examined. Finally, the best angles to use in an ART-like algorithm are studied. A certain set of unequally spaced angles was found to be preferred in several contexts. 15 figures, 6 tables

Lie Algebroids in Classical Mechanics and Optimal Control

Directory of Open Access Journals (Sweden)

Eduardo Martínez

2007-03-01

Full Text Available We review some recent results on the theory of Lagrangian systems on Lie algebroids. In particular we consider the symplectic and variational formalism and we study reduction. Finally we also consider optimal control systems on Lie algebroids and we show how to reduce Pontryagin maximum principle.

Optimal river monitoring network using optimal partition analysis: a case study of Hun River, Northeast China.

Science.gov (United States)

Wang, Hui; Liu, Chunyue; Rong, Luge; Wang, Xiaoxu; Sun, Lina; Luo, Qing; Wu, Hao

2018-01-09

River monitoring networks play an important role in water environmental management and assessment, and it is critical to develop an appropriate method to optimize the monitoring network. In this study, an effective method was proposed based on the attainment rate of National Grade III water quality, optimal partition analysis and Euclidean distance, and Hun River was taken as a method validation case. There were 7 sampling sites in the monitoring network of the Hun River, and 17 monitoring items were analyzed once a month during January 2009 to December 2010. The results showed that the main monitoring items in the surface water of Hun River were ammonia nitrogen (NH 4 + -N), chemical oxygen demand, and biochemical oxygen demand. After optimization, the required number of monitoring sites was reduced from seven to three, and 57% of the cost was saved. In addition, there were no significant differences between non-optimized and optimized monitoring networks, and the optimized monitoring networks could correctly represent the original monitoring network. The duplicate setting degree of monitoring sites decreased after optimization, and the rationality of the monitoring network was improved. Therefore, the optimal method was identified as feasible, efficient, and economic.

Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs

Directory of Open Access Journals (Sweden)

Jiajun Liu

2017-10-01

Full Text Available Energy storage systems (ESS play an important role in the performance of mining vehicles. A hybrid ESS combining both batteries (BTs and supercapacitors (SCs is one of the most promising solutions. As a case study, this paper discusses the optimal hybrid ESS sizing and energy management strategy (EMS of 14-ton underground load-haul-dump vehicles (LHDs. Three novel contributions are added to the relevant literature. First, a multi-objective optimization is formulated regarding energy consumption and the total cost of a hybrid ESS, which are the key factors of LHDs, and a battery capacity degradation model is used. During the process, dynamic programming (DP-based EMS is employed to obtain the optimal energy consumption and hybrid ESS power profiles. Second, a 10-year life cycle cost model of a hybrid ESS for LHDs is established to calculate the total cost, including capital cost, operating cost, and replacement cost. According to the optimization results, three solutions chosen from the Pareto front are compared comprehensively, and the optimal one is selected. Finally, the optimal and battery-only options are compared quantitatively using the same objectives, and the hybrid ESS is found to be a more economical and efficient option.

Coach simplified structure modeling and optimization study based on the PBM method

Science.gov (United States)

Zhang, Miaoli; Ren, Jindong; Yin, Ying; Du, Jian

2016-09-01

Pareto solution set is acquired, and the selection strategy of the final solution is discussed. The case study demonstrates that the mechanical performances of the structure can be well-modeled and simulated by PBM beam. Because of the merits of fewer parameters and convenience of use, this method is suitable to be applied in the concept stage. Another merit is that the optimization results are the requirements for the mechanical performance of the beam section instead of those of the shape and dimensions, bringing flexibility to the succeeding design.

Final Focus Systems in Linear Colliders

International Nuclear Information System (INIS)

Raubenheimer, Tor

1998-01-01

In colliding beam facilities, the ''final focus system'' must demagnify the beams to attain the very small spot sizes required at the interaction points. The first final focus system with local chromatic correction was developed for the Stanford Linear Collider where very large demagnifications were desired. This same conceptual design has been adopted by all the future linear collider designs as well as the SuperConducting Supercollider, the Stanford and KEK B-Factories, and the proposed Muon Collider. In this paper, the over-all layout, physics constraints, and optimization techniques relevant to the design of final focus systems for high-energy electron-positron linear colliders are reviewed. Finally, advanced concepts to avoid some of the limitations of these systems are discussed

Optimal Procedure for siting of Nuclear Power Plant

International Nuclear Information System (INIS)

Aziuddin, Khairiah Binti; Park, Seo Yeon; Roh, Myung Sub

2013-01-01

This study discusses on a simulation approach for sensitivity analysis of the weights of multi-criteria decision models. The simulation procedures can also be used to aid the actual decision process, particularly when the task is to select a subset of superior alternatives. This study is to identify the criteria or parameters which are sensitive to the weighting factor that can affect the results in the decision making process to determine the optimal site for nuclear power plant (NPP) site. To perform this study, we adhere to IAEA NS-R-3 and DS 433. The siting process for nuclear installation consists of site survey and site selection stages. The siting process generally consists of an investigation of a large region to select one or more candidate sites by surveying the sites. After comparing the ROI, two candidate sites are compared for final determination, which are Wolsong and Kori site. Some assumptions are taken into consideration due to limitations and constraints throughout performing this study. Sensitivity analysis of multi criteria decision models is performed in this study to determine the optimal site in the site selection stage. Logical Decisions software will be employed as a tool to perform this analysis. Logical Decisions software helps to formulate the preferences and then rank the alternatives. It provides clarification of the rankings and hence aids the decision makers on evaluating the alternatives, and finally draw a conclusion on the selection of the optimal site

Optimal Procedure for siting of Nuclear Power Plant

Energy Technology Data Exchange (ETDEWEB)

Aziuddin, Khairiah Binti; Park, Seo Yeon; Roh, Myung Sub [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2013-10-15

This study discusses on a simulation approach for sensitivity analysis of the weights of multi-criteria decision models. The simulation procedures can also be used to aid the actual decision process, particularly when the task is to select a subset of superior alternatives. This study is to identify the criteria or parameters which are sensitive to the weighting factor that can affect the results in the decision making process to determine the optimal site for nuclear power plant (NPP) site. To perform this study, we adhere to IAEA NS-R-3 and DS 433. The siting process for nuclear installation consists of site survey and site selection stages. The siting process generally consists of an investigation of a large region to select one or more candidate sites by surveying the sites. After comparing the ROI, two candidate sites are compared for final determination, which are Wolsong and Kori site. Some assumptions are taken into consideration due to limitations and constraints throughout performing this study. Sensitivity analysis of multi criteria decision models is performed in this study to determine the optimal site in the site selection stage. Logical Decisions software will be employed as a tool to perform this analysis. Logical Decisions software helps to formulate the preferences and then rank the alternatives. It provides clarification of the rankings and hence aids the decision makers on evaluating the alternatives, and finally draw a conclusion on the selection of the optimal site.

Design of the Precipitation Process for Ni-Al Alloys with Optimal Mechanical Properties: A Phase-Field Study

Science.gov (United States)

Ta, Na; Zhang, Lijun; Du, Yong

2014-04-01

An attempt to design the heat treatment schedule for binary Ni-Al alloys with optimal mechanical properties was made in the present work. A series of quantitative three-dimensional (3-D) phase-field simulations of microstructure evolution in Ni-Al alloys during the precipitation process were first performed using MICRESS (MICRostructure Evolution Simulation Software) package developed in the formalism of the multi-phase field model. The coupling to CALPHAD (CALculation of PHAse Diagram) thermodynamic and atomic mobility databases was realized via TQ interface. Moreover, the temperature-dependent lattice misfits and elastic constants were utilized for simulation. The effect of the alloy composition and aging temperature on microstructure evolution was extensively studied with the aid of statistical analysis. After that, an evaluation function was proposed for evaluating the optimal heat treatment schedule by choosing the phase fraction, grain size, and shape factor of γ' precipitate as the evaluation indicators. Based on 50 groups of phase-field-simulated and experimental microstructure information, as well as the proposed evaluation function, the optimal alloy composition, aging temperature, and aging time for binary Ni-Al alloy with optimal mechanical properties were finally chosen. The successful application in the present Ni-Al alloys indicates that it is possible to design the optimal alloy composition and heat treatment for other binary and even multicomponent alloys with optimal mechanical properties based on the evaluation function and the sufficient microstructure information. Additionally, the combination of the present method and the key experiments can definitely accelerate the material design and improve the efficiency and accuracy.

ESFR core optimization and uncertainty studies

International Nuclear Information System (INIS)

Rineiski, A.; Vezzoni, B.; Zhang, D.; Marchetti, M.; Gabrielli, F.; Maschek, W.; Chen, X.-N.; Buiron, L.; Krepel, J.; Sun, K.; Mikityuk, K.; Polidoro, F.; Rochman, D.; Koning, A.J.; DaCruz, D.F.; Tsige-Tamirat, H.; Sunderland, R.

2015-01-01

In the European Sodium Fast Reactor (ESFR) project supported by EURATOM in 2008-2012, a concept for a large 3600 MWth sodium-cooled fast reactor design was investigated. In particular, reference core designs with oxide and carbide fuel were optimized to improve their safety parameters. Uncertainties in these parameters were evaluated for the oxide option. Core modifications were performed first to reduce the sodium void reactivity effect. Introduction of a large sodium plenum with an absorber layer above the core and a lower axial fertile blanket improve the total sodium void effect appreciably, bringing it close to zero for a core with fresh fuel, in line with results obtained worldwide, while not influencing substantially other core physics parameters. Therefore an optimized configuration, CONF2, with a sodium plenum and a lower blanket was established first and used as a basis for further studies in view of deterioration of safety parameters during reactor operation. Further options to study were an inner fertile blanket, introduction of moderator pins, a smaller core height, special designs for pins, such as 'empty' pins, and subassemblies. These special designs were proposed to facilitate melted fuel relocation in order to avoid core re-criticality under severe accident conditions. In the paper further CONF2 modifications are compared in terms of safety and fuel balance. They may bring further improvements in safety, but their accurate assessment requires additional studies, including transient analyses. Uncertainty studies were performed by employing a so-called Total Monte-Carlo method, for which a large number of nuclear data files is produced for single isotopes and then used in Monte-Carlo calculations. The uncertainties for the criticality, sodium void and Doppler effects, effective delayed neutron fraction due to uncertainties in basic nuclear data were assessed for an ESFR core. They prove applicability of the available nuclear data for ESFR

Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing.

Science.gov (United States)

Kou, Weibin; Chen, Xumei; Yu, Lei; Gong, Huibo

2018-04-18

Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development. Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

Radiation Load Optimization in the Final Focus System of FCC-hh

CERN Document Server

Martin, Roman; Cerutti, Francesco; Tomás, Rogelio

2016-01-01

With a center-of-mass energy of up to 100 TeV, FCC-hh will produce highly energetic collision debris at the Interaction Point (IP). Protecting the final focus quadrupoles from this radiation is challenging, since the required amount of shielding placed inside the magnets will reduce the free aperture, thereby limiting the β^{*} reach and luminosity. Hence, radiation mitigation strategies that make best use of the available aperture are required. In this paper, we study the possibility to split the first quadrupole Q1 into two quadrupoles with individual apertures, in order to distribute the radiation load more evenly and reduce the peak dose.

Optimal Time-Abstract Schedulers for CTMDPs and Markov Games

Directory of Open Access Journals (Sweden)

Markus Rabe

2010-06-01

Full Text Available We study time-bounded reachability in continuous-time Markov decision processes for time-abstract scheduler classes. Such reachability problems play a paramount role in dependability analysis and the modelling of manufacturing and queueing systems. Consequently, their analysis has been studied intensively, and techniques for the approximation of optimal control are well understood. From a mathematical point of view, however, the question of approximation is secondary compared to the fundamental question whether or not optimal control exists. We demonstrate the existence of optimal schedulers for the time-abstract scheduler classes for all CTMDPs. Our proof is constructive: We show how to compute optimal time-abstract strategies with finite memory. It turns out that these optimal schedulers have an amazingly simple structure---they converge to an easy-to-compute memoryless scheduling policy after a finite number of steps. Finally, we show that our argument can easily be lifted to Markov games: We show that both players have a likewise simple optimal strategy in these more general structures.

Efficient dynamic optimization of logic programs

Science.gov (United States)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

Development of TRU transmuters for optimization of the global fuel cycle. Final Report for the NERI Project

International Nuclear Information System (INIS)

Lee, John C.

2009-01-01

This final report summarizes the research activities during the entire performance period of the NERI grant, including the extra 9 months granted under a no-cost time extension. Building up on the 14 quarterly reports submitted through October 2008, we present here an overview of the research accomplishments under the five tasks originally proposed in July 2004, together with citations for publications resulting from the project. The AFCI-NERI project provided excellent support for two undergraduate and 10 graduates students at the University of Michigan during a period of three years and nine months. Significant developments were achieved in three areas: (1) Efficient deterministic fuel cycle optimization algorithms both for PWR and SFR configurations, (2) Efficient search algorithm for PWR equilibrium cycles, and (3) Simplified Excel-based script for dynamic fuel cycle analysis of diverse cycles. The project resulted in a total of 8 conference papers and three journal papers, including two that will be submitted shortly. Three pending publications are attached to the report

A short numerical study on the optimization methods influence on topology optimization

DEFF Research Database (Denmark)

Rojas Labanda, Susana; Sigmund, Ole; Stolpe, Mathias

2017-01-01

Structural topology optimization problems are commonly defined using continuous design variables combined with material interpolation schemes. One of the challenges for density based topology optimization observed in the review article (Sigmund and Maute Struct Multidiscip Optim 48(6):1031–1055...... 2013) is the slow convergence that is often encountered in practice, when an almost solid-and-void design is found. The purpose of this forum article is to present some preliminary observations on how designs evolves during the optimization process for different choices of optimization methods...

Pointwise second-order necessary optimality conditions and second-order sensitivity relations in optimal control

Science.gov (United States)

Frankowska, Hélène; Hoehener, Daniel

2017-06-01

This paper is devoted to pointwise second-order necessary optimality conditions for the Mayer problem arising in optimal control theory. We first show that with every optimal trajectory it is possible to associate a solution p (ṡ) of the adjoint system (as in the Pontryagin maximum principle) and a matrix solution W (ṡ) of an adjoint matrix differential equation that satisfy a second-order transversality condition and a second-order maximality condition. These conditions seem to be a natural second-order extension of the maximum principle. We then prove a Jacobson like necessary optimality condition for general control systems and measurable optimal controls that may be only ;partially singular; and may take values on the boundary of control constraints. Finally we investigate the second-order sensitivity relations along optimal trajectories involving both p (ṡ) and W (ṡ).

Optimization of Sealed Tube Graphitization Method for Environmental C-14 Studies Using MICADAS

Energy Technology Data Exchange (ETDEWEB)

Rinyu, Laszlo, E-mail: rinyu@atomki.hu [Hertelendi Laboratory of Environmental Studies, Institute of Nuclear Research of the Hungarian Academy of Sciences (ATOMKI), H-4026 Debrecen (Hungary); Isotoptech Zrt., H-4025 Debrecen (Hungary); Molnar, Mihaly [Hertelendi Laboratory of Environmental Studies, Institute of Nuclear Research of the Hungarian Academy of Sciences (ATOMKI), H-4026 Debrecen (Hungary); Ion Beam Physics, ETH Zuerich, CH-8093 Zuerich (Switzerland); Major, Istvan [Hertelendi Laboratory of Environmental Studies, Institute of Nuclear Research of the Hungarian Academy of Sciences (ATOMKI), H-4026 Debrecen (Hungary); Nagy, Tamas; Veres, Mihaly [Isotoptech Zrt., H-4025 Debrecen (Hungary); Kimak, Adam [University of Debrecen, H-4032 Debrecen (Hungary); Wacker, Lukas; Synal, Hans-Arno [Ion Beam Physics, ETH Zuerich, CH-8093 Zuerich (Switzerland)

2013-01-15

The original sealed tube zinc reduction graphitization process was first developed for rapid low-precision measurements of biomedical tracer samples and later also applied for high precision measurements of not too old samples. In this study we tested the MICADAS (mini radiocarbon dating system [1]) radiocarbon measurements of targets prepared by sealed tube graphitization process. We found the optimal iron catalyst and reagents (TiH{sub 2} and Zn) amount whereby we can reach a relatively low background level, and minimized the overall {delta}{sup 13}C fractionation during the graphitization. Repeated measurements of normalization standards and real samples with known {sup 14}C activities were very well reproduced. Finally, we demonstrated the applicability of the sealed tube graphitization on real environmental samples covering a wide range of {sup 14}C concentrations.

Optimism and Cause-Specific Mortality: A Prospective Cohort Study.

Science.gov (United States)

Kim, Eric S; Hagan, Kaitlin A; Grodstein, Francine; DeMeo, Dawn L; De Vivo, Immaculata; Kubzansky, Laura D

2017-01-01

Growing evidence has linked positive psychological attributes like optimism to a lower risk of poor health outcomes, especially cardiovascular disease. It has been demonstrated in randomized trials that optimism can be learned. If associations between optimism and broader health outcomes are established, it may lead to novel interventions that improve public health and longevity. In the present study, we evaluated the association between optimism and cause-specific mortality in women after considering the role of potential confounding (sociodemographic characteristics, depression) and intermediary (health behaviors, health conditions) variables. We used prospective data from the Nurses' Health Study (n = 70,021). Dispositional optimism was measured in 2004; all-cause and cause-specific mortality rates were assessed from 2006 to 2012. Using Cox proportional hazard models, we found that a higher degree of optimism was associated with a lower mortality risk. After adjustment for sociodemographic confounders, compared with women in the lowest quartile of optimism, women in the highest quartile had a hazard ratio of 0.71 (95% confidence interval: 0.66, 0.76) for all-cause mortality. Adding health behaviors, health conditions, and depression attenuated but did not eliminate the associations (hazard ratio = 0.91, 95% confidence interval: 0.85, 0.97). Associations were maintained for various causes of death, including cancer, heart disease, stroke, respiratory disease, and infection. Given that optimism was associated with numerous causes of mortality, it may provide a valuable target for new research on strategies to improve health. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Final report: Compiled MPI. Cost-Effective Exascale Application Development

Energy Technology Data Exchange (ETDEWEB)

Gropp, William Douglas [Univ. of Illinois, Urbana-Champaign, IL (United States)

2015-12-21

This is the final report on Compiled MPI: Cost-Effective Exascale Application Development, and summarizes the results under this project. The project investigated runtime enviroments that improve the performance of MPI (Message-Passing Interface) programs; work at Illinois in the last period of this project looked at optimizing data access optimizations expressed with MPI datatypes.

Anger and health in dementia caregivers: exploring the mediation effect of optimism.

Science.gov (United States)

López, J; Romero-Moreno, R; Márquez-González, M; Losada, A

2015-04-01

Although previous studies indicate a negative association between caregivers' anger and health, the potential mechanisms linking this relationship are not yet fully understood. The aim of this study was to explore the potential mediating role of optimism in the relationship between anger and caregivers' physical health. Dementia caregivers (n = 108) were interviewed and filled out instruments assessing their anger (reaction), optimism and health (vitality). A mediational model was tested to determine whether optimism partially mediated the relationship between anger and vitality. Angry reaction was negatively associated with optimism and vitality; optimism was positively associated with vitality. Finally, the relationship between angry reaction and vitality decreased when optimism was entered simultaneously. A non-parametric bootstrap approach confirmed that optimism significantly mediated some of the relationship between angry reaction and vitality. These findings suggest that low optimism may help explain the association between caregivers' anger and reduced sense of vitality. The results provide a specific target for intervention with caregivers. Copyright © 2013 John Wiley & Sons, Ltd.

Optimization of Calcine Blending During Retrieval From Binsets

International Nuclear Information System (INIS)

Taylor, D.D.; Mohr, C.M.; Nelson, L.O.

2000-01-01

This report documents a study performed during advanced feasibility studies for the INTEC Technology Development Facility (ITDF). The study was commissioned to provide information about functional requirements for the ITDF related to development of equipment and procedures for retrieving radioactive calcine from binset storage at the Idaho Nuclear Technology and Engineering Center (INTEC) at the Idaho National Engineering and Environmental Laboratory (INEEL). Calcine will be retrieved prior to treating it for permanent disposal in a national repository for high level waste. The objective this study was to estimate the degree of homogenization of the calcine that might be achieved through optimized retrieval and subsequent blending. Such homogenization has the potential of reducing the costs for treatment of the calcine and for qualifying of the final waste forms for acceptance at the repository. Results from the study indicate that optimized retrieval and blending can reduce the peak c oncentration variations of key components (Al, Zr, F) in blended batches of retrieved calcine. During un-optimized retrieval these variations are likely to be 81-138% while optimized retrieval can reduce them to the 5-10% range

Positivity in healthcare: relation of optimism to performance.

Science.gov (United States)

Luthans, Kyle W; Lebsack, Sandra A; Lebsack, Richard R

2008-01-01

The purpose of this paper is to explore the linkage between nurses' levels of optimism and performance outcomes. The study sample consisted of 78 nurses in all areas of a large healthcare facility (hospital) in the Midwestern United States. The participants completed surveys to determine their current state of optimism. Supervisory performance appraisal data were gathered in order to measure performance outcomes. Spearman correlations and a one-way ANOVA were used to analyze the data. The results indicated a highly significant positive relationship between the nurses' measured state of optimism and their supervisors' ratings of their commitment to the mission of the hospital, a measure of contribution to increasing customer satisfaction, and an overall measure of work performance. This was an exploratory study. Larger sample sizes and longitudinal data would be beneficial because it is probable that state optimism levels will vary and that it might be more accurate to measure state optimism at several points over time in order to better predict performance outcomes. Finally, the study design does not imply causation. Suggestions for effectively developing and managing nurses' optimism to positively impact their performance are provided. To date, there has been very little empirical evidence assessing the impact that positive psychological capacities such as optimism of key healthcare professionals may have on performance. This paper was designed to help begin to fill this void by examining the relationship between nurses' self-reported optimism and their supervisors' evaluations of their performance.

Study and optimization of the ultrasound-enhanced cleaning of an ultrafiltration ceramic membrane through a combined experimental-statistical approach.

Science.gov (United States)

Alventosa-deLara, E; Barredo-Damas, S; Alcaina-Miranda, M I; Iborra-Clar, M I

2014-05-01

Membrane fouling is one of the main drawbacks of ultrafiltration technology during the treatment of dye-containing effluents. Therefore, the optimization of the membrane cleaning procedure is essential to improve the overall efficiency. In this work, a study of the factors affecting the ultrasound-assisted cleaning of an ultrafiltration ceramic membrane fouled by dye particles was carried out. The effect of transmembrane pressure (0.5, 1.5, 2.5 bar), cross-flow velocity (1, 2, 3 ms(-1)), ultrasound power level (40%, 70%, 100%) and ultrasound frequency mode (37, 80 kHz and mixed wave) on the cleaning efficiency was evaluated. The lowest frequency showed better results, although the best cleaning performance was obtained using the mixed wave mode. A Box-Behnken Design was used to find the optimal conditions for the cleaning procedure through a response surface study. The optimal operating conditions leading to the maximum cleaning efficiency predicted (32.19%) were found to be 1.1 bar, 3 ms(-1) and 100% of power level. Finally, the optimized response was compared to the efficiency of a chemical cleaning with NaOH solution, with and without the use of ultrasound. By using NaOH, cleaning efficiency nearly triples, and it improves up to 25% by adding ultrasound. Copyright © 2013 Elsevier B.V. All rights reserved.

OPTIMAL PRICING OF A PERSONALIZED PRODUCT

Institute of Scientific and Technical Information of China (English)

Suresh P.SETHI

2008-01-01

This paper deals with optimal pricing of a personalized product such as a personal portrait or photo.A new model of the pricing structure inspired by two real-life cases is introduced to the literature and solved to obtain optimal photo sitting fees and the final product price.A sensitivity analysis with respect to the problem parameters is performed.

Investigation of optimize graded concrete for Oklahoma : phase 1 : final report.

Science.gov (United States)

2013-10-01

Optimized Graded Concrete has been a subject widely discussed through the history of concrete. Since aggregates make up over 70% of the volume in a mixture, gradation is critical to the strength, workability, and durability of concrete. In practice o...

Comparative Study on the Optimization Path of Industrial Value Chain in China’s Resource-Based Cities

Directory of Open Access Journals (Sweden)

Menglin Xing

2018-04-01

Full Text Available China’s resource-based cities have currently entered a period of comprehensive transformation. The differences in the economic and technical environment and significant policy orientation make it unique to some extent. This study applied value chain theory to analyze the industrial value chain of China’s resource-based cities, and three important types of optimization paths that have been applied differently by different cities were proposed. Grey relational analysis was used to compare the comprehensive value creation capacity of the three paths and its relationship with the comparative advantage of local industry. We found that a circular economy system has significant capacity to optimize economic and social value and favorable prospects for environmental value. However, this may have obvious instability in early periods of transition. This disadvantage can be remedied by cultivating related industries that have significantly comprehensive advantages in the early period. In the long term, the other two paths need to be combined with cultivating emerging industries. Finally, we found that the value creation capacity of China’s resource-based cities has roots in optimization of the industrial value chain rather than enhancement of the industrial comparative advantage. The reason for this is that value creation capacity has not yet been transformed into a source of industrial comparative advantage.

A Nonlinear Fuel Optimal Reaction Jet Control Law

National Research Council Canada - National Science Library

Breitfeller, Eric

2002-01-01

We derive a nonlinear fuel optimal attitude control system (ACS) that drives the final state to the desired state according to a cost function that weights the final state angular error relative to the angular rate error...

Optimization experiments on the study of giant resonance in nuclei

International Nuclear Information System (INIS)

Lyubarskij, G.Ya.; Savitskij, G.A.; Fartushnyj, V.A.; Khazhmuradov, M.A.; Levandovskij, S.P.

1988-01-01

Optimum choice of the target exposure to a beam in experiments on the study of giant resonances in nuclei is considered. Optimization is aimed at reducing mean square errors of defined formfactors. Four different optimization quality criteria - variances of four form factor experimental values are considered. Variances resulting form optimization are 1.5-2 times as less as variances in real experiment. The effect of experiment design optimization criterion on form factors determination errors is ascertained. 1 ref.; 3 tabs

Multi-objective optimization of a joule cycle for re-liquefaction of the Liquefied Natural Gas

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn; Babaelahi, M.

2011-01-01

Highlights: → A typical LNG boil off gas re-liquefaction plant system is optimized. → Objective functions based on thermodynamic and thermoeconomic analysis are obtained. → The cost of the system product and the exergetic efficiency are optimized, simultaneously. → A decision-making process for selection of the final optimal design is introduced. → Results obtained using various optimization scenarios are compared and discussed. - Abstract: A LNG re-liquefaction plant is optimized with a multi-objective approach which simultaneously considers exergetic and exergoeconomic objectives. In this regard, optimization is performed in order to maximize the exergetic efficiency of plant and minimize the unit cost of the system product (refrigeration effect), simultaneously. Thermodynamic modeling is performed based on energy and exergy analyses, while an exergoeconomic model based on the total revenue requirement (TRR) are developed. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms namely NSGA-II. This approach which is based on the Genetic Algorithm is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained and a final optimal solution is selected in a decision-making process. An example of decision-making process for selection of the final solution from the available optimal points of the Pareto frontier is presented here. The feature of selected final optimal system is compared with corresponding features of the base case and exergoeconomic single-objective optimized systems and discussed.

Optimized Power Dispatch Strategy for Offshore Wind Farms

DEFF Research Database (Denmark)

Hou, Peng; Hu, Weihao; Zhang, Baohua

2016-01-01

which are related to electrical system topology. This paper proposed an optimized power dispatch strategy (OPD) for minimizing the levelized production cost (LPC) of a wind farm. Particle swarm optimization (PSO) is employed to obtain final solution for the optimization problem. Both regular shape......Maximizing the power production of offshore wind farms using proper control strategy has become an important issue for wind farm operators. However, the power transmitted to the onshore substation (OS) is not only related to the power production of each wind turbine (WT) but also the power losses...... and irregular shape wind farm are chosen for the case study. The proposed dispatch strategy is compared with two other control strategies. The simulation results show the effectiveness of the proposed strategy....

Optimization of the gas chromatographic separations; Optimacion de las separaciones cromatograficas en fase gaseosa

Energy Technology Data Exchange (ETDEWEB)

Gasco Sanchez, L

1973-07-01

A review and a critical study on the optimization of the gas chromatographic separations are made. After dealing with the fundamental gas chromatographic equations, some methods of expressing column performances are discussed: performance indices, performance parameters, resolution and effective plate number per unit time. This is completed with a comparative study on performances of various types of columns. Moreover, optimization methods for operating chromatographic conditions are extensively dealt with: as resolution optimization, separation time, and normalization techniques for the time of analysis in order to achieve the maximum resolution at constant time. Finally, some others non operating parameters such as: selectivity of stationary phases, column preparation and optimization methods by means of computers are studied. (Author) 68 refs.

Intelligent structural optimization: Concept, Model and Methods

International Nuclear Information System (INIS)

Lu, Dagang; Wang, Guangyuan; Peng, Zhang

2002-01-01

Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

Optimization of fed-batch fermentation for a staphylokinase-hirudin ...

African Journals Online (AJOL)

TUOYO

2010-08-09

Aug 9, 2010 ... In this study, the fed-batch fermentation technique was applied to improve the yield of STH, a chimeric protein composed ... Under optimal conditions (GMYT and complex medium), a final STH expression of 1.48 g/l fermentation broth was ... STH production contained the following materials (per L): Sucrose.

Conventional treatment planning optimization using simulated annealing

International Nuclear Information System (INIS)

Morrill, S.M.; Langer, M.; Lane, R.G.

1995-01-01

Purpose: Simulated annealing (SA) allows for the implementation of realistic biological and clinical cost functions into treatment plan optimization. However, a drawback to the clinical implementation of SA optimization is that large numbers of beams appear in the final solution, some with insignificant weights, preventing the delivery of these optimized plans using conventional (limited to a few coplanar beams) radiation therapy. A preliminary study suggested two promising algorithms for restricting the number of beam weights. The purpose of this investigation was to compare these two algorithms using our current SA algorithm with the aim of producing a algorithm to allow clinically useful radiation therapy treatment planning optimization. Method: Our current SA algorithm, Variable Stepsize Generalized Simulated Annealing (VSGSA) was modified with two algorithms to restrict the number of beam weights in the final solution. The first algorithm selected combinations of a fixed number of beams from the complete solution space at each iterative step of the optimization process. The second reduced the allowed number of beams by a factor of two at periodic steps during the optimization process until only the specified number of beams remained. Results of optimization of beam weights and angles using these algorithms were compared using a standard cadre of abdominal cases. The solution space was defined as a set of 36 custom-shaped open and wedged-filtered fields at 10 deg. increments with a target constant target volume margin of 1.2 cm. For each case a clinically-accepted cost function, minimum tumor dose was maximized subject to a set of normal tissue binary dose-volume constraints. For this study, the optimized plan was restricted to four (4) fields suitable for delivery with conventional therapy equipment. Results: The table gives the mean value of the minimum target dose obtained for each algorithm averaged over 5 different runs and the comparable manual treatment

Sequential Optimization Methods for Augmentation of Marine Enzymes Production in Solid-State Fermentation: l-Glutaminase Production a Case Study.

Science.gov (United States)

Sathish, T; Uppuluri, K B; Veera Bramha Chari, P; Kezia, D

There is an increased l-glutaminase market worldwide due to its relevant industrial applications. Salt tolerance l-glutaminases play a vital role in the increase of flavor of different types of foods like soya sauce and tofu. This chapter is presenting the economically viable l-glutaminases production in solid-state fermentation (SSF) by Aspergillus flavus MTCC 9972 as a case study. The enzyme production was improved following a three step optimization process. Initially mixture design (MD) (augmented simplex lattice design) was employed to optimize the solid substrate mixture. Such solid substrate mixture consisted of 59:41 of wheat bran and Bengal gram husk has given higher amounts of l-glutaminase. Glucose and l-glutamine were screened as a finest additional carbon and nitrogen sources for l-glutaminase production with help of Plackett-Burman Design (PBD). l-Glutamine also acting as a nitrogen source as well as inducer for secretion of l-glutaminase from A. flavus MTCC 9972. In the final step of optimization various environmental and nutritive parameters such as pH, temperature, moisture content, inoculum concentration, glucose, and l-glutamine levels were optimized through the use of hybrid feed forward neural networks (FFNNs) and genetic algorithm (GA). Through sequential optimization methods MD-PBD-FFNN-GA, the l-glutaminase production in SSF could be improved by 2.7-fold (453-1690U/g). © 2016 Elsevier Inc. All rights reserved.

A study on a new algorithm to optimize ball mill system based on modeling and GA

International Nuclear Information System (INIS)

Wang Heng; Jia Minping; Huang Peng; Chen Zuoliang

2010-01-01

Aiming at the disadvantage of conventional optimization method for ball mill pulverizing system, a novel approach based on RBF neural network and genetic algorithm was proposed in the present paper. Firstly, the experiments and measurement for fill level based on vibration signals of mill shell was introduced. Then, main factors which affected the power consumption of ball mill pulverizing system were analyzed, and the input variables of RBF neural network were determined. RBF neural network was used to map the complex non-linear relationship between the electric consumption and process parameters and the non-linear model of power consumption was built. Finally, the model was optimized by genetic algorithm and the optimal work conditions of ball mill pulverizing system were determined. The results demonstrate that the method is reliable and practical, and can reduce the electric consumption obviously and effectively.

Lean and Efficient Software: Whole Program Optimization of Executables

Science.gov (United States)

2016-12-31

19b. TELEPHONE NUMBER (Include area code) 12/31/2016 Final Technical Report (Phase I - Base Period) 30-06-2014 - 31-12-2016 Lean and Efficient...Software: Whole-Program Optimization of Executables Final Report Evan Driscoll Tom Johnson GrammaTech, Inc. 531 Esty Street Ithaca, NY 14850 Office of...hardening U U U UU 30 Tom Johnson (607) 273-7340 x.134 Page 1 of 30 “ Lean and Efficient Software: Whole-Program Optimization of Executables

Topology-optimized metasurfaces: impact of initial geometric layout.

Science.gov (United States)

Yang, Jianji; Fan, Jonathan A

2017-08-15

Topology optimization is a powerful iterative inverse design technique in metasurface engineering and can transform an initial layout into a high-performance device. With this method, devices are optimized within a local design phase space, making the identification of suitable initial geometries essential. In this Letter, we examine the impact of initial geometric layout on the performance of large-angle (75 deg) topology-optimized metagrating deflectors. We find that when conventional metasurface designs based on dielectric nanoposts are used as initial layouts for topology optimization, the final devices have efficiencies around 65%. In contrast, when random initial layouts are used, the final devices have ultra-high efficiencies that can reach 94%. Our numerical experiments suggest that device topologies based on conventional metasurface designs may not be suitable to produce ultra-high-efficiency, large-angle metasurfaces. Rather, initial geometric layouts with non-trivial topologies and shapes are required.

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

Energy Technology Data Exchange (ETDEWEB)

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa; Jones, Katherine A

2016-05-01

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.

