Recent advances in evolutionary multi-objective optimization

CERN Document Server

Datta, Rituparna; Gupta, Abhishek

2017-01-01

This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-andcoming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include:< optimization in dynamic environments, multi-objective bilevel programming, handling high ...

Recent Advances in Multidisciplinary Analysis and Optimization, part 3

Science.gov (United States)

Barthelemy, Jean-Francois M. (Editor)

1989-01-01

This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: aircraft design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

Recent advances in stellarator optimization

Science.gov (United States)

Gates, D. A.; Boozer, A. H.; Brown, T.; Breslau, J.; Curreli, D.; Landreman, M.; Lazerson, S. A.; Lore, J.; Mynick, H.; Neilson, G. H.; Pomphrey, N.; Xanthopoulos, P.; Zolfaghari, A.

2017-12-01

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. The purpose of this paper is to outline a select set of new concepts for stellarator optimization that, when taken as a group, present a significant step forward in the stellarator concept. One of the criticisms that has been leveled at existing methods of design is the complexity of the resultant field coils. Recently, a new coil optimization code—COILOPT++, which uses a spline instead of a Fourier representation of the coils,—was written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. The code has been tested by generating coil designs for optimized quasi-axisymmetric stellarator plasma configurations of different aspect ratios. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. New ideas on methods for the optimization of turbulent transport have garnered much attention since these methods have led to design concepts that are calculated to have reduced turbulent heat loss. We have explored possibilities for generating an experimental database to test whether the reduction in transport that is predicted is consistent with experimental observations. To this end, a series of equilibria that can be made in the now latent QUASAR experiment have been identified that will test the predicted transport scalings. Fast particle confinement studies aimed at developing a generalized optimization algorithm are also

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.

Advanced and flexible genetic algorithms for BWR fuel loading pattern optimization

International Nuclear Information System (INIS)

Martin-del-Campo, Cecilia; Palomera-Perez, Miguel-Angel; Francois, Juan-Luis

2009-01-01

This work proposes advances in the implementation of a flexible genetic algorithm (GA) for fuel loading pattern optimization for Boiling Water Reactors (BWRs). In order to avoid specific implementations of genetic operators and to obtain a more flexible treatment, a binary representation of the solution was implemented; this representation had to take into account that a little change in the genotype must correspond to a little change in the phenotype. An identifier number is assigned to each assembly by means of a Gray Code of 7 bits and the solution (the loading pattern) is represented by a binary chain of 777 bits of length. Another important contribution is the use of a Fitness Function which includes a Heuristic Function and an Objective Function. The Heuristic Function which is defined to give flexibility on the application of a set of positioning rules based on knowledge, and the Objective Function that contains all the parameters which qualify the neutronic and thermal hydraulic performances of each loading pattern. Experimental results illustrating the effectiveness and flexibility of this optimization algorithm are presented and discussed.

Issues and recent advances in optimal experimental design for site investigation (Invited)

Science.gov (United States)

Nowak, W.

2013-12-01

This presentation provides an overview over issues and recent advances in model-based experimental design for site exploration. The addressed issues and advances are (1) how to provide an adequate envelope to prior uncertainty, (2) how to define the information needs in a task-oriented manner, (3) how to measure the expected impact of a data set that it not yet available but only planned to be collected, and (4) how to perform best the optimization of the data collection plan. Among other shortcomings of the state-of-the-art, it is identified that there is a lack of demonstrator studies where exploration schemes based on expert judgment are compared to exploration schemes obtained by optimal experimental design. Such studies will be necessary do address the often voiced concern that experimental design is an academic exercise with little improvement potential over the well- trained gut feeling of field experts. When addressing this concern, a specific focus has to be given to uncertainty in model structure, parameterizations and parameter values, and to related surprises that data often bring about in field studies, but never in synthetic-data based studies. The background of this concern is that, initially, conceptual uncertainty may be so large that surprises are the rule rather than the exception. In such situations, field experts have a large body of experience in handling the surprises, and expert judgment may be good enough compared to meticulous optimization based on a model that is about to be falsified by the incoming data. In order to meet surprises accordingly and adapt to them, there needs to be a sufficient representation of conceptual uncertainty within the models used. Also, it is useless to optimize an entire design under this initial range of uncertainty. Thus, the goal setting of the optimization should include the objective to reduce conceptual uncertainty. A possible way out is to upgrade experimental design theory towards real-time interaction

Fuzzy portfolio optimization advances in hybrid multi-criteria methodologies

CERN Document Server

Gupta, Pankaj; Inuiguchi, Masahiro; Chandra, Suresh

2014-01-01

This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuin...