Optimization of Vehicular Trajectories under Gaussian Noise Disturbances

Directory of Open Access Journals (Sweden)

Joan Garcia-Haro

2012-12-01

Full Text Available Nowadays, research on Vehicular Technology aims at automating every single mechanical element of vehicles, in order to increase passengers’ safety, reduce human driving intervention and provide entertainment services on board. Automatic trajectory tracing for vehicles under especially risky circumstances is a field of research that is currently gaining enormous attention. In this paper, we show some results on how to develop useful policies to execute maneuvers by a vehicle at high speeds with the mathematical optimization of some already established mobility conditions of the car. We also study how the presence of Gaussian noise on measurement sensors while maneuvering can disturb motion and affect the final trajectories. Different performance criteria for the optimization of such maneuvers are presented, and an analysis is shown on how path deviations can be minimized by using trajectory smoothing techniques like the Kalman Filter. We finalize the paper with a discussion on how communications can be used to implement these schemes.

Configuration space analysis of common cost functions in radiotherapy beam-weight optimization algorithms

Energy Technology Data Exchange (ETDEWEB)

Rowbottom, Carl Graham [Joint Department of Physics, Institute of Cancer Research and the Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom); Webb, Steve [Joint Department of Physics, Institute of Cancer Research and the Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom)

2002-01-07

The successful implementation of downhill search engines in radiotherapy optimization algorithms depends on the absence of local minima in the search space. Such techniques are much faster than stochastic optimization methods but may become trapped in local minima if they exist. A technique known as 'configuration space analysis' was applied to examine the search space of cost functions used in radiotherapy beam-weight optimization algorithms. A downhill-simplex beam-weight optimization algorithm was run repeatedly to produce a frequency distribution of final cost values. By plotting the frequency distribution as a function of final cost, the existence of local minima can be determined. Common cost functions such as the quadratic deviation of dose to the planning target volume (PTV), integral dose to organs-at-risk (OARs), dose-threshold and dose-volume constraints for OARs were studied. Combinations of the cost functions were also considered. The simple cost function terms such as the quadratic PTV dose and integral dose to OAR cost function terms are not susceptible to local minima. In contrast, dose-threshold and dose-volume OAR constraint cost function terms are able to produce local minima in the example case studied. (author)

Surrogate Model Application to the Identification of Optimal Groundwater Exploitation Scheme Based on Regression Kriging Method—A Case Study of Western Jilin Province

Directory of Open Access Journals (Sweden)

Yongkai An

2015-07-01

Full Text Available This paper introduces a surrogate model to identify an optimal exploitation scheme, while the western Jilin province was selected as the study area. A numerical simulation model of groundwater flow was established first, and four exploitation wells were set in the Tongyu county and Qian Gorlos county respectively so as to supply water to Daan county. Second, the Latin Hypercube Sampling (LHS method was used to collect data in the feasible region for input variables. A surrogate model of the numerical simulation model of groundwater flow was developed using the regression kriging method. An optimization model was established to search an optimal groundwater exploitation scheme using the minimum average drawdown of groundwater table and the minimum cost of groundwater exploitation as multi-objective functions. Finally, the surrogate model was invoked by the optimization model in the process of solving the optimization problem. Results show that the relative error and root mean square error of the groundwater table drawdown between the simulation model and the surrogate model for 10 validation samples are both lower than 5%, which is a high approximation accuracy. The contrast between the surrogate-based simulation optimization model and the conventional simulation optimization model for solving the same optimization problem, shows the former only needs 5.5 hours, and the latter needs 25 days. The above results indicate that the surrogate model developed in this study could not only considerably reduce the computational burden of the simulation optimization process, but also maintain high computational accuracy. This can thus provide an effective method for identifying an optimal groundwater exploitation scheme quickly and accurately.

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

International Nuclear Information System (INIS)

Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

2016-01-01

This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.

Many-objective thermodynamic optimization of Stirling heat engine

International Nuclear Information System (INIS)

Patel, Vivek; Savsani, Vimal; Mudgal, Anurag

2017-01-01

This paper presents a rigorous investigation of many-objective (four-objective) thermodynamic optimization of a Stirling heat engine. Many-objective optimization problem is formed by considering maximization of thermal efficiency, power output, ecological function and exergy efficiency. Multi-objective heat transfer search (MOHTS) algorithm is proposed and applied to obtain a set of Pareto-optimal points. Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space. Thus, results of four-objective optimization are represented by six Pareto fronts in two dimension objective space. These six Pareto fronts are compared with their corresponding two-objective Pareto fronts. Quantitative assessment of the obtained Pareto solutions is reported in terms of spread and the spacing measures. Different decision making approaches such as LINMAP, TOPSIS and fuzzy are used to select a final optimal solution from Pareto optimal set of many-objective optimization. Finally, to reveal the level of conflict between these objectives, distribution of each decision variable in their allowable range is also shown in two dimensional objective spaces. - Highlights: • Many-objective (i.e. four objective) optimization of Stirling engine is investigated. • MOHTS algorithm is introduced and applied to obtain a set of Pareto points. • Comparative results of many-objective and multi-objectives are presented. • Relationship of design variables in many-objective optimization are obtained. • Optimum solution is selected by using decision making approaches.

Novel Verification Method for Timing Optimization Based on DPSO

Directory of Open Access Journals (Sweden)

Chuandong Chen

2018-01-01

Full Text Available Timing optimization for logic circuits is one of the key steps in logic synthesis. Extant research data are mainly proposed based on various intelligence algorithms. Hence, they are neither comparable with timing optimization data collected by the mainstream electronic design automation (EDA tool nor able to verify the superiority of intelligence algorithms to the EDA tool in terms of optimization ability. To address these shortcomings, a novel verification method is proposed in this study. First, a discrete particle swarm optimization (DPSO algorithm was applied to optimize the timing of the mixed polarity Reed-Muller (MPRM logic circuit. Second, the Design Compiler (DC algorithm was used to optimize the timing of the same MPRM logic circuit through special settings and constraints. Finally, the timing optimization results of the two algorithms were compared based on MCNC benchmark circuits. The timing optimization results obtained using DPSO are compared with those obtained from DC, and DPSO demonstrates an average reduction of 9.7% in the timing delays of critical paths for a number of MCNC benchmark circuits. The proposed verification method directly ascertains whether the intelligence algorithm has a better timing optimization ability than DC.

Final report for project "Next-Generation Semiconductors for Solar Photoelectrolysis"

Energy Technology Data Exchange (ETDEWEB)

Khalifah, Peter [Stony Brook Univ., NY (United States)

2016-09-15

In this paper, effective methods have been developed for preparing high-quality LaTiO₂N films on conductive La₅Ti₅O₁₇ substrates that can serve as photoanodes for photoelectrochemical water oxidation. One paper has been written by the post-doc who completed this comprehensive, interdisciplinary study, and it is presently being finalized for submission. Our approach to this system integrates expertise that we have developed in single crystal growth, thin film growth, and thin film post-processing. Through this work, LTON films have been fully optimized for light harvesting, as their band gap is optimally matched with the incident solar spectrum and the film thicknesses have been optimized based on the absolute absorption coefficients that we have measured for this system. The next step is to optimize the co-catalyst functionalization and the solution conditions to maximize the catalytic activity for water oxidation. Since the preliminary tests described here were done without a water oxidation co-catalyst, and since good water oxidation catalysts have previously been identified based on studies of powder samples, this next step is highly likely to be successful.

Study on Design Optimization of Centrifugal Compressors Considering Efficiency and Weight

International Nuclear Information System (INIS)

Lee, Younghwan; Kang, Shinhyoung; Ha, Kyunggu

2015-01-01

Various centrifugal compressors are currently used extensively in industrial fields, where the design requirements are more complicated. This makes it more difficult to determine the optimal design point of a centrifugal compressor. Traditionally, the efficiency is an important factor for optimization. In this study, the weight of the compressor was also considered. The aim of this study was to present the design tendency considering the stage efficiency and weight. In addition, this study suggested possibility of a selection of compressor design objectives at an early design stage based on the optimization results. Only a vaneless diffuser was considered in this case. The Kriging method was used with sample points from 1D design program data. The optimal points were determined in a substitute design space.

Study on Design Optimization of Centrifugal Compressors Considering Efficiency and Weight

Energy Technology Data Exchange (ETDEWEB)

Lee, Younghwan; Kang, Shinhyoung [Seoul National University, Seoul (Korea, Republic of); Ha, Kyunggu [Hyundai Motor Group, Ulsan (Korea, Republic of)

2015-04-15

Various centrifugal compressors are currently used extensively in industrial fields, where the design requirements are more complicated. This makes it more difficult to determine the optimal design point of a centrifugal compressor. Traditionally, the efficiency is an important factor for optimization. In this study, the weight of the compressor was also considered. The aim of this study was to present the design tendency considering the stage efficiency and weight. In addition, this study suggested possibility of a selection of compressor design objectives at an early design stage based on the optimization results. Only a vaneless diffuser was considered in this case. The Kriging method was used with sample points from 1D design program data. The optimal points were determined in a substitute design space.

Welding Robot Collision-Free Path Optimization

Directory of Open Access Journals (Sweden)

Xuewu Wang

2017-02-01

Full Text Available Reasonable welding path has a significant impact on welding efficiency, and a collision-free path should be considered first in the process of welding robot path planning. The shortest path length is considered as an optimization objective, and obstacle avoidance is considered as the constraint condition in this paper. First, a grid method is used as a modeling method after the optimization objective is analyzed. For local collision-free path planning, an ant colony algorithm is selected as the search strategy. Then, to overcome the shortcomings of the ant colony algorithm, a secondary optimization is presented to improve the optimization performance. Finally, the particle swarm optimization algorithm is used to realize global path planning. Simulation results show that the desired welding path can be obtained based on the optimization strategy.

Reliability Based Optimization of Structural Systems

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

1987-01-01

The optimization problem to design structural systems such that the reliability is satisfactory during the whole lifetime of the structure is considered in this paper. Some of the quantities modelling the loads and the strength of the structure are modelled as random variables. The reliability...... is estimated using first. order reliability methods ( FORM ). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements satisfies given requirements or such that the systems reliability satisfies a given requirement....... For these optimization problems it is described how a sensitivity analysis can be performed. Next, new optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability based optimization problem sequentially using quasi-analytical derivatives. Finally...

Optimization of annatto (Bixa orellana L. drying in fixed bed

Directory of Open Access Journals (Sweden)

Faria L.J.G.

2000-01-01

Full Text Available The drying of annatto seeds (Bixa orellana L., red piave cultivate, was studied in a fixed bed dryer. The best conditions were estimated to minimize the loss of coloring and to obtain final moisture of the seeds in appropriate levels to its conservation and maintenance of quality. The quantification of the influence of entrance variables in the final contents of bixin and moisture seeds and the identification of the optimal point was performed through the techniques of factorial design, response surfaces methodology, canonical analysis and desirability function. It was verified that the final moisture of the seeds may be estimated by a second-order polynomial model and that the final content of bixin is only significantly influenced by the time of drying being described properly by a linear model, for the seeds used in this study.

Optimized controllers for enhancing dynamic performance of PV interface system

Directory of Open Access Journals (Sweden)

Mahmoud A. Attia

2018-05-01

Full Text Available The dynamic performance of PV interface system can be improved by optimizing the gains of the Proportional–Integral (PI controller. In this work, gravitational search algorithm and harmony search algorithm are utilized to optimal tuning of PI controller gains. Performance comparison between the PV system with optimized PI gains utilizing different techniques are carried out. Finally, the dynamic behavior of the system is studied under hypothetical sudden variations in irradiance. The examination of the proposed techniques for optimal tuning of PI gains is conducted using MATLAB/SIMULINK software package. The main contribution of this work is investigating the dynamic performance of PV interfacing system with application of gravitational search algorithm and harmony search algorithm for optimal PI parameters tuning. Keywords: Photovoltaic power systems, Gravitational search algorithm, Harmony search algorithm, Genetic algorithm, Artificial intelligence

Setting value optimization method in integration for relay protection based on improved quantum particle swarm optimization algorithm

Science.gov (United States)

Yang, Guo Sheng; Wang, Xiao Yang; Li, Xue Dong

2018-03-01

With the establishment of the integrated model of relay protection and the scale of the power system expanding, the global setting and optimization of relay protection is an extremely difficult task. This paper presents a kind of application in relay protection of global optimization improved particle swarm optimization algorithm and the inverse time current protection as an example, selecting reliability of the relay protection, selectivity, quick action and flexibility as the four requires to establish the optimization targets, and optimizing protection setting values of the whole system. Finally, in the case of actual power system, the optimized setting value results of the proposed method in this paper are compared with the particle swarm algorithm. The results show that the improved quantum particle swarm optimization algorithm has strong search ability, good robustness, and it is suitable for optimizing setting value in the relay protection of the whole power system.

Emergency strategy optimization for the environmental control system in manned spacecraft

Science.gov (United States)

Li, Guoxiang; Pang, Liping; Liu, Meng; Fang, Yufeng; Zhang, Helin

2018-02-01

It is very important for a manned environmental control system (ECS) to be able to reconfigure its operation strategy in emergency conditions. In this article, a multi-objective optimization is established to design the optimal emergency strategy for an ECS in an insufficient power supply condition. The maximum ECS lifetime and the minimum power consumption are chosen as the optimization objectives. Some adjustable key variables are chosen as the optimization variables, which finally represent the reconfigured emergency strategy. The non-dominated sorting genetic algorithm-II is adopted to solve this multi-objective optimization problem. Optimization processes are conducted at four different carbon dioxide partial pressure control levels. The study results show that the Pareto-optimal frontiers obtained from this multi-objective optimization can represent the relationship between the lifetime and the power consumption of the ECS. Hence, the preferred emergency operation strategy can be recommended for situations when there is suddenly insufficient power.

Optimization of Calcine Blending During Retrieval From Binsets; TOPICAL

International Nuclear Information System (INIS)

Taylor, D.D.; Mohr, C.M.; Nelson, L.O.

2000-01-01

This report documents a study performed during advanced feasibility studies for the INTEC Technology Development Facility (ITDF). The study was commissioned to provide information about functional requirements for the ITDF related to development of equipment and procedures for retrieving radioactive calcine from binset storage at the Idaho Nuclear Technology and Engineering Center (INTEC) at the Idaho National Engineering and Environmental Laboratory (INEEL). Calcine will be retrieved prior to treating it for permanent disposal in a national repository for high level waste. The objective this study was to estimate the degree of homogenization of the calcine that might be achieved through optimized retrieval and subsequent blending. Such homogenization has the potential of reducing the costs for treatment of the calcine and for qualifying of the final waste forms for acceptance at the repository. Results from the study indicate that optimized retrieval and blending can reduce the peak c oncentration variations of key components (Al, Zr, F) in blended batches of retrieved calcine. During un-optimized retrieval these variations are likely to be 81-138% while optimized retrieval can reduce them to the 5-10% range

A study for optimal transmutation system

International Nuclear Information System (INIS)

Park, W.S.; Song, T.Y.; Shin, H.S.; Park, C.K.

1996-01-01

Couple of transmutation systems are being under investigation to design the optimal transmutation device. Several basic studies were performed for that objectives: (1) select the radioactive nuclides to be transmuted: (2) investigate the physical characteristics of each nuclide; (3) study the most favorable neutron energy environment for the transmutation. The existing LWR and LMFBR cores were found to be not a satisfiable ones in terms of transmutation rate itself. (author). 5 refs, 2 figs, 3 tabs

Therapeutic treatment plan optimization with probability density-based dose prescription

International Nuclear Information System (INIS)

Lian Jun; Cotrutz, Cristian; Xing Lei

2003-01-01

The dose optimization in inverse planning is realized under the guidance of an objective function. The prescription doses in a conventional approach are usually rigid values, defining in most instances an ill-conditioned optimization problem. In this work, we propose a more general dose optimization scheme based on a statistical formalism [Xing et al., Med. Phys. 21, 2348-2358 (1999)]. Instead of a rigid dose, the prescription to a structure is specified by a preference function, which describes the user's preference over other doses in case the most desired dose is not attainable. The variation range of the prescription dose and the shape of the preference function are predesigned by the user based on prior clinical experience. Consequently, during the iterative optimization process, the prescription dose is allowed to deviate, with a certain preference level, from the most desired dose. By not restricting the prescription dose to a fixed value, the optimization problem becomes less ill-defined. The conventional inverse planning algorithm represents a special case of the new formalism. An iterative dose optimization algorithm is used to optimize the system. The performance of the proposed technique is systematically studied using a hypothetical C-shaped tumor with an abutting circular critical structure and a prostate case. It is shown that the final dose distribution can be manipulated flexibly by tuning the shape of the preference function and that using a preference function can lead to optimized dose distributions in accordance with the planner's specification. The proposed framework offers an effective mechanism to formalize the planner's priorities over different possible clinical scenarios and incorporate them into dose optimization. The enhanced control over the final plan may greatly facilitate the IMRT treatment planning process

Plant systems/components modularization study. Final report

International Nuclear Information System (INIS)

1977-07-01

The final results are summarized of a Plant Systems/Components Modularization Study based on Stone and Webster's Pressurized Water Reactor Reference Design. The program has been modified to include evaluation of the most promising areas for modular consideration based on the level of the Sundesert Project engineering design completion and the feasibility of their incorporation into the plant construction effort

Optimal design of link systems using successive zooming genetic algorithm

Science.gov (United States)

Kwon, Young-Doo; Sohn, Chang-hyun; Kwon, Soon-Bum; Lim, Jae-gyoo

2009-07-01

Link-systems have been around for a long time and are still used to control motion in diverse applications such as automobiles, robots and industrial machinery. This study presents a procedure involving the use of a genetic algorithm for the optimal design of single four-bar link systems and a double four-bar link system used in diesel engine. We adopted the Successive Zooming Genetic Algorithm (SZGA), which has one of the most rapid convergence rates among global search algorithms. The results are verified by experiment and the Recurdyn dynamic motion analysis package. During the optimal design of single four-bar link systems, we found in the case of identical input/output (IO) angles that the initial and final configurations show certain symmetry. For the double link system, we introduced weighting factors for the multi-objective functions, which minimize the difference between output angles, providing balanced engine performance, as well as the difference between final output angle and the desired magnitudes of final output angle. We adopted a graphical method to select a proper ratio between the weighting factors.

Methodology of shell structure reinforcement layout optimization

Science.gov (United States)

Szafrański, Tomasz; Małachowski, Jerzy; Damaziak, Krzysztof

2018-01-01

This paper presents an optimization process of a reinforced shell diffuser intended for a small wind turbine (rated power of 3 kW). The diffuser structure consists of multiple reinforcement and metal skin. This kind of structure is suitable for optimization in terms of selection of reinforcement density, stringers cross sections, sheet thickness, etc. The optimisation approach assumes the reduction of the amount of work to be done between the optimization process and the final product design. The proposed optimization methodology is based on application of a genetic algorithm to generate the optimal reinforcement layout. The obtained results are the basis for modifying the existing Small Wind Turbine (SWT) design.

Performance evaluation of Genetic Algorithms on loading pattern optimization of PWRs

International Nuclear Information System (INIS)

Tombakoglu, M.; Bekar, K.B.; Erdemli, A.O.

2001-01-01

Genetic Algorithm (GA) based systems are used for search and optimization problems. There are several applications of GAs in literature successfully applied for loading pattern optimization problems. In this study, we have selected loading pattern optimization problem of Pressurised Water Reactor (PWR). The main objective of this work is to evaluate the performance of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection and construction of initial population and its size for PWR loading pattern optimization problems. The performance of GA with antithetic variates is compared to traditional GA. Antithetic variates are used to generate the initial population and its use with GA operators are also discussed. Finally, the results of multi-cycle optimization problems are discussed for objective function taking into account cycle burn-up and discharge burn-up.(author)

Characterization and optimization of the R A-6 s on-line neutron radiography facility

International Nuclear Information System (INIS)

Mezio Guanes, Federico Andres

2007-01-01

With the objective of characterizing and optimizing the radiation-field filters behavior in the beam of the R A-6 on-line Neutron Radiography facility, some improvements have been done to the facility devices.We studied the camera sensibility, the best camera acquisition software configuration, the best depth of field, we increased the system tuning efficiency.We also studied the linearity of the facility vs the reactor core neutron fluence and finally we constructed a device that ensure the repeatability of the measurements.The main parameters chosen to represent the best radiation-field set-up are the thermal neutron flux and dose in the position of the camera.Finally, a camera shield optimization haven been done in function of its position [es

Optimal time policy for deteriorating items of two-warehouse

Indian Academy of Sciences (India)

... goods in which the first is rented warehouse and the second is own warehouse that deteriorates with two different rates. The aim of this study is to determine the optimal order quantity to maximize the profit of the projected model. Finally, some numerical examples and sensitivity analysis of parameters are made to validate ...

Experimental study and numerical optimization of tensegrity domes - A case study

Science.gov (United States)

Winkelmann, Karol; Kłos, Filip; Rąpca, Mateusz

2018-01-01

The paper deals with the design, experimental analysis and numerical optimization of tensegrity dome models. Two structures are analyzed - a Geiger system dome (preliminary dome), with PVC-U bars and PA6/PP/PET tendons and a Fuller system dome (target dome), with wooden bars and steel cables as tendons. All used materials are experimentally tested in terms of Young's modulus and yield stress values, the compressed bars are also tested for the limit length demarcating the elastic buckling from plastic failure. The data obtained in experiments is then implemented in SOFiSTiK commercial software FE model. The model's geometrical parameters are considered uniform random variables. Geometrically and materially nonlinear analysis is carried out. Based on the obtained structural response (displacements), a Monte Carlo simulation - based approach is incorporated for both structural design point formulation and the SLS requirements fulfillment analysis. Finally, an attempt is made to erect the Fuller dome model in order to compare the numerical results of an experimentally-derived model with the in situ measurements of an actual structure.

Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

Science.gov (United States)

Otero-Muras, Irene; Banga, Julio R

2017-07-21

In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.

Joint global optimization of tomographic data based on particle swarm optimization and decision theory

Science.gov (United States)

Paasche, H.; Tronicke, J.

2012-04-01

In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto

Design Optimization of Hybrid FRP/RC Bridge

Science.gov (United States)

Papapetrou, Vasileios S.; Tamijani, Ali Y.; Brown, Jeff; Kim, Daewon

2018-04-01

The hybrid bridge consists of a Reinforced Concrete (RC) slab supported by U-shaped Fiber Reinforced Polymer (FRP) girders. Previous studies on similar hybrid bridges constructed in the United States and Europe seem to substantiate these hybrid designs for lightweight, high strength, and durable highway bridge construction. In the current study, computational and optimization analyses were carried out to investigate six composite material systems consisting of E-glass and carbon fibers. Optimization constraints are determined by stress, deflection and manufacturing requirements. Finite Element Analysis (FEA) and optimization software were utilized, and a framework was developed to run the complete analyses in an automated fashion. Prior to that, FEA validation of previous studies on similar U-shaped FRP girders that were constructed in Poland and Texas is presented. A finer optimization analysis is performed for the case of the Texas hybrid bridge. The optimization outcome of the hybrid FRP/RC bridge shows the appropriate composite material selection and cross-section geometry that satisfies all the applicable Limit States (LS) and, at the same time, results in the lightest design. Critical limit states show that shear stress criteria determine the optimum design for bridge spans less than 15.24 m and deflection criteria controls for longer spans. Increased side wall thickness can reduce maximum observed shear stresses, but leads to a high weight penalty. A taller cross-section and a thicker girder base can efficiently lower the observed deflections and normal stresses. Finally, substantial weight savings can be achieved by the optimization framework if base and side-wall thickness are treated as independent variables.

Theoretical and experimental studies for optimization of PCRV top closures

International Nuclear Information System (INIS)

Ottosen, N.S.; Andersen, S.I.

1975-01-01

The results from the remaining part of the parameter study and the preparations for the verification of an optimized design are presented. Three models have been made in the same scale and with the same depth to span ratio α as the low LM-3 model from the first investigation, i.e. α=0.35. The model LM-5 was provided with reinforcement in the tensile zone, the upper part of the closure. This reinforcement did not influence the stresses and strains in the load carrying concrete, and the dome failed at the same pressure as in the unreinforced model LM-3. However, the closure did not disintegrate, but failed due to large overall deformations causing seal leakage. In the model LM-6, the inverted dome, which is formed at higher loads as demonstrated in LM-3, was reinforced perpendicular to the supposed middle surface. This reinforcement proved to be effective, giving the dome a higher ultimate load capacity. The LM-6 test stopped due to a circumferential crack in the flange. Finally, the unreinforced LM-7 closure was tested to failure. Apart from minor changes in the flange, LM-7 was identical to LM-3 except for the excavated upper part of the concrete, which in LM-3 formed the heavily cracked tensile zone. The ultimate load and the failure mode observed for this closure were the same as for the LM-3. The experimental results are compared to finite element calculations, in which plasticity and cracking of the concrete are taken into account, and the influence of different material models for the concrete is investigated. A unique failure criterion, which includes failure of the concrete for both tensile and compressive stresses in the same mathematical expression, is proposed. Based on the results obtained from the parameter study, a new closure design is proposed, which is optimized with respect to the requirements at service conditions and ultimate load

Minimizing transient influence in WHPA delineation: An optimization approach for optimal pumping rate schemes

Science.gov (United States)

Rodriguez-Pretelin, A.; Nowak, W.

2017-12-01

For most groundwater protection management programs, Wellhead Protection Areas (WHPAs) have served as primarily protection measure. In their delineation, the influence of time-varying groundwater flow conditions is often underestimated because steady-state assumptions are commonly made. However, it has been demonstrated that temporary variations lead to significant changes in the required size and shape of WHPAs. Apart from natural transient groundwater drivers (e.g., changes in the regional angle of flow direction and seasonal natural groundwater recharge), anthropogenic causes such as transient pumping rates are of the most influential factors that require larger WHPAs. We hypothesize that WHPA programs that integrate adaptive and optimized pumping-injection management schemes can counter transient effects and thus reduce the additional areal demand in well protection under transient conditions. The main goal of this study is to present a novel management framework that optimizes pumping schemes dynamically, in order to minimize the impact triggered by transient conditions in WHPA delineation. For optimizing pumping schemes, we consider three objectives: 1) to minimize the risk of pumping water from outside a given WHPA, 2) to maximize the groundwater supply and 3) to minimize the involved operating costs. We solve transient groundwater flow through an available transient groundwater and Lagrangian particle tracking model. The optimization problem is formulated as a dynamic programming problem. Two different optimization approaches are explored: I) the first approach aims for single-objective optimization under objective (1) only. The second approach performs multiobjective optimization under all three objectives where compromise pumping rates are selected from the current Pareto front. Finally, we look for WHPA outlines that are as small as possible, yet allow the optimization problem to find the most suitable solutions.

Optimization of reconstruction algorithms using Monte Carlo simulation

International Nuclear Information System (INIS)

Hanson, K.M.

1989-01-01

A method for optimizing reconstruction algorithms is presented that is based on how well a specified task can be performed using the reconstructed images. Task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, reconstruction, and performance of the stated task based on the final image. The use of this method is demonstrated through the optimization of the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections by a iterative procedure. The optimization is accomplished by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a nonnegativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART. The general method presented may be applied to the problem of designing neutron-diffraction spectrometers. 11 refs., 6 figs., 2 tabs

Optimization of reconstruction algorithms using Monte Carlo simulation

International Nuclear Information System (INIS)

Hanson, K.M.

1989-01-01

A method for optimizing reconstruction algorithms is presented that is based on how well a specified task can be performed using the reconstructed images. Task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, reconstruction, and performance of the stated task based on the final image. The use of this method is demonstrated through the optimization of the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections by an iterative procedure. The optimization is accomplished by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a non-negativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART. The general method presented may be applied to the problem of designing neutron-diffraction spectrometers. (author)

The computational optimization of heat exchange efficiency in stack chimneys

Energy Technology Data Exchange (ETDEWEB)

Van Goch, T.A.J.

2012-02-15

For many industrial processes, the chimney is the final step before hot fumes, with high thermal energy content, are discharged into the atmosphere. Tapping into this energy and utilizing it for heating or cooling applications, could improve sustainability, efficiency and/or reduce operational costs. Alternatively, an unused chimney, like the monumental chimney at the Eindhoven University of Technology, could serve as an 'energy channeler' once more; it can enhance free cooling by exploiting the stack effect. This study aims to identify design parameters that influence annual heat exchange in such stack chimney applications and optimize these parameters for specific scenarios to maximize the performance. Performance is defined by annual heat exchange, system efficiency and costs. The energy required for the water pump as compared to the energy exchanged, defines the system efficiency, which is expressed in an efficiency coefficient (EC). This study is an example of applying building performance simulation (BPS) tools for decision support in the early phase of the design process. In this study, BPS tools are used to provide design guidance, performance evaluation and optimization. A general method for optimization of simulation models will be studied, and applied in two case studies with different applications (heating/cooling), namely; (1) CERES case: 'Eindhoven University of Technology monumental stack chimney equipped with a heat exchanger, rejects heat to load the cold source of the aquifer system on the campus of the university and/or provides free cooling to the CERES building'; and (2) Industrial case: 'Heat exchanger in an industrial stack chimney, which recoups heat for use in e.g. absorption cooling'. The main research question, addressing the concerns of both cases, is expressed as follows: 'what is the optimal set of design parameters so heat exchange in stack chimneys is optimized annually for the cases in which a

Commitment and dispatch of heat and power units via affinely adjustable robust optimization

DEFF Research Database (Denmark)

Zugno, Marco; Morales González, Juan Miguel; Madsen, Henrik

2016-01-01

compromising computational tractability. We perform an extensive numerical study based on data from the Copenhagen area in Denmark, which highlights important features of the proposed model. Firstly, we illustrate commitment and dispatch choices that increase conservativeness in the robust optimization...... and conservativeness of the solution. Finally, we perform a thorough comparison with competing models based on deterministic optimization and stochastic programming. (C) 2016 Elsevier Ltd. All rights reserved....

Time optimal paths for high speed maneuvering

Energy Technology Data Exchange (ETDEWEB)

Reister, D.B.; Lenhart, S.M.

1993-01-01

Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature of the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.

Generalized Benders’ Decomposition for topology optimization problems

DEFF Research Database (Denmark)

Munoz Queupumil, Eduardo Javier; Stolpe, Mathias

2011-01-01

) problems with discrete design variables to global optimality. We present the theoretical aspects of the method, including a proof of finite convergence and conditions for obtaining global optimal solutions. The method is also linked to, and compared with, an Outer-Approximation approach and a mixed 0......–1 semi definite programming formulation of the considered problem. Several ways to accelerate the method are suggested and an implementation is described. Finally, a set of truss topology optimization problems are numerically solved to global optimality.......This article considers the non-linear mixed 0–1 optimization problems that appear in topology optimization of load carrying structures. The main objective is to present a Generalized Benders’ Decomposition (GBD) method for solving single and multiple load minimum compliance (maximum stiffness...

Design and Optimization of Tube Type Interior Permanent Magnets Generator for Free Piston Applications

Directory of Open Access Journals (Sweden)

Serdal ARSLAN

2017-05-01

Full Text Available In this study a design and optimization of a generator to be used in free piston applications was made. In order to supply required initial force, an IPM (interior permanent magnets cavity tube type linear generator was selected. By using analytical equations’ basic dimensioning of generator was made. By using Ansys-Maxwell dimensioning, analysis and optimization of the generator was realized. Also, the effects of design basic variables (pole step ratio, cavity step ratio, inner diameter - outer diameter ratio, primary final length, air interval on pinking force were examined by using parametric analyses. Among these variables, cavity step ratio, inner diameter - outer diameter ratio, primary final length were optimally determined by algorithm and sequential nonlinear programming. The two methods were compared in terms of pinking force calculation problem. Preliminary application of the linear generator was performed for free piston application.

An Optimization Study on Syngas Production and Economic Evaluation

Directory of Open Access Journals (Sweden)

Qasim Faraz

2016-01-01

Full Text Available Syngas production in Gas-to-liquid (GTL process is focused in past by several researchers to increase the production with minimal capital and operating costs. In this study, syngas production process is simulated and optimized to increase its production and the economic analysis is studied for the proposed optimized process. Aspen HYSYS v8.4 is used for all process simulation work in this article. A new configuration is rigorously simulated while using auto-thermal reforming. Results exhibit a tremendous rise in production of syngas.

Conversion of Oleum papaveris seminis oil into methyl esters via esterification process optimization and kinetic study

Energy Technology Data Exchange (ETDEWEB)

Syam, A.M.; Rashid, U.; Yunus, R.; Hamid, H.A.; Al-Resayes, S.I.; Nehdi, I.A.; Al-Muhtaseb, A.H.

2016-07-01

This paper presents an acid pre-treatment process and a kinetic study for the esterification reaction of Oleum papaveris seminis oil with methanol in the presence of amberlite 120 as a solid catalyst to convert the oil into methyl esters. Response surface methodology (RSM) was applied to optimize the reaction parameters, i.e. reaction time, percentage of the catalyst and volume ratio of methanol to oil. The results revealed that 0.87% w/w of catalyst concentration and 44.70% v/v of methanol to oil ratio provided final free fatty acid (FFA) contents of 0.60% w/w at 102.40 min of reaction time. It proved that the contribution of Amberlite 120 in the esterification of FFA was highly significant. The kinetics of the esterification in Oleum papaveris seminis oil with methanol in the presence of the amberlite 120 catalyst were also investigated to establish the reaction rate constant (k), reaction order, and activation energy. The study was performed under the optimized parameters at three reaction temperatures (50, 55, and 60 ºC). The value of k was in the range of 0.013 to 0.027 min-1. The first-order kinetics’ model was suitable for this irreversible FFA esterification with the activation energy of about 60.9 KJ·mol-1. (Author)

Stochastic optimization-based study of dimerization kinetics

Indian Academy of Sciences (India)

To this end, we study dimerization kinetics of protein as a model system. We follow the dimerization kinetics using a stochastic simulation algorithm and ... optimization; dimerization kinetics; sensitivity analysis; stochastic simulation ... tion in large molecules and clusters, or the design ..... An unbiased strategy of allocating.

Optimal Stochastic Advertising Strategies for the U.S. Beef Industry

OpenAIRE

Kun C. Lee; Stanley Schraufnagel; Earl O. Heady

1982-01-01

An important decision variable in the promotional strategy for the beef sector is the optimal level of advertising expenditures over time. Optimal stochastic and deterministic advertising expenditures are derived for the U.S. beef industry for the period `1966 through 1980. They are compared with historical levels and gains realized by optimal advertising strategies are measured. Finally, the optimal advertising expenditures in the future are forecasted.

Probing Entanglement in Adiabatic Quantum Optimization with Trapped Ions

Directory of Open Access Journals (Sweden)

Philipp eHauke

2015-04-01

Full Text Available Adiabatic quantum optimization has been proposed as a route to solve NP-complete problems, with a possible quantum speedup compared to classical algorithms. However, the precise role of quantum effects, such as entanglement, in these optimization protocols is still unclear. We propose a setup of cold trapped ions that allows one to quantitatively characterize, in a controlled experiment, the interplay of entanglement, decoherence, and non-adiabaticity in adiabatic quantum optimization. We show that, in this way, a broad class of NP-complete problems becomes accessible for quantum simulations, including the knapsack problem, number partitioning, and instances of the max-cut problem. Moreover, a general theoretical study reveals correlations of the success probability with entanglement at the end of the protocol. From exact numerical simulations for small systems and linear ramps, however, we find no substantial correlations with the entanglement during the optimization. For the final state, we derive analytically a universal upper bound for the success probability as a function of entanglement, which can be measured in experiment. The proposed trapped-ion setups and the presented study of entanglement address pertinent questions of adiabatic quantum optimization, which may be of general interest across experimental platforms.

Optimization of entanglement witnesses

Science.gov (United States)

Lewenstein, M.; Kraus, B.; Cirac, J. I.; Horodecki, P.

2000-11-01

An entanglement witness (EW) is an operator that allows the detection of entangled states. We give necessary and sufficient conditions for such operators to be optimal, i.e., to detect entangled states in an optimal way. We show how to optimize general EW, and then we particularize our results to the nondecomposable ones; the latter are those that can detect positive partial transpose entangled states (PPTES's). We also present a method to systematically construct and optimize this last class of operators based on the existence of ``edge'' PPTES's, i.e., states that violate the range separability criterion [Phys. Lett. A 232, 333 (1997)] in an extreme manner. This method also permits a systematic construction of nondecomposable positive maps (PM's). Our results lead to a sufficient condition for entanglement in terms of nondecomposable EW's and PM's. Finally, we illustrate our results by constructing optimal EW acting on H=C2⊗C4. The corresponding PM's constitute examples of PM's with minimal ``qubit'' domains, or-equivalently-minimal Hermitian conjugate codomains.

Modeling and energy efficiency optimization of belt conveyors

International Nuclear Information System (INIS)

Zhang, Shirong; Xia, Xiaohua

2011-01-01

Highlights: → We take optimization approach to improve operation efficiency of belt conveyors. → An analytical energy model, originating from ISO 5048, is proposed. → Then an off-line and an on-line parameter estimation schemes are investigated. → In a case study, six optimization problems are formulated with solutions in simulation. - Abstract: The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment and operation levels. Specifically, variable speed control, an equipment level intervention, is recommended to improve operation efficiency of belt conveyors. However, the current implementations mostly focus on lower level control loops without operational considerations at the system level. This paper intends to take a model based optimization approach to improve the efficiency of belt conveyors at the operational level. An analytical energy model, originating from ISO 5048, is firstly proposed, which lumps all the parameters into four coefficients. Subsequently, both an off-line and an on-line parameter estimation schemes are applied to identify the new energy model, respectively. Simulation results are presented for the estimates of the four coefficients. Finally, optimization is done to achieve the best operation efficiency of belt conveyors under various constraints. Six optimization problems of a typical belt conveyor system are formulated, respectively, with solutions in simulation for a case study.

Computer models for optimizing radiation therapy

International Nuclear Information System (INIS)

Duechting, W.

1998-01-01

The aim of this contribution is to outline how methods of system analysis, control therapy and modelling can be applied to simulate normal and malignant cell growth and to optimize cancer treatment as for instance radiation therapy. Based on biological observations and cell kinetic data, several types of models have been developed describing the growth of tumor spheroids and the cell renewal of normal tissue. The irradiation model is represented by the so-called linear-quadratic model describing the survival fraction as a function of the dose. Based thereon, numerous simulation runs for different treatment schemes can be performed. Thus, it is possible to study the radiation effect on tumor and normal tissue separately. Finally, this method enables a computer-assisted recommendation for an optimal patient-specific treatment schedule prior to clinical therapy. (orig.) [de

Comparative study of flare control laws. [optimal control of b-737 aircraft approach and landing

Science.gov (United States)

Nadkarni, A. A.; Breedlove, W. J., Jr.

1979-01-01

A digital 3-D automatic control law was developed to achieve an optimal transition of a B-737 aircraft between various initial glid slope conditions and the desired final touchdown condition. A discrete, time-invariant, optimal, closed-loop control law presented for a linear regulator problem, was extended to include a system being acted upon by a constant disturbance. Two forms of control laws were derived to solve this problem. One method utilized the feedback of integral states defined appropriately and augmented with the original system equations. The second method formulated the problem as a control variable constraint, and the control variables were augmented with the original system. The control variable constraint control law yielded a better performance compared to feedback control law for the integral states chosen.

Hanford 100-N Area Tracer Study Final Report

International Nuclear Information System (INIS)

Kretzschmar, S.P.; Bedi, G.S.; Martinez, P.; Ervin, K.

1996-09-01

This document provides an engineering tracer study final report for the determination of contact time for the disinfection process at Group A Nontransient Noncommunity water treatment plant for the 100- N Water Plant (located on the Hanford Site in Richland, Washington). The purpose of this study is to determine the actual detention time within the plant clearwell, and the disinfection contact time at several clearwell effluent flow rates

An ion-optical design study of a carbon-ion rotating gantry with a superconducting final bending magnet

International Nuclear Information System (INIS)

Bokor, J.; Pavlovič, M.

2016-01-01

Ion-optical designs of an isocentric ion gantry with a compact curved superconducting final bending magnet are presented. The gantry is designed for transporting carbon-therapy beams with nominal kinetic energy of 400 MeV/u, which corresponds to the penetration range of C"6"+ beam in water of about 28 cm. In contrast to other existing designs, we present a “hybrid” beam transport system containing a single superconducting element – the last bending magnet. All other elements are based on conventional warm technology. Ion-optical properties of such a hybrid system are investigated in case of transporting non-symmetric (i.e. different emittance patterns in the horizontal and vertical plane) beams. Different conditions for transporting the non-symmetric beams are analyzed aiming at finding the optimal, i.e. the most compact, gantry version. The final gantry layout is presented including a 2D parallel scanning. The ion-optical and scanning properties of the final gantry design are described, discussed and illustrated by computer simulations performed by WinAGILE.

Efficient Iris Localization via Optimization Model

Directory of Open Access Journals (Sweden)

Qi Wang

2017-01-01

Full Text Available Iris localization is one of the most important processes in iris recognition. Because of different kinds of noises in iris image, the localization result may be wrong. Besides this, localization process is time-consuming. To solve these problems, this paper develops an efficient iris localization algorithm via optimization model. Firstly, the localization problem is modeled by an optimization model. Then SIFT feature is selected to represent the characteristic information of iris outer boundary and eyelid for localization. And SDM (Supervised Descent Method algorithm is employed to solve the final points of outer boundary and eyelids. Finally, IRLS (Iterative Reweighted Least-Square is used to obtain the parameters of outer boundary and upper and lower eyelids. Experimental result indicates that the proposed algorithm is efficient and effective.

The Czech longitudinal study of optimal development

Czech Academy of Sciences Publication Activity Database

Kebza, V.; Šolcová, Iva; Kodl, M.; Kernová, V.

2012-01-01

Roč. 47, Suppl. 1 (2012), s. 266-266 ISSN 0020-7594. [International Congress of Psychology /30./. 22.07.2012-27.07.2012, Cape Town] R&D Projects: GA ČR GAP407/10/2410 Institutional support: RVO:68081740 Keywords : optimal development * Prague longitudinal study Subject RIV: AN - Psychology

A method optimization study for atomic absorption ...

African Journals Online (AJOL)

A sensitive, reliable and relative fast method has been developed for the determination of total zinc in insulin by atomic absorption spectrophotometer. This designed study was used to optimize the procedures for the existing methods. Spectrograms of both standard and sample solutions of zinc were recorded by measuring ...

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

Science.gov (United States)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Economic optimization of natural hazard protection - conceptual study of existing approaches

Science.gov (United States)

Spackova, Olga; Straub, Daniel

2013-04-01

Risk-based planning of protection measures against natural hazards has become a common practice in many countries. The selection procedure aims at identifying an economically efficient strategy with regard to the estimated costs and risk (i.e. expected damage). A correct setting of the evaluation methodology and decision criteria should ensure an optimal selection of the portfolio of risk protection measures under a limited state budget. To demonstrate the efficiency of investments, indicators such as Benefit-Cost Ratio (BCR), Marginal Costs (MC) or Net Present Value (NPV) are commonly used. However, the methodologies for efficiency evaluation differ amongst different countries and different hazard types (floods, earthquakes etc.). Additionally, several inconsistencies can be found in the applications of the indicators in practice. This is likely to lead to a suboptimal selection of the protection strategies. This study provides a general formulation for optimization of the natural hazard protection measures from a socio-economic perspective. It assumes that all costs and risks can be expressed in monetary values. The study regards the problem as a discrete hierarchical optimization, where the state level sets the criteria and constraints, while the actual optimization is made on the regional level (towns, catchments) when designing particular protection measures and selecting the optimal protection level. The study shows that in case of an unlimited budget, the task is quite trivial, as it is sufficient to optimize the protection measures in individual regions independently (by minimizing the sum of risk and cost). However, if the budget is limited, the need for an optimal allocation of resources amongst the regions arises. To ensure this, minimum values of BCR or MC can be required by the state, which must be achieved in each region. The study investigates the meaning of these indicators in the optimization task at the conceptual level and compares their

Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors

Directory of Open Access Journals (Sweden)

Yanjun Zhang

2015-01-01

Full Text Available A new optimized extreme learning machine- (ELM- based method for power system transient stability prediction (TSP using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.

Warpage improvement on wheel caster by optimizing the process parameters using genetic algorithm (GA)

Science.gov (United States)

Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

In injection moulding process, the defects will always encountered and affected the final product shape and functionality. This study is concerning on minimizing warpage and optimizing the process parameter of injection moulding part. Apart from eliminating product wastes, this project also giving out best recommended parameters setting. This research studied on five parameters. The optimization showed that warpage have been improved 42.64% from 0.6524 mm to 0.30879 mm in Autodesk Moldflow Insight (AMI) simulation result and Genetic Algorithm (GA) respectively.

Multiobjective optimization design of an rf gun based electron diffraction beam line

Directory of Open Access Journals (Sweden)

Colwyn Gulliford

2017-03-01

Full Text Available Multiobjective genetic algorithm optimizations of a single-shot ultrafast electron diffraction beam line comprised of a 100  MV/m 1.6-cell normal conducting rf (NCRF gun, as well as a nine-cell 2π/3 bunching cavity placed between two solenoids, have been performed. These include optimization of the normalized transverse emittance as a function of bunch charge, as well as optimization of the transverse coherence length as a function of the rms bunch length of the beam at the sample location for a fixed charge of 10^{6} electrons. Analysis of the resulting solutions is discussed in terms of the relevant scaling laws, and a detailed description of one of the resulting solutions from the coherence length optimizations is given. For a charge of 10^{6} electrons and final beam sizes of σ_{x}≥25  μm and σ_{t}≈5  fs, we found a relative coherence length of L_{c,x}/σ_{x}≈0.07 using direct optimization of the coherence length. Additionally, based on optimizations of the emittance as a function of final bunch length, we estimate the relative coherence length for bunch lengths of 30 and 100 fs to be roughly 0.1 and 0.2  nm/μm, respectively. Finally, using the scaling of the optimal emittance with bunch charge, for a charge of 10^{5} electrons, we estimate relative coherence lengths of 0.3, 0.5, and 0.92  nm/μm for final bunch lengths of 5, 30 and 100 fs, respectively.

A Pilot Study Assessing ECG versus ECHO Ventriculoventricular Optimization in Pediatric Resynchronization Patients.

Science.gov (United States)

Punn, Rajesh; Hanisch, Debra; Motonaga, Kara S; Rosenthal, David N; Ceresnak, Scott R; Dubin, Anne M

2016-02-01

Cardiac resynchronization therapy indications and management are well described in adults. Echocardiography (ECHO) has been used to optimize mechanical synchrony in these patients; however, there are issues with reproducibility and time intensity. Pediatric patients add challenges, with diverse substrates and limited capacity for cooperation. Electrocardiographic (ECG) methods to assess electrical synchrony are expeditious but have not been extensively studied in children. We sought to compare ECHO and ECG CRT optimization in children. Prospective, pediatric, single-center cross-over trial comparing ECHO and ECG optimization with CRT. Patients were assigned to undergo either ECHO or ECG optimization, followed for 6 months, and crossed-over to the other assignment for another 6 months. ECHO pulsed-wave tissue Doppler and 12-lead ECG were obtained for 5 VV delays. ECG optimization was defined as the shortest QRSD and ECHO optimization as the lowest dyssynchrony index. ECHOs/ECGs were interpreted by readers blinded to optimization technique. After each 6 month period, these data were collected: ejection fraction, velocimetry-derived cardiac index, quality of life, ECHO-derived stroke distance, M-mode dyssynchrony, study cost, and time. Outcomes for each optimization method were compared. From June 2012 to December 2013, 19 patients enrolled. Mean age was 9.1 ± 4.3 years; 14 (74%) had structural heart disease. The mean time for optimization was shorter using ECG than ECHO (9 ± 1 min vs. 68 ± 13 min, P cost for charges was $4,400 ± 700 less for ECG. No other outcome differed between groups. ECHO optimization of synchrony was not superior to ECG optimization in this pilot study. ECG optimization required less time and cost than ECHO optimization. © 2015 Wiley Periodicals, Inc.

Accelerating GW calculations with optimal polarizability basis

Energy Technology Data Exchange (ETDEWEB)

Umari, P.; Stenuit, G. [CNR-IOM DEMOCRITOS Theory Elettra Group, Basovizza (Trieste) (Italy); Qian, X.; Marzari, N. [Department of Materials Science and Engineering, MIT, Cambridge, MA (United States); Giacomazzi, L.; Baroni, S. [CNR-IOM DEMOCRITOS Theory Elettra Group, Basovizza (Trieste) (Italy); SISSA - Scuola Internazionale Superiore di Studi Avanzati, Trieste (Italy)

2011-03-15

We present a method for accelerating GW quasi-particle (QP) calculations. This is achieved through the introduction of optimal basis sets for representing polarizability matrices. First the real-space products of Wannier like orbitals are constructed and then optimal basis sets are obtained through singular value decomposition. Our method is validated by calculating the vertical ionization energies of the benzene molecule and the band structure of crystalline silicon. Its potentialities are illustrated by calculating the QP spectrum of a model structure of vitreous silica. Finally, we apply our method for studying the electronic structure properties of a model of quasi-stoichiometric amorphous silicon nitride and of its point defects. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Optimal control of quantum systems: a projection approach

International Nuclear Information System (INIS)

Cheng, C.-J.; Hwang, C.-C.; Liao, T.-L.; Chou, G.-L.

2005-01-01

This paper considers the optimal control of quantum systems. The controlled quantum systems are described by the probability-density-matrix-based Liouville-von Neumann equation. Using projection operators, the states of the quantum system are decomposed into two sub-spaces, namely the 'main state' space and the 'remaining state' space. Since the control energy is limited, a solution for optimizing the external control force is proposed in which the main state is brought to the desired main state at a certain target time, while the population of the remaining state is simultaneously suppressed in order to diminish its effects on the final population of the main state. The optimization problem is formulated by maximizing a general cost functional of states and control force. An efficient algorithm is developed to solve the optimization problem. Finally, using the hydrogen fluoride (HF) molecular population transfer problem as an illustrative example, the effectiveness of the proposed scheme for a quantum system initially in a mixed state or in a pure state is investigated through numerical simulations

Optimization of a particle optical system in a mutilprocessor environment

International Nuclear Information System (INIS)

Wei Lei; Yin Hanchun; Wang Baoping; Tong Linsu

2002-01-01

In the design of a charged particle optical system, many geometrical and electric parameters have to be optimized to improve the performance characteristics. In every optimization cycle, the electromagnetic field and particle trajectories have to be calculated. Therefore, the optimization of a charged particle optical system is limited by the computer resources seriously. Apart from this, numerical errors of calculation may also influence the convergence of merit function. This article studies how to improve the optimization of charged particle optical systems. A new method is used to determine the gradient matrix. With this method, the accuracy of the Jacobian matrix can be improved. In this paper, the charged particle optical system is optimized with a Message Passing Interface (MPI). The electromagnetic field, particle trajectories and gradients of optimization variables are calculated on networks of workstations. Therefore, the speed of optimization has been increased largely. It is possible to design a complicated charged particle optical system with optimum quality on a MPI environment. Finally, an electron gun for a cathode ray tube has been optimized on a MPI environment to verify the method proposed in this paper

Customer demand prediction of service-oriented manufacturing using the least square support vector machine optimized by particle swarm optimization algorithm

Science.gov (United States)

Cao, Jin; Jiang, Zhibin; Wang, Kangzhou

2017-07-01

Many nonlinear customer satisfaction-related factors significantly influence the future customer demand for service-oriented manufacturing (SOM). To address this issue and enhance the prediction accuracy, this article develops a novel customer demand prediction approach for SOM. The approach combines the phase space reconstruction (PSR) technique with the optimized least square support vector machine (LSSVM). First, the prediction sample space is reconstructed by the PSR to enrich the time-series dynamics of the limited data sample. Then, the generalization and learning ability of the LSSVM are improved by the hybrid polynomial and radial basis function kernel. Finally, the key parameters of the LSSVM are optimized by the particle swarm optimization algorithm. In a real case study, the customer demand prediction of an air conditioner compressor is implemented. Furthermore, the effectiveness and validity of the proposed approach are demonstrated by comparison with other classical predication approaches.

Optimization of aerodynamic efficiency for twist morphing MAV wing

Directory of Open Access Journals (Sweden)

N.I. Ismail

2014-06-01

Full Text Available Twist morphing (TM is a practical control technique in micro air vehicle (MAV flight. However, TM wing has a lower aerodynamic efficiency (CL/CD compared to membrane and rigid wing. This is due to massive drag penalty created on TM wing, which had overwhelmed the successive increase in its lift generation. Therefore, further CL/CDmax optimization on TM wing is needed to obtain the optimal condition for the morphing wing configuration. In this paper, two-way fluid–structure interaction (FSI simulation and wind tunnel testing method are used to solve and study the basic wing aerodynamic performance over (non-optimal TM, membrane and rigid wings. Then, a multifidelity data metamodel based design optimization (MBDO process is adopted based on the Ansys-DesignXplorer frameworks. In the adaptive MBDO process, Kriging metamodel is used to construct the final multifidelity CL/CD responses by utilizing 23 multi-fidelity sample points from the FSI simulation and experimental data. The optimization results show that the optimal TM wing configuration is able to produce better CL/CDmax magnitude by at least 2% than the non-optimal TM wings. The flow structure formation reveals that low TV strength on the optimal TM wing induces low CD generation which in turn improves its overall CL/CDmax performance.

Optimal boarding method for airline passengers

Energy Technology Data Exchange (ETDEWEB)

Steffen, Jason H.; /Fermilab

2008-02-01

Using a Markov Chain Monte Carlo optimization algorithm and a computer simulation, I find the passenger ordering which minimizes the time required to board the passengers onto an airplane. The model that I employ assumes that the time that a passenger requires to load his or her luggage is the dominant contribution to the time needed to completely fill the aircraft. The optimal boarding strategy may reduce the time required to board and airplane by over a factor of four and possibly more depending upon the dimensions of the aircraft. I explore some features of the optimal boarding method and discuss practical modifications to the optimal. Finally, I mention some of the benefits that could come from implementing an improved passenger boarding scheme.

Multi-Objective Optimization for Solid Amine CO2 Removal Assembly in Manned Spacecraft

Directory of Open Access Journals (Sweden)

Rong A

2017-07-01

Full Text Available Carbon Dioxide Removal Assembly (CDRA is one of the most important systems in the Environmental Control and Life Support System (ECLSS for a manned spacecraft. With the development of adsorbent and CDRA technology, solid amine is increasingly paid attention due to its obvious advantages. However, a manned spacecraft is launched far from the Earth, and its resources and energy are restricted seriously. These limitations increase the design difficulty of solid amine CDRA. The purpose of this paper is to seek optimal design parameters for the solid amine CDRA. Based on a preliminary structure of solid amine CDRA, its heat and mass transfer models are built to reflect some features of the special solid amine adsorbent, Polyethylenepolyamine adsorbent. A multi-objective optimization for the design of solid amine CDRA is discussed further in this paper. In this study, the cabin CO2 concentration, system power consumption and entropy production are chosen as the optimization objectives. The optimization variables consist of adsorption cycle time, solid amine loading mass, adsorption bed length, power consumption and system entropy production. The Improved Non-dominated Sorting Genetic Algorithm (NSGA-II is used to solve this multi-objective optimization and to obtain optimal solution set. A design example of solid amine CDRA in a manned space station is used to show the optimal procedure. The optimal combinations of design parameters can be located on the Pareto Optimal Front (POF. Finally, Design 971 is selected as the best combination of design parameters. The optimal results indicate that the multi-objective optimization plays a significant role in the design of solid amine CDRA. The final optimal design parameters for the solid amine CDRA can guarantee the cabin CO2 concentration within the specified range, and also satisfy the requirements of lightweight and minimum energy consumption.

SLC Final Performance and Lessons

International Nuclear Information System (INIS)

Phinney, Nan

2000-01-01

The Stanford Linear Collider (SLC) was the first prototype of a new type of accelerator, the electron-positron linear collider. Many years of dedicated effort were required to understand the physics of this new technology and to develop the techniques for maximizing performance. Key issues were emittance dilution, stability, final beam optimization and background control. Precision, non-invasive diagnostics were required to measure and monitor the beams throughout the machine. Beam-based feedback systems were needed to stabilize energy, trajectory, intensity and the final beam size at the interaction point. variety of new tuning techniques were developed to correct for residual optical or alignment errors. The final focus system underwent a series of refinements in order to deliver sub-micron size beams. It also took many iterations to understand the sources of backgrounds and develop the methods to control them. The benefit from this accumulated experience was seen in the performance of the SLC during its final run in 1997-98. The luminosity increased by a factor of three to 3*10 30 and the 350,000 Z data sample delivered was nearly double that from all previous runs combined

Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study

Directory of Open Access Journals (Sweden)

Kangji Li

2017-02-01

Full Text Available Numerous conflicting criteria exist in building design optimization, such as energy consumption, greenhouse gas emission and indoor thermal performance. Different simulation-based optimization strategies and various optimization algorithms have been developed. A few of them are analyzed and compared in solving building design problems. This paper presents an efficient optimization framework to facilitate optimization designs with the aid of commercial simulation software and MATLAB. The performances of three optimization strategies, including the proposed approach, GenOpt method and artificial neural network (ANN method, are investigated using a case study of a simple building energy model. Results show that the proposed optimization framework has competitive performances compared with the GenOpt method. Further, in another practical case, four popular multi-objective algorithms, e.g., the non-dominated sorting genetic algorithm (NSGA-II, multi-objective particle swarm optimization (MOPSO, the multi-objective genetic algorithm (MOGA and multi-objective differential evolution (MODE, are realized using the propose optimization framework and compared with three criteria. Results indicate that MODE achieves close-to-optimal solutions with the best diversity and execution time. An uncompetitive result is achieved by the MOPSO in this case study.

Optimization of stochastic discrete systems and control on complex networks computational networks

CERN Document Server

Lozovanu, Dmitrii

2014-01-01

This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors' new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book's final chapter is devoted to finite horizon stochastic con...

Taxing Strategies for Carbon Emissions: A Bilevel Optimization Approach

Directory of Open Access Journals (Sweden)

Wei Wei

2014-04-01

Full Text Available This paper presents a quantitative and computational method to determine the optimal tax rate among generating units. To strike a balance between the reduction of carbon emission and the profit of energy sectors, the proposed bilevel optimization model can be regarded as a Stackelberg game between the government agency and the generation companies. The upper-level, which represents the government agency, aims to limit total carbon emissions within a certain level by setting optimal tax rates among generators according to their emission performances. The lower-level, which represents decision behaviors of the grid operator, tries to minimize the total production cost under the tax rates set by the government. The bilevel optimization model is finally reformulated into a mixed integer linear program (MILP which can be solved by off-the-shelf MILP solvers. Case studies on a 10-unit system as well as a provincial power grid in China demonstrate the validity of the proposed method and its capability in practical applications.

Shape optimization of metal forming and forging products using the stress equivalent static loads calculated from a virtual model

International Nuclear Information System (INIS)

Jang, Hwan Hak; Jeong, Seong Beom; Park, Gyung Jin

2012-01-01

A shape optimization is proposed to obtain the desired final shape of forming and forging products in the manufacturing process. The final shape of a forming product depends on the shape parameters of the initial blank shape. The final shape of a forging product depends on the shape parameters of the billet shape. Shape optimization can be used to determine the shape of the blank and billet to obtain the appropriate final forming and forging products. The equivalent static loads method for non linear static response structural optimization (ESLSO) is used to perform metal forming and forging optimization since nonlinear dynamic analysis is required. Stress equivalent static loads (stress ESLs) are newly defined using a virtual model by redefining the value of the material properties. The examples in this paper show that optimization using the stress ESLs is quite useful and the final shapes of a forming and forging products are identical to the desired shapes

Multicriteria VMAT optimization

International Nuclear Information System (INIS)

Craft, David; McQuaid, Dualta; Wala, Jeremiah; Chen, Wei; Salari, Ehsan; Bortfeld, Thomas

2012-01-01

Purpose: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency. Methods: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE. Results: VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than 5 min on average. Conclusions: VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan, which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems.

Acquisition Pricing and Inventory Decisions on Dual-Source Spare-Part System with Final Production and Remanufacturing

Directory of Open Access Journals (Sweden)

Yancong Zhou

2016-01-01

Full Text Available The life spans of durable goods are longer than their warranty periods. To satisfy the service demand of spare parts and keep the market competition advantage, enterprises have to maintain the longer inventory planning of spare parts. However, how to obtain a valid number of spare parts is difficult for those enterprises. In this paper, we consider a spare-part inventory problem, where the inventory can be replenished by two ways including the final production order and the remanufacturing way. Especially for the remanufacturing way, we consider the acquisition management problem of used products concerning an acquisition pricing decision. In a multiperiod setting, we formulate the problem into a dynamic optimization problem, where the system decisions include the final production order and acquisition price of used products at each period. By stochastic dynamic programming, we obtain the optimal policy of the acquisition pricing at each period and give the optimal policy structure of the optimization problem at the first period. Then, a recursion algorithm is designed to calculate the optimal decisions and the critical points in the policy. Finally, the numerical analyses show the effects of demand information and customer’s sensitive degree on the related decisions and the optimal cost.

Preliminary study for a nuclear multi-cycle reload optimization system

International Nuclear Information System (INIS)

Baptista, Rafael Pereira; Lima, Alan Miranda M. de; Medeiros, Jose Antonio Carlos Canedo; Schirru, Roberto

2007-01-01

Fuel assemblies in a reactor are discharged normally after several fuel cycles. This happens because of the concentration of fissile material existing in the fuel assemblies in the core decreases to values such that it is not more possible to keep the reactor operating producing energy at normal rated power. Therefore, the refueling optimization for a nuclear power plant is in fact a multi-cycle problem. A typical multi-cycle reload optimization depends on several kinds of relationships: one is the relationship between the locations where the fuel assemblies are placed for a specified fuel cycle; another is the relationship between fuel loading patterns for the subsequent fuel cycles. This makes the problem very complex and difficult to solve. Until the moment, all the presented proposals for solution are far from solving the multi-cycle optimization problems in reactor fuel management. In this work, we will show preliminary studies of possible solutions for a typical multi-cycle reload optimization problem trying to consider most important restrictions of a real model. In the initial comparisons, the optimization results will be compared with those obtained by the successive single cycle optimizations. (author)

Site-selection studies for final disposal of spent fuel in Finland

International Nuclear Information System (INIS)

Vuorela, P.; Aeikaes, T.

1984-02-01

In the management of waste by the Industrial Power Company Ltd. (TVO) preparations are being made for the final disposal of unprocessed spent fuel into the Finnish bedrock. The site selection program will advance in three phases. The final disposal site must be made at the latest by the end of the year 2000, in accordance with a decision laid down by the Finnish Government. In the first phase, 1983-85, the main object is to find homogeneous stable bedrock blocks surrounded by fracture zones located at a safe distance from the planned disposal area. The work usually starts with a regional structural analysis of mosaics of Landsat-1 winter and summer imagery. Next an assortment of different maps, which cover the whole country, is used. Technical methods for geological and hydrogeological site investigations are being developed during the very first phase of the studies, and a borehole 1000 meters deep will be made in southwestern Finland. Studies for the final disposal of spent fuel or high-level reprocessing waste have been made since 1974 in Finland. General suitability studies of the bedrock have been going on since 1977. The present results indicate that suitable investigation areas for the final disposal of highly active waste can be found in Finland

Optimal Control for a Class of Chaotic Systems

Directory of Open Access Journals (Sweden)

Jianxiong Zhang

2012-01-01

Full Text Available This paper proposes the optimal control methods for a class of chaotic systems via state feedback. By converting the chaotic systems to the form of uncertain piecewise linear systems, we can obtain the optimal controller minimizing the upper bound on cost function by virtue of the robust optimal control method of piecewise linear systems, which is cast as an optimization problem under constraints of bilinear matrix inequalities (BMIs. In addition, the lower bound on cost function can be achieved by solving a semidefinite programming (SDP. Finally, numerical examples are given to illustrate the results.

Advances in metaheuristic algorithms for optimal design of structures

CERN Document Server

Kaveh, A

2017-01-01

This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...

Advances in metaheuristic algorithms for optimal design of structures

CERN Document Server

Kaveh, A

2014-01-01

This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...

Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

Directory of Open Access Journals (Sweden)

Jianzhou Wang

2015-01-01

Full Text Available This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP and optimized support vector regression (SVR. Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA, particle swarm optimization algorithm (PSO, and cuckoo optimization algorithm (COA. Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1 analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2 the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3 the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.

Optimization Parameters and Some Electronic Properties of AlSb Diamondoids: A Density Function Theory Study

Directory of Open Access Journals (Sweden)

Hayder M. Abduljalil

2018-05-01

Full Text Available Density function theory with LSDA/3-21G basis set is used to investigate the optimization parameters such as (angles and bonds and some electronic properties include (cohesive energy, energy gap and lattice constant of AlSb at nano diamantine and different size of(Linear, Ring, Diamantine and Tetramantine. The results of the present work show that the angles of AlSbH nano molecule in range (96,21-126.05 Å are near to standard angle of diamond (109.47 Å. Therefore, it is found that the cohesive energy for molecules of studied in decrease state with increase size but the energy gap decreased in gradually shape from (5.2-2.1eV with increase of the number of atoms, that typical is on the lattice constant. It is finally shown that the size molecules has direct effect on electronic properties to material studied that can used this material in different applications and according to the purpose asked for

Numerical optimization of conical flow waveriders including detailed viscous effects

Science.gov (United States)

Bowcutt, Kevin G.; Anderson, John D., Jr.; Capriotti, Diego

1987-01-01

A family of optimized hypersonic waveriders is generated and studied wherein detailed viscous effects are included within the optimization process itself. This is in contrast to previous optimized waverider work, wherein purely inviscid flow is used to obtain the waverider shapes. For the present waveriders, the undersurface is a streamsurface of an inviscid conical flowfield, the upper surface is a streamsurface of the inviscid flow over a tapered cylinder (calculated by the axisymmetric method of characteristics), and the viscous effects are treated by integral solutions of the boundary layer equations. Transition from laminar to turbulent flow is included within the viscous calculations. The optimization is carried out using a nonlinear simplex method. The resulting family of viscous hypersonic waveriders yields predicted high values of lift/drag, high enough to break the L/D barrier based on experience with other hypersonic configurations. Moreover, the numerical optimization process for the viscous waveriders results in distinctly different shapes compared to previous work with inviscid-designed waveriders. Also, the fine details of the viscous solution, such as how the shear stress is distributed over the surface, and the location of transition, are crucial to the details of the resulting waverider geometry. Finally, the moment coefficient variations and heat transfer distributions associated with the viscous optimized waveriders are studied.

The Sizing and Optimization Language (SOL): A computer language to improve the user/optimizer interface

Science.gov (United States)

Lucas, S. H.; Scotti, S. J.

1989-01-01

The nonlinear mathematical programming method (formal optimization) has had many applications in engineering design. A figure illustrates the use of optimization techniques in the design process. The design process begins with the design problem, such as the classic example of the two-bar truss designed for minimum weight as seen in the leftmost part of the figure. If formal optimization is to be applied, the design problem must be recast in the form of an optimization problem consisting of an objective function, design variables, and constraint function relations. The middle part of the figure shows the two-bar truss design posed as an optimization problem. The total truss weight is the objective function, the tube diameter and truss height are design variables, with stress and Euler buckling considered as constraint function relations. Lastly, the designer develops or obtains analysis software containing a mathematical model of the object being optimized, and then interfaces the analysis routine with existing optimization software such as CONMIN, ADS, or NPSOL. This final state of software development can be both tedious and error-prone. The Sizing and Optimization Language (SOL), a special-purpose computer language whose goal is to make the software implementation phase of optimum design easier and less error-prone, is presented.

Optimization on Spaces of Curves

DEFF Research Database (Denmark)

Møller-Andersen, Jakob

in Rd, and methods to solve the initial and boundary value problem for geodesics allowing us to compute the Karcher mean and principal components analysis of data of curves. We apply the methods to study shape variation in synthetic data in the Kimia shape database, in HeLa cell nuclei and cycles...... of cardiac deformations. Finally we investigate a new application of Riemannian shape analysis in shape optimization. We setup a simple elliptic model problem, and describe how to apply shape calculus to obtain directional derivatives in the manifold of planar curves. We present an implementation based...

A Degree Distribution Optimization Algorithm for Image Transmission

Science.gov (United States)

Jiang, Wei; Yang, Junjie

2016-09-01

Luby Transform (LT) code is the first practical implementation of digital fountain code. The coding behavior of LT code is mainly decided by the degree distribution which determines the relationship between source data and codewords. Two degree distributions are suggested by Luby. They work well in typical situations but not optimally in case of finite encoding symbols. In this work, the degree distribution optimization algorithm is proposed to explore the potential of LT code. Firstly selection scheme of sparse degrees for LT codes is introduced. Then probability distribution is optimized according to the selected degrees. In image transmission, bit stream is sensitive to the channel noise and even a single bit error may cause the loss of synchronization between the encoder and the decoder. Therefore the proposed algorithm is designed for image transmission situation. Moreover, optimal class partition is studied for image transmission with unequal error protection. The experimental results are quite promising. Compared with LT code with robust soliton distribution, the proposed algorithm improves the final quality of recovered images obviously with the same overhead.

Optimization methods applied to hybrid vehicle design

Science.gov (United States)

Donoghue, J. F.; Burghart, J. H.

1983-01-01

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.

Optimizing of the recycling of contaminated concrete debris. Final report

International Nuclear Information System (INIS)

Kloeckner, J.; Rasch, H.; Schloesser, K.H.; Schon, T.

1999-01-01

1. Latest research: So far concrete debris from nuclear facilities has been free released or was treated as radioactive waste. 2. Objective: The objective of this study is to develop solutions and methods for recycling concrete debris. The amount of materials used in nuclear facilities should be limited and the contamination of new materials should be avoided. 3. Methods: The status of recycling was presented using examples of operating or completed decommissioning as well as available studies and literature. The quality requirements for the production of new concrete products using recycled materials has been discussed. The expected amounts of concrete debris for the next 12 years was estimated. For the proposed recycling examples, radiological and economic aspects have been considered. 4. Results: The production of qualified concrete products from concrete debris is possible by using modified receptions. Technical regulations to this are missing. There is no need for the utilization of large amounts of concrete debris for shielding walls. For the production of new shielding-containers for radioactive waste, concrete debris can be applied. Regarding the distance to a central recycling facility the use of mobile equipment can be economical. By using the concrete for filling the cavity or space in a final storage, it is possible to dispose the whole radioactive debris. 5. Application possibilities: The use of concrete debris as an inner concrete shielding in waste-containers today is already possible. For the manufacture of qualified concrete products by using recycling products, further developments and regulations are necessary. (orig.) [de

On the role of final-state interactions in Dalitz plot studies

International Nuclear Information System (INIS)

Kubis, Bastian; Niecknig, Franz; Schneider, Sebastian P.