Extending the horizons advances in computing, optimization, and decision technologies

CERN Document Server

Joseph, Anito; Mehrotra, Anuj; Trick, Michael

2007-01-01

Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state-of-the-art in the interface between OR/MS and CS/AI and of the high caliber of research being conducted by members of the INFORMS Computing Society. EXTENDING THE HORIZONS: Advances in Computing, Optimization, and Decision Technologies is a volume that presents the latest, leading research in the design and analysis of algorithms, computational optimization, heuristic search and learning, modeling languages, parallel and distributed computing, simulation, computational logic and visualization. This volume also emphasizes a variety of novel applications in the interface of CS, AI, and OR/MS.

Topology Optimization and Robotic Fabrication of Advanced Timber Space-frame Structures

DEFF Research Database (Denmark)

Søndergaard, Asbjørn; Amir, Oded; Eversmann, Phillip

2016-01-01

This paper presents a novel method for integrated topology optimization and fabrication of advanced timber space-frame structures. The method, developed in research collaboration between ETH Zürich, Aarhus School of Architecture and Israel Institute of Technology, entails the coupling of truss...... processes solving timber joint intersections, robotically controlling member prefabrication, and spatial robotic assembly of the optimized timber structures. The implication of this concept is studied through pilot fabrication and load-testing of a full scale prototype structure.......-based topology optimization with digital procedures for rationalization and robotic assembly of bespoke timber members, through a procedural, cross-application workflow. Through this, a direct chaining of optimization and robotic fabrication is established, in which optimization data is driving subsequent...

Characteristics of positive-interaction parenting style among primiparous teenage, optimal age, and advanced age mothers in Canada

OpenAIRE

Kim, Theresa H. M.; Connolly, Jennifer A.; Rotondi, Michael; Tamim, Hala

2018-01-01

Background Positive-interaction parenting early in childhood is encouraged due to its association with behavioural development later in life. The objective of this study was to examine if the level of positive-interaction parenting style differs among teen, optimal age, and advanced age mothers in Canada, and to identify the characteristics associated with positive-interaction parenting style separately for each age group. Methods This was a cross-sectional secondary analysis of the National ...

AIC identifies optimal representation of longitudinal dietary variables.

Science.gov (United States)

VanBuren, John; Cavanaugh, Joseph; Marshall, Teresa; Warren, John; Levy, Steven M

2017-09-01

The Akaike Information Criterion (AIC) is a well-known tool for variable selection in multivariable modeling as well as a tool to help identify the optimal representation of explanatory variables. However, it has been discussed infrequently in the dental literature. The purpose of this paper is to demonstrate the use of AIC in determining the optimal representation of dietary variables in a longitudinal dental study. The Iowa Fluoride Study enrolled children at birth and dental examinations were conducted at ages 5, 9, 13, and 17. Decayed or filled surfaces (DFS) trend clusters were created based on age 13 DFS counts and age 13-17 DFS increments. Dietary intake data (water, milk, 100 percent-juice, and sugar sweetened beverages) were collected semiannually using a food frequency questionnaire. Multinomial logistic regression models were fit to predict DFS cluster membership (n=344). Multiple approaches could be used to represent the dietary data including averaging across all collected surveys or over different shorter time periods to capture age-specific trends or using the individual time points of dietary data. AIC helped identify the optimal representation. Averaging data for all four dietary variables for the whole period from age 9.0 to 17.0 provided a better representation in the multivariable full model (AIC=745.0) compared to other methods assessed in full models (AICs=750.6 for age 9 and 9-13 increment dietary measurements and AIC=762.3 for age 9, 13, and 17 individual measurements). The results illustrate that AIC can help researchers identify the optimal way to summarize information for inclusion in a statistical model. The method presented here can be used by researchers performing statistical modeling in dental research. This method provides an alternative approach for assessing the propriety of variable representation to significance-based procedures, which could potentially lead to improved research in the dental community. © 2017 American

Statistical identifiability and convergence evaluation for nonlinear pharmacokinetic models with particle swarm optimization.