2012-01-01

The study of Dalitz plots of heavy-meson decays to multi-hadron final states has received intensified interest by the possibility to gain access to precision investigations of CP violation. A thorough understanding of the hadronic final-state interactions is a prerequisite to achieve a highly sensitive, model-independent study of such Dalitz plots. We illustrate some of the theoretical tools, predominantly taken from dispersion theory, available for these and related purposes, and discuss the low-energy decays ω,φ→3π in some more detail.

On the role of final-state interactions in Dalitz plot studies

Energy Technology Data Exchange (ETDEWEB)

Kubis, Bastian, E-mail: kubis@hiskp.uni-bonn.de [Helmholtz-Institut fuer Strahlen- und Kernphysik and Bethe Center for Theoretical Physics, Universitaet Bonn (Germany); Niecknig, Franz; Schneider, Sebastian P. [Helmholtz-Institut fuer Strahlen- und Kernphysik and Bethe Center for Theoretical Physics, Universitaet Bonn (Germany)

2012-04-15

The study of Dalitz plots of heavy-meson decays to multi-hadron final states has received intensified interest by the possibility to gain access to precision investigations of CP violation. A thorough understanding of the hadronic final-state interactions is a prerequisite to achieve a highly sensitive, model-independent study of such Dalitz plots. We illustrate some of the theoretical tools, predominantly taken from dispersion theory, available for these and related purposes, and discuss the low-energy decays {omega},{phi}{yields}3{pi} in some more detail.

On the role of final-state interactions in Dalitz plot studies

Science.gov (United States)

Kubis, Bastian; Niecknig, Franz; Schneider, Sebastian P.

2012-04-01

The study of Dalitz plots of heavy-meson decays to multi-hadron final states has received intensified interest by the possibility to gain access to precision investigations of CP violation. A thorough understanding of the hadronic final-state interactions is a prerequisite to achieve a highly sensitive, model-independent study of such Dalitz plots. We illustrate some of the theoretical tools, predominantly taken from dispersion theory, available for these and related purposes, and discuss the low-energy decays ω,ϕ→3π in some more detail.

Original Framework for Optimizing Hybrid Energy Supply

Directory of Open Access Journals (Sweden)

Amevi Acakpovi

2016-01-01

Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.

Simultaneous Optimization of Topology and Component Sizes for Double Planetary Gear Hybrid Powertrains

Directory of Open Access Journals (Sweden)

Weichao Zhuang

2016-05-01

Full Text Available Hybrid powertrain technologies are successful in the passenger car market and have been actively developed in recent years. Optimal topology selection, component sizing, and controls are required for competitive hybrid vehicles, as multiple goals must be considered simultaneously: fuel efficiency, emissions, performance, and cost. Most of the previous studies explored these three design dimensions separately. In this paper, two novel frameworks combining these three design dimensions together are presented and compared. One approach is nested optimization which searches through the whole design space exhaustively. The second approach is called enhanced iterative optimization, which executes the topology optimization and component sizing alternately. A case study shows that the later method can converge to the global optimal design generated from the nested optimization, and is much more computationally efficient. In addition, we also address a known issue of optimal designs: their sensitivity to parameters, such as varying vehicle weight, which is a concern especially for the design of hybrid buses. Therefore, the iterative optimization process is applied to design a robust multi-mode hybrid electric bus under different loading scenarios as the final design challenge of this paper.

Energy-optimal electrical excitation of nerve fibers.

Science.gov (United States)

Jezernik, Saso; Morari, Manfred

2005-04-01

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

Multi-objective optimization of a vertical ground source heat pump using evolutionary algorithm

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn; Amlashi, Emad Hadaddi; Amidpour, Majid

2009-01-01

Thermodynamic and thermoeconomic optimization of a vertical ground source heat pump system has been studied. A model based on the energy and exergy analysis is presented here. An economic model of the system is developed according to the Total Revenue Requirement (TRR) method. The objective functions based on the thermodynamic and thermoeconomic analysis are developed. The proposed vertical ground source heat pump system including eight decision variables is considered for optimization. An artificial intelligence technique known as evolutionary algorithm (EA) has been utilized as an optimization method. This approach has been applied to minimize either the total levelized cost of the system product or the exergy destruction of the system. Three levels of optimization including thermodynamic single objective, thermoeconomic single objective and multi-objective optimizations are performed. In Multi-objective optimization, both thermodynamic and thermoeconomic objectives are considered, simultaneously. In the case of multi-objective optimization, an example of decision-making process for selection of the final solution from available optimal points on Pareto frontier is presented. The results obtained using the various optimization approaches are compared and discussed. Further, the sensitivity of optimized systems to the interest rate, to the annual number of operating hours and to the electricity cost are studied in detail.

Optimizing Teleportation Cost in Distributed Quantum Circuits

Science.gov (United States)

Zomorodi-Moghadam, Mariam; Houshmand, Mahboobeh; Houshmand, Monireh

2018-03-01

The presented work provides a procedure for optimizing the communication cost of a distributed quantum circuit (DQC) in terms of the number of qubit teleportations. Because of technology limitations which do not allow large quantum computers to work as a single processing element, distributed quantum computation is an appropriate solution to overcome this difficulty. Previous studies have applied ad-hoc solutions to distribute a quantum system for special cases and applications. In this study, a general approach is proposed to optimize the number of teleportations for a DQC consisting of two spatially separated and long-distance quantum subsystems. To this end, different configurations of locations for executing gates whose qubits are in distinct subsystems are considered and for each of these configurations, the proposed algorithm is run to find the minimum number of required teleportations. Finally, the configuration which leads to the minimum number of teleportations is reported. The proposed method can be used as an automated procedure to find the configuration with the optimal communication cost for the DQC. This cost can be used as a basic measure of the communication cost for future works in the distributed quantum circuits.

Optimal redundant systems for works with random processing time

International Nuclear Information System (INIS)

Chen, M.; Nakagawa, T.

2013-01-01

This paper studies the optimal redundant policies for a manufacturing system processing jobs with random working times. The redundant units of the parallel systems and standby systems are subject to stochastic failures during the continuous production process. First, a job consisting of only one work is considered for both redundant systems and the expected cost functions are obtained. Next, each redundant system with a random number of units is assumed for a single work. The expected cost functions and the optimal expected numbers of units are derived for redundant systems. Subsequently, the production processes of N tandem works are introduced for parallel and standby systems, and the expected cost functions are also summarized. Finally, the number of works is estimated by a Poisson distribution for the parallel and standby systems. Numerical examples are given to demonstrate the optimization problems of redundant systems

Plant systems/components modularization study. Final report. [PWR

Energy Technology Data Exchange (ETDEWEB)

1977-07-01

The final results are summarized of a Plant Systems/Components Modularization Study based on Stone and Webster's Pressurized Water Reactor Reference Design. The program has been modified to include evaluation of the most promising areas for modular consideration based on the level of the Sundesert Project engineering design completion and the feasibility of their incorporation into the plant construction effort.

Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization.

Science.gov (United States)

Huang, Daizheng; Wu, Zhihui

2017-01-01

Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empirical mode decomposition and back-propagation artificial neural networks optimized by particle swarm optimization is developed to forecast outpatient visits on the basis of monthly numbers. The data outpatient visits are retrieved from January 2005 to December 2013 and first obtained as the original time series. Second, the original time series is decomposed into a finite and often small number of intrinsic mode functions by the empirical mode decomposition technique. Third, a three-layer back-propagation artificial neural network is constructed to forecast each intrinsic mode functions. To improve network performance and avoid falling into a local minimum, particle swarm optimization is employed to optimize the weights and thresholds of back-propagation artificial neural networks. Finally, the superposition of forecasting results of the intrinsic mode functions is regarded as the ultimate forecasting value. Simulation indicates that the proposed method attains a better performance index than the other four methods.

Ring rolling process simulation for geometry optimization

Science.gov (United States)

Franchi, Rodolfo; Del Prete, Antonio; Donatiello, Iolanda; Calabrese, Maurizio

2017-10-01

Ring Rolling is a complex hot forming process where different rolls are involved in the production of seamless rings. Since each roll must be independently controlled, different speed laws must be set; usually, in the industrial environment, a milling curve is introduced to monitor the shape of the workpiece during the deformation in order to ensure the correct ring production. In the present paper a ring rolling process has been studied and optimized in order to obtain anular components to be used in aerospace applications. In particular, the influence of process input parameters (feed rate of the mandrel and angular speed of main roll) on geometrical features of the final ring has been evaluated. For this purpose, a three-dimensional finite element model for HRR (Hot Ring Rolling) has been implemented in SFTC DEFORM V11. The FEM model has been used to formulate a proper optimization problem. The optimization procedure has been implemented in the commercial software DS ISight in order to find the combination of process parameters which allows to minimize the percentage error of each obtained dimension with respect to its nominal value. The software allows to find the relationship between input and output parameters applying Response Surface Methodology (RSM), by using the exact values of output parameters in the control points of the design space explored through FEM simulation. Once this relationship is known, the values of the output parameters can be calculated for each combination of the input parameters. After the calculation of the response surfaces for the selected output parameters, an optimization procedure based on Genetic Algorithms has been applied. At the end, the error between each obtained dimension and its nominal value has been minimized. The constraints imposed were the maximum values of standard deviations of the dimensions obtained for the final ring.

Nanomaterial Case Study: Nanoscale Silver in Disinfectant Spray (Final Report)

Science.gov (United States)

EPA announced the release of the final report, Nanomaterial Case Study: Nanoscale Silver in Disinfectant Spray. This report represents a case study of engineered nanoscale silver (nano-Ag), focusing on the specific example of nano-Ag as possibly used in disinfectant spr...

Quantitative description of a high Jc Nb-Ti superconductor during its final optimization strain. I. Microstructure, Tc, Hc2, and resistivity

International Nuclear Information System (INIS)

Meingast, C.; Lee, P.J.; Larbalestier, D.C.

1989-01-01

A most important step in the critical current density (J c ) optimization of Nb-Ti is the large final drawing strain, in which α-Ti precipitates, initially approximately equiaxed and 100--200 nm in diameter, are drawn into ribbons, whose thickness (1--2 nm) is less than the superconducting coherence length [ξ (4.2 K)∼5 nm]. Using transmission electron microscopy, the precipitate thickness, spacing, cross-sectional area, and circumference were measured over the whole final drawing strain range. Each of these parameters was found to have a simple power dependence on the wire diameter. T c , H c2 , and the resistivity (ρ n ) were also change considerably during the refinement of the precipitates. Directly after precipitation, T c increased, and (dH c2 /dT) T c and ρ n were reduced from the single-phase values. Drawing the wire returned these parameters to their single-phase values, as the precipitate thickness was reduced to less than ξ. This observation explains a long-standing peculiarity in this system, namely that the optimum H c2 of high J c conductors occurs for a composition close to Nb 46 wt.% Ti, even when the precipitation of 18 vol % of α-Ti shifts the matrix composition to a Nb-rich composition of theoretically lower H c2

Comparative efficiency of final endodontic cleansing procedures in removing a radioactive albumin from root canal systems

International Nuclear Information System (INIS)

Cecic, P.A.; Peters, D.D.; Grower, M.F.

1984-01-01

Fifty-six teeth were initially instrumented, with the use of seven irrigants or irrigant combinations, and filled with radioactive albumin. The study then showed the relative ability of three final endodontic procedures (copious reirrigation with saline solution, drying with paper points, and reassuring patency of the canal with the final instrument) to remove the albumin. Even after copious irrigation, each additional procedure removed statistically significant amounts of albumin. Alternating an organic solvent and an inorganic solvent did appear to leave the canal system in the optimal condition for final cleansing procedures. The study then correlated the relative efficiency of irrigation alone versus instrumentation plus irrigation in removing the remaining albumin from the canal systems. Reinstrumentation plus copious irrigation removed significantly more albumin than copious irrigation alone

IMRT optimization: Variability of solutions and its radiobiological impact

International Nuclear Information System (INIS)

Mattia, Maurizio; Del Giudice, Paolo; Caccia, Barbara

2004-01-01

We aim at (1) defining and measuring a 'complexity' index for the optimization process of an intensity modulated radiation therapy treatment plan (IMRT TP), (2) devising an efficient approximate optimization strategy, and (3) evaluating the impact of the complexity of the optimization process on the radiobiological quality of the treatment. In this work, for a prostate therapy case, the IMRT TP optimization problem has been formulated in terms of dose-volume constraints. The cost function has been minimized in order to achieve the optimal solution, by means of an iterative procedure, which is repeated for many initial modulation profiles, and for each of them the final optimal solution is recorded. To explore the complexity of the space of such solutions we have chosen to minimize the cost function with an algorithm that is unable to avoid local minima. The size of the (sub)optimal solutions distribution is taken as an indicator of the complexity of the optimization problem. The impact of the estimated complexity on the probability of success of the therapy is evaluated using radiobiological indicators (Poissonian TCP model [S. Webb and A. E. Nahum, Phys. Med. Biol. 38(6), 653-666 (1993)] and NTCP relative seriality model [Kallman et al., Int. J. Radiat. Biol. 62(2), 249-262 (1992)]). We find in the examined prostate case a nontrivial distribution of local minima, which has symmetry properties allowing a good estimate of near-optimal solutions with a moderate computational load. We finally demonstrate that reducing the a priori uncertainty in the optimal solution results in a significant improvement of the probability of success of the TP, based on TCP and NTCP estimates

Application of evolution strategy algorithm for optimization of a single-layer sound absorber

Directory of Open Access Journals (Sweden)

Morteza Gholamipoor

2014-12-01

Full Text Available Depending on different design parameters and limitations, optimization of sound absorbers has always been a challenge in the field of acoustic engineering. Various methods of optimization have evolved in the past decades with innovative method of evolution strategy gaining more attention in the recent years. Based on their simplicity and straightforward mathematical representations, single-layer absorbers have been widely used in both engineering and industrial applications and an optimized design for these absorbers has become vital. In the present study, the method of evolution strategy algorithm is used for optimization of a single-layer absorber at both a particular frequency and an arbitrary frequency band. Results of the optimization have been compared against different methods of genetic algorithm and penalty functions which are proved to be favorable in both effectiveness and accuracy. Finally, a single-layer absorber is optimized in a desired range of frequencies that is the main goal of an industrial and engineering optimization process.

[Optimal solution and analysis of muscular force during standing balance].

Science.gov (United States)

Wang, Hongrui; Zheng, Hui; Liu, Kun

2015-02-01

The present study was aimed at the optimal solution of the main muscular force distribution in the lower extremity during standing balance of human. The movement musculoskeletal system of lower extremity was simplified to a physical model with 3 joints and 9 muscles. Then on the basis of this model, an optimum mathematical model was built up to solve the problem of redundant muscle forces. Particle swarm optimization (PSO) algorithm is used to calculate the single objective and multi-objective problem respectively. The numerical results indicated that the multi-objective optimization could be more reasonable to obtain the distribution and variation of the 9 muscular forces. Finally, the coordination of each muscle group during maintaining standing balance under the passive movement was qualitatively analyzed using the simulation results obtained.

Formulation optimization of gentamicin loaded Eudragit RS100 microspheres using factorial design study.

Science.gov (United States)

Singh, Deependra; Saraf, Swarnlata; Dixit, Vinod Kumar; Saraf, Shailendra

2008-04-01

Gentamicin-Eudragit RS100 microspheres were prepared by modified double emulsion method. A 3(2) full factorial experiment was designed to study the effects of the composition of outer aqueous phase in terms of amount of glycerol (viscosity effect) and sodium chloride (osmotic pressure gradient effect) on the entrapment efficiency and % yield and microsphere size. The results of analysis of variance test for responses measured indicated that the test is significant (p>0.05). The contribution of sodium chloride concentration was found to be higher on entrapment efficiency and % yield, whereas glycerol produced significant effect on the mean diameter of microspheres. Microspheres demonstrated spherical particles in the size range of 33.24-60.43 microm. In vitro release profile of optimized formulation demonstrated sustained release for 24 h following Higuchi kinetics. Finally, drug bioactivity was found to remain intact after microencapsulation. Response surface graphs are presented to examine the effects of independent variables on the responses studied. Thus, by formulation design important parameters affecting formulation characteristics of gentamicin loaded Eudragit RS100 microspheres can be identified for controlled delivery with desirable characters in terms of maximum entrapment and yield.

The Improvement of Particle Swarm Optimization: a Case Study of Optimal Operation in Goupitan Reservoir

Science.gov (United States)

Li, Haichen; Qin, Tao; Wang, Weiping; Lei, Xiaohui; Wu, Wenhui

2018-02-01

Due to the weakness in holding diversity and reaching global optimum, the standard particle swarm optimization has not performed well in reservoir optimal operation. To solve this problem, this paper introduces downhill simplex method to work together with the standard particle swarm optimization. The application of this approach in Goupitan reservoir optimal operation proves that the improved method had better accuracy and higher reliability with small investment.

In-plant demonstration of energy optimization in beck dyeing of carpet. Final report, June 1, 1979-January 1, 1980

Energy Technology Data Exchange (ETDEWEB)

Tincher, W.C.

1980-01-01

Several energy-conservative technologies have been successfully combined and transferred to a commercial carpet finishing plant to optimize beck dyeing. The technology of bump-and-run, in which the dyebath temperature was allowed to drift for the last 85% of the hold time instead of being maintained by active steam sparging, reduced the energy consumption by 38% with negligible capital investment required. Merging of dyebath reuse with bump-and-run only marginally increased the energy consumption (to 39%), but substantially lowered the plant's finishing costs further by directly recycling dyes, auxiliary chemicals, and water. Final optimization, which merged a technique whereby the carpet was pulled directly from the hot bath with bump-and-run and dyebath reuse, further improved the economics by drastically reducing water/sewer requirements by 90% and eliminating the holding tank/pumping assembly as a reuse requirement. From a carpet industry viewpoint, the demonstrated modifications have a direct energy conservation potential of 2.4 x 10/sup 5/ barrels of oil equivalent per year assuming the technology is directly transferable to similar atmospheric dyeing processes, e.g., beck dyeing of nylon and polyester fabrics, the potential to the entire textile industry is 2.6 x 10/sup 6/ BOE/year. Economically, total potential savings for the carpet industry on reuse incorporation was $1.2 x 10/sup 7//year, based on a 2.3 cents/lb. savings figure. When the allied fabric industry was included, the national potential was raised to $1.0 x 10/sup 8//year. These figures include cost savings due to materials recycled (water, auxiliary chemicals and dyes) as well as energy conservation.

Some Studies on Forming Optimization with Genetic Algorithm

Directory of Open Access Journals (Sweden)

Ganesh Marotrao KAKANDIKAR

2012-07-01

Full Text Available Forming is a compression-tension process involving wide spectrum of operations andflow conditions. The result of the process depends on the large number of parameters and theirinterdependence. The selection of various parameters is still based on trial and error methods. In thispaper the authors present a new approach to optimize the geometry parameters of circularcomponents, process parameters such as blank holder pressure and coefficient of friction etc. Theoptimization problem has been formulated with the objective of optimizing the maximum formingload required in Forming. Genetic algorithm is used as a tool for the optimization: to optimize thedrawing load and to optimize the process parameters. A finite element analysis simulation softwareFast Form Advanced is used for the validations of the results after optimization with prior results.

Research on Multidisciplinary Optimization Design of Bridge Crane

Directory of Open Access Journals (Sweden)

Tong Yifei

2013-01-01

Full Text Available Bridge crane is one of the most widely used cranes in our country, which is indispensable equipment for material conveying in the modern production. In this paper, the framework of multidisciplinary optimization for bridge crane is proposed. The presented research on crane multidisciplinary design technology for energy saving includes three levels, respectively: metal structures level, transmission design level, and electrical system design level. The shape optimal mathematical model of the crane is established for shape optimization design of metal structure level as well as size optimal mathematical model and topology optimal mathematical model of crane for topology optimization design of metal structure level is established. Finally, system-level multidisciplinary energy-saving optimization design of bridge crane is further carried out with energy-saving transmission design results feedback to energy-saving optimization design of metal structure. The optimization results show that structural optimization design can reduce total mass of crane greatly by using the finite element analysis and multidisciplinary optimization technology premised on the design requirements of cranes such as stiffness and strength; thus, energy-saving design can be achieved.

Survey on Recent Research and Implementation of Ant Colony Optimization in Various Engineering Applications

Directory of Open Access Journals (Sweden)

Mohan B. Chandra

2011-08-01

Full Text Available Ant colony optimization (ACO takes inspiration from the foraging behaviour of real ant species. This ACO exploits a similar mechanism for solving optimization problems for the various engineering field of study. Many successful implementations using ACO are now available in many applications. This paper reviewing varies systematic approach on recent research and implementation of ACO. Finally it presents the experimental result of ACO which is applied for routing problem and compared with existing algorithms.

Parametric Study and Multi-Criteria Optimization in Laser Cladding by a High Power Direct Diode Laser

Science.gov (United States)

Farahmand, Parisa; Kovacevic, Radovan

2014-12-01

In laser cladding, the performance of the deposited layers subjected to severe working conditions (e.g., wear and high temperature conditions) depends on the mechanical properties, the metallurgical bond to the substrate, and the percentage of dilution. The clad geometry and mechanical characteristics of the deposited layer are influenced greatly by the type of laser used as a heat source and process parameters used. Nowadays, the quality of fabricated coating by laser cladding and the efficiency of this process has improved thanks to the development of high-power diode lasers, with power up to 10 kW. In this study, the laser cladding by a high power direct diode laser (HPDDL) as a new heat source in laser cladding was investigated in detail. The high alloy tool steel material (AISI H13) as feedstock was deposited on mild steel (ASTM A36) by a HPDDL up to 8kW laser and with new design lateral feeding nozzle. The influences of the main process parameters (laser power, powder flow rate, and scanning speed) on the clad-bead geometry (specifically layer height and depth of the heat affected zone), and clad microhardness were studied. Multiple regression analysis was used to develop the analytical models for desired output properties according to input process parameters. The Analysis of Variance was applied to check the accuracy of the developed models. The response surface methodology (RSM) and desirability function were used for multi-criteria optimization of the cladding process. In order to investigate the effect of process parameters on the molten pool evolution, in-situ monitoring was utilized. Finally, the validation results for optimized process conditions show the predicted results were in a good agreement with measured values. The multi-criteria optimization makes it possible to acquire an efficient process for a combination of clad geometrical and mechanical characteristics control.

PV-PCM integration in glazed building. Co-simulation and genetic optimization study

DEFF Research Database (Denmark)

Elarga, Hagar; Dal Monte, Andrea; Andersen, Rune Korsholm

2017-01-01

. An exploratory step has also been considered prior to the optimization algorithm: it evaluates the energy profiles before and after the application of PCM to PV module integrated in glazed building. The optimization analysis investigate parameters such as ventilation flow rates and time schedule to obtain......The study describes a multi-objective optimization algorithm for an innovative integration of forced ventilated PV-PCM modules in glazed façade buildings: the aim is to identify and optimize the parameters that most affect thermal and energy performances. 1-D model, finite difference method FDM...

Presentation of Malaria Epidemics Using Multiple Optimal Controls

Directory of Open Access Journals (Sweden)

Abid Ali Lashari

2012-01-01

Full Text Available An existing model is extended to assess the impact of some antimalaria control measures, by re-formulating the model as an optimal control problem. This paper investigates the fundamental role of three type of controls, personal protection, treatment, and mosquito reduction strategies in controlling the malaria. We work in the nonlinear optimal control framework. The existence and the uniqueness results of the solution are discussed. A characterization of the optimal control via adjoint variables is established. The optimality system is solved numerically by a competitive Gauss-Seidel-like implicit difference method. Finally, numerical simulations of the optimal control problem, using a set of reasonable parameter values, are carried out to investigate the effectiveness of the proposed control measures.

Optimization of cooling tower performance analysis using Taguchi method

Directory of Open Access Journals (Sweden)

Ramkumar Ramakrishnan

2013-01-01

Full Text Available This study discuss the application of Taguchi method in assessing maximum cooling tower effectiveness for the counter flow cooling tower using expanded wire mesh packing. The experiments were planned based on Taguchi’s L27 orthogonal array .The trail was performed under different inlet conditions of flow rate of water, air and water temperature. Signal-to-noise ratio (S/N analysis, analysis of variance (ANOVA and regression were carried out in order to determine the effects of process parameters on cooling tower effectiveness and to identity optimal factor settings. Finally confirmation tests verified this reliability of Taguchi method for optimization of counter flow cooling tower performance with sufficient accuracy.

Damage tolerance optimization of composite stringer run-out under tensile load

DEFF Research Database (Denmark)

Badalló, Pere; Trias, Daniel; Lindgaard, Esben

2015-01-01

. The influence of some geometric variables of the run-out in the interface of the set stringer-panel is crucial to avoid the onset and growth of delamination cracks. In this study, a damage tolerant design of a stringer run-out is achieved by a process of design optimization and surrogate modeling techniques....... A parametric finite element model created with python was used to generate a number of different geometrical designs of the stringer run-out. The relevant information of these models was adjusted using Radial Basis Functions (RBF). Finally, the optimization problem was solved using Quasi-Newton method...

Integrated Reliability-Based Optimal Design of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Thoft-Christensen, Palle

1987-01-01

In conventional optimal design of structural systems the weight or the initial cost of the structure is usually used as objective function. Further, the constraints require that the stresses and/or strains at some critical points have to be less than some given values. Finally, all variables......-based optimal design is discussed. Next, an optimal inspection and repair strategy for existing structural systems is presented. An optimization problem is formulated , where the objective is to minimize the expected total future cost of inspection and repair subject to the constraint that the reliability...... value. The reliability can be measured from an element and/or a systems point of view. A number of methods to solve reliability-based optimization problems has been suggested, see e.g. Frangopol [I]. Murotsu et al. (2], Thoft-Christensen & Sørensen (3] and Sørensen (4). For structures where...

Adaptive stimulus optimization for sensory systems neuroscience.

Science.gov (United States)

DiMattina, Christopher; Zhang, Kechen

2013-01-01

In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

Memetic Approaches for Optimizing Hidden Markov Models: A Case Study in Time Series Prediction

Science.gov (United States)

Bui, Lam Thu; Barlow, Michael

We propose a methodology for employing memetics (local search) within the framework of evolutionary algorithms to optimize parameters of hidden markov models. With this proposal, the rate and frequency of using local search are automatically changed over time either at a population or individual level. At the population level, we allow the rate of using local search to decay over time to zero (at the final generation). At the individual level, each individual is equipped with information of when it will do local search and for how long. This information evolves over time alongside the main elements of the chromosome representing the individual.

Essays on variational approximation techniques for stochastic optimization problems

Science.gov (United States)

Deride Silva, Julio A.

This dissertation presents five essays on approximation and modeling techniques, based on variational analysis, applied to stochastic optimization problems. It is divided into two parts, where the first is devoted to equilibrium problems and maxinf optimization, and the second corresponds to two essays in statistics and uncertainty modeling. Stochastic optimization lies at the core of this research as we were interested in relevant equilibrium applications that contain an uncertain component, and the design of a solution strategy. In addition, every stochastic optimization problem relies heavily on the underlying probability distribution that models the uncertainty. We studied these distributions, in particular, their design process and theoretical properties such as their convergence. Finally, the last aspect of stochastic optimization that we covered is the scenario creation problem, in which we described a procedure based on a probabilistic model to create scenarios for the applied problem of power estimation of renewable energies. In the first part, Equilibrium problems and maxinf optimization, we considered three Walrasian equilibrium problems: from economics, we studied a stochastic general equilibrium problem in a pure exchange economy, described in Chapter 3, and a stochastic general equilibrium with financial contracts, in Chapter 4; finally from engineering, we studied an infrastructure planning problem in Chapter 5. We stated these problems as belonging to the maxinf optimization class and, in each instance, we provided an approximation scheme based on the notion of lopsided convergence and non-concave duality. This strategy is the foundation of the augmented Walrasian algorithm, whose convergence is guaranteed by lopsided convergence, that was implemented computationally, obtaining numerical results for relevant examples. The second part, Essays about statistics and uncertainty modeling, contains two essays covering a convergence problem for a sequence

A Sensitivity Study of Human Errors in Optimizing Surveillance Test Interval (STI) and Allowed Outage Time (AOT) of Standby Safety System

International Nuclear Information System (INIS)

Chung, Dae Wook; Shin, Won Ky; You, Young Woo; Yang, Hui Chang

1998-01-01

In most cases, the surveillance test intervals (STIs), allowed outage times (AOTS) and testing strategies of safety components in nuclear power plant are prescribed in plant technical specifications. And, in general, it is required that standby safety system shall be redundant (i.e., composed of multiple components) and these components are tested by either staggered test strategy or sequential test strategy. In this study, a linear model is presented to incorporate the effects of human errors associated with test into the evaluation of unavailability. The average unavailabilities of 1/4, 2/4 redundant systems are computed considering human error and testing strategy. The adverse effects of test on system unavailability, such as component wear and test-induced transient have been modelled. The final outcome of this study would be the optimized human error domain from 3-D human error sensitivity analysis by selecting finely classified segment. The results of sensitivity analysis show that the STI and AOT can be optimized provided human error probability is maintained within allowable range. (authors)

Shape optimization of a sodium cooled fast reactor

International Nuclear Information System (INIS)

Schmitt, D.; Allaire, G.; Pantz, O.; Pozin, N.

2013-01-01

Traditional designs of sodium cooled fast reactors have a positive sodium expansion feedback. During a loss of flow transient without scram, sodium heating and boiling thus insert a positive reactivity and prevents the power from decreasing. Recent studies led at CEA, AREVA and EDF show that cores with complex geometries can feature a very low or even a negative sodium void worth. Usual optimization methods for core conception are based on a parametric description of a given core design. New core concepts and shapes can then only be found by hand. Shape optimization methods have proven very efficient in the conception of optimal structures under thermal or mechanical constraints. First studies show that these methods could be applied to sodium cooled core conception. In this paper, a shape optimization method is applied to the conception of a sodium cooled fast reactor core with low sodium void worth. An objective function to be minimized is defined. It includes the reactivity change induced by a 1% sodium density decrease. The optimization variable is a displacement field changing the core geometry from one shape to another. Additionally, a parametric optimization of the plutonium content distribution of the core is made, so as to ensure that the core is kept critical, and that the power shape is flat enough. The final shape obtained must then be adjusted to a given realistic core layout. Its characteristics can be checked with reference neutronic codes such as ERANOS. Thanks to this method, new shapes of reactor cores could be inferred, and lead to new design ideas. (authors)

Comparative study for the design of optimal composite pressure vessels

International Nuclear Information System (INIS)

Butt, A.M.; Haq, S.W.U.

2009-01-01

Composite pressure vessels require special design attention to the dome region because of the varying wind angles generated using the filament winding process. Geometric variations in the dome region cause the fiber to change angels and thickness and hence offer difficulty to acquire a constant stress profile (isotensoid). Therefore a dome contour which allows an isotensoid behavior is the required structure. Two design methods to generate dome profiles for similar dome openings were investigated namely Netting Analysis and Optimal Design method. Both methods assume that loads are carried by the fiber alone (monotropic) ignoring the complete composite behavior. Former method produced a lower dome internal volume and a higher fiber thickness as compared to the later optimal design method when studied against different normalized dome opening radiuses. The optimal dome contour was studied in ANSYS with a trial design. The dome was considered to have transversely isotropic property with a dome contour based on monotropic model. While investigating the dome with non linear large displacement finite element analysis, the dome still exhibited isotensoid behavior with transverse isotropic material assignment. Elliptic integrals were used to generate the optimal dome contours and hence elliptic dome contours were formed which were isotensoid in nature with complete composite representation. (author)

Optimized concentrating/passive tracking solar collector. Final report

Energy Technology Data Exchange (ETDEWEB)

Sterne, K E; Johnson, A L; Grotheer, R H

1979-01-01

A concentrating solar collector having about half the material cost of other collectors with similar performance is described. The selected design is a Compound Parabolic Concentrator (CPC) which concentrates solar energy throughout the year without requiring realignment. Output is a fluid heated to 100/sup 0/C with good efficiency. The optical design of the reflector surface was optimized, yielding a 2.0:1 concentration ratio with a 60/sup 0/C acceptance angle and a low profile. Double glazing was chosen consisting of a polyester film outer glazing and an inner glazing of glass tubes around the absorbers. The selectively coated steel absorber tubes are connected in series with flexible plastic tubing. Much development effort went into the materials for the reflector subassembly. A laminate of metalized plastic film over plaster was chosen for the reflective surface. The reflector is rigidized by attaching filled epoxy header plates at each end. Aluminum side rails and an insulating back complete the structure. The finished design resulted in a material cost of $21.40 per square meter in production quantities. Performance testing of a prototype produced a 50% initial efficiency rating. This is somewhat lower than expected, and is due to materials and processes used in the prototype for the outer glazing, reflective surface and absorber coating. However, the efficiency curve drops only slightly with increasing temperature differential, showing the inherent advantage of the concentrator over flat plate collectors.

Photovoltaic subsystem optimization and design tradeoff study. Final report

Energy Technology Data Exchange (ETDEWEB)

Stolte, W.J.

1982-03-01

Tradeoffs and subsystem choices are examined in photovoltaic array subfield design, power-conditioning sizing and selection, roof- and ground-mounted structure installation, energy loss, operating voltage, power conditioning cost, and subfield size. Line- and self-commutated power conditioning options are analyzed to determine the most cost-effective technology in the megawatt power range. Methods for reducing field installation of flat panels and roof mounting of intermediate load centers are discussed, including the cost of retrofit installations.

Optimization of importance factors in inverse planning

International Nuclear Information System (INIS)

Xing, L.

1999-01-01

Inverse treatment planning starts with a treatment objective and obtains the solution by optimizing an objective function. The clinical objectives are usually multifaceted and potentially incompatible with one another. A set of importance factors is often incorporated in the objective function to parametrize trade-off strategies and to prioritize the dose conformality in different anatomical structures. Whereas the general formalism remains the same, different sets of importance factors characterize plans of obviously different flavour and thus critically determine the final plan. Up to now, the determination of these parameters has been a 'guessing' game based on empirical knowledge because the final dose distribution depends on the parameters in a complex and implicit way. The influence of these parameters is not known until the plan optimization is completed. In order to compromise properly the conflicting requirements of the target and sensitive structures, the parameters are usually adjusted through a trial-and-error process. In this paper, a method to estimate these parameters computationally is proposed and an iterative computer algorithm is described to determine these parameters numerically. The treatment plan selection is done in two steps. First, a set of importance factors are chosen and the corresponding beam parameters (e.g. beam profiles) are optimized under the guidance of a quadratic objective function using an iterative algorithm reported earlier. The 'optimal' plan is then evaluated by an additional scoring function. The importance factors in the objective function are accordingly adjusted to improve the ranking of the plan. For every change in the importance factors, the beam parameters need to be re-optimized. This process continues in an iterative fashion until the scoring function is saturated. The algorithm was applied to two clinical cases and the results demonstrated that it has the potential to improve significantly the existing method of

Parallel optimization of IDW interpolation algorithm on multicore platform

Science.gov (United States)

Guan, Xuefeng; Wu, Huayi

2009-10-01

Due to increasing power consumption, heat dissipation, and other physical issues, the architecture of central processing unit (CPU) has been turning to multicore rapidly in recent years. Multicore processor is packaged with multiple processor cores in the same chip, which not only offers increased performance, but also presents significant challenges to application developers. As a matter of fact, in GIS field most of current GIS algorithms were implemented serially and could not best exploit the parallelism potential on such multicore platforms. In this paper, we choose Inverse Distance Weighted spatial interpolation algorithm (IDW) as an example to study how to optimize current serial GIS algorithms on multicore platform in order to maximize performance speedup. With the help of OpenMP, threading methodology is introduced to split and share the whole interpolation work among processor cores. After parallel optimization, execution time of interpolation algorithm is greatly reduced and good performance speedup is achieved. For example, performance speedup on Intel Xeon 5310 is 1.943 with 2 execution threads and 3.695 with 4 execution threads respectively. An additional output comparison between pre-optimization and post-optimization is carried out and shows that parallel optimization does to affect final interpolation result.

Optimalization studies concerning volume reduction and conditioning of radioactive waste in view of storage and disposal (geological disposal into clay)

International Nuclear Information System (INIS)

Dejonghe, P.; Van De Voorde, N.; Bonne, A.

1984-01-01

Volume reduction of low-level and medium-level wastes, and simultaneous optimization of the quality of the conditioned end-product is a major challenge in the management of radioactive wastes. Comments will be given on recent achievements in treatment of non-high-level liquid and solid wastes from power reactors and low-level plutonium contaminated wastes. The latter results can contribute to an overall optimization of a radioactive waste management scheme, including the final disposal of the conditioned materials. Some detailed results will be given concerning volume reduction, decontamination factors, degree of immobilization of the contained radioelements, and cost considerations

Optimal control of native predators

Science.gov (United States)

Martin, Julien; O'Connell, Allan F.; Kendall, William L.; Runge, Michael C.; Simons, Theodore R.; Waldstein, Arielle H.; Schulte, Shiloh A.; Converse, Sarah J.; Smith, Graham W.; Pinion, Timothy; Rikard, Michael; Zipkin, Elise F.

2010-01-01

We apply decision theory in a structured decision-making framework to evaluate how control of raccoons (Procyon lotor), a native predator, can promote the conservation of a declining population of American Oystercatchers (Haematopus palliatus) on the Outer Banks of North Carolina. Our management objective was to maintain Oystercatcher productivity above a level deemed necessary for population recovery while minimizing raccoon removal. We evaluated several scenarios including no raccoon removal, and applied an adaptive optimization algorithm to account for parameter uncertainty. We show how adaptive optimization can be used to account for uncertainties about how raccoon control may affect Oystercatcher productivity. Adaptive management can reduce this type of uncertainty and is particularly well suited for addressing controversial management issues such as native predator control. The case study also offers several insights that may be relevant to the optimal control of other native predators. First, we found that stage-specific removal policies (e.g., yearling versus adult raccoon removals) were most efficient if the reproductive values among stage classes were very different. Second, we found that the optimal control of raccoons would result in higher Oystercatcher productivity than the minimum levels recommended for this species. Third, we found that removing more raccoons initially minimized the total number of removals necessary to meet long term management objectives. Finally, if for logistical reasons managers cannot sustain a removal program by removing a minimum number of raccoons annually, managers may run the risk of creating an ecological trap for Oystercatchers.

Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm

Directory of Open Access Journals (Sweden)

Ahmet Demir

2017-01-01

Full Text Available In the fields which require finding the most appropriate value, optimization became a vital approach to employ effective solutions. With the use of optimization techniques, many different fields in the modern life have found solutions to their real-world based problems. In this context, classical optimization techniques have had an important popularity. But after a while, more advanced optimization problems required the use of more effective techniques. At this point, Computer Science took an important role on providing software related techniques to improve the associated literature. Today, intelligent optimization techniques based on Artificial Intelligence are widely used for optimization problems. The objective of this paper is to provide a comparative study on the employment of classical optimization solutions and Artificial Intelligence solutions for enabling readers to have idea about the potential of intelligent optimization techniques. At this point, two recently developed intelligent optimization algorithms, Vortex Optimization Algorithm (VOA and Cognitive Development Optimization Algorithm (CoDOA, have been used to solve some multidisciplinary optimization problems provided in the source book Thomas' Calculus 11th Edition and the obtained results have compared with classical optimization solutions. 

Smoothing optimization of supporting quadratic surfaces with Zernike polynomials

Science.gov (United States)

Zhang, Hang; Lu, Jiandong; Liu, Rui; Ma, Peifu

2018-03-01

A new optimization method to get a smooth freeform optical surface from an initial surface generated by the supporting quadratic method (SQM) is proposed. To smooth the initial surface, a 9-vertex system from the neighbor quadratic surface and the Zernike polynomials are employed to establish a linear equation system. A local optimized surface to the 9-vertex system can be build by solving the equations. Finally, a continuous smooth optimization surface is constructed by stitching the above algorithm on the whole initial surface. The spot corresponding to the optimized surface is no longer discrete pixels but a continuous distribution.

Sequential Optimization of Global Sequence Alignments Relative to Different Cost Functions

KAUST Repository

Odat, Enas M.

2011-05-01

The purpose of this dissertation is to present a methodology to model global sequence alignment problem as directed acyclic graph which helps to extract all possible optimal alignments. Moreover, a mechanism to sequentially optimize sequence alignment problem relative to different cost functions is suggested. Sequence alignment is mostly important in computational biology. It is used to find evolutionary relationships between biological sequences. There are many algo- rithms that have been developed to solve this problem. The most famous algorithms are Needleman-Wunsch and Smith-Waterman that are based on dynamic program- ming. In dynamic programming, problem is divided into a set of overlapping sub- problems and then the solution of each subproblem is found. Finally, the solutions to these subproblems are combined into a final solution. In this thesis it has been proved that for two sequences of length m and n over a fixed alphabet, the suggested optimization procedure requires O(mn) arithmetic operations per cost function on a single processor machine. The algorithm has been simulated using C#.Net programming language and a number of experiments have been done to verify the proved statements. The results of these experiments show that the number of optimal alignments is reduced after each step of optimization. Furthermore, it has been verified that as the sequence length increased linearly then the number of optimal alignments increased exponentially which also depends on the cost function that is used. Finally, the number of executed operations increases polynomially as the sequence length increase linearly.

Trade Liberalization and Optimal Environmental Policies in Vertical Related Markets

Directory of Open Access Journals (Sweden)

Yan-Shu Lin

2012-12-01

Full Text Available This paper establishes a symmetric two-country model with vertically related markets. In the downstream market, there is one firm in each country selling a homogeneous good, whose production generates pollution, to its home and the foreign markets a la Brander (1981. In the intermediate good market, there is also one upstream firm in each country, supplying the intermediate good only to its own country’s downstream market. The upstream firms can choose either price or quantity to maximize their profits. With this setting, the paper examines the optimal environmental policy and how it is affected by the tariff on the final good. It is found that, under free trade, the optimal final-good output with imperfect intermediate-good market will have the same output level as that with perfect intermediate-good market after imposing the optimal emission tax. The optimal environmental tax is smaller and the optimal environmental policy is less likely to be a green strategy under trade liberalization if the market structure in the intermediate good market is imperfect than perfect competition. On the other hand, the optimal environmental tax is necessarily higher if the upstream firm chooses price than quantity. Moreover, the optimal environmental policy is less likely to be a green strategy under trade liberalization if the upstream firms choose quantity than price to maximize their profits.

Optimal moment determination in POME-copula based hydrometeorological dependence modelling

Science.gov (United States)

Liu, Dengfeng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi

2017-07-01

Copula has been commonly applied in multivariate modelling in various fields where marginal distribution inference is a key element. To develop a flexible, unbiased mathematical inference framework in hydrometeorological multivariate applications, the principle of maximum entropy (POME) is being increasingly coupled with copula. However, in previous POME-based studies, determination of optimal moment constraints has generally not been considered. The main contribution of this study is the determination of optimal moments for POME for developing a coupled optimal moment-POME-copula framework to model hydrometeorological multivariate events. In this framework, margins (marginals, or marginal distributions) are derived with the use of POME, subject to optimal moment constraints. Then, various candidate copulas are constructed according to the derived margins, and finally the most probable one is determined, based on goodness-of-fit statistics. This optimal moment-POME-copula framework is applied to model the dependence patterns of three types of hydrometeorological events: (i) single-site streamflow-water level; (ii) multi-site streamflow; and (iii) multi-site precipitation, with data collected from Yichang and Hankou in the Yangtze River basin, China. Results indicate that the optimal-moment POME is more accurate in margin fitting and the corresponding copulas reflect a good statistical performance in correlation simulation. Also, the derived copulas, capturing more patterns which traditional correlation coefficients cannot reflect, provide an efficient way in other applied scenarios concerning hydrometeorological multivariate modelling.

Optimal pattern synthesis for speech recognition based on principal component analysis

Science.gov (United States)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Optimal control of stretching process of flexible solar arrays on spacecraft based on a hybrid optimization strategy

Directory of Open Access Journals (Sweden)

Qijia Yao

2017-07-01

Full Text Available The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated, and a hybrid optimization strategy based on Gauss pseudospectral method (GPM and direct shooting method (DSM is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions. The results indicate that the method is effective with good robustness. Keywords: Motion planning, Multibody spacecraft, Optimal control, Gauss pseudospectral method, Direct shooting method

Optimizing the construction of devices to control inaccesible surfaces - case study

Science.gov (United States)

Niţu, E. L.; Costea, A.; Iordache, M. D.; Rizea, A. D.; Babă, Al

2017-10-01

The modern concept for the evolution of manufacturing systems requires multi-criteria optimization of technological processes and equipments, prioritizing associated criteria according to their importance. Technological preparation of the manufacturing can be developed, depending on the volume of production, to the limit of favourable economical effects related to the recovery of the costs for the design and execution of the technological equipment. Devices, as subsystems of the technological system, in the general context of modernization and diversification of machines, tools, semi-finished products and drives, are made in a multitude of constructive variants, which in many cases do not allow their identification, study and improvement. This paper presents a case study in which the multi-criteria analysis of some structures, based on a general optimization method, of novelty character, is used in order to determine the optimal construction variant of a control device. The rational construction of the control device confirms that the optimization method and the proposed calculation methods are correct and determine a different system configuration, new features and functions, and a specific method of working to control inaccessible surfaces.

Feasibility Study and Optimization of An Hybrid System (Eolian ...

African Journals Online (AJOL)

Feasibility Study and Optimization of An Hybrid System (Eolian- Photovoltaic - Diesel) With Provision of Electric Energy Completely Independent. ... reducing emissions of greenhouse gas (CO2 rate = 16086 kg / year for a system using only the generator diesel and is 599 kg / year for the stand alone hybrid system studied).

Research on robust optimization of emergency logistics network considering the time dependence characteristic

Science.gov (United States)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

Oral bioavailability enhancement of raloxifene by developing microemulsion using D-optimal mixture design: optimization and in-vivo pharmacokinetic study.

Science.gov (United States)

Shah, Nirmal; Seth, Avinashkumar; Balaraman, R; Sailor, Girish; Javia, Ankur; Gohil, Dipti

2018-04-01

The objective of this work was to utilize a potential of microemulsion for the improvement in oral bioavailability of raloxifene hydrochloride, a BCS class-II drug with 2% bioavailability. Drug-loaded microemulsion was prepared by water titration method using Capmul MCM C8, Tween 20, and Polyethylene glycol 400 as oil, surfactant, and co-surfactant respectively. The pseudo-ternary phase diagram was constructed between oil and surfactants mixture to obtain appropriate components and their concentration ranges that result in large existence area of microemulsion. D-optimal mixture design was utilized as a statistical tool for optimization of microemulsion considering oil, S mix , and water as independent variables with percentage transmittance and globule size as dependent variables. The optimized formulation showed 100 ± 0.1% transmittance and 17.85 ± 2.78 nm globule size which was identically equal with the predicted values of dependent variables given by the design expert software. The optimized microemulsion showed pronounced enhancement in release rate compared to plain drug suspension following diffusion controlled release mechanism by the Higuchi model. The formulation showed zeta potential of value -5.88 ± 1.14 mV that imparts good stability to drug loaded microemulsion dispersion. Surface morphology study with transmission electron microscope showed discrete spherical nano sized globules with smooth surface. In-vivo pharmacokinetic study of optimized microemulsion formulation in Wistar rats showed 4.29-fold enhancements in bioavailability. Stability study showed adequate results for various parameters checked up to six months. These results reveal the potential of microemulsion for significant improvement in oral bioavailability of poorly soluble raloxifene hydrochloride.

Optimal probabilistic energy management in a typical micro-grid based-on robust optimization and point estimate method

International Nuclear Information System (INIS)

Alavi, Seyed Arash; Ahmadian, Ali; Aliakbar-Golkar, Masoud

2015-01-01

Highlights: • Energy management is necessary in the active distribution network to reduce operation costs. • Uncertainty modeling is essential in energy management studies in active distribution networks. • Point estimate method is a suitable method for uncertainty modeling due to its lower computation time and acceptable accuracy. • In the absence of Probability Distribution Function (PDF) robust optimization has a good ability for uncertainty modeling. - Abstract: Uncertainty can be defined as the probability of difference between the forecasted value and the real value. As this probability is small, the operation cost of the power system will be less. This purpose necessitates modeling of system random variables (such as the output power of renewable resources and the load demand) with appropriate and practicable methods. In this paper, an adequate procedure is proposed in order to do an optimal energy management on a typical micro-grid with regard to the relevant uncertainties. The point estimate method is applied for modeling the wind power and solar power uncertainties, and robust optimization technique is utilized to model load demand uncertainty. Finally, a comparison is done between deterministic and probabilistic management in different scenarios and their results are analyzed and evaluated

Optimization study on pin tip diameter of an impact-pin nozzle at high pressure ratio

Energy Technology Data Exchange (ETDEWEB)

Kumar, C. Palani; Lee, Kwon Hee [FMTRC, Daejoo Machinery Co. Ltd., Daegu (Korea, Republic of); Park, Tae Choon; Cha, Bong Jun [Engine Components Research Team, Korea Aerospace Research Institute, Daejeon (Korea, Republic of); Kim, Heuy Dong [Dept. of Mechanical Engineering, Andong National University, Andong (Korea, Republic of)

2016-09-15

Wet compression system is typically installed in a gas turbine engine to increase the net power output and efficiency. A crucial component of the wet compression system is the nozzle which generates fine water droplets for injection into the compressor. The main objective of present work is to optimize a kind of nozzle called impact-pin spray nozzle and thereby produce better quality droplets. To achieve this, the dynamics occurring in the water jet impinging on the pin tip, the subsequent formation of water sheet, which finally breaks into water droplets, must be studied. In this manuscript, the progress on the numerical studies on impact-pin nozzle are reported. A small computational domain covering the orifice, pin tip and the region where primary atomization occurs is selected for numerical analysis. The governing equations are selected in three dimensional cartesian form and simulations are performed to predict the dynamics of water jet impinging on the pin. Systematic studies were carried out and the results leading to the choice of turbulence model and the effect of pin tip diameter are reported here. Further studies are proposed to show the future directions of the present research work.

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Directory of Open Access Journals (Sweden)

Yongpeng Shen

2016-02-01

Full Text Available Auxiliary power units (APUs are widely used for electric power generation in various types of electric vehicles, improvements in fuel economy and emissions of these vehicles directly depend on the operating point of the APUs. In order to balance the conflicting goals of fuel consumption and emissions reduction in the process of operating point choice, the APU operating point optimization problem is formulated as a constrained multi-objective optimization problem (CMOP firstly. The four competing objectives of this CMOP are fuel-electricity conversion cost, hydrocarbon (HC emissions, carbon monoxide (CO emissions and nitric oxide (NO x emissions. Then, the multi-objective particle swarm optimization (MOPSO algorithm and weighted metric decision making method are employed to solve the APU operating point multi-objective optimization model. Finally, bench experiments under New European driving cycle (NEDC, Federal test procedure (FTP and high way fuel economy test (HWFET driving cycles show that, compared with the results of the traditional fuel consumption single-objective optimization approach, the proposed multi-objective optimization approach shows significant improvements in emissions performance, at the expense of a slight drop in fuel efficiency.

Using Chemicals to Optimize Conformance Control in Fractured Reservoirs; TOPICAL

International Nuclear Information System (INIS)

Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Wang, Ying; Kumar, Ananad; Wavrik, Kathryn

2001-01-01

This report describes work performed during the third and final year of the project, Using Chemicals to Optimize Conformance Control in Fractured Reservoirs. This research project had three objectives. The first objective was to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective was to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective was to develop procedures to optimize blocking agent placement in naturally fractured reservoirs

The Process of Optimizing Mechanical Sound Quality in Product Design

DEFF Research Database (Denmark)

Eriksen, Kaare; Holst, Thomas

2011-01-01

The research field concerning optimizing product sound quality is a relatively unexplored area, and may become difficult for designers to operate in. To some degree, sound is a highly subjective parameter, which is normally targeted sound specialists. This paper describes the theoretical...... and practical background for managing a process of optimizing the mechanical sound quality in a product design by using simple tools and workshops systematically. The procedure is illustrated by a case study of a computer navigation tool (computer mouse or mouse). The process is divided into 4 phases, which...... clarify the importance of product sound, defining perceptive demands identified by users, and, finally, how to suggest mechanical principles for modification of an existing sound design. The optimized mechanical sound design is followed by tests on users of the product in its use context. The result...

PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN

Institute of Scientific and Technical Information of China (English)

HU Jie; PENG Yinghong; XIONG Guangleng

2006-01-01

A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.

[Optimize preparation of compound licorice microemulsion with D-optimal design].

Science.gov (United States)

Ma, Shu-Wei; Wang, Yong-Jie; Chen, Cheng; Qiu, Yue; Wu, Qing

2018-03-01

In order to increase the solubility of essential oil in compound licorice microemulsion and improve the efficacy of the decoction for treating chronic eczema, this experiment intends to prepare the decoction into microemulsion. The essential oil was used as the oil phase of the microemulsion and the extract was used as the water phase. Then the microemulsion area and maximum ratio of water capacity was obtained by plotting pseudo-ternary phase diagram, to determine the appropriate types of surfactant and cosurfactant, and Km value-the mass ratio between surfactant and cosurfactant. With particle size and skin retention of active ingredients as the index, microemulsion prescription was optimized by D-optimal design method, to investigate the in vitro release behavior of the optimized prescription. The results showed that the microemulsion was optimal with tween-80 as the surfactant and anhydrous ethanol as the cosurfactant. When the Km value was 1, the area of the microemulsion region was largest while when the concentration of extract was 0.5 g·mL⁻¹, it had lowest effect on the particle size distribution of microemulsion. The final optimized formulation was as follows: 9.4% tween-80, 9.4% anhydrous ethanol, 1.0% peppermint oil and 80.2% 0.5 g·mL⁻¹ extract. The microemulsion prepared under these conditions had a small viscosity, good stability and high skin retention of drug; in vitro release experiment showed that microemulsion had a sustained-release effect on glycyrrhizic acid and liquiritin, basically achieving the expected purpose of the project. Copyright© by the Chinese Pharmaceutical Association.

A Casting Yield Optimization Case Study: Forging Ram

DEFF Research Database (Denmark)

Kotas, Petr; Tutum, Cem Celal; Hattel, Jesper Henri

2010-01-01

This work summarizes the findings of multi-objective optimization of a gravity sand-cast steel part for which an increase of the casting yield via riser optimization was considered. This was accomplished by coupling a casting simulation software package with an optimization module. The benefits...... of this approach, recently adopted in foundry industry world wide and based on fully automated computer optimization, were demonstrated. First, analyses of filling and solidification of the original casting design were conducted in the standard simulation environment to determine potential flaws and inadequacies...

Data processing and optimization system to study prospective interstate power interconnections

Science.gov (United States)

Podkovalnikov, Sergei; Trofimov, Ivan; Trofimov, Leonid

2018-01-01

The paper presents Data processing and optimization system for studying and making rational decisions on the formation of interstate electric power interconnections, with aim to increasing effectiveness of their functioning and expansion. The technologies for building and integrating a Data processing and optimization system including an object-oriented database and a predictive mathematical model for optimizing the expansion of electric power systems ORIRES, are described. The technology of collection and pre-processing of non-structured data collected from various sources and its loading to the object-oriented database, as well as processing and presentation of information in the GIS system are described. One of the approaches of graphical visualization of the results of optimization model is considered on the example of calculating the option for expansion of the South Korean electric power grid.

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn

2009-01-01

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied

Optimality study of a gust alleviation system for light wing-loading STOL aircraft

Science.gov (United States)

Komoda, M.

1976-01-01

An analytical study was made of an optimal gust alleviation system that employs a vertical gust sensor mounted forward of an aircraft's center of gravity. Frequency domain optimization techniques were employed to synthesize the optimal filters that process the corrective signals to the flaps and elevator actuators. Special attention was given to evaluating the effectiveness of lead time, that is, the time by which relative wind sensor information should lead the actual encounter of the gust. The resulting filter is expressed as an implicit function of the prescribed control cost. A numerical example for a light wing loading STOL aircraft is included in which the optimal trade-off between performance and control cost is systematically studied.

Multicriteria optimization informed VMAT planning

Energy Technology Data Exchange (ETDEWEB)

Chen, Huixiao; Craft, David L.; Gierga, David P., E-mail: dgierga@partners.org

2014-04-01

We developed a patient-specific volumetric-modulated arc therapy (VMAT) optimization procedure using dose-volume histogram (DVH) information from multicriteria optimization (MCO) of intensity-modulated radiotherapy (IMRT) plans. The study included 10 patients with prostate cancer undergoing standard fractionation treatment, 10 patients with prostate cancer undergoing hypofractionation treatment, and 5 patients with head/neck cancer. MCO-IMRT plans using 20 and 7 treatment fields were generated for each patient on the RayStation treatment planning system (clinical version 2.5, RaySearch Laboratories, Stockholm, Sweden). The resulting DVH of the 20-field MCO-IMRT plan for each patient was used as the reference DVH, and the extracted point values of the resulting DVH of the MCO-IMRT plan were used as objectives and constraints for VMAT optimization. Weights of objectives or constraints of VMAT optimization or both were further tuned to generate the best match with the reference DVH of the MCO-IMRT plan. The final optimal VMAT plan quality was evaluated by comparison with MCO-IMRT plans based on homogeneity index, conformity number of planning target volume, and organ at risk sparing. The influence of gantry spacing, arc number, and delivery time on VMAT plan quality for different tumor sites was also evaluated. The resulting VMAT plan quality essentially matched the 20-field MCO-IMRT plan but with a shorter delivery time and less monitor units. VMAT plan quality of head/neck cancer cases improved using dual arcs whereas prostate cases did not. VMAT plan quality was improved by fine gantry spacing of 2 for the head/neck cancer cases and the hypofractionation-treated prostate cancer cases but not for the standard fractionation–treated prostate cancer cases. MCO-informed VMAT optimization is a useful and valuable way to generate patient-specific optimal VMAT plans, though modification of the weights of objectives or constraints extracted from resulting DVH of MCO

Optimal experimental design for placement of boreholes

Science.gov (United States)

Padalkina, Kateryna; Bücker, H. Martin; Seidler, Ralf; Rath, Volker; Marquart, Gabriele; Niederau, Jan; Herty, Michael

2014-05-01

Drilling for deep resources is an expensive endeavor. Among the many problems finding the optimal drilling location for boreholes is one of the challenging questions. We contribute to this discussion by using a simulation based assessment of possible future borehole locations. We study the problem of finding a new borehole location in a given geothermal reservoir in terms of a numerical optimization problem. In a geothermal reservoir the temporal and spatial distribution of temperature and hydraulic pressure may be simulated using the coupled differential equations for heat transport and mass and momentum conservation for Darcy flow. Within this model the permeability and thermal conductivity are dependent on the geological layers present in the subsurface model of the reservoir. In general, those values involve some uncertainty making it difficult to predict actual heat source in the ground. Within optimal experimental the question is which location and to which depth to drill the borehole in order to estimate conductivity and permeability with minimal uncertainty. We introduce a measure for computing the uncertainty based on simulations of the coupled differential equations. The measure is based on the Fisher information matrix of temperature data obtained through the simulations. We assume that the temperature data is available within the full borehole. A minimization of the measure representing the uncertainty in the unknown permeability and conductivity parameters is performed to determine the optimal borehole location. We present the theoretical framework as well as numerical results for several 2d subsurface models including up to six geological layers. Also, the effect of unknown layers on the introduced measure is studied. Finally, to obtain a more realistic estimate of optimal borehole locations, we couple the optimization to a cost model for deep drilling problems.

Optimism in prolonged grief and depression following loss: A three-wave longitudinal study.

Science.gov (United States)

Boelen, Paul A

2015-06-30

There is considerable evidence that optimism, the predisposition to have generalized favorable expectancies for the future, is associated with numerous desirable outcomes. Few studies have examined the association of optimism with emotional distress following the death of a loved one. Doing so is important, because optimism may be an important target for interventions for post-loss psychopathology. In the current study, we examined the degree to which optimism, assessed in the first year post-loss (Time 1, T1), was associated with symptom levels of prolonged grief and depression six months (Time 2, T2) and fifteen months (Time 3, T3) later, controlling for baseline symptoms and also taking into account positive automatic cognitions at T1. Findings showed that higher optimism at T1 was associated with lower concurrent prolonged grief and depression severity. Higher optimism at T1 was also inversely related with depression symptom severity at T2 and T3, but not prolonged grief severity at T2 and T3. Implications of these findings are discussed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Optimization of a PV/T (photovoltaic/thermal) active solar still

International Nuclear Information System (INIS)

Saeedi, F.; Sarhaddi, F.; Behzadmehr, A.

2015-01-01

In this paper, the optimization of a PV/T (photovoltaic/thermal) active solar still is carried out. Analytical expressions for glass cover temperature, basin temperature, brackish water temperature and fresh water productivity are obtained by writing energy balance for different components of PV/T active solar still. The output electrical power of PV/T active solar still is calculated by four-parameter I–V (current–voltage) model. Objective function in present study is the energy efficiency of PV/T active solar still. A computer simulation program has been developed in order to obtain thermal and electrical parameters, respectively. The simulation results of the present study are in fair agreement with the experimental data of previous literatures. Finally, the optimization of PV/T active solar still has been carried out and the optimized value of mass flow rate, number of PV/T collector and the objective function have been obtained. Furthermore, the effect of various operating parameters on energy efficiency have been investigated. - Highlights: • The comprehensive optimization of a PV/T active solar still is carried out. • Present study is based on numerical simulation. • A modified energy efficiency for PV/T active solar still is obtained. • The effect of design and operating parameters is investigated on energy efficiency

Optimal Investment-Consumption Strategy under Inflation in a Markovian Regime-Switching Market

Directory of Open Access Journals (Sweden)

Huiling Wu

2016-01-01

Full Text Available This paper studies an investment-consumption problem under inflation. The consumption price level, the prices of the available assets, and the coefficient of the power utility are assumed to be sensitive to the states of underlying economy modulated by a continuous-time Markovian chain. The definition of admissible strategies and the verification theory corresponding to this stochastic control problem are presented. The analytical expression of the optimal investment strategy is derived. The existence, boundedness, and feasibility of the optimal consumption are proven. Finally, we analyze in detail by mathematical and numerical analysis how the risk aversion, the correlation coefficient between the inflation and the stock price, the inflation parameters, and the coefficient of utility affect the optimal investment and consumption strategy.

Optimism and recovery after acute coronary syndrome: a clinical cohort study.

Science.gov (United States)

Ronaldson, Amy; Molloy, Gerard J; Wikman, Anna; Poole, Lydia; Kaski, Juan-Carlos; Steptoe, Andrew

2015-04-01

Optimism is associated with reduced cardiovascular mortality, but its impact on recovery after acute coronary syndrome (ACS) is poorly understood. We hypothesized that greater optimism would lead to more effective physical and emotional adaptation after ACS and would buffer the impact of persistent depressive symptoms on clinical outcomes. This prospective observational clinical study took place in an urban general hospital and involved 369 patients admitted with a documented ACS. Optimism was assessed with a standardized questionnaire. The main outcomes were physical health status, depressive symptoms, smoking, physical activity, and fruit and vegetable consumption measured 12 months after ACS, and composite major adverse cardiac events (cardiovascular death, readmission with reinfarction or unstable angina, and coronary artery bypass graft surgery) assessed over an average of 45.7 months. We found that optimism predicted better physical health status 12 months after ACS independently of baseline physical health, age, sex, ethnicity, social deprivation, and clinical risk factors (B = 0.65, 95% confidence interval [CI] = 0.10-1.20). Greater optimism also predicted reduced risk of depressive symptoms (odds ratio = 0.82, 95% CI = 0.74-0.90), more smoking cessation, and more fruit and vegetable consumption at 12 months. Persistent depressive symptoms 12 months after ACS predicted major adverse cardiac events over subsequent years (odds ratio = 2.56, 95% CI = 1.16-5.67), but only among individuals low in optimism (optimism × depression interaction; p = .014). Optimism predicts better physical and emotional health after ACS. Measuring optimism may help identify individuals at risk. Pessimistic outlooks can be modified, potentially leading to improved recovery after major cardiac events.

Optimal Face-Iris Multimodal Fusion Scheme

Directory of Open Access Journals (Sweden)

Omid Sharifi

2016-06-01

Full Text Available Multimodal biometric systems are considered a way to minimize the limitations raised by single traits. This paper proposes new schemes based on score level, feature level and decision level fusion to efficiently fuse face and iris modalities. Log-Gabor transformation is applied as the feature extraction method on face and iris modalities. At each level of fusion, different schemes are proposed to improve the recognition performance and, finally, a combination of schemes at different fusion levels constructs an optimized and robust scheme. In this study, CASIA Iris Distance database is used to examine the robustness of all unimodal and multimodal schemes. In addition, Backtracking Search Algorithm (BSA, a novel population-based iterative evolutionary algorithm, is applied to improve the recognition accuracy of schemes by reducing the number of features and selecting the optimized weights for feature level and score level fusion, respectively. Experimental results on verification rates demonstrate a significant improvement of proposed fusion schemes over unimodal and multimodal fusion methods.

Reduction of initial stress stiffening by topology optimization

DEFF Research Database (Denmark)

Philippine, M. A.; Sigmund, Ole; Rebeiz, G. M.

2012-01-01

Topology optimization is a rigorous method of obtaining non-intuitive designs. We use it to obtain a capacitive RF switch that stiffens little in response to an increase of the in-plane biaxial stresses that typically develop during MEMS fabrication. The actuation voltage is closely related...... level. We include a volume constraint and a compliance constraint. Topology optimized designs are compared to an intuitively-designed RF switch. The switches contain similar features. The compliance constraint is varied such that the topology optimized switch performance approaches the intuitively......-designed one. Finally, the importance of the compliance constraint and of the robust formulation are discussed....

Optimization of Markov chains for a SUSY fitter: Fittino

Energy Technology Data Exchange (ETDEWEB)

Prudent, Xavier [IKTP, Technische Universitaet, Dresden (Germany); Bechtle, Philip [DESY, Hamburg (Germany); Desch, Klaus; Wienemann, Peter [Universitaet Bonn (Germany)

2010-07-01

A Markov chains is a ''random walk'' algorithm which allows an efficient scan of a given profile and the search of the absolute minimum, even when this profil suffers from the presence of many secondary minima. This property makes them particularly suited to the study of Supersymmetry (SUSY) models, where minima have to be found in up-to 18-dimensional space for the general MSSM. Hence the SUSY fitter ''Fittino'' uses a Metropolis*Hastings Markov chain in a frequentist interpretation to study the impact of current low -energy measurements, as well as expected measurements from LHC and ILC, on the SUSY parameter space. The expected properties of an optimal Markov chain should be the independence of final results with respect to the starting point and a fast convergence. These two points can be achieved by optimizing the width of the proposal distribution, that is the ''average step length'' between two links in the chain. We developped an algorithm for the optimization of the proposal width, by modifying iteratively the width so that the rejection rate be around fifty percent. This optimization leads to a starting point independent chain as well as a faster convergence.

Mathematical programming methods for large-scale topology optimization problems

DEFF Research Database (Denmark)

Rojas Labanda, Susana

for mechanical problems, but has rapidly extended to many other disciplines, such as fluid dynamics and biomechanical problems. However, the novelty and improvements of optimization methods has been very limited. It is, indeed, necessary to develop of new optimization methods to improve the final designs......, and at the same time, reduce the number of function evaluations. Nonlinear optimization methods, such as sequential quadratic programming and interior point solvers, have almost not been embraced by the topology optimization community. Thus, this work is focused on the introduction of this kind of second...... for the classical minimum compliance problem. Two of the state-of-the-art optimization algorithms are investigated and implemented for this structural topology optimization problem. A Sequential Quadratic Programming (TopSQP) and an interior point method (TopIP) are developed exploiting the specific mathematical...

Optimization (Alara) and probabilistic exposures: the application of optimization criteria to the control of risks due to exposures of a probabilistic nature

International Nuclear Information System (INIS)

Gonzalez, A.J.

1989-01-01

The paper described the application of the principles of optimization recommended by the International Commission on Radiological Protection (ICRP) to the restrain of radiation risks due to exposures that may or may not be incurred and to which a probability of occurrence can be assigned. After describing the concept of probabilistic exposures, it proposes a basis for a converging policy of control for both certain and probabilistic exposures, namely the dose-risk relationship adopted for radiation protection purposes. On that basis some coherent approaches for dealing with probabilistic exposures, such as the limitation of individual risks, are discussed. The optimization of safety for reducing all risks from probabilistic exposures to as-low-as-reasonably-achievable (ALARA) levels is reviewed in full. The principles of optimization of protection are used as a basic framework and the relevant factors to be taken into account when moving to probabilistic exposures are presented. The paper also reviews the decision-aiding techniques suitable for performing optimization with particular emphasis to the multi-attribute utility-analysis technique. Finally, there is a discussion on some practical application of decision-aiding multi-attribute utility analysis to probabilistic exposures including the use of probabilistic utilities. In its final outlook, the paper emphasizes the need for standardization and solutions to generic problems, if optimization of safety is to be successful

Optimal Allocation of Generalized Power Sources in Distribution Network Based on Multi-Objective Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Li Ran

2017-01-01

Full Text Available Optimal allocation of generalized power sources in distribution network is researched. A simple index of voltage stability is put forward. Considering the investment and operation benefit, the stability of voltage and the pollution emissions of generalized power sources in distribution network, a multi-objective optimization planning model is established. A multi-objective particle swarm optimization algorithm is proposed to solve the optimal model. In order to improve the global search ability, the strategies of fast non-dominated sorting, elitism and crowding distance are adopted in this algorithm. Finally, tested the model and algorithm by IEEE-33 node system to find the best configuration of GP, the computed result shows that with the generalized power reasonable access to the active distribution network, the investment benefit and the voltage stability of the system is improved, and the proposed algorithm has better global search capability.

Research on Optimal Observation Scale for Damaged Buildings after Earthquake Based on Optimal Feature Space

Science.gov (United States)

Chen, J.; Chen, W.; Dou, A.; Li, W.; Sun, Y.