Science.gov (United States)

Kim, Seongho; Li, Lang

2014-02-01

The statistical identifiability of nonlinear pharmacokinetic (PK) models with the Michaelis-Menten (MM) kinetic equation is considered using a global optimization approach, which is particle swarm optimization (PSO). If a model is statistically non-identifiable, the conventional derivative-based estimation approach is often terminated earlier without converging, due to the singularity. To circumvent this difficulty, we develop a derivative-free global optimization algorithm by combining PSO with a derivative-free local optimization algorithm to improve the rate of convergence of PSO. We further propose an efficient approach to not only checking the convergence of estimation but also detecting the identifiability of nonlinear PK models. PK simulation studies demonstrate that the convergence and identifiability of the PK model can be detected efficiently through the proposed approach. The proposed approach is then applied to clinical PK data along with a two-compartmental model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Optimal synthesis and operation of advanced energy supply systems for standard and domotic home

International Nuclear Information System (INIS)

Buoro, Dario; Casisi, Melchiorre; Pinamonti, Piero; Reini, Mauro

2012-01-01

Highlights: ► Definition of an optimization model for a home energy supply system. ► Optimization of the energy supply system for standard and domotic home. ► Strong improvement can be achieved adopting the optimal system in standard and domotic home. ► The improvements are consistent if supply side and demand side strategies are applied together. ► Solutions with internal combustion engines are less sensible to market price of electricity and gas. - Abstract: The paper deals with the optimization of an advanced energy supply systems for two dwellings: a standard home and an advanced domotic home, where some demand side energy saving strategies have been implemented. In both cases the optimal synthesis, design and operation of the whole energy supply system have been obtained and a sensitivity analysis has been performed, by introducing different economic constraints. The optimization model is based on a Mixed Integer Linear Program (MILP) and includes different kinds of small-scale cogenerators, geothermal heat pumps, boilers, heat storages, solar thermal and photovoltaic panels. In addition, absorption machines, supplied with cogenerated heat, can be used instead of conventional electrical chiller to face the cooling demand. The aim of the analysis is to address the question if advanced demand strategies and supply strategies have to be regarded as alternatives, or if they have to be simultaneously applied, in order to obtain the maximum energy and economic benefit.

A Method for Consensus Reaching in Product Kansei Evaluation Using Advanced Particle Swarm Optimization.

Science.gov (United States)

Yang, Yan-Pu

2017-01-01

Consumers' opinions toward product design alternatives are often subjective and perceptual, which reflect their perception about a product and can be described using Kansei adjectives. Therefore, Kansei evaluation is often employed to determine consumers' preference. However, how to identify and improve the reliability of consumers' Kansei evaluation opinions toward design alternatives has an important role in adding additional insurance and reducing uncertainty to successful product design. To solve this problem, this study employs a consensus model to measure consistence among consumers' opinions, and an advanced particle swarm optimization (PSO) algorithm combined with Linearly Decreasing Inertia Weight (LDW) method is proposed for consensus reaching by minimizing adjustment of consumers' opinions. Furthermore, the process of the proposed method is presented and the details are illustrated using an example of electronic scooter design evaluation. The case study reveals that the proposed method is promising for reaching a consensus through searching optimal solutions by PSO and improving the reliability of consumers' evaluation opinions toward design alternatives according to Kansei indexes.

Evaluation of the effect of advanced coagulation process to optimize ...

African Journals Online (AJOL)

Evaluation of the effect of advanced coagulation process to optimize the removal of natural organic matter in water (Case study: drinking water of Mashhad's ... and in addition to giving taste, color and odor to the water, they can intervene in the oxidization and removal of heavy metals such as arsenic, iron and manganese.

Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC

Science.gov (United States)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

2014-10-01

The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.

Dynamic modeling and optimal joint torque coordination of advanced robotic systems

Science.gov (United States)

Kang, Hee-Jun

The development is documented of an efficient dynamic modeling algorithm and the subsequent optimal joint input load coordination of advanced robotic systems for industrial application. A closed-form dynamic modeling algorithm for the general closed-chain robotic linkage systems is presented. The algorithm is based on the transfer of system dependence from a set of open chain Lagrangian coordinates to any desired system generalized coordinate set of the closed-chain. Three different techniques for evaluation of the kinematic closed chain constraints allow the representation of the dynamic modeling parameters in terms of system generalized coordinates and have no restriction with regard to kinematic redundancy. The total computational requirement of the closed-chain system model is largely dependent on the computation required for the dynamic model of an open kinematic chain. In order to improve computational efficiency, modification of an existing open-chain KIC based dynamic formulation is made by the introduction of the generalized augmented body concept. This algorithm allows a 44 pct. computational saving over the current optimized one (O(N4), 5995 when N = 6). As means of resolving redundancies in advanced robotic systems, local joint torque optimization is applied for effectively using actuator power while avoiding joint torque limits. The stability problem in local joint torque optimization schemes is eliminated by using fictitious dissipating forces which act in the necessary null space. The performance index representing the global torque norm is shown to be satisfactory. In addition, the resulting joint motion trajectory becomes conservative, after a transient stage, for repetitive cyclic end-effector trajectories. The effectiveness of the null space damping method is shown. The modular robot, which is built of well defined structural modules from a finite-size inventory and is controlled by one general computer system, is another class of evolving

Observation on optimal transition from conventional energy with resource constraints to advanced energy with virtually unlimited resource

International Nuclear Information System (INIS)

Suzuki, Atsuyuki

1980-01-01

The paper is aimed at making a theoretical analysis on optimal shift from finite energy resources like presently used oil toward advanced energy sources like nuclear and solar. First, the value of conventional energy as a finite resource is derived based on the variational principle. Second, a simplified model on macroeconomy is used to obtain and optimal relationship between energy production and consumption and thereby the optimality on energy price is provided. Third, the meaning of research and development of advanced energy is shown by taking into account resource constraints and technological progress. Finally, an optimal timing of the shift from conventional to advanced energies is determined by making use of the maximum principle. The methematical model employed there is much simplified but can be used to conclude that in order to make an optimal shift some policy-oriented decision must be made prior to when an economically competitive condition comes and that, even with that decision made, some recession of energy demand is inevitable during the transitional phase. (author)

The application of particle swarm optimization to identify gamma spectrum with neural network

International Nuclear Information System (INIS)

Shi Dongsheng; Di Yuming; Zhou Chunlin

2006-01-01

Aiming at the shortcomings that BP algorithm is usually trapped to a local optimum and it has a low speed of convergence in the application of neural network to identify gamma spectrum, according to the advantage of the globe optimal searching of particle swarm optimization, this paper put forward a new algorithm for neural network training by combining BP algorithm and Particle Swarm Optimization-mixed PSO-BP algorithm. In the application to identify gamma spectrum, the new algorithm overcomes the shortcoming that BP algorithm is usually trapped to a local optimum and the neural network trained by it has a high ability of generalization with identification result of one hundred percent correct. Practical example shows that the mixed PSO-BP algorithm can effectively and reliably be used to identify gamma spectrum. (authors)

Identifying factors affecting optimal management of agricultural water

Directory of Open Access Journals (Sweden)

Masoud Samian

2015-01-01

In addition to quantitative methodology such as descriptive statistics and factor analysis a qualitative methodology was employed for dynamic simulation among variables through Vensim software. In this study, the factor analysis technique was used through the Kaiser-Meyer-Olkin (KMO and Bartlett tests. From the results, four key elements were identified as factors affecting the optimal management of agricultural water in Hamedan area. These factors were institutional and legal factors, technical and knowledge factors, economic factors and social factors.

The optimized advanced demonstrator for the SC CW heavy ion linac at GSI

Energy Technology Data Exchange (ETDEWEB)

Schwarz, Malte; Basten, Markus; Busch, Marco; Dziuba, Florian; Podlech, Holger; Ratzinger, Ulrich; Tiede, Rudolf [Institut fuer Angewandte Physik, Goethe-Universitaet Frankfurt am Main (Germany); Gettmann, Viktor; Heilmann, Manuel [GSI Helmholtzzentrum, Darmstadt (Germany); Barth, Winfried; Mickat, Sascha [GSI Helmholtzzentrum, Darmstadt (Germany); HIM, Helmholtzinstitut, Mainz (Germany); Miski-Oglu, Maksym [HIM, Helmholtzinstitut, Mainz (Germany); Aulenbacher, Kurt [KPH, Johannes Gutenberg Universitaet, Mainz (Germany)

2016-07-01

For future experiments with heavy ions at the coulomb barrier within the SHE research project a multi-stage R and D program of GSI, HIM and IAP is currently under progress. It aims at developing a superconducting (sc) continuous wave (cw) LINAC with multiple CH-cavities as key components. As intermediate step towards the whole LINAC, the Optimized Advanced Demonstrator is proposed. Consisting of short CH-cavities and cryostats, it could provide several advantages regarding velocity acceptance, higher tolerance with respect to frequency and field deviation, easier mounting, handling and maintenance as well as a more robust longitudinal beam dynamic. The beam dynamics concept is based on EQUUS (Equidistant Multigap Structure) constant-beta cavities. The corresponding simulations for the proposed next extension stage - the Optimized Advanced Demonstrator - will be presented.

Observation on optimal transition from conventional energy with resource constraints to advanced energy with virtually unlimited resource, (2)

International Nuclear Information System (INIS)

Ohkubo, Hiroo; Suzuki, Atsuyuki; Kiyose, Ryohei

1983-01-01

This is an extension of the Suzuki model (base model) on optimal transition from resource-limited energy (oil) to advanced energy with virtually unlimited resource. The finite length of plant life, fuel cost, technological progress factor of advanced energy and the upper limit upon annual consumption rate of oil are taken into account for such an extension. The difference in optimal solutions obtained from extended and base models is shown by an application of the maximum principle. The implication of advanced energy R and D andenergy conservation effort is also discussed. (author)

Assessing the Value of Information for Identifying Optimal Floodplain Management Portfolios

Science.gov (United States)

Read, L.; Bates, M.; Hui, R.; Lund, J. R.

2014-12-01

Floodplain management is a complex portfolio problem that can be analyzed from an integrated perspective incorporating traditionally structural and nonstructural options. One method to identify effective strategies for preparing, responding to, and recovering from floods is to optimize for a portfolio of temporary (emergency) and permanent floodplain management options. A risk-based optimization approach to this problem assigns probabilities to specific flood events and calculates the associated expected damages. This approach is currently limited by: (1) the assumption of perfect flood forecast information, i.e. implementing temporary management activities according to the actual flood event may differ from optimizing based on forecasted information and (2) the inability to assess system resilience across a range of possible future events (risk-centric approach). Resilience is defined here as the ability of a system to absorb and recover from a severe disturbance or extreme event. In our analysis, resilience is a system property that requires integration of physical, social, and information domains. This work employs a 3-stage linear program to identify the optimal mix of floodplain management options using conditional probabilities to represent perfect and imperfect flood stages (forecast vs. actual events). We assess the value of information in terms of minimizing damage costs for two theoretical cases - urban and rural systems. We use portfolio analysis to explore how the set of optimal management options differs depending on whether the goal is for the system to be risk-adverse to a specified event or resilient over a range of events.

Optimizing meridional advection of the Advanced Research WRF (ARW) dynamics for Intel Xeon Phi coprocessor

Science.gov (United States)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.

2015-05-01

The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.

Identification of distinct phenotypes of locally advanced pancreatic adenocarcinoma.

LENUS (Irish Health Repository)

Teo, Minyuen

2013-03-01

A significant number of pancreatic ductal adenocarcinoma present as locally advanced disease. Optimal treatment remains controversial. We sought to analyze the clinical course of locally advanced pancreatic adenocarcinoma (LAPC) in order to identify potential distinct clinical phenotypes.

Multicycle Optimization of Advanced Gas-Cooled Reactor Loading Patterns Using Genetic Algorithms

International Nuclear Information System (INIS)

Ziver, A. Kemal; Carter, Jonathan N.; Pain, Christopher C.; Oliveira, Cassiano R.E. de; Goddard, Antony J. H.; Overton, Richard S.

2003-01-01

A genetic algorithm (GA)-based optimizer (GAOPT) has been developed for in-core fuel management of advanced gas-cooled reactors (AGRs) at HINKLEY B and HARTLEPOOL, which employ on-load and off-load refueling, respectively. The optimizer has been linked to the reactor analysis code PANTHER for the automated evaluation of loading patterns in a two-dimensional geometry, which is collapsed from the three-dimensional reactor model. GAOPT uses a directed stochastic (Monte Carlo) algorithm to generate initial population members, within predetermined constraints, for use in GAs, which apply the standard genetic operators: selection by tournament, crossover, and mutation. The GAOPT is able to generate and optimize loading patterns for successive reactor cycles (multicycle) within acceptable CPU times even on single-processor systems. The algorithm allows radial shuffling of fuel assemblies in a multicycle refueling optimization, which is constructed to aid long-term core management planning decisions. This paper presents the application of the GA-based optimization to two AGR stations, which apply different in-core management operational rules. Results obtained from the testing of GAOPT are discussed

Application of particle swarm optimization to identify gamma spectrum with neural network

International Nuclear Information System (INIS)

Shi Dongsheng; Di Yuming; Zhou Chunlin

2007-01-01

In applying neural network to identification of gamma spectra back propagation (BP) algorithm is usually trapped to a local optimum and has a low speed of convergence, whereas particle swarm optimization (PSO) is advantageous in terms of globe optimal searching. In this paper, we propose a new algorithm for neural network training, i.e. combined BP and PSO optimization, or PSO-BP algorithm. Practical example shows that the new algorithm can overcome shortcomings of BP algorithm and the neural network trained by it has a high ability of generalization with identification result of 100% correctness. It can be used effectively and reliably to identify gamma spectra. (authors)

3rd International Workshop on Advances in Simulation-Driven Optimization and Modeling

CERN Document Server

Leifsson, Leifur; Yang, Xin-She

2016-01-01

This edited volume is devoted to the now-ubiquitous use of computational models across most disciplines of engineering and science, led by a trio of world-renowned researchers in the field. Focused on recent advances of modeling and optimization techniques aimed at handling computationally-expensive engineering problems involving simulation models, this book will be an invaluable resource for specialists (engineers, researchers, graduate students) working in areas as diverse as electrical engineering, mechanical and structural engineering, civil engineering, industrial engineering, hydrodynamics, aerospace engineering, microwave and antenna engineering, ocean science and climate modeling, and the automotive industry, where design processes are heavily based on CPU-heavy computer simulations. Various techniques, such as knowledge-based optimization, adjoint sensitivity techniques, and fast replacement models (to name just a few) are explored in-depth along with an array of the latest techniques to optimize the...

Synergism between profile and cross section shape optimization for negative central shear advanced tokamaks

International Nuclear Information System (INIS)

Turnbull, A.D.; Taylor, T.S.; Lao, L.L.

1996-01-01

The Advanced Tokamak (AT) concept is aimed at achieving high beta, high confinement, and a well aligned high bootstrap current fraction in a tokamak configuration consistent with steady state operation. The required improvements over the simple O-D scaling laws, normally used to predict standard, pulsed tokamak performance, axe obtained by taking into account the dependence of the stability and confinement on the 2-D equilibrium; the planned TPX experiment was designed to take full advantage of both advanced profiles and advanced cross-section shaping. Systematic stability studies of the promising Negative Central Shear (NCS) configuration have been performed for a wide variety of cross-section shapes and profile variations. The ideal MHD beta limit is found to be strongly dependent on both and, in fact, there is a clear synergistic relationship between the gains in beta from optimizing the profiles and optimizing the shape. Specifically, for a circular cross-section with highly peaked profiles, β is limited to normalized β values of β N = β/(I/aB) ∼ 2% (mT/MA). A small gain in beta can be achieved by broadening the pressure; however, the root-mean-square beta (β*) is slightly reduced. With peaked pressure profiles, a small increase in β N over that in a circular cross-section is also obtained by strong shaping. At fixed q, this translates to a much larger gain in β and β*. With both optimal profiles and strong shaping, however, the gain in all the relevant fusion performance parameters is dramatic; β and β* can be increased a factor 5 for example. Moreover, the bootstrap alignment is improved. For an optimized strongly shaped configuration, confinement, beta values, and bootstrap alignment adequate for a practical AT power plant appear to be realizable. Data from DIII-D supports these predictions and analysis of the DIII-D data will be presented

Multi-center evaluation of post-operative morbidity and mortality after optimal cytoreductive surgery for advanced ovarian cancer.

Directory of Open Access Journals (Sweden)

Arash Rafii

Full Text Available PURPOSE: While optimal cytoreduction is the standard of care for advanced ovarian cancer, the related post-operative morbidity has not been clearly documented outside pioneering centers. Indeed most of the studies are monocentric with inclusions over several years inducing heterogeneity in techniques and goals of surgery. We assessed the morbidity of optimal cytoreduction surgery for advanced ovarian cancer within a short inclusion period in 6 referral centers dedicated to achieve complete cytoreduction. PATIENTS AND METHODS: The 30 last optimal debulking surgeries of 6 cancer centers were included. Inclusion criteria included: stage IIIc- IV ovarian cancer and optimal surgery performed at the site of inclusion. All post-operative complications within 30 days of surgery were recorded and graded using the Memorial secondary events grading system. Student-t, Chi2 and non-parametric statistical tests were performed. RESULTS: 180 patients were included. There was no demographic differences between the centers. 63 patients underwent surgery including intestinal resections (58 recto-sigmoid resection, 24 diaphragmatic resections, 17 splenectomies. 61 patients presented complications; One patient died post-operatively. Major (grade 3-5 complications requiring subsequent surgeries occurred in 21 patients (11.5%. 76% of patients with a major complication had undergone an ultraradical surgery (P = 0.004. CONCLUSION: While ultraradical surgery may result in complete resection of peritoneal disease in advanced ovarian cancer, the associated complication rate is not negligible. Patients should be carefully evaluated and the timing of their surgery optimized in order to avoid major complications.

Optimization method for identifying the source term in an inverse wave equation

Directory of Open Access Journals (Sweden)

Arumugam Deiveegan

2017-08-01

Full Text Available In this work, we investigate the inverse problem of identifying a space-wise dependent source term of wave equation from the measurement on the boundary. On the basis of the optimal control framework, the inverse problem is transformed into an optimization problem. The existence and necessary condition of the minimizer for the cost functional are obtained. The projected gradient method and two-parameter model function method are applied to the minimization problem and numerical results are illustrated.

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

International Nuclear Information System (INIS)

Liu, Kailong; Li, Kang; Yang, Zhile; Zhang, Cheng; Deng, Jing

2017-01-01

Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled thermoelectric model. An advanced optimal charging strategy is then proposed to develop the optimal constant-current-constant-voltage (CCCV) charge current profile, which gives the best trade-off among three conflicting but important objectives for battery management. To be specific, a coupled thermoelectric battery model is first presented. Then, a specific triple-objective function consisting of three objectives, namely charging time, energy loss, and temperature rise (both the interior and surface), is proposed. Heuristic methods such as Teaching-learning-based-optimization (TLBO) and particle swarm optimization (PSO) are applied to optimize the triple-objective function, and their optimization performances are compared. The impacts of the weights for different terms in the objective function are then assessed. Experimental results show that the proposed optimal charging strategy is capable of offering desirable effective optimal charging current profiles and a proper trade-off among the conflicting objectives. Further, the proposed optimal charging strategy can be easily extended to other battery types.

Optimism, Symptom Distress, Illness Appraisal, and Coping in Patients With Advanced-Stage Cancer Diagnoses Undergoing Chemotherapy Treatment.

Science.gov (United States)

Sumpio, Catherine; Jeon, Sangchoon; Northouse, Laurel L; Knobf, M Tish

2017-05-01

To explore the relationships between optimism, self-efficacy, symptom distress, treatment complexity, illness appraisal, coping, and mood disturbance in patients with advanced-stage cancer.
. Cross-sectional study.
. Smilow Cancer Hospital at Yale New Haven in Connecticut, an outpatient comprehensive cancer center.
. A convenience sample of 121 adult patients with stages III-IV cancer undergoing active chemotherapy.
. Participants completed common self-report questionnaires to measure variables. Treatment hours and visits were calculated from data retrieved from medical record review. Mediation and path analysis were conducted to identify direct and indirect pathways from the significant antecedent variables to mood disturbance.
. Dispositional optimism, self-efficacy, social support, treatment complexity, symptom distress, illness appraisal, coping, and mood disturbance.
. Greater optimism and self-efficacy were associated with less negative illness appraisal, less avoidant coping, and decreased mood disturbance. Conversely, greater symptom distress was associated with greater negative illness appraisal, greater avoidant coping, and greater mood disturbance. In the final model, optimism and symptom distress had direct and indirect effects on mood disturbance. Indirect effects were partially mediated by illness appraisal.
. Mood disturbance resulted from an interaction of disease stressors, personal resources, and cognitive appraisal of illness. Avoidant coping was associated with greater disturbed mood, but neither avoidant nor active coping had a significant effect on mood in the multivariate model. 
. Illness appraisal, coping style, and symptom distress are important targets for intervention. Optimism is a beneficial trait and should be included, along with coping style, in comprehensive nursing assessments of patients with cancer.

Optimal Inventory Control with Advance Supply Information

Directory of Open Access Journals (Sweden)

Marko Jaksic

2016-09-01

Full Text Available It has been shown in numerous situations that sharing information between the companies leads to improved performance of the supply chain. We study a positive lead time periodic-review inventory system of a retailer facing stochastic demand from his customer and stochastic limited supply capacity of the manufacturer supplying the products to him. The consequence of stochastic supply capacity is that the orders might not be delivered in full, and the exact size of the replenishment might not be known to the retailer. The manufacturer is willing to share the so-called advance supply information (ASI about the actual replenishment of the retailer's pipeline order with the retailer. ASI is provided at a certain time after the orders have been placed and the retailer can now use this information to decrease the uncertainty of the supply, and thus improve its inventory policy. For this model, we develop a dynamic programming formulation, and characterize the optimal ordering policy as a state-dependent base-stock policy. In addition, we show some properties of the base-stock level. While the optimal policy is highly complex, we obtain some additional insights by comparing it to the state-dependent myopic inventory policy. We conduct the numerical analysis to estimate the in uence of the system parameters on the value of ASI. While we show that the interaction between the parameters is relatively complex, the general insight is that due to increasing marginal returns, the majority of the benets are gained only in the case of full, or close to full, ASI visibility.

Optimal design of advanced distillation configuration for enhanced energy efficiency of waste solvent recovery process in semiconductor industry

International Nuclear Information System (INIS)

Chaniago, Yus Donald; Minh, Le Quang; Khan, Mohd Shariq; Koo, Kee-Kahb; Bahadori, Alireza; Lee, Moonyong

2015-01-01

Highlights: • Thermally coupled distillation process is proposed for waste solvent recovery. • A systematic optimization procedure is used to optimize distillation columns. • Response surface methodology is applied to optimal design of distillation column. • Proposed advanced distillation allows energy efficient waste solvent recovery. - Abstract: The semiconductor industry is one of the largest industries in the world. On the other hand, the huge amount of solvent used in the industry results in high production cost and potential environmental damage because most of the valuable chemicals discharged from the process are incinerated at high temperatures. A distillation process is used to recover waste solvent, reduce the production-related costs and protect the environment from the semiconductor industrial waste. Therefore, in this study, a distillation process was used to recover the valuable chemicals from semiconductor industry discharge, which otherwise would have been lost to the environment. The conventional sequence of distillation columns, which was optimized using the Box and sequential quadratic programming method for minimum energy objectives, was used. The energy demands of a distillation problem may have a substantial influence on the profitability of a process. A thermally coupled distillation and heat pump-assisted distillation sequence was implemented to further improve the distillation performance. Finally, a comparison was made between the conventional and advanced distillation sequences, and the optimal conditions for enhancing recovery were determined. The proposed advanced distillation configuration achieved a significant energy saving of 40.5% compared to the conventional column sequence

Advanced BDD optimization

CERN Document Server

Ebendt, Rudiger; Drechsler, Rolf

2005-01-01

BDD and SAT are major concepts in VLSI CADNew objective functions for design space exploration require new algorithms for BDD optimizationLatest trend: fusion of the concepts BDD and SATMajor impulses come from Artificial Intelligence (AI)Unifying view, transfers the latest theoretical insights into practical applications.

Optimization of advanced gas-cooled reactor fuel performance by a stochastic method

International Nuclear Information System (INIS)

Parks, G.T.

1987-01-01

A brief description is presented of a model representing the in-core behaviour of a single advanced gas-cooled reactor fuel channel, developed specifically for optimization studies. The performances of the only suitable Numerical Algorithms Group (NAG) library package and a Metropolis algorithm routine on this problem are discussed and contrasted. It is concluded that, for the problem in question, the stochastic Metropolis algorithm has distinct advantages over the deterministic NAG routine. (author)

Advanced Nuclear Fuel Cycle Transitions: Optimization, Modeling Choices, and Disruptions

Science.gov (United States)

Carlsen, Robert W.

Many nuclear fuel cycle simulators have evolved over time to help understan the nuclear industry/ecosystem at a macroscopic level. Cyclus is one of th first fuel cycle simulators to accommodate larger-scale analysis with it liberal open-source licensing and first-class Linux support. Cyclus also ha features that uniquely enable investigating the effects of modeling choices o fuel cycle simulators and scenarios. This work is divided into thre experiments focusing on optimization, effects of modeling choices, and fue cycle uncertainty. Effective optimization techniques are developed for automatically determinin desirable facility deployment schedules with Cyclus. A novel method fo mapping optimization variables to deployment schedules is developed. Thi allows relationships between reactor types and scenario constraints to b represented implicitly in the variable definitions enabling the usage o optimizers lacking constraint support. It also prevents wasting computationa resources evaluating infeasible deployment schedules. Deployed power capacit over time and deployment of non-reactor facilities are also included a optimization variables There are many fuel cycle simulators built with different combinations o modeling choices. Comparing results between them is often difficult. Cyclus flexibility allows comparing effects of many such modeling choices. Reacto refueling cycle synchronization and inter-facility competition