2018-04-01

A new information extraction method of damaged buildings rooted in optimal feature space is put forward on the basis of the traditional object-oriented method. In this new method, ESP (estimate of scale parameter) tool is used to optimize the segmentation of image. Then the distance matrix and minimum separation distance of all kinds of surface features are calculated through sample selection to find the optimal feature space, which is finally applied to extract the image of damaged buildings after earthquake. The overall extraction accuracy reaches 83.1 %, the kappa coefficient 0.813. The new information extraction method greatly improves the extraction accuracy and efficiency, compared with the traditional object-oriented method, and owns a good promotional value in the information extraction of damaged buildings. In addition, the new method can be used for the information extraction of different-resolution images of damaged buildings after earthquake, then to seek the optimal observation scale of damaged buildings through accuracy evaluation. It is supposed that the optimal observation scale of damaged buildings is between 1 m and 1.2 m, which provides a reference for future information extraction of damaged buildings.

A Framework for Constrained Optimization Problems Based on a Modified Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Biwei Tang

2016-01-01

Full Text Available This paper develops a particle swarm optimization (PSO based framework for constrained optimization problems (COPs. Aiming at enhancing the performance of PSO, a modified PSO algorithm, named SASPSO 2011, is proposed by adding a newly developed self-adaptive strategy to the standard particle swarm optimization 2011 (SPSO 2011 algorithm. Since the convergence of PSO is of great importance and significantly influences the performance of PSO, this paper first theoretically investigates the convergence of SASPSO 2011. Then, a parameter selection principle guaranteeing the convergence of SASPSO 2011 is provided. Subsequently, a SASPSO 2011-based framework is established to solve COPs. Attempting to increase the diversity of solutions and decrease optimization difficulties, the adaptive relaxation method, which is combined with the feasibility-based rule, is applied to handle constraints of COPs and evaluate candidate solutions in the developed framework. Finally, the proposed method is verified through 4 benchmark test functions and 2 real-world engineering problems against six PSO variants and some well-known methods proposed in the literature. Simulation results confirm that the proposed method is highly competitive in terms of the solution quality and can be considered as a vital alternative to solve COPs.

Optimization design of blade shapes for wind turbines

DEFF Research Database (Denmark)

Chen, Jin; Wang, Xudong; Shen, Wen Zhong

2010-01-01

For the optimization design of wind turbines, the new normal and tangential induced factors of wind turbines are given considering the tip loss of the normal and tangential forces based on the blade element momentum theory and traditional aerodynamic model. The cost model of the wind turbines...... and the optimization design model are developed. In the optimization model, the objective is the minimum cost of energy and the design variables are the chord length, twist angle and the relative thickness. Finally, the optimization is carried out for a 2 MW blade by using this optimization design model....... The performance of blades is validated through the comparison and analysis of the results. The reduced cost shows that the optimization model is good enough for the design of wind turbines. The results give a proof for the design and research on the blades of large scale wind turbines and also establish...

Formulation optimization and in vivo proof-of-concept study of thermosensitive liposomes balanced by phospholipid, elastin-like polypeptide, and cholesterol.

Directory of Open Access Journals (Sweden)

Sun Min Park

Full Text Available One application of nanotechnology in medicine that is presently being developed involves a drug delivery system (DDS employing nanoparticles to deliver drugs to diseased sites in the body avoiding damage of healthy tissue. Recently, the mild hyperthermia-triggered drug delivery combined with anticancer agent-loaded thermosensitive liposomes was widely investigated. In this study, thermosensitive liposomes (TSLs, composed of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethyleneglycol-2000] (DSPE-PEG, cholesterol, and a fatty acid conjugated elastin-like polypeptide (ELP, were developed and optimized for triggered drug release, controlled by external heat stimuli. We introduced modified ELP, tunable for various biomedical purposes, to our thermosensitive liposome (e-TSL to convey a high thermoresponsive property. We modulated thermosensitivity and stability by varying the ratios of e-TSL components, such as phospholipid, ELP, and cholesterol. Experimental data obtained in this study corresponded to results from a simulation study that demonstrated, through the calculation of the lateral diffusion coefficient, increased permeation of the lipid bilayer with higher ELP concentrations, and decreased permeation in the presence of cholesterol. Finally, we identified effective drug accumulation in tumor tissues and antitumor efficacy with our optimized e-TSL, while adjusting lag-times for systemic accumulation.

Optimization of imprintable nanostructured a-Si solar cells: FDTD study.

Science.gov (United States)

Fisker, Christian; Pedersen, Thomas Garm

2013-03-11

We present a finite-difference time-domain (FDTD) study of an amorphous silicon (a-Si) thin film solar cell, with nano scale patterns on the substrate surface. The patterns, based on the geometry of anisotropically etched silicon gratings, are optimized with respect to the period and anti-reflection (AR) coating thickness for maximal absorption in the range of the solar spectrum. The structure is shown to increase the cell efficiency by 10.2% compared to a similar flat solar cell with an optimized AR coating thickness. An increased back reflection can be obtained with a 50 nm zinc oxide layer on the back reflector, which gives an additional efficiency increase, leading to a total of 14.9%. In addition, the patterned cells are shown to be up to 3.8% more efficient than an optimized textured reference cell based on the Asahi U-type glass surface. The effects of variations of the optimized solar cell structure due to the manufacturing process are investigated, and shown to be negligible for variations below ±10%.

Measuring micron size beams in the SLC final focus

International Nuclear Information System (INIS)

McCormick, D.; Ross, M.; DeBarger, S.

1994-10-01

A pair of high resolution wire scanners have been built and installed in the SLC final focus. The final focus optics uses a set of de-magnifying telescopes, and an ideal location for a beam size monitor is at one of the magnified image points of the interaction point. The image point chosen for these scanners is in the middle of a large bend magnet. The design beam spots here are about 2 microns in the vertical and 20 microns in the horizontal plane. The scanners presented a number of design challenges. In this paper we discuss the mechanical design of the scanner, and fabrication techniques of its ceramic wire support card which holds many 4 and 7 um carbon wires. Accurate motion of the wire during a scan is critical. In this paper we describe tests of stepper motors, gear combinations, and radiation hardened encoders needed to produce the required motion with a step resolution of 80 nanometers. Also presented here are the results of scattered radiation detector placement studies carried out to optimize the signal from the 4 micron wires. Finally, we present measurements from the scanner

STUDY THE PROBLEMS OF OPTIMIZING THE CAPITAL STRUCTURE OF THE COMPANY

Directory of Open Access Journals (Sweden)

Olga Gaydarzhyyska

2016-11-01

Full Text Available The aim of this work is to study the problem of optimizing the capital structure of the company. Optimization of capital structure is a necessary condition of adaptation the enterprises regardless of the branch of economy to which a company belongs, to changes in the economy in its development. Methods and criteria of optimisation of the capital structure of the enterprise. The method of determining the optimal capital structure of the enterprise according to the criteria of maximizing financial profitability. Technique. The study is based on the theoretical analysis of scientific works and practical activity of enterprises. Results. It is proved that in the process of optimizing the capital structure necessary to take into account the predictable result of economic activity of the enterprise, that is, financial result from usual activity before taxation. The study of problems of optimization of capital structure aimed at opening opportunities for the effective organization of business enterprises, providing conditions for disclosure for businesses achieving the goals of any order, and the creation of opportunities for enterprise maximum level of profit. The principle of optimization is to select the solution that best would take into account internal possibilities and external terms of activity of the enterprise. Optimization is the choice of a certain economic indicator that would allow to compare the effectiveness of any solutions. Also it is advisable to pay attention to the use of different types of loan capital to business enterprises, to know that helps to speed up circulation of funds and increase returns on invested capital, increase the efficiency of financial activities of a business entity. Value. Today, the economic activities of enterprises has a significant impact on the development of trade and economy. The achievement of dynamic growth of the basic indicators of work of enterprises of any sector of the economy, is the basic

Optimal GENCO bidding strategy

Science.gov (United States)

Gao, Feng

Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed

Optimal design of marine steam turbine

International Nuclear Information System (INIS)

Liu Chengyang; Yan Changqi; Wang Jianjun

2012-01-01

The marine steam turbine is one of the key equipment in marine power plant, and it tends to using high power steam turbine, which makes the steam turbine to be heavier and larger, it causes difficulties to the design and arrangement of the steam turbine, and the marine maneuverability is seriously influenced. Therefore, it is necessary to apply optimization techniques to the design of the steam turbine in order to achieve the minimum weight or volume by means of finding the optimum combination of design parameters. The math model of the marine steam turbine design calculation was established. The sensitivities of condenser pressure, power ratio of HP turbine with LP turbine, and the ratio of diameter with height at the end stage of LP turbine, which influence the weight of the marine steam turbine, were analyzed. The optimal design of the marine steam turbine, aiming at the weight minimization while satisfying the structure and performance constraints, was carried out with the hybrid particle swarm optimization algorithm. The results show that, steam turbine weight is reduced by 3.13% with the optimization scheme. Finally, the optimization results were analyzed, and the steam turbine optimization design direction was indicated. (authors)

Study of electron and neutrino interactions. Final report

International Nuclear Information System (INIS)

Abashian, A.

1997-01-01

This is the final report for the DOE-sponsored experimental particle physics program at Virginia Tech to study the properties of the Standard Model of strong and electroweak interactions. This contract (DE-AS05-80ER10713) covers the period from August 1, 1980 to January 31, 1993. Task B of this contract, headed by Professor Alexander Abashian, is described in this final report. This program has been pursued on many fronts by the researchers in a search for axions at SLAC, in electron-positron collisions in the AMY experiment at the TRISTAN collider in Japan, in measurements of muon decay properties in the MEGA and RHO experiments at the LAMPF accelerator, in a detailed analysis of scattering effects in the purported observation of a 17 keV neutrino at Oxford, in a search for a disoriented chiral condensate with the MiniMax experiment at Fermilab, and in an R ampersand D program on resistive plate counters that could find use in low-cost high-quality charged particle detection at low rates

Joint Optimization of Preventive Maintenance and Spare Parts Inventory with Appointment Policy

Directory of Open Access Journals (Sweden)

Jing Cai

2017-01-01

Full Text Available Under the background of the wide application of condition-based maintenance (CBM in maintenance practice, the joint optimization of maintenance and spare parts inventory is becoming a hot research to take full advantage of CBM and reduce the operational cost. In order to avoid both the high inventory level and the shortage of spare parts, an appointment policy of spare parts is first proposed based on the prediction of remaining useful lifetime, and then a corresponding joint optimization model of preventive maintenance and spare parts inventory is established. Due to the complexity of the model, the combination method of genetic algorithm and Monte Carlo is presented to get the optimal maximum inventory level, safety inventory level, potential failure threshold, and appointment threshold to minimize the cost rate. Finally, the proposed model is studied through a case study and compared with both the separate optimization and the joint optimization without appointment policy, and the results show that the proposed model is more effective. In addition, the sensitivity analysis shows that the proposed model is consistent with the actual situation of maintenance practices and inventory management.

Compressed Biogas-Diesel Dual-Fuel Engine Optimization Study for Ultralow Emission

Directory of Open Access Journals (Sweden)

Hasan Koten

2014-06-01

Full Text Available The aim of this study is to find out the optimum operating conditions in a diesel engine fueled with compressed biogas (CBG and pilot diesel dual-fuel. One-dimensional (1D and three-dimensional (3D computational fluid dynamics (CFD code and multiobjective optimization code were employed to investigate the influence of CBG-diesel dual-fuel combustion performance and exhaust emissions on a diesel engine. In this paper, 1D engine code and multiobjective optimization code were coupled and evaluated about 15000 cases to define the proper boundary conditions. In addition, selected single diesel fuel (dodecane and dual-fuel (CBG-diesel combustion modes were modeled to compare the engine performances and exhaust emission characteristics by using CFD code under various operating conditions. In optimization study, start of pilot diesel fuel injection, CBG-diesel flow rate, and engine speed were optimized and selected cases were compared using CFD code. CBG and diesel fuels were defined as leading reactants using user defined code. The results showed that significantly lower NOx emissions were emitted under dual-fuel operation for all cases compared to single-fuel mode at all engine load conditions.

Fuel optimization for low-thrust Earth-Moon transfer via indirect optimal control

Science.gov (United States)

Pérez-Palau, Daniel; Epenoy, Richard

2018-02-01

The problem of designing low-energy transfers between the Earth and the Moon has attracted recently a major interest from the scientific community. In this paper, an indirect optimal control approach is used to determine minimum-fuel low-thrust transfers between a low Earth orbit and a Lunar orbit in the Sun-Earth-Moon Bicircular Restricted Four-Body Problem. First, the optimal control problem is formulated and its necessary optimality conditions are derived from Pontryagin's Maximum Principle. Then, two different solution methods are proposed to overcome the numerical difficulties arising from the huge sensitivity of the problem's state and costate equations. The first one consists in the use of continuation techniques. The second one is based on a massive exploration of the set of unknown variables appearing in the optimality conditions. The dimension of the search space is reduced by considering adapted variables leading to a reduction of the computational time. The trajectories found are classified in several families according to their shape, transfer duration and fuel expenditure. Finally, an analysis based on the dynamical structure provided by the invariant manifolds of the two underlying Circular Restricted Three-Body Problems, Earth-Moon and Sun-Earth is presented leading to a physical interpretation of the different families of trajectories.

Multiobjective optimizations of a novel cryocooled dc gun based ultrafast electron diffraction beam line

Directory of Open Access Journals (Sweden)

Colwyn Gulliford

2016-09-01

Full Text Available We present the results of multiobjective genetic algorithm optimizations of a single-shot ultrafast electron diffraction beam line utilizing a 225 kV dc gun with a novel cryocooled photocathode system and buncher cavity. Optimizations of the transverse projected emittance as a function of bunch charge are presented and discussed in terms of the scaling laws derived in the charge saturation limit. Additionally, optimization of the transverse coherence length as a function of final rms bunch length at the sample location have been performed for three different sample radii: 50, 100, and 200  μm, for two final bunch charges: 10^{5} electrons (16 fC and 10^{6} electrons (160 fC. Example optimal solutions are analyzed, and the effects of disordered induced heating estimated. In particular, a relative coherence length of L_{c,x}/σ_{x}=0.27  nm/μm was obtained for a final bunch charge of 10^{5} electrons and final bunch length of σ_{t}≈100  fs. For a final charge of 10^{6} electrons the cryogun produces L_{c,x}/σ_{x}≈0.1  nm/μm for σ_{t}≈100–200  fs and σ_{x}≥50  μm. These results demonstrate the viability of using genetic algorithms in the design and operation of ultrafast electron diffraction beam lines.

Multiobjective Optimization of Linear Cooperative Spectrum Sensing: Pareto Solutions and Refinement.

Science.gov (United States)

Yuan, Wei; You, Xinge; Xu, Jing; Leung, Henry; Zhang, Tianhang; Chen, Chun Lung Philip

2016-01-01

In linear cooperative spectrum sensing, the weights of secondary users and detection threshold should be optimally chosen to minimize missed detection probability and to maximize secondary network throughput. Since these two objectives are not completely compatible, we study this problem from the viewpoint of multiple-objective optimization. We aim to obtain a set of evenly distributed Pareto solutions. To this end, here, we introduce the normal constraint (NC) method to transform the problem into a set of single-objective optimization (SOO) problems. Each SOO problem usually results in a Pareto solution. However, NC does not provide any solution method to these SOO problems, nor any indication on the optimal number of Pareto solutions. Furthermore, NC has no preference over all Pareto solutions, while a designer may be only interested in some of them. In this paper, we employ a stochastic global optimization algorithm to solve the SOO problems, and then propose a simple method to determine the optimal number of Pareto solutions under a computational complexity constraint. In addition, we extend NC to refine the Pareto solutions and select the ones of interest. Finally, we verify the effectiveness and efficiency of the proposed methods through computer simulations.

Aerodynamic reconfiguration and multicriterial optimization of centrifugal compressors – a case study

Directory of Open Access Journals (Sweden)

Valeriu DRAGAN

2014-12-01

Full Text Available This paper continues the recent research of the author, with application to 3D computational fluid dynamics multicriterial optimization of turbomachinery parts. Computational Fluid Dynamics has been an ubicuous tool for compressor design for decades, helping the designers to test the aerodynamic parameters of their machines with great accuracy. Due to advances of multigrid methods and the improved robustness of structured solvers, CFD can nowadays be part of an optimization loop with artificial neural networks or evolutive algorithms. This paper presents a case study of an air centrifugal compressor rotor optimized using Numeca's Design 3D CFD suite. The turbulence model used for the database generation and the optimization stage is Spalart Allmaras. Results indicate a fairly quick convergence time per individual as well as a good convergence of the artificial neural network optimizer.

Optimal Model-Based Control in HVAC Systems

DEFF Research Database (Denmark)

Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

2008-01-01

is developed. Then the optimal control structure is designed and implemented. The HVAC system is splitted into two subsystems. By selecting the right set-points and appropriate cost functions for each subsystem controller the optimal control strategy is respected to gaurantee the minimum thermal and electrical......This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...... energy consumption. Finally, the controller is applied to control the mentioned HVAC system and the results show that the expected goals are fulfilled....

Effective factors on optimizing banks’ balance sheet using fuzzy analytical hierarchy process

Directory of Open Access Journals (Sweden)

Shoja Rezaei

2013-11-01

Full Text Available Every bank seeks methods to optimize its assets and liabilities, thus the main subject is managing assets-liabilities in the balance sheet and the main question is by which factor banks will be enabled to have an optimized combination of assets and liabilities in a common level of risk to get the most return. This case study is dedicated to Refah bank and is an applicable study. The data has collected from the headquarter by a questionnaire and finally effective factors weight on optimizing bank balance sheet determined by using Fuzzy analytical hierarchy process. Results showed that revenue has more effect on optimizing for %39.5 and also loan to deposit ratio for %.74, regarding revenue as a symbol of efficiency in banks, it seems to be the most important factor and goal in banking industry. Furthermore banks need to have some liquidity to respond customers demand to cover one of the most important risks of banking. This factor importance determined to be %18 in Refah Bank by using model and experts view.

Modeling, Simulation and Optimization of Hydrogen Production Process from Glycerol using Steam Reforming

International Nuclear Information System (INIS)

Park, Jeongpil; Cho, Sunghyun; Kim, Tae-Ok; Shin, Dongil; Lee, Seunghwan; Moon, Dong Ju

2014-01-01

For improved sustainability of the biorefinery industry, biorefinery-byproduct glycerol is being investigated as an alternate source for hydrogen production. This research designs and optimizes a hydrogen-production process for small hydrogen stations using steam reforming of purified glycerol as the main reaction, replacing existing processes relying on steam methane reforming. Modeling, simulation and optimization using a commercial process simulator are performed for the proposed hydrogen production process from glycerol. The mixture of glycerol and steam are used for making syngas in the reforming process. Then hydrogen are produced from carbon monoxide and steam through the water-gas shift reaction. Finally, hydrogen is separated from carbon dioxide using PSA. This study shows higher yield than former U.S.. DOE and Linde studies. Economic evaluations are performed for optimal planning of constructing domestic hydrogen energy infrastructure based on the proposed glycerol-based hydrogen station

An integrated DEA-COLS-SFA algorithm for optimization and policy making of electricity distribution units

International Nuclear Information System (INIS)

Azadeh, A.; Ghaderi, S.F.; Omrani, H.; Eivazy, H.

2009-01-01

This paper presents an integrated data envelopment analysis (DEA)-corrected ordinary least squares (COLS)-stochastic frontier analysis (SFA)-principal component analysis (PCA)-numerical taxonomy (NT) algorithm for performance assessment, optimization and policy making of electricity distribution units. Previous studies have generally used input-output DEA models for benchmarking and evaluation of electricity distribution units. However, this study proposes an integrated flexible approach to measure the rank and choose the best version of the DEA method for optimization and policy making purposes. It covers both static and dynamic aspects of information environment due to involvement of SFA which is finally compared with the best DEA model through the Spearman correlation technique. The integrated approach would yield in improved ranking and optimization of electricity distribution systems. To illustrate the usability and reliability of the proposed algorithm, 38 electricity distribution units in Iran have been considered, ranked and optimized by the proposed algorithm of this study.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

Science.gov (United States)

Chen, Wei

2015-07-01

In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

Optimal quantum learning of a unitary transformation

International Nuclear Information System (INIS)

Bisio, Alessandro; Chiribella, Giulio; D'Ariano, Giacomo Mauro; Facchini, Stefano; Perinotti, Paolo

2010-01-01

We address the problem of learning an unknown unitary transformation from a finite number of examples. The problem consists in finding the learning machine that optimally emulates the examples, thus reproducing the unknown unitary with maximum fidelity. Learning a unitary is equivalent to storing it in the state of a quantum memory (the memory of the learning machine) and subsequently retrieving it. We prove that, whenever the unknown unitary is drawn from a group, the optimal strategy consists in a parallel call of the available uses followed by a 'measure-and-rotate' retrieving. Differing from the case of quantum cloning, where the incoherent 'measure-and-prepare' strategies are typically suboptimal, in the case of learning the 'measure-and-rotate' strategy is optimal even when the learning machine is asked to reproduce a single copy of the unknown unitary. We finally address the problem of the optimal inversion of an unknown unitary evolution, showing also in this case the optimality of the 'measure-and-rotate' strategies and applying our result to the optimal approximate realignment of reference frames for quantum communication.

Replica analysis for the duality of the portfolio optimization problem.

Science.gov (United States)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Replica analysis for the duality of the portfolio optimization problem

Science.gov (United States)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Shape optimization of draft tubes for Agnew microhydro turbines

International Nuclear Information System (INIS)

Shojaeefard, Mohammad Hasan; Mirzaei, Ammar; Babaei, Ali

2014-01-01

Highlights: • The draft tube of Agnew microhydro turbine was optimized. • Pareto optimal solutions were determined by neural networks and NSGA-II algorithm. • The pressure recovery factor increases with height and angle over design ranges. • The loss coefficient reaches the minimum values at angles about 2 o . • Swirl of the incoming flow has great influence on the optimization results. - Abstract: In this study, the shape optimization of draft tubes utilized in Agnew type microhydro turbines has been discussed. The design parameters of the draft tube such as the cone angle and the height above the tailrace are considered in defining an optimization problem whose goal is to maximize the pressure recovery factor and minimize the energy loss coefficient of flow. The design space is determined by considering the experimental constraints and parameterized by the method of face-centered uniform ascertain distribution. The numerical simulations are performed using the boundary conditions found from laboratory tests and the obtained results are analyzed to create and validate a feed-forward neural network model, which is implemented as a surrogate model. The optimal Pareto solutions are finally determined using the NSGA-II evolutionary algorithm and compared for different inlet conditions. The results predict that the high swirl of the incoming flow drastically reduces the performance of the draft tube

AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening

Directory of Open Access Journals (Sweden)

Pajeva Ilza

2008-10-01

Full Text Available Abstract Background Virtual or in silico ligand screening combined with other computational methods is one of the most promising methods to search for new lead compounds, thereby greatly assisting the drug discovery process. Despite considerable progresses made in virtual screening methodologies, available computer programs do not easily address problems such as: structural optimization of compounds in a screening library, receptor flexibility/induced-fit, and accurate prediction of protein-ligand interactions. It has been shown that structural optimization of chemical compounds and that post-docking optimization in multi-step structure-based virtual screening approaches help to further improve the overall efficiency of the methods. To address some of these points, we developed the program AMMOS for refining both, the 3D structures of the small molecules present in chemical libraries and the predicted receptor-ligand complexes through allowing partial to full atom flexibility through molecular mechanics optimization. Results The program AMMOS carries out an automatic procedure that allows for the structural refinement of compound collections and energy minimization of protein-ligand complexes using the open source program AMMP. The performance of our package was evaluated by comparing the structures of small chemical entities minimized by AMMOS with those minimized with the Tripos and MMFF94s force fields. Next, AMMOS was used for full flexible minimization of protein-ligands complexes obtained from a mutli-step virtual screening. Enrichment studies of the selected pre-docked complexes containing 60% of the initially added inhibitors were carried out with or without final AMMOS minimization on two protein targets having different binding pocket properties. AMMOS was able to improve the enrichment after the pre-docking stage with 40 to 60% of the initially added active compounds found in the top 3% to 5% of the entire compound collection

Optimal Control for Fast and Robust Generation of Entangled States in Anisotropic Heisenberg Chains

Science.gov (United States)

Zhang, Xiong-Peng; Shao, Bin; Zou, Jian

2017-05-01

Motivated by some recent results of the optimal control (OC) theory, we study anisotropic XXZ Heisenberg spin-1/2 chains with control fields acting on a single spin, with the aim of exploring how maximally entangled state can be prepared. To achieve the goal, we use a numerical optimization algorithm (e.g., the Krotov algorithm, which was shown to be capable of reaching the quantum speed limit) to search an optimal set of control parameters, and then obtain OC pulses corresponding to the target fidelity. We find that the minimum time for implementing our target state depending on the anisotropy parameter Δ of the model. Finally, we analyze the robustness of the obtained results for the optimal fidelities and the effectiveness of the Krotov method under some realistic conditions.

Stochastic optimization of loading pattern for PWR

International Nuclear Information System (INIS)

Smuc, T.; Pevec, D.

1994-01-01

The application of stochastic optimization methods in solving in-core fuel management problems is restrained by the need for a large number of proposed solutions loading patterns, if a high quality final solution is wanted. Proposed loading patterns have to be evaluated by core neutronics simulator, which can impose unrealistic computer time requirements. A new loading pattern optimization code Monte Carlo Loading Pattern Search has been developed by coupling the simulated annealing optimization algorithm with a fast one-and-a-half dimensional core depletion simulator. The structure of the optimization method provides more efficient performance and allows the user to empty precious experience in the search process, thus reducing the search space size. Hereinafter, we discuss the characteristics of the method and illustrate them on the results obtained by solving the PWR reload problem. (authors). 7 refs., 1 tab., 1 fig

Mirror hybrid reactor optimization studies

International Nuclear Information System (INIS)

Bender, D.J.

1976-01-01

A system model of the mirror hybrid reactor has been developed. The major components of the model include (1) the reactor description, (2) a capital cost analysis, (3) various fuel management schemes, and (4) an economic analysis that includes the hybrid plus its associated fission burner reactors. The results presented describe the optimization of the mirror hybrid reactor, the objective being to minimize the cost of electricity from the hybrid fission-burner reactor complex. We have examined hybrid reactors with two types of blankets, one containing natural uranium, the other thorium. The major difference between the two optimized reactors is that the uranium hybrid is a significant net electrical power producer, whereas the thorium hybrid just about breaks even on electrical power. Our projected costs for fissile fuel production are approximately 50 $/g for 239 Pu and approximately 125 $/g for 233 U

Genetic Algorithm and its Application in Optimal Sensor Layout

Directory of Open Access Journals (Sweden)

Xiang-Yang Chen

2015-05-01

Full Text Available This paper aims at the problem of multi sensor station distribution, based on multi- sensor systems of different types as the research object, in the analysis of various types of sensors with different application background, different indicators of demand, based on the different constraints, for all kinds of multi sensor station is studied, the application of genetic algorithms as a tool for the objective function of the models optimization, then the optimal various types of multi sensor station distribution plan, improve the performance of the system, and achieved good military effect. In the field of application of sensor radar, track measuring instrument, the satellite, passive positioning equipment of various types, specific problem, use care indicators and station arrangement between the mathematical model of geometry, using genetic algorithm to get the optimization results station distribution, to solve a variety of practical problems provides useful help, but also reflects the improved genetic algorithm in electronic weapon system based on multi sensor station distribution on the applicability and effectiveness of the optimization; finally the genetic algorithm for integrated optimization of multi sensor station distribution using the good to the training exercise tasks based on actual in, and have achieved good military effect.

Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach

KAUST Repository

Amin, Osama

2015-04-23

In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.

Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach

KAUST Repository

Amin, Osama; Bedeer, Ebrahim; Ahmed, Mohamed; Dobre, Octavia

2015-01-01

In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.

An Optimization Method for Condition Based Maintenance of Aircraft Fleet Considering Prognostics Uncertainty

Directory of Open Access Journals (Sweden)

Qiang Feng

2014-01-01

Full Text Available An optimization method for condition based maintenance (CBM of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL distribution of the key line replaceable Module (LRM has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success.

A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

Science.gov (United States)

Yang, Shaofu; Liu, Qingshan; Wang, Jun

2018-04-01

This paper is concerned with multiple-objective distributed optimization. Based on objective weighting and decision space decomposition, a collaborative neurodynamic approach to multiobjective distributed optimization is presented. In the approach, a system of collaborative neural networks is developed to search for Pareto optimal solutions, where each neural network is associated with one objective function and given constraints. Sufficient conditions are derived for ascertaining the convergence to a Pareto optimal solution of the collaborative neurodynamic system. In addition, it is proved that each connected subsystem can generate a Pareto optimal solution when the communication topology is disconnected. Then, a switching-topology-based method is proposed to compute multiple Pareto optimal solutions for discretized approximation of Pareto front. Finally, simulation results are discussed to substantiate the performance of the collaborative neurodynamic approach. A portfolio selection application is also given.

Environmental Multiobjective Optimization of the Use of Biomass Resources for Energy

DEFF Research Database (Denmark)

Vadenbo, Carl; Tonini, Davide; Astrup, Thomas Fruergaard

2017-01-01

of the optimization model is exemplified by a case aimed at determining the environmentally optimal use of biomass in the Danish energy system in 2025. A multiobjective formulation based on fuzzy intervals for six environmental impact categories resulted in impact reductions of 13-43% compared to the baseline...... environmental consequences. To circumvent the limitations of scenario-based life cycle assessment (LCA), we develop a multiobjective optimization model to systematically identify the environmentally optimal use of biomass for energy under given system constraints. Besides satisfying annual final energy demand...

Multi-objective optimal design of sandwich panels using a genetic algorithm

Science.gov (United States)

Xu, Xiaomei; Jiang, Yiping; Pueh Lee, Heow

2017-10-01

In this study, an optimization problem concerning sandwich panels is investigated by simultaneously considering the two objectives of minimizing the panel mass and maximizing the sound insulation performance. First of all, the acoustic model of sandwich panels is discussed, which provides a foundation to model the acoustic objective function. Then the optimization problem is formulated as a bi-objective programming model, and a solution algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is provided to solve the proposed model. Finally, taking an example of a sandwich panel that is expected to be used as an automotive roof panel, numerical experiments are carried out to verify the effectiveness of the proposed model and solution algorithm. Numerical results demonstrate in detail how the core material, geometric constraints and mechanical constraints impact the optimal designs of sandwich panels.

Does optimism act as a buffer against posttraumatic stress over time? A longitudinal study of the protective role of optimism after the 2011 Oslo bombing.

Science.gov (United States)

Birkeland, Marianne Skogbrott; Blix, Ines; Solberg, Øivind; Heir, Trond

2017-03-01

Cross-sectional studies have revealed that high levels of optimism can protect against high levels of posttraumatic stress after exposure to trauma. However, this is the first study to explore (a) the protective role of optimism in a longitudinal perspective and (b) optimism's protective effects on specific symptom clusters within the posttraumatic stress symptomatology. This study used prospective survey data from ministerial employees (n = 256) collected approximately 1, 2, and 3 years after the 2011 Oslo bombing. To examine relationships between optimism and development of posttraumatic stress, we applied a series of latent growth curve analyses of both overall posttraumatic stress and the 5 clusters within the posttraumatic stress symptomatology (intrusions, avoidance, numbing, dysphoric arousal, and anxious arousal) with predictors and interaction terms. The results showed that levels of exposure and optimism had main effects on starting levels of all clusters of posttraumatic stress. In addition, optimism had a protective-stabilizing effect on starting levels of avoidance, numbing, and dysphoric arousal. No associations between optimism and rate of change in symptoms clusters were found. These results suggest that optimism may help to neutralize the effects of high exposure on levels of symptoms of avoidance, numbing, and dysphoric arousal but not on the symptoms of intrusions and anxious arousal. Thus, individuals high in optimism still experience intrusions and anxious arousal after trauma, but may be better equipped to cope with these so they do not develop into avoidance, numbing and dyshorical arousal. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Study of the Optimal Planning Model for Reservoir Sustainable Management- A Case Study of Shihmen Reservoir

Science.gov (United States)

Chen, Y. Y.; Ho, C. C.; Chang, L. C.

2017-12-01

The reservoir management in Taiwan faces lots of challenge. Massive sediment caused by landslide were flushed into reservoir, which will decrease capacity, rise the turbidity, and increase supply risk. Sediment usually accompanies nutrition that will cause eutrophication problem. Moreover, the unevenly distribution of rainfall cause water supply instability. Hence, how to ensure sustainable use of reservoirs has become an important task in reservoir management. The purpose of the study is developing an optimal planning model for reservoir sustainable management to find out an optimal operation rules of reservoir flood control and sediment sluicing. The model applies Genetic Algorithms to combine with the artificial neural network of hydraulic analysis and reservoir sediment movement. The main objective of operation rules in this study is to prevent reservoir outflow caused downstream overflow, minimum the gap between initial and last water level of reservoir, and maximum sluicing sediment efficiency. A case of Shihmen reservoir was used to explore the different between optimal operating rule and the current operation of the reservoir. The results indicate optimal operating rules tended to open desilting tunnel early and extend open duration during flood discharge period. The results also show the sluicing sediment efficiency of optimal operating rule is 36%, 44%, 54% during Typhoon Jangmi, Typhoon Fung-Wong, and Typhoon Sinlaku respectively. The results demonstrate the optimal operation rules do play a role in extending the service life of Shihmen reservoir and protecting the safety of downstream. The study introduces a low cost strategy, alteration of operation reservoir rules, into reservoir sustainable management instead of pump dredger in order to improve the problem of elimination of reservoir sediment and high cost.

Final Report: Optimization of Chemical Process Heater and Combustion Systems, September 1, 1996 - August 31, 1999

Energy Technology Data Exchange (ETDEWEB)

Smith, Phillip

1999-08-31

The optimization of ethylene furnace operations using cfd-based simulations has been addressed. The optimization problems have been cast into various formulations: the Multidisciplinary feasible (MDF) approach, the All-At-Once (AAO) approach and the Individual discipline feasible (IDF) approach. These approaches mainly differ in their handling of the state equations as constraints, and hence some of the formulations place restrictions on the methods used to solve the state equations.

MANAGERIAL OPTIMISM AND DEBT FINANCING: CASE STUDY ON INDONESIA MANUFACTURING LISTED FIRMS

Directory of Open Access Journals (Sweden)

Gesti Memarista

2016-10-01

Full Text Available Managerial’s psychology can affect financial decision in the company. This paper analyzes the influence of managerial optimism on the debt financing by using regression analysis. The dependent variable in this paper is debt financing. The independent variable is managerial optimism and the control variable are firm value, firm size, and firm performance that are occurred in the previous period. The sample used in this study is manufacturing companies that listed in Indonesian stock exchange during 2010-2014. The result on this study shows that managerial optimism, firm value, and firm size that are occurred in the previous period have positive significantly impact on debt financing, whereas firm performance in the previous period has negative significantly impact on debt financing.

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

Science.gov (United States)

Burt, Adam O.; Hull, Patrick V.

2014-01-01

This paper presents a design automation process using optimization via a genetic algorithm to design the conceptual structure of a Lunar Pallet Lander. The goal is to determine a design that will have the primary natural frequencies at or above a target value as well as minimize the total mass. Several iterations of the process are presented. First, a concept optimization is performed to determine what class of structure would produce suitable candidate designs. From this a stiffened sheet metal approach was selected leading to optimization of beam placement through generating a two-dimensional mesh and varying the physical location of reinforcing beams. Finally, the design space is reformulated as a binary problem using 1-dimensional beam elements to truncate the design space to allow faster convergence and additional mechanical failure criteria to be included in the optimization responses. Results are presented for each design space configuration. The final flight design was derived from these results.

Study on transfer optimization of urban rail transit and conventional public transport

Science.gov (United States)

Wang, Jie; Sun, Quan Xin; Mao, Bao Hua

2018-04-01

This paper mainly studies the time optimization of feeder connection between rail transit and conventional bus in a shopping center. In order to achieve the goal of connecting rail transportation effectively and optimizing the convergence between the two transportations, the things had to be done are optimizing the departure intervals, shorting the passenger transfer time and improving the service level of public transit. Based on the goal that has the minimum of total waiting time of passengers and the number of start of classes, establish the optimizing model of bus connecting of departure time. This model has some constrains such as transfer time, load factor, and the convergence of public transportation grid spacing. It solves the problems by using genetic algorithms.

Investigation on multi-objective performance optimization algorithm application of fan based on response surface method and entropy method

Science.gov (United States)

Zhang, Li; Wu, Kexin; Liu, Yang

2017-12-01

A multi-objective performance optimization method is proposed, and the problem that single structural parameters of small fan balance the optimization between the static characteristics and the aerodynamic noise is solved. In this method, three structural parameters are selected as the optimization variables. Besides, the static pressure efficiency and the aerodynamic noise of the fan are regarded as the multi-objective performance. Furthermore, the response surface method and the entropy method are used to establish the optimization function between the optimization variables and the multi-objective performances. Finally, the optimized model is found when the optimization function reaches its maximum value. Experimental data shows that the optimized model not only enhances the static characteristics of the fan but also obviously reduces the noise. The results of the study will provide some reference for the optimization of multi-objective performance of other types of rotating machinery.

Technical and economic optimization study for HLW waste management

International Nuclear Information System (INIS)

Deffes, A.

1989-01-01

This study was conducted to assess the technical and economic aspects of high level waste (HLW) management with the objective of optimizing the interim storage duration and the dimensions of the underground repository site. The procedure consisted in optimizing the economic criterion under specified constraints. The results are intended to identify trends and guide the choice from among available options; simple and highly flexible models were therefore used in this study, and only nearfield thermal constraints were taken into consideration. Because of the present uncertainty on the physicochemical properties of the repository environment and on the unit cost figures, this study focused on developing a suitable method rather than on obtaining definitive results. With the physical and economic data bases used for the two media investigated (granite and salt) the optimum values found show that it is advisable to minimize the interim storage time, and that the geological repository should feature a high degree of spatial dilution. These results depend to a considerable extent on the assumption of high interim storage costs

A comparative study on stress and compliance based structural topology optimization

Science.gov (United States)

Hailu Shimels, G.; Dereje Engida, W.; Fakhruldin Mohd, H.

2017-10-01

Most of structural topology optimization problems have been formulated and solved to either minimize compliance or weight of a structure under volume or stress constraints, respectively. Even if, a lot of researches are conducted on these two formulation techniques separately, there is no clear comparative study between the two approaches. This paper intends to compare these formulation techniques, so that an end user or designer can choose the best one based on the problems they have. Benchmark problems under the same boundary and loading conditions are defined, solved and results are compared based on these formulations. Simulation results shows that the two formulation techniques are dependent on the type of loading and boundary conditions defined. Maximum stress induced in the design domain is higher when the design domains are formulated using compliance based formulations. Optimal layouts from compliance minimization formulation has complex layout than stress based ones which may lead the manufacturing of the optimal layouts to be challenging. Optimal layouts from compliance based formulations are dependent on the material to be distributed. On the other hand, optimal layouts from stress based formulation are dependent on the type of material used to define the design domain. High computational time for stress based topology optimization is still a challenge because of the definition of stress constraints at element level. Results also shows that adjustment of convergence criterions can be an alternative solution to minimize the maximum stress developed in optimal layouts. Therefore, a designer or end user should choose a method of formulation based on the design domain defined and boundary conditions considered.

Jointly Production and Correlated Maintenance Optimization for Parallel Leased Machines

Directory of Open Access Journals (Sweden)

Tarek ASKRI

2017-04-01

Full Text Available This paper deals with a preventive maintenance strategy optimization correlated to production for a manufacturing system made by several parallel machines under lease contract. In order to minimize the total cost of production and maintenance by reducing the production system interruptions due to maintenance activities, a correlated group preventive maintenance policy is developed using the gravity center approach (GCA. The aim of this study is to determine an economical production plan and an optimal group preventive maintenance interval Tn at which all machines are maintained simultaneously. An analytical correlation between failure rate of machines and production level is considered and the impact of the preventive maintenance policy on the production plan is studied. Finally, the proposed maintenance policy GPM is compared with an individual simple strategy approach IPM in order to illustrate its efficiency.

Defending against the Advanced Persistent Threat: An Optimal Control Approach

Directory of Open Access Journals (Sweden)

Pengdeng Li

2018-01-01

Full Text Available The new cyberattack pattern of advanced persistent threat (APT has posed a serious threat to modern society. This paper addresses the APT defense problem, that is, the problem of how to effectively defend against an APT campaign. Based on a novel APT attack-defense model, the effectiveness of an APT defense strategy is quantified. Thereby, the APT defense problem is modeled as an optimal control problem, in which an optimal control stands for a most effective APT defense strategy. The existence of an optimal control is proved, and an optimality system is derived. Consequently, an optimal control can be figured out by solving the optimality system. Some examples of the optimal control are given. Finally, the influence of some factors on the effectiveness of an optimal control is examined through computer experiments. These findings help organizations to work out policies of defending against APTs.

Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle

International Nuclear Information System (INIS)

Lei, Fei; Du, Bin; Liu, Xin; Xie, Xiaoping; Chai, Tian

2016-01-01

In this paper, implicit constrained multi-physics model of a motor wheel for an electric vehicle is built and then optimized. A novel optimization approach is proposed to solve the compliance problem between implicit constraints and stochastic global optimization. Firstly, multi-physics model of motor wheel is built from the theories of structural mechanics, electromagnetism and thermal physics. Then, implicit constraints are applied from the vehicle performances and magnetic characteristics. Implicit constrained optimization is carried out by a series of unconstrained optimization and verifications. In practice, sequentially updated subspaces are designed to completely substitute the original design space in local areas. In each subspace, a solution is obtained and is then verified by the implicit constraints. Optimal solutions which satisfy the implicit constraints are accepted as final candidates. The final global optimal solution is optimized from those candidates. Discussions are carried out to discover the differences between optimal solutions with unconstrained problem and different implicit constrained problems. Results show that the implicit constraints have significant influences on the optimal solution and the proposed approach is effective in finding the optimals. - Highlights: • An implicit constrained multi-physics model is built for sizing a motor wheel. • Vehicle dynamic performances are applied as implicit constraints for nonlinear system. • An efficient novel optimization is proposed to explore the constrained design space. • The motor wheel is optimized to achieve maximum efficiency on vehicle dynamics. • Influences of implicit constraints on vehicle performances are compared and analyzed.

Recent Progress on Data-Based Optimization for Mineral Processing Plants

Directory of Open Access Journals (Sweden)

Jinliang Ding

2017-04-01

Full Text Available In the globalized market environment, increasingly significant economic and environmental factors within complex industrial plants impose importance on the optimization of global production indices; such optimization includes improvements in production efficiency, product quality, and yield, along with reductions of energy and resource usage. This paper briefly overviews recent progress in data-driven hybrid intelligence optimization methods and technologies in improving the performance of global production indices in mineral processing. First, we provide the problem description. Next, we summarize recent progress in data-based optimization for mineral processing plants. This optimization consists of four layers: optimization of the target values for monthly global production indices, optimization of the target values for daily global production indices, optimization of the target values for operational indices, and automation systems for unit processes. We briefly overview recent progress in each of the different layers. Finally, we point out opportunities for future works in data-based optimization for mineral processing plants.

Thermal preference of juvenile Dover sole (Solea solea in relation to thermal acclimation and optimal growth temperature.

Directory of Open Access Journals (Sweden)

Edward Schram

Full Text Available Dover sole (Solea solea is an obligate ectotherm with a natural thermal habitat ranging from approximately 5 to 27°C. Thermal optima for growth lie in the range of 20 to 25°C. More precise information on thermal optima for growth is needed for cost-effective Dover sole aquaculture. The main objective of this study was to determine the optimal growth temperature of juvenile Dover sole (Solea solea and in addition to test the hypothesis that the final preferendum equals the optimal growth temperature. Temperature preference was measured in a circular preference chamber for Dover sole acclimated to 18, 22 and 28°C. Optimal growth temperature was measured by rearing Dover sole at 19, 22, 25 and 28°C. The optimal growth temperature resulting from this growth experiment was 22.7°C for Dover sole with a size between 30 to 50 g. The temperature preferred by juvenile Dover sole increases with acclimation temperature and exceeds the optimal temperature for growth. A final preferendum could not be detected. Although a confounding effect of behavioural fever on temperature preference could not be entirely excluded, thermal preference and thermal optima for physiological processes seem to be unrelated in Dover sole.

Optimal interference code based on machine learning

Science.gov (United States)

Qian, Ye; Chen, Qian; Hu, Xiaobo; Cao, Ercong; Qian, Weixian; Gu, Guohua

2016-10-01

In this paper, we analyze the characteristics of pseudo-random code, by the case of m sequence. Depending on the description of coding theory, we introduce the jamming methods. We simulate the interference effect or probability model by the means of MATLAB to consolidate. In accordance with the length of decoding time the adversary spends, we find out the optimal formula and optimal coefficients based on machine learning, then we get the new optimal interference code. First, when it comes to the phase of recognition, this study judges the effect of interference by the way of simulating the length of time over the decoding period of laser seeker. Then, we use laser active deception jamming simulate interference process in the tracking phase in the next block. In this study we choose the method of laser active deception jamming. In order to improve the performance of the interference, this paper simulates the model by MATLAB software. We find out the least number of pulse intervals which must be received, then we can make the conclusion that the precise interval number of the laser pointer for m sequence encoding. In order to find the shortest space, we make the choice of the greatest common divisor method. Then, combining with the coding regularity that has been found before, we restore pulse interval of pseudo-random code, which has been already received. Finally, we can control the time period of laser interference, get the optimal interference code, and also increase the probability of interference as well.

Multi-objective Reactive Power Optimization Based on Improved Particle Swarm Algorithm

Science.gov (United States)

Cui, Xue; Gao, Jian; Feng, Yunbin; Zou, Chenlu; Liu, Huanlei

2018-01-01

In this paper, an optimization model with the minimum active power loss and minimum voltage deviation of node and maximum static voltage stability margin as the optimization objective is proposed for the reactive power optimization problems. By defining the index value of reactive power compensation, the optimal reactive power compensation node was selected. The particle swarm optimization algorithm was improved, and the selection pool of global optimal and the global optimal of probability (p-gbest) were introduced. A set of Pareto optimal solution sets is obtained by this algorithm. And by calculating the fuzzy membership value of the pareto optimal solution sets, individuals with the smallest fuzzy membership value were selected as the final optimization results. The above improved algorithm is used to optimize the reactive power of IEEE14 standard node system. Through the comparison and analysis of the results, it has been proven that the optimization effect of this algorithm was very good.

Dispositional Optimism

Science.gov (United States)

Carver, Charles S.; Scheier, Michael F.

2014-01-01

Optimism is a cognitive construct (expectancies regarding future outcomes) that also relates to motivation: optimistic people exert effort, whereas pessimistic people disengage from effort. Study of optimism began largely in health contexts, finding positive associations between optimism and markers of better psychological and physical health. Physical health effects likely occur through differences in both health-promoting behaviors and physiological concomitants of coping. Recently, the scientific study of optimism has extended to the realm of social relations: new evidence indicates that optimists have better social connections, partly because they work harder at them. In this review, we examine the myriad ways this trait can benefit an individual, and our current understanding of the biological basis of optimism. PMID:24630971

Optimal Compensation with Hidden Action and Lump-Sum Payment in a Continuous-Time Model

International Nuclear Information System (INIS)

Cvitanic, Jaksa; Wan, Xuhu; Zhang Jianfeng

2009-01-01

We consider a problem of finding optimal contracts in continuous time, when the agent's actions are unobservable by the principal, who pays the agent with a one-time payoff at the end of the contract. We fully solve the case of quadratic cost and separable utility, for general utility functions. The optimal contract is, in general, a nonlinear function of the final outcome only, while in the previously solved cases, for exponential and linear utility functions, the optimal contract is linear in the final output value. In a specific example we compute, the first-best principal's utility is infinite, while it becomes finite with hidden action, which is increasing in value of the output. In the second part of the paper we formulate a general mathematical theory for the problem. We apply the stochastic maximum principle to give necessary conditions for optimal contracts. Sufficient conditions are hard to establish, but we suggest a way to check sufficiency using non-convex optimization

Patient Dose Optimization in Fluoroscopically Guided Interventional Procedures. Final Report of a Coordinated Research Project

International Nuclear Information System (INIS)

2010-01-01

In recent years, many surgical procedures have increasingly been replaced by interventional procedures that guide catheters into the arteries under X ray fluoroscopic guidance to perform a variety of operations such as ballooning, embolization, implantation of stents etc. The radiation exposure to patients and staff in such procedures is much higher than in simple radiographic examinations like X ray of chest or abdomen such that radiation induced skin injuries to patients and eye lens opacities among workers have been reported in the 1990's and after. Interventional procedures have grown both in frequency and importance during the last decade. This Coordinated Research Project (CRP) and TECDOC were developed within the International Atomic Energy Agency's (IAEA) framework of statutory responsibility to provide for the worldwide application of the standards for the protection of people against exposure to ionizing radiation. The CRP took place between 2003 and 2005 in six countries, with a view of optimizing the radiation protection of patients undergoing interventional procedures. The Fundamental Safety Principles and the International Basic Safety Standards for Protection against Ionizing Radiation (BSS) issued by the IAEA and co-sponsored by the Food and Agriculture Organization of the United Nations (FAO), the International Labour Organization (ILO), the World Health Organization (WHO), the Pan American Health Organization (PAHO) and the Nuclear Energy Agency (NEA), among others, require the radiation protection of patients undergoing medical exposures through justification of the procedures involved and through optimization. In keeping with its responsibility on the application of standards, the IAEA programme on Radiological Protection of Patients encourages the reduction of patient doses. To facilitate this, it has issued specific advice on the application of the BSS in the field of radiology in Safety Reports Series No. 39 and the three volumes on Radiation

Solving Bilevel Multiobjective Programming Problem by Elite Quantum Behaved Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Tao Zhang

2012-01-01

Full Text Available An elite quantum behaved particle swarm optimization (EQPSO algorithm is proposed, in which an elite strategy is exerted for the global best particle to prevent premature convergence of the swarm. The EQPSO algorithm is employed for solving bilevel multiobjective programming problem (BLMPP in this study, which has never been reported in other literatures. Finally, we use eight different test problems to measure and evaluate the proposed algorithm, including low dimension and high dimension BLMPPs, as well as attempt to solve the BLMPPs whose theoretical Pareto optimal front is not known. The experimental results show that the proposed algorithm is a feasible and efficient method for solving BLMPPs.

Optimization-based topology identification of complex networks

International Nuclear Information System (INIS)

Tang Sheng-Xue; Chen Li; He Yi-Gang

2011-01-01

In many cases, the topological structures of a complex network are unknown or uncertain, and it is of significance to identify the exact topological structure. An optimization-based method of identifying the topological structure of a complex network is proposed in this paper. Identification of the exact network topological structure is converted into a minimal optimization problem by using the estimated network. Then, an improved quantum-behaved particle swarm optimization algorithm is used to solve the optimization problem. Compared with the previous adaptive synchronization-based method, the proposed method is simple and effective and is particularly valid to identify the topological structure of synchronization complex networks. In some cases where the states of a complex network are only partially observable, the exact topological structure of a network can also be identified by using the proposed method. Finally, numerical simulations are provided to show the effectiveness of the proposed method. (general)

Optimization Research of Generation Investment Based on Linear Programming Model

Science.gov (United States)

Wu, Juan; Ge, Xueqian

Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

PID controller tuning using metaheuristic optimization algorithms for benchmark problems

Science.gov (United States)

Gholap, Vishal; Naik Dessai, Chaitali; Bagyaveereswaran, V.

2017-11-01

This paper contributes to find the optimal PID controller parameters using particle swarm optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm. The algorithms were developed through simulation of chemical process and electrical system and the PID controller is tuned. Here, two different fitness functions such as Integral Time Absolute Error and Time domain Specifications were chosen and applied on PSO, GA and SA while tuning the controller. The proposed Algorithms are implemented on two benchmark problems of coupled tank system and DC motor. Finally, comparative study has been done with different algorithms based on best cost, number of iterations and different objective functions. The closed loop process response for each set of tuned parameters is plotted for each system with each fitness function.

Design thinking for website optimization. A case study

DEFF Research Database (Denmark)

Somoza Sanchez, Vella Veronica; Andersen, Frederik; Schneider-Kamp, Peter

This paper presents results from a pilot study, which is part of a larger research project where we study the process innovation of website optimization as a service through the use of big data. Over a process of design thinking we investigate which type of website design best addresses the needs...... for observing the users in their native environment. Furthermore, we use the method of Digital Anthropology to complete the loop between the human-centric designs and the possibilities offered by the analysis of big data....

Topology optimization and lattice Boltzmann methods

DEFF Research Database (Denmark)

Nørgaard, Sebastian Arlund

This thesis demonstrates the application of the lattice Boltzmann method for topology optimization problems. Specifically, the focus is on problems in which time-dependent flow dynamics have significant impact on the performance of the devices to be optimized. The thesis introduces new topology...... a discrete adjoint approach. To handle the complexity of the discrete adjoint approach more easily, a method for computing it based on automatic differentiation is introduced, which can be adapted to any lattice Boltzmann type method. For example, while it is derived in the context of an isothermal lattice...... Boltzmann model, it is shown that the method can be easily extended to a thermal model as well. Finally, the predicted behavior of an optimized design is compared to the equiva-lent prediction from a commercial finite element solver. It is found that the weakly compressible nature of the lattice Boltzmann...

An optimization approach for black-and-white and hinge-removal topology designs

Energy Technology Data Exchange (ETDEWEB)

Fu, Yongqing; Zhang, Xianmin [South China University of Technology, Guangzhou (China)

2014-02-15

An optimization approach for black-and-white and hinge-removal topology designs is studied. To achieve this motive, an optimal topology allowing grey boundaries is found firstly. When a suitable design has been obtained, this solution is then used as a starting point for the follow-up optimization with the goal to free unfavorable intermediate elements. For this purpose, an updated optimality criterion in which a threshold factor is introduced to gradually suppress elements with low density is proposed. The typical optimality method and new technique proposed are applied to the design procedure sequentially. Besides, to circumvent the one-point hinge connection problem producing in the process of freeing intermediate elements, a hinge-removal strategy is also proposed. During the optimization, the binary constraints on design variables are relaxed based on the scheme of solid isotropic material with penalization. Meanwhile, the mesh independency filter is employed to ensure the existence of a solution and remove well-known checkerboards. In this way, a solution that has few intermediate elements and is free of one-point hinge connections is obtained. Finally, different numerical examples including the compliance minimization, compliant mechanisms and vibration problems demonstrate the validity of the proposed approach.

Optimal experiment design in a filtering context with application to sampled network data

OpenAIRE

Singhal, Harsh; Michailidis, George

2010-01-01

We examine the problem of optimal design in the context of filtering multiple random walks. Specifically, we define the steady state E-optimal design criterion and show that the underlying optimization problem leads to a second order cone program. The developed methodology is applied to tracking network flow volumes using sampled data, where the design variable corresponds to controlling the sampling rate. The optimal design is numerically compared to a myopic and a naive strategy. Finally, w...

Multi-objective optimization of Stirling engine systems using Front-based Yin-Yang-Pair Optimization

International Nuclear Information System (INIS)

Punnathanam, Varun; Kotecha, Prakash

2017-01-01

Highlights: • Efficient multi-objective optimization algorithm F-YYPO demonstrated. • Three Stirling engine applications with a total of eight cases. • Improvements in the objective function values of up to 30%. • Superior to the popularly used gamultiobj of MATLAB. • F-YYPO has extremely low time complexity. - Abstract: In this work, we demonstrate the performance of Front-based Yin-Yang-Pair Optimization (F-YYPO) to solve multi-objective problems related to Stirling engine systems. The performance of F-YYPO is compared with that of (i) a recently proposed multi-objective optimization algorithm (Multi-Objective Grey Wolf Optimizer) and (ii) an algorithm popularly employed in literature due to its easy accessibility (MATLAB’s inbuilt multi-objective Genetic Algorithm function: gamultiobj). We consider three Stirling engine based optimization problems: (i) the solar-dish Stirling engine system which considers objectives of output power, thermal efficiency and rate of entropy generation; (ii) Stirling engine thermal model which considers the associated irreversibility of the cycle with objectives of output power, thermal efficiency and pressure drop; and finally (iii) an experimentally validated polytropic finite speed thermodynamics based Stirling engine model also with objectives of output power and pressure drop. We observe F-YYPO to be significantly more effective as compared to its competitors in solving the problems, while requiring only a fraction of the computational time required by the other algorithms.

Optimization of a furniture factory layout

Directory of Open Access Journals (Sweden)

Tadej Kanduč

2015-03-01

Full Text Available This paper deals with the problem of optimizing a factory floor layout in a Slovenian furniture factory. First, the current state of the manufacturing system is analyzed by constructing a discrete event simulation (DES model that reflects the manufacturing processes. The company produces over 10,000 different products, and their manufacturing processes include approximately 30,000 subprocesses. Therefore, manually constructing a model to include every subprocess is not feasible. To overcome this problem, a method for automated model construction was developed to construct a DES model based on a selection of manufacturing orders and relevant subprocesses. The obtained simulation model provided insight into the manufacturing processes and enable easy modification of model parameters for optimizing the manufacturing processes. Finally, the optimization problem was solved: the total distance the products had to traverse between machines was minimized by devising an optimal machine layout. With the introduction of certain simplifications, the problem was best described as a quadratic assignment problem. A novel heuristic method based on force-directed graph drawing algorithms was developed. Optimizing the floor layout resulted in a significant reduction of total travel distance for the products.

Optimal Scheduling of Residential Microgrids Considering Virtual Energy Storage System

Directory of Open Access Journals (Sweden)

Weiliang Liu

2018-04-01

Full Text Available The increasingly complex residential microgrids (r-microgrid consisting of renewable generation, energy storage systems, and residential buildings require a more intelligent scheduling method. Firstly, aiming at the radiant floor heating/cooling system widely utilized in residential buildings, the mathematical relationship between the operative temperature and heating/cooling demand is established based on the equivalent thermodynamic parameters (ETP model, by which the thermal storage capacity is analyzed. Secondly, the radiant floor heating/cooling system is treated as virtual energy storage system (VESS, and an optimization model based on mixed-integer nonlinear programming (MINLP for r-microgrid scheduling is established which takes thermal comfort level and economy as the optimization objectives. Finally, the optimal scheduling results of two typical r-microgrids are analyzed. Case studies demonstrate that the proposed scheduling method can effectively employ the thermal storage capacity of radiant floor heating/cooling system, thus lowering the operating cost of the r-microgrid effectively while ensuring the thermal comfort level of users.

A Shape Optimization Study for Tool Design in Resistance Welding

DEFF Research Database (Denmark)

Bogomolny, Michael; Bendsøe, Martin P.; Hattel, Jesper Henri

2009-01-01

The purpose of this study is to apply shape optimization tools for design of resistance welding electrodes. The numerical simulation of the welding process has been performed by a simplified FEM model implemented in COMSOL. The design process is formulated as an optimization problem where...... the objective is to prolong the life-time of the electrodes. Welding parameters like current, time and electrode shape parameters are selected to be the design variables while constraints are chosen to ensure a high quality of the welding. Surrogate models based on a Kriging approximation has been used in order...

Optimism in prolonged grief and depression following loss : A three-wave longitudinal study

NARCIS (Netherlands)

Boelen, Paul A

2015-01-01

There is considerable evidence that optimism, the predisposition to have generalized favorable expectancies for the future, is associated with numerous desirable outcomes. Few studies have examined the association of optimism with emotional distress following the death of a loved one. Doing so is

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

Science.gov (United States)

Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

Simulation Modeling to Compare High-Throughput, Low-Iteration Optimization Strategies for Metabolic Engineering.

Science.gov (United States)

Heinsch, Stephen C; Das, Siba R; Smanski, Michael J

2018-01-01

Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems.

A characteristic study of CCF modeling techniques and optimization of CCF defense strategies

International Nuclear Information System (INIS)

Kim, Min Chull

2000-02-01

Common Cause Failures (CCFs ) are among the major contributors to risk and core damage frequency (CDF ) from operating nuclear power plants (NPPs ). Our study on CCF focused on the following aspects : 1) a characteristic study on the CCF modeling techniques and 2) development of the optimal CCF defense strategy. Firstly, the characteristics of CCF modeling techniques were studied through sensitivity study of CCF occurrence probability upon system redundancy. The modeling techniques considered in this study include those most widely used worldwide, i.e., beta factor, MGL, alpha factor, and binomial failure rate models. We found that MGL and alpha factor models are essentially identical in terms of the CCF probability. Secondly, in the study for CCF defense, the various methods identified in the previous studies for defending against CCF were classified into five different categories. Based on these categories, we developed a generic method by which the optimal CCF defense strategy can be selected. The method is not only qualitative but also quantitative in nature: the selection of the optimal strategy among candidates is based on the use of analytic hierarchical process (AHP). We applied this method to two motor-driven valves for containment sump isolation in Ulchin 3 and 4 nuclear power plants. The result indicates that the method for developing an optimal CCF defense strategy is effective

Optimal Deterministic Investment Strategies for Insurers

Directory of Open Access Journals (Sweden)

Ulrich Rieder

2013-11-01

Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.

Dynamic optimization of the complex adaptive controlling by the structure of enterprise’s product range

Directory of Open Access Journals (Sweden)

Andrey Fyodorovich Shorikov

2013-06-01

Full Text Available This paper reviews a methodical approach to solve multi-step dynamic problem of optimal integrated adaptive management of a product portfolio structure of the enterprise. For the organization of optimal adaptive terminal control of the system the recurrent algorithm, which reduces an initial multistage problem to the realization of the final sequence of problems of optimal program terminal control is offered. In turn, the decision of each problem of optimal program terminal control is reduced to the realization of the final sequence only single-step operations in the form of the problems solving of linear and convex mathematical programming. Thus, the offered approach allows to develop management solutions at current information support, which consider feedback, and which create the optimal structure of an enterprise’s product lines, contributing to optimising of profits, as well as maintenance of the desired level of profit for a long period of time

Systems study 'Alternative Entsorgung'. Final report. Technical annex 6

International Nuclear Information System (INIS)

1984-08-01

In the conditioning plant, fuel elements which have been stored for ten years are loaded into transport containers, unloaded, identified and welded into a dry storage box. The dry store barrel is introduced into a final storage container, which, after being closed, is packed in lost shielding. This so-called final storage barrel is finally placed in a transport container and leaves the conditioning plant in this form by rail for transport to the final storage mine. The fuel element method of treatment 'packing of three complete fuel elements' was used as the reference process. In addition, the method of treatment 'fuel elements dismantled into fuel rods' was also examined. The handling of fuel elements and secondary waste treatment in the reference process are described in detail. (orig./HP) [de

Quantum optimal control theory and dynamic coupling in the spin-boson model

International Nuclear Information System (INIS)

Jirari, H.; Poetz, W.

2006-01-01

A Markovian master equation describing the evolution of open quantum systems in the presence of a time-dependent external field is derived within the Bloch-Redfield formalism. It leads to a system-bath interaction which depends on the control field. Optimal control theory is used to select control fields which allow accelerated or decelerated system relaxation, or suppression of relaxation (dissipation) altogether, depending on the dynamics we impose on the quantum system. The control-dissipation correlation and the nonperturbative treatment of the control field are essential for reaching this goal. The optimal control problem is formulated within Pontryagin's minimum principle and the resulting optimal differential system is solved numerically. As an application, we study the dynamics of a spin-boson model in the strong coupling regime under the influence of an external control field. We show how trapping the system in unstable quantum states and transfer of population can be achieved by optimized control of the dissipative quantum system. We also used optimal control theory to find the driving field that generates the quantum Z gate. In several cases studied, we find that the selected optimal field which reduces the purity loss significantly is a multicomponent low-frequency field including higher harmonics, all of which lie below the phonon cutoff frequency. Finally, in the undriven case we present an analytic result for the Lamb shift at zero temperature

The FERMI (at) Elettra Technical Optimization Study: Preliminary Parameter Set and Initial Studies

International Nuclear Information System (INIS)

Byrd, John; Corlett, John; Doolittle, Larry; Fawley, William; Lidia, Steven; Penn, Gregory; Ratti, Alex; Staples, John; Wilcox, Russell; Wurtele, Jonathan; Zholents, Alexander

2005-01-01

The goal of the FERMI (at) Elettra Technical Optimization Study is to produce a machine design and layout consistent with user needs for radiation in the approximate ranges 100 nm to 40 nm, and 40 nm to 10 nm, using seeded FEL's. The Study will involve collaboration between Italian and US physicists and engineers, and will form the basis for the engineering design and the cost estimation

Optimal control approaches for aircraft conflict avoidance using speed regulation : a numerical study

OpenAIRE

Cellier , Loïc; Cafieri , Sonia; Messine , Frederic

2013-01-01

International audience; In this paper a numerical study is provided to solve the aircraft conflict avoidance problem through velocity regulation maneuvers. Starting from optimal controlbased model and approaches in which aircraft accelerations are the controls, and by applying the direct shooting technique, we propose to study two different largescale nonlinear optimization problems. In order to compare different possibilities of implementation, two environments (AMPL and MATLAB) and determin...

Additional EIPC Study Analysis. Final Report

Energy Technology Data Exchange (ETDEWEB)

Hadley, Stanton W [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gotham, Douglas J. [Purdue Univ., West Lafayette, IN (United States); Luciani, Ralph L. [Navigant Consultant Inc., Suwanee, GA (United States)

2014-12-01

Between 2010 and 2012 the Eastern Interconnection Planning Collaborative (EIPC) conducted a major long-term resource and transmission study of the Eastern Interconnection (EI). With guidance from a Stakeholder Steering Committee (SSC) that included representatives from the Eastern Interconnection States Planning Council (EISPC) among others, the project was conducted in two phases. Phase 1 involved a long-term capacity expansion analysis that involved creation of eight major futures plus 72 sensitivities. Three scenarios were selected for more extensive transmission- focused evaluation in Phase 2. Five power flow analyses, nine production cost model runs (including six sensitivities), and three capital cost estimations were developed during this second phase. The results from Phase 1 and 2 provided a wealth of data that could be examined further to address energy-related questions. A list of 14 topics was developed for further analysis. This paper brings together the earlier interim reports of the first 13 topics plus one additional topic into a single final report.

Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.

Science.gov (United States)

Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P

2013-04-09

Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.

On simultaneous shape and orientational design for eigenfrequency optimization

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2007-01-01

Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design of an or......Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design...... of an orthotropic material that can be considered as a fiber-net within each finite element. This fiber-net is optimally oriented in the individual elements of the finite element discretization. The optimizations are performed using the finite element method for analysis, and the optimization approach is a two......-step method. In the first step, we find the best design on the basis of a recursive optimization procedure based on optimality criteria. In the second step, mathematical programming and sensitivity analysis are applied to find the final optimized design....

An Optimized Forecasting Approach Based on Grey Theory and Cuckoo Search Algorithm: A Case Study for Electricity Consumption in New South Wales

Directory of Open Access Journals (Sweden)

Ping Jiang

2014-01-01

Full Text Available With rapid economic growth, electricity demand is clearly increasing. It is difficult to store electricity for future use; thus, the electricity demand forecast, especially the electricity consumption forecast, is crucial for planning and operating a power system. Due to various unstable factors, it is challenging to forecast electricity consumption. Therefore, it is necessary to establish new models for accurate forecasts. This study proposes a hybrid model, which includes data selection, an abnormality analysis, a feasibility test, and an optimized grey model to forecast electricity consumption. First, the original electricity consumption data are selected to construct different schemes (Scheme 1: short-term selection and Scheme 2: long-term selection; next, the iterative algorithm (IA and cuckoo search algorithm (CS are employed to select the best parameter of GM(1,1. The forecasted day is then divided into several smooth parts because the grey model is highly accurate in the smooth rise and drop phases; thus, the best scheme for each part is determined using the grey correlation coefficient. Finally, the experimental results indicate that the GM(1,1 optimized using CS has the highest forecasting accuracy compared with the GM(1,1 and the GM(1,1 optimized using the IA and the autoregressive integrated moving average (ARIMA model.

Effect of different seed treatments on maize seed germination parameters under optimal and suboptimal temperature conditions

Directory of Open Access Journals (Sweden)

Vujošević Bojana

2017-01-01

Full Text Available The aim of this study was to determine the effect of different seed treatments on germination parameters of three maize genotypes under optimal and suboptimal temperature conditions. Seed was treated with recommended doses of three commercial pesticide formulations: metalaxyl-m 10 g/L + fludioxonil 25 g/L, metalaxyl 20 g/kg + prothioconazole 100 g/kg and thiacloprid 400 g/L. Testing was conducted at 25°C and 15°C. Results of the study indicate that there are differences in response of maize genotypes to applied seed treatments, as well as to a specific treatment at optimal and suboptimal temperatures. Some treatments, depending on the mixing partner and temperature conditions, can affect final germination. In other cases, germination rate can be accelerated or prolonged, but with no effect on final germination. In order to provide fast and uniform emergence under different temperature conditions, further examination of the response of maize genotypes to specific seed treatments would be beneficial.

Simulation-based optimization for product and process design

NARCIS (Netherlands)

Driessen, L.

2006-01-01

The design of products and processes has gradually shifted from a purely physical process towards a process that heavily relies on computer simulations (virtual prototyping). To optimize this virtual design process in terms of speed and final product quality, statistical methods and mathematical

A Study on Development of a Cost Optimal and Energy Saving Building Model: Focused on Industrial Building

Directory of Open Access Journals (Sweden)

Hye Yeon Kim

2016-03-01

Full Text Available This study suggests an optimization method for the life cycle cost (LCC in an economic feasibility analysis when applying energy saving techniques in the early design stage of a building. Literature and previous studies were reviewed to select appropriate optimization and LCC analysis techniques. The energy simulation (Energy Plus and computational program (MATLAB were linked to provide an automated optimization process. From the results, it is suggested that this process could outline the cost optimization model with which it is possible to minimize the LCC. To aid in understanding the model, a case study on an industrial building was performed to outline the operations of the cost optimization model including energy savings. An energy optimization model was also presented to illustrate the need for the cost optimization model.

Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm

International Nuclear Information System (INIS)

Duan, Chen; Wang, Xinggang; Shu, Shuiming; Jing, Changwei; Chang, Huawei

2014-01-01

Highlights: • An improved thermodynamic model taking into account irreversibility parameter was developed. • A multi-objective optimization method for designing Stirling engine was investigated. • Multi-objective particle swarm optimization algorithm was adopted in the area of Stirling engine for the first time. - Abstract: In the recent years, the interest in Stirling engine has remarkably increased due to its ability to use any heat source from outside including solar energy, fossil fuels and biomass. A large number of studies have been done on Stirling cycle analysis. In the present study, a mathematical model based on thermodynamic analysis of Stirling engine considering regenerative losses and internal irreversibilities has been developed. Power output, thermal efficiency and the cycle irreversibility parameter of Stirling engine are optimized simultaneously using Particle Swarm Optimization (PSO) algorithm, which is more effective than traditional genetic algorithms. In this optimization problem, some important parameters of Stirling engine are considered as decision variables, such as temperatures of the working fluid both in the high temperature isothermal process and in the low temperature isothermal process, dead volume ratios of each heat exchanger, volumes of each working spaces, effectiveness of the regenerator, and the system charge pressure. The Pareto optimal frontier is obtained and the final design solution has been selected by Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP). Results show that the proposed multi-objective optimization approach can significantly outperform traditional single objective approaches

An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics

Science.gov (United States)

Baluja, Shumeet

1995-01-01

This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.

Rules of Normalisation and their Importance for Interpretation of Systems of Optimal Taxation

DEFF Research Database (Denmark)

Munk, Knud Jørgen

representation of the general equilibrium conditions the rules of normalisation in standard optimal tax models. This allows us to provide an intuitive explanation of what determines the optimal tax system. Finally, we review a number of examples where lack of precision with respect to normalisation in otherwise...... important contributions to the literature on optimal taxation has given rise to misinterpretations of of analytical results....

Performance optimization in electro- discharge machining using a suitable multiresponse optimization technique

Directory of Open Access Journals (Sweden)

I. Nayak

2017-06-01

Full Text Available In the present research work, four different multi response optimization techniques, viz. multiple response signal-to-noise (MRSN ratio, weighted signal-to-noise (WSN ratio, Grey relational analysis (GRA and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian methods have been used to optimize the electro-discharge machining (EDM performance characteristics such as material removal rate (MRR, tool wear rate (TWR and surface roughness (SR simultaneously. Experiments have been planned on a D2 steel specimen based on L9 orthogonal array. Experimental results are analyzed using the standard procedure. The optimum level combinations of input process parameters such as voltage, current, pulse-on-time and pulse-off-time, and percentage contributions of each process parameter using ANOVA technique have been determined. Different correlations have been developed between the various input process parameters and output performance characteristics. Finally, the optimum performances of these four methods are compared and the results show that WSN ratio method is the best multiresponse optimization technique for this process. From the analysis, it is also found that the current has the maximum effect on the overall performance of EDM operation as compared to other process parameters.

Optimization for routing vehicles of seafood product transportation

Science.gov (United States)

Soenandi, I. A.; Juan, Y.; Budi, M.

2017-12-01

Recently, increasing usage of marine products is creating new challenges for businesses of marine products in terms of transportation that used to carry the marine products like seafood to the main warehouse. This can be a problem if the carrier fleet is limited, and there are time constraints in terms of the freshness of the marine product. There are many ways to solve this problem, including the optimization of routing vehicles. In this study, this strategy is to implement in the marine product business in Indonesia with such an expected arrangement of the company to optimize routing problem in transportation with time and capacity windows. Until now, the company has not used the scientific method to manage the routing of their vehicle from warehouse to the location of marine products source. This study will solve a stochastic Vehicle Routing Problems (VRP) with time and capacity windows by using the comparison of six methods and looking the best results for the optimization, in this situation the company could choose the best method, in accordance with the existing condition. In this research, we compared the optimization with another method such as branch and bound, dynamic programming and Ant Colony Optimization (ACO). Finally, we get the best result after running ACO algorithm with existing travel time data. With ACO algorithm was able to reduce vehicle travel time by 3189.65 minutes, which is about 23% less than existing and based on consideration of the constraints of time within 2 days (including rest time for the driver) using 28 tons capacity of truck and the companies need two units of vehicles for transportation.

Adaptively optimizing stochastic resonance in visual system

Science.gov (United States)

Yang, Tao

1998-08-01

Recent psychophysics experiment has showed that the noise strength could affect the perceived image quality. This work gives an adaptive process for achieving the optimal perceived image quality in a simple image perception array, which is a simple model of an image sensor. A reference image from memory is used for constructing a cost function and defining the optimal noise strength where the cost function gets its minimum point. The reference image is a binary image, which is used to define the background and the object. Finally, an adaptive algorithm is proposed for searching the optimal noise strength. Computer experimental results show that if the reference image is a thresholded version of the sub-threshold input image then the output of the sensor array gives an optimal output, in which the background and the object have the biggest contrast. If the reference image is different from a thresholded version of the sub-threshold input image then the output usually gives a sub-optimal contrast between the object and the background.

Oyster Creek cycle 10 nodal model parameter optimization study using PSMS

International Nuclear Information System (INIS)

Dougher, J.D.

1987-01-01

The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed

Experimental design: Case studies of diagnostics optimization for W7-X

International Nuclear Information System (INIS)

Dreier, H.; Dinklage, A.; Fischer, R.; Hartfuss, H.-J.; Hirsch, M.; Kornejew, P.; Pasch, E.; Turkin, Yu.

2005-01-01

The preparation of diagnostics for Wendelstein 7-X is accompanied by diagnostics simulations and optimization. Starting from the physical objectives, the design of diagnostics should incorporate predictive modelling (e.g. transport modelling) and simulations of respective measurements. Although technical constraints are governing design considerations, it appears that several design parameters of different diagnostics can be optimized. However, a general formulation for fusion diagnostics design in terms of optimization is lacking. In this paper, first case studies of Bayesian experimental design aiming at applications on W7-X diagnostics preparation are presented. The information gain of a measurement is formulated as a utility function which is expressed in terms of the Kullback-Leibler divergence. Then, the expected range of data is to be included and the resulting expected utility represents the objective for optimization. Bayesian probability theory gives a framework allowing us for an appropriate formulation of the design problem in terms of probability distribution functions. Results are obtained for the information gain from interferometry and for the design of polychromators for Thomson scattering. For interferometry, studies of the choice of line-of-sights for optimum signal and for the reproduction of gradient positions are presented for circular, elliptical and W7-X geometries. For Thomson scattering, the design of filter transmissions for density and temperature measurements are discussed. (author)

Experimental Study On The Optimization Of Extraction Process Of ...

African Journals Online (AJOL)

The objective is to study the extraction process of garlic oil and its antibacterial effects. Materials and Methods: CO2 Supercritical extraction was used to investigate the optimal processing conditions for garlic oil extraction; filter paper test and suspension dilution test were applied to determine the bacteriostatic action of ...

Enablers and barriers for women with gestational diabetes mellitus to achieve optimal glycaemic control - a qualitative study using the theoretical domains framework.

Science.gov (United States)

Martis, Ruth; Brown, Julie; McAra-Couper, Judith; Crowther, Caroline A

2018-04-11

Glycaemic target recommendations vary widely between international professional organisations for women with gestational diabetes mellitus (GDM). Some studies have reported women's experiences of having GDM, but little is known how this relates to their glycaemic targets. The aim of this study was to identify enablers and barriers for women with GDM to achieve optimal glycaemic control. Women with GDM were recruited from two large, geographically different, hospitals in New Zealand to participate in a semi-structured interview to explore their views and experiences focusing on enablers and barriers to achieving optimal glycaemic control. Final thematic analysis was performed using the Theoretical Domains Framework. Sixty women participated in the study. Women reported a shift from their initial negative response to accepting their diagnosis but disliked the constant focus on numbers. Enablers and barriers were categorised into ten domains across the three study questions. Enablers included: the ability to attend group teaching sessions with family and hear from women who have had GDM; easy access to a diabetes dietitian with diet recommendations tailored to a woman's context including ethnic food and financial considerations; free capillary blood glucose (CBG) monitoring equipment, health shuttles to take women to appointments; child care when attending clinic appointments; and being taught CBG testing by a community pharmacist. Barriers included: lack of health information, teaching sessions, consultations, and food diaries in a woman's first language; long waiting times at clinic appointments; seeing a different health professional every clinic visit; inconsistent advice; no tailored physical activities assessments; not knowing where to access appropriate information on the internet; unsupportive partners, families, and workplaces; and unavailability of social media or support groups for women with GDM. Perceived judgement by others led some women only to share

A discrete optimization method for nuclear fuel management

International Nuclear Information System (INIS)

Argaud, J.P.

1993-01-01

Nuclear fuel management can be seen as a large discrete optimization problem under constraints, and optimization methods on such problems are numerically costly. After an introduction of the main aspects of nuclear fuel management, this paper presents a new way to treat the combinatorial problem by using information included in the gradient of optimized cost function. A new search process idea is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method. Finally, connections with classical simulated annealing and genetic algorithms are described as an attempt to improve search processes. 16 refs., 2 figs

Ecological optimization and parametric study of irreversible Stirling and Ericsson heat pumps

International Nuclear Information System (INIS)

Tyagi, S.K.; Kaushik, S.C.; Salohtra, R.

2002-01-01

This communication presents the ecological optimization and parametric study of irreversible Stirling and Ericsson heat pump cycles, in which the external irreversibility is due to finite temperature difference between working fluid and external reservoirs while the internal irreversibilities are due to regenerative heat loss and other entropy generations within the cycle. The ecological function is defined as the heating load minus the irreversibility (power loss) which is ambient temperature times the entropy generation. The ecological function is optimized with respect to working fluid temperatures, and the expressions for various parameters at the optimal operating condition are obtained. The effects of different operating parameters on the performance of these cycles have been studied. It is found that the effect of internal irreversibility parameter is more pronounced than the other parameters on the performance of these cycles. (author)

Application of Strain Energy on BIW Mode Optimization

Directory of Open Access Journals (Sweden)

Chang Guangbao

2015-01-01

Full Text Available This paper takes the BIW model as the research object, completes modal analysis, and verifies the finite element model by comparing the simulation results with the test results. In order to improve the frequency of BIW, the weak structure of D pillar is found and then optimized by the method of strain energy, and the frequency of BIW is changed from 28.80Hz to 32.15Hz. Finally, the method of strain energy has great positive effects on modal optimization.

Optimization and anti-optimization of structures under uncertainty

National Research Council Canada - National Science Library

Elishakoff, Isaac; Ohsaki, Makoto

2010-01-01

The volume presents a collaboration between internationally recognized experts on anti-optimization and structural optimization, and summarizes various novel ideas, methodologies and results studied over 20 years...

Combinatorial Clustering Algorithm of Quantum-Behaved Particle Swarm Optimization and Cloud Model

Directory of Open Access Journals (Sweden)

Mi-Yuan Shan

2013-01-01

Full Text Available We propose a combinatorial clustering algorithm of cloud model and quantum-behaved particle swarm optimization (COCQPSO to solve the stochastic problem. The algorithm employs a novel probability model as well as a permutation-based local search method. We are setting the parameters of COCQPSO based on the design of experiment. In the comprehensive computational study, we scrutinize the performance of COCQPSO on a set of widely used benchmark instances. By benchmarking combinatorial clustering algorithm with state-of-the-art algorithms, we can show that its performance compares very favorably. The fuzzy combinatorial optimization algorithm of cloud model and quantum-behaved particle swarm optimization (FCOCQPSO in vague sets (IVSs is more expressive than the other fuzzy sets. Finally, numerical examples show the clustering effectiveness of COCQPSO and FCOCQPSO clustering algorithms which are extremely remarkable.

Post-processing of Monte Carlo simulations for rapid BNCT source optimization studies

International Nuclear Information System (INIS)

Bleuel, D.L.; Chu, W.T.; Donahue, R.J.; Ludewigt, B.A.; Vujic, J.

2000-01-01

A great advantage of some neutron sources, such as accelerator-produced sources, is that they can be tuned to produce different spectra. Unfortunately, optimization studies are often time-consuming and difficult, as they require a lengthy Monte Carlo simulation for each source. When multiple characteristics, such as energy, angle, and spatial distribution of a neutron beam are allowed to vary, an overwhelming number of simulations may be required. Many optimization studies, therefore, suffer from a small number of datapoints, restrictive treatment conditions, or poor statistics. By scoring pertinent information from every particle tally in a Monte Carlo simulation, then applying appropriate source variable weight factors in a post-processing algorithm, a single simulation can be used to model any number of multiple sources. Through this method, the response to a new source can be modeled in minutes or seconds, rather than hours or days, allowing for the analysis of truly variable source conditions of much greater resolution than is normally possible when a new simulation must be run for each datapoint in a study. This method has been benchmarked and used to recreate optimization studies in a small fraction of the time spent in the original studies

Topology optimization of periodic microstructures for enhanced dynamic properties of viscoelastic composite materials

DEFF Research Database (Denmark)

Andreassen, Erik; Jensen, Jakob Søndergaard

2014-01-01

We present a topology optimization method for the design of periodic composites with dissipative materials for maximizing the loss/attenuation of propagating waves. The computational model is based on a finite element discretization of the periodic unit cell and a complex eigenvalue problem...... with a prescribed wave frequency. The attenuation in the material is described by its complex wavenumber, and we demonstrate in several examples optimized distributions of a stiff low loss and a soft lossy material in order to maximize the attenuation. In the examples we cover different frequency ranges and relate...... the results to previous studies on composites with high damping and stiffness based on quasi-static conditions for low frequencies and the bandgap phenomenon for high frequencies. Additionally, we consider the issues of stiffness and connectivity constraints and finally present optimized composites...

Ferrocyanide safety project ferrocyanide aging studies. Final report

International Nuclear Information System (INIS)

Lilga, M.A.; Hallen, R.T.; Alderson, E.V.

1996-06-01

This final report gives the results of the work conducted by Pacific Northwest National Laboratory (PNNL) from FY 1992 to FY 1996 on the Ferrocyanide Aging Studies, part of the Ferrocyanide Safety Project. The Ferrocyanide Safety Project was initiated as a result of concern raised about the safe storage of ferrocyanide waste intermixed with oxidants, such as nitrate and nitrite salts, in Hanford Site single-shell tanks (SSTs). In the laboratory, such mixtures can be made to undergo uncontrolled or explosive reactions by heating dry reagents to over 200 degrees C. In 1987, an Environmental Impact Statement (EIS), published by the U.S. Department of Energy (DOE), Final Environmental Impact Statement, Disposal of Hanford Defense High-Level Transuranic and Tank Waste, Hanford Site, Richland, Washington, included an environmental impact analysis of potential explosions involving ferrocyanide-nitrate mixtures. The EIS postulated that an explosion could occur during mechanical retrieval of saltcake or sludge from a ferrocyanide waste tank, and concluded that this worst-case accident could create enough energy to release radioactive material to the atmosphere through ventilation openings, exposing persons offsite to a short-term radiation dose of approximately 200 mrem. Later, in a separate study (1990), the General Accounting Office postulated a worst-case accident of one to two orders of magnitude greater than that postulated in the DOE EIS. The uncertainties regarding the safety envelope of the Hanford Site ferrocyanide waste tanks led to the declaration of the Ferrocyanide Unreviewed Safety Question (USQ) in October 1990

Improved Quantum Particle Swarm Optimization for Mangroves Classification

Directory of Open Access Journals (Sweden)

Zhehuang Huang

2016-01-01

Full Text Available Quantum particle swarm optimization (QPSO is a population based optimization algorithm inspired by social behavior of bird flocking which combines the ideas of quantum computing. For many optimization problems, traditional QPSO algorithm can produce high-quality solution within a reasonable computation time and relatively stable convergence characteristics. But QPSO algorithm also showed some unsatisfactory issues in practical applications, such as premature convergence and poor ability in global optimization. To solve these problems, an improved quantum particle swarm optimization algorithm is proposed and implemented in this paper. There are three main works in this paper. Firstly, an improved QPSO algorithm is introduced which can enhance decision making ability of the model. Secondly, we introduce synergetic neural network model to mangroves classification for the first time which can better handle fuzzy matching of remote sensing image. Finally, the improved QPSO algorithm is used to realize the optimization of network parameter. The experiments on mangroves classification showed that the improved algorithm has more powerful global exploration ability and faster convergence speed.

Improving scanner wafer alignment performance by target optimization

Science.gov (United States)

Leray, Philippe; Jehoul, Christiane; Socha, Robert; Menchtchikov, Boris; Raghunathan, Sudhar; Kent, Eric; Schoonewelle, Hielke; Tinnemans, Patrick; Tuffy, Paul; Belen, Jun; Wise, Rich

2016-03-01

In the process nodes of 10nm and below, the patterning complexity along with the processing and materials required has resulted in a need to optimize alignment targets in order to achieve the required precision, accuracy and throughput performance. Recent industry publications on the metrology target optimization process have shown a move from the expensive and time consuming empirical methodologies, towards a faster computational approach. ASML's Design for Control (D4C) application, which is currently used to optimize YieldStar diffraction based overlay (DBO) metrology targets, has been extended to support the optimization of scanner wafer alignment targets. This allows the necessary process information and design methodology, used for DBO target designs, to be leveraged for the optimization of alignment targets. In this paper, we show how we applied this computational approach to wafer alignment target design. We verify the correlation between predictions and measurements for the key alignment performance metrics and finally show the potential alignment and overlay performance improvements that an optimized alignment target could achieve.

Impacts of stress, self-efficacy, and optimism on suicide ideation among rehabilitation patients with acute pesticide poisoning.

Science.gov (United States)

Feng, Jun; Li, Shusheng; Chen, Huawen

2015-01-01

The high incidence of pesticide ingestion as a means to commit suicide is a critical public health problem. An important predictor of suicidal behavior is suicide ideation, which is related to stress. However, studies on how to defend against stress-induced suicidal thoughts are limited. This study explores the impact of stress on suicidal ideation by investigating the mediating effect of self-efficacy and dispositional optimism. Direct and indirect (via self-efficacy and dispositional optimism) effects of stress on suicidal ideation were investigated among 296 patients with acute pesticide poisoning from four general hospitals. For this purpose, structural equation modeling (SEM) and bootstrap method were used. Results obtained using SEM and bootstrap method show that stress has a direct effect on suicide ideation. Furthermore, self-efficacy and dispositional optimism partially weakened the relationship between stress and suicidal ideation. The final model shows a significant relationship between stress and suicidal ideation through self-efficacy or dispositional optimism. The findings extended prior studies and provide enlightenment on how self-efficacy and optimism prevents stress-induced suicidal thoughts.

Optimal investment and consumption when allowing terminal debt

NARCIS (Netherlands)

Chen, A.; Vellekoop, M.

2017-01-01

We analyze a dynamic optimization problem which involves the consumption and investment of an investor with constant relative risk aversion for consumption but with a risk aversion for final wealth which does not necessarily imply that terminal wealth must always be positive. We require risk

Aerodynamic Shape Optimization Using Hybridized Differential Evolution

Science.gov (United States)

Madavan, Nateri K.

2003-01-01

An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

Pareto optimality in organelle energy metabolism analysis.

Science.gov (United States)

Angione, Claudio; Carapezza, Giovanni; Costanza, Jole; Lió, Pietro; Nicosia, Giuseppe

2013-01-01

In low and high eukaryotes, energy is collected or transformed in compartments, the organelles. The rich variety of size, characteristics, and density of the organelles makes it difficult to build a general picture. In this paper, we make use of the Pareto-front analysis to investigate the optimization of energy metabolism in mitochondria and chloroplasts. Using the Pareto optimality principle, we compare models of organelle metabolism on the basis of single- and multiobjective optimization, approximation techniques (the Bayesian Automatic Relevance Determination), robustness, and pathway sensitivity analysis. Finally, we report the first analysis of the metabolic model for the hydrogenosome of Trichomonas vaginalis, which is found in several protozoan parasites. Our analysis has shown the importance of the Pareto optimality for such comparison and for insights into the evolution of the metabolism from cytoplasmic to organelle bound, involving a model order reduction. We report that Pareto fronts represent an asymptotic analysis useful to describe the metabolism of an organism aimed at maximizing concurrently two or more metabolite concentrations.

Mathematical Modelling, Simulation, and Optimal Control of the 2014 Ebola Outbreak in West Africa

Directory of Open Access Journals (Sweden)

Amira Rachah

2015-01-01

it is crucial to modelize the virus and simulate it. In this paper, we begin by studying a simple mathematical model that describes the 2014 Ebola outbreak in Liberia. Then, we use numerical simulations and available data provided by the World Health Organization to validate the obtained mathematical model. Moreover, we develop a new mathematical model including vaccination of individuals. We discuss different cases of vaccination in order to predict the effect of vaccination on the infected individuals over time. Finally, we apply optimal control to study the impact of vaccination on the spread of the Ebola virus. The optimal control problem is solved numerically by using a direct multiple shooting method.

Thermal-economic optimization of an air-cooled heat exchanger unit

International Nuclear Information System (INIS)

Alinia Kashani, Amir Hesam; Maddahi, Alireza; Hajabdollahi, Hassan

2013-01-01

Thermodynamic modeling and optimal design of an air-cooled heat exchanger (ACHE) unit are developed in this study. For this purpose, ε–NTU method and mathematical relations are applied to estimate the fluids outlet temperatures and pressure drops in tube and air sides. The main goal of this study is minimizing of two conflicting objective functions namely the temperature approach and the minimum total annual cost, simultaneously. For this purpose, fast and elitist non-dominated sorting genetic-algorithm (NSGA-II) is applied to minimize the objective functions by considering ten design parameters. In addition, a set of typical constraints, governing on the ACHE unit design, is subjected to obtain more practical optimum design points. Furthermore, sensitivity analysis of change in the objective functions, when the optimum design parameters vary, is conducted and the degree of each parameter on conflicting objective functions has been investigated. Finally, a selection procedure of the best optimum point is introduced and final optimum design point is determined. -- Highlights: ► Multi-objective optimization of air-cooled heat exchanger. ► Considering ten new design parameters in this type of heat exchanger. ► A detailed cost function is used to estimate the heat exchanger investment cost. ► Presenting a mathematical relation for optimum total cost vs. temperature approach. ► The sensitivity analysis of parameters in the optimum situation

A two-stage approach for multi-objective decision making with applications to system reliability optimization

International Nuclear Information System (INIS)

Li Zhaojun; Liao Haitao; Coit, David W.

2009-01-01

This paper proposes a two-stage approach for solving multi-objective system reliability optimization problems. In this approach, a Pareto optimal solution set is initially identified at the first stage by applying a multiple objective evolutionary algorithm (MOEA). Quite often there are a large number of Pareto optimal solutions, and it is difficult, if not impossible, to effectively choose the representative solutions for the overall problem. To overcome this challenge, an integrated multiple objective selection optimization (MOSO) method is utilized at the second stage. Specifically, a self-organizing map (SOM), with the capability of preserving the topology of the data, is applied first to classify those Pareto optimal solutions into several clusters with similar properties. Then, within each cluster, the data envelopment analysis (DEA) is performed, by comparing the relative efficiency of those solutions, to determine the final representative solutions for the overall problem. Through this sequential solution identification and pruning process, the final recommended solutions to the multi-objective system reliability optimization problem can be easily determined in a more systematic and meaningful way.

Sequential Optimization of Global Sequence Alignments Relative to Different Cost Functions

KAUST Repository

Odat, Enas M.

2011-01-01

The algorithm has been simulated using C#.Net programming language and a number of experiments have been done to verify the proved statements. The results of these experiments show that the number of optimal alignments is reduced after each step of optimization. Furthermore, it has been verified that as the sequence length increased linearly then the number of optimal alignments increased exponentially which also depends on the cost function that is used. Finally, the number of executed operations increases polynomially as the sequence length increase linearly.

Optimal and Autonomous Control Using Reinforcement Learning: A Survey.

Science.gov (United States)

Kiumarsi, Bahare; Vamvoudakis, Kyriakos G; Modares, Hamidreza; Lewis, Frank L

2018-06-01

This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively. Moreover, we discuss a new direction of off-policy RL for both CT and DT systems. Finally, we review several applications.

Component sizing optimization of plug-in hybrid electric vehicles

International Nuclear Information System (INIS)

Wu, Xiaolan; Cao, Binggang; Li, Xueyan; Xu, Jun; Ren, Xiaolong

2011-01-01

Plug-in hybrid electric vehicles (PHEVs) are considered as one of the most promising means to improve the near-term sustainability of the transportation and stationary energy sectors. This paper describes a methodology for the optimization of PHEVs component sizing using parallel chaos optimization algorithm (PCOA). In this approach, the objective function is defined so as to minimize the drivetrain cost. In addition, the driving performance requirements are considered as constraints. Finally, the optimization process is performed over three different all electric range (AER) and two types of batteries. The results from computer simulation show the effectiveness of the approach and the reduction in drivetrian cost while ensuring the vehicle performance.

A New Energy-Based Structural Design Optimization Concept under Seismic Actions

Directory of Open Access Journals (Sweden)

George Papazafeiropoulos

2017-07-01

Full Text Available A new optimization concept is introduced which involves the optimization of non-linear planar shear buildings by using gradients based on equivalent linear structures, instead of the traditional practice of calculating the gradients from the non-linear objective function. The optimization problem is formulated as an equivalent linear system of equations in which a target fundamental eigenfrequency and equal dissipated energy distribution within the storeys of the building are the components of the objective function. The concept is applied in a modified Newton–Raphson algorithm in order to find the optimum stiffness distribution of two representative linear or non-linear MDOF shear buildings, so that the distribution of viscously damped and hysteretically dissipated energy, respectively, over the structural height is uniform. A number of optimization results are presented in which the effect of the earthquake excitation, the critical modal damping ratio, and the normalized yield inter-storey drift limit on the optimum stiffness distributions is studied. Structural design based on the proposed approach is more rational and technically feasible compared to other optimization strategies (e.g., uniform ductility concept, whereas it is expected to provide increased protection against global collapse and loss of life during strong earthquake events. Finally, it is proven that the new optimization concept not only reduces running times by as much as 91% compared to the classical optimization algorithms but also can be applied in other optimization algorithms which use gradient information to proceed to the optimum point.

A Comparative Study of Temperature Optimal Control in a Solid State Fermentation Process for Edible Mushroom Growing

Directory of Open Access Journals (Sweden)

K. J. Gurubel

2017-04-01

Full Text Available In this paper, optimal control strategies for temperature trajectory determination in order to maximize thermophilic bacteria in a fed-batch solid-state fermentation reactor are proposed. This process is modeled by nonlinear differential equations, which has been previously validated experimentally with scale reactor temperature profiles. The dynamic input aeration rate of the reactor is determined to increase microorganisms growth of a selective substrate for edible mushroom cultivation. In industrial practice, the process is comprised of three thermal stages with constant input air flow and three types of microorganisms in a 150-hour lapse. Scytalidium thermophilum and actinobacteria are desired in order to obtain a final biomass composition with acceptable microorganisms concentration. The Steepest Descent gradient algorithm in continuous time and the Gradient Projection algorithm in discrete-time are used for the process optimal control. A comparison of simulation results in the presence of disturbances is presented, where the resulting temperature trajectories exhibit similar tendencies as industrial data.

Optimism and Mortality in Older Men and Women: The Rancho Bernardo Study

Directory of Open Access Journals (Sweden)

Ericha G. Anthony

2016-01-01

Full Text Available Purpose. To examine the associations of optimism and pessimism with all-cause, cardiovascular disease (CVD, coronary heart disease (CHD, and cancer mortality in a population-based sample of older men and women followed ≤12 years. Methods. 367 men and 509 women aged ≥50 from the Rancho Bernardo Study attended a 1999–2002 research clinic visit when demographic, behavioral, and medical history were obtained and completed a 1999 mailed survey including the Life Orientation Test-Revised (LOT-R. Mortality outcomes were followed through 2012. Results. Average age at baseline was 74.1 years; during follow-up (mean = 8.1 years, 198 participants died, 62 from CVD, 22 from CHD, and 49 from cancer. Total LOT-R, optimism and pessimism scores were calculated. Participants with the highest optimism were younger and reported less alcohol use and smoking and more exercise. Cox proportional hazard models showed that higher total LOT-R and optimism, but not pessimism scores, were associated with reduced odds of CHD mortality after adjusting for age, sex, alcohol, smoking, obesity, physical exercise, and medication (HR = 0.86, 95% CI = 0.75, 0.99; HR = 0.77, 95% CI = 0.61, 0.99, resp.. No associations were found for all-cause, CVD, or cancer mortality. Conclusions. Optimism was associated with reduced CHD mortality in older men and women. The association of positive attitudes with mortality merits further study.

A non-standard optimal control problem arising in an economics application

Directory of Open Access Journals (Sweden)

Alan Zinober

2013-04-01

Full Text Available A recent optimal control problem in the area of economics has mathematical properties that do not fall into the standard optimal control problem formulation. In our problem the state value at the final time the state, y(T = z, is free and unknown, and additionally the Lagrangian integrand in the functional is a piecewise constant function of the unknown value y(T. This is not a standard optimal control problem and cannot be solved using Pontryagin's Minimum Principle with the standard boundary conditions at the final time. In the standard problem a free final state y(T yields a necessary boundary condition p(T = 0, where p(t is the costate. Because the integrand is a function of y(T, the new necessary condition is that y(T should be equal to a certain integral that is a continuous function of y(T. We introduce a continuous approximation of the piecewise constant integrand function by using a hyperbolic tangent approach and solve an example using a C++ shooting algorithm with Newton iteration for solving the Two Point Boundary Value Problem (TPBVP. The minimising free value y(T is calculated in an outer loop iteration using the Golden Section or Brent algorithm. Comparative nonlinear programming (NP discrete-time results are also presented.

Study of optimal exposure windows using 320-Detector rows dynamic volume CT

Directory of Open Access Journals (Sweden)

Gang Sun

2010-12-01

Full Text Available Gang Sun1, Min Li1, Li Li1, Guo-ying Li1, Zhi-wei Jing21Departments of Medical Imaging, 2Medical Statistics, Jinan Military General Hospital, Shandong Province, ChinaAbstract: The purpose of this study was to determine the optimal electrocardiographic (ECG pulsing windows and evaluate the effect on reduced dose and accuracy using 320-detector rows dynamic volume computed tomography (DVCT. A total of 170 patients were prospectively studied. The optimal reconstruction windows were analyzed in 76 patients scanned using retrospective ECG gating. Forty-seven patients were scanned by the predicted triggering windows. The optimal positions of exposure intervals according to different heart rates were evaluated. Optimal image quality, radiation dose, and diagnostic accuracy were then investigated by applying optimal triggering windows. The optimal ECG pulsing windows were determined as follows: when heart rate was <70 beats per minute, the exposure windows should be preset at 60%–80%; for a heart rate 70–90 beats per minute at 70%–90%; and for a heart rate ≥90 beats per minute at 30%–50%. The radiation dose for patients scanned with prospective ECG gating was significantly lower (5.9 versus 12.9 mSv, P < 0.001. However, because two or three heart beats were needed when heart rate was >70 beats per minute, the radiation dose increased with increasing heart rate for both retrospective and prospective ECG gating (r = 0.64, P < 0.001 and r = 0.59, P < 0.001, respectively. On the basis of a per segment analysis, overall sensitivity was 98.0% (49/50, specificity was 99.2% (602/607, the positive predictive value was 90.7% (49/54, and the negative predictive value was 99.8% (602/603. In conclusion, DVCT has the potential to provide high image quality across a wide range of heart rates using an optimized ECG pulsing window. However, it is recommended to control heart rate below 70 beats per minute, if possible, to decrease the radiation dose

Optimal coherent control of dissipative N-level systems

International Nuclear Information System (INIS)

Jirari, H.; Poetz, W.

2005-01-01

General optimal coherent control of dissipative N-level systems in the Markovian time regime is formulated within Pointryagin's principle and the Lindblad equation. In the present paper, we study feasibility and limitations of steering of dissipative two-, three-, and four-level systems from a given initial pure or mixed state into a desired final state under the influence of an external electric field. The time evolution of the system is computed within the Lindblad equation and a conjugate gradient method is used to identify optimal control fields. The influence of both field-independent population and polarization decay on achieving the objective is investigated in systematic fashion. It is shown that, for realistic dephasing times, optimum control fields can be identified which drive the system into the target state with very high success rate and in economical fashion, even when starting from a poor initial guess. Furthermore, the optimal fields obtained give insight into the system dynamics. However, if decay rates of the system cannot be subjected to electromagnetic control, the dissipative system cannot be maintained in a specific pure or mixed state, in general

Optimization and scale up of microfluidic nanolipomer production method for preclinical and potential clinical trials.

Science.gov (United States)

Gdowski, Andrew; Johnson, Kaitlyn; Shah, Sunil; Gryczynski, Ignacy; Vishwanatha, Jamboor; Ranjan, Amalendu

2018-02-12

The process of optimization and fabrication of nanoparticle synthesis for preclinical studies can be challenging and time consuming. Traditional small scale laboratory synthesis techniques suffer from batch to batch variability. Additionally, the parameters used in the original formulation must be re-optimized due to differences in fabrication techniques for clinical production. Several low flow microfluidic synthesis processes have been reported in recent years for developing nanoparticles that are a hybrid between polymeric nanoparticles and liposomes. However, use of high flow microfluidic synthetic techniques has not been described for this type of nanoparticle system, which we will term as nanolipomer. In this manuscript, we describe the successful optimization and functional assessment of nanolipomers fabricated using a microfluidic synthesis method under high flow parameters. The optimal total flow rate for synthesis of these nanolipomers was found to be 12 ml/min and flow rate ratio 1:1 (organic phase: aqueous phase). The PLGA polymer concentration of 10 mg/ml and a DSPE-PEG lipid concentration of 10% w/v provided optimal size, PDI and stability. Drug loading and encapsulation of a representative hydrophobic small molecule drug, curcumin, was optimized and found that high encapsulation efficiency of 58.8% and drug loading of 4.4% was achieved at 7.5% w/w initial concentration of curcumin/PLGA polymer. The final size and polydispersity index of the optimized nanolipomer was 102.11 nm and 0.126, respectively. Functional assessment of uptake of the nanolipomers in C4-2B prostate cancer cells showed uptake at 1 h and increased uptake at 24 h. The nanolipomer was more effective in the cell viability assay compared to free drug. Finally, assessment of in vivo retention in mice of these nanolipomers revealed retention for up to 2 h and were completely cleared at 24 h. In this study, we have demonstrated that a nanolipomer formulation can be successfully

A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2014-01-01

Full Text Available The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009 competition. The performance assessment is done by using the inverted generational distance (IGD measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

Optimization and implementation study of plutonium disposition using existing CANDU Reactors. Final report

International Nuclear Information System (INIS)

1996-09-01

Since early 1994, the Department of Energy has been sponsoring studies aimed at evaluating the merits of disposing of surplus US weapons plutonium as Mixed Oxide (MOX) fuel in existing commercial Canadian Pressurized Heavy Water reactors, known as CANDU's. The first report, submitted to DOE in July, 1994 (the 1994 Executive Summary is attached), identified practical and safe options for the consumption of 50 to 100 tons of plutonium in 25 years in some of the existing CANDU reactors operating the Bruce A generating station, on Lake Huron, about 300 km north east of Detroit. By designing the fuel and nuclear performance to operate within existing experience and operating/performance envelope, and by utilizing existing fuel fabrication and transportation facilities and methods, a low cost, low risk method for long term plutonium disposition was developed. In December, 1995, in response to evolving Mission Requirements, the DOE requested a further study of the CANDU option with emphasis on more rapid disposition of the plutonium, and retaining the early start and low risk features of the earlier work. This report is the result of that additional work

Optimization study on inductive-resistive circuit for broadband piezoelectric energy harvesters

Directory of Open Access Journals (Sweden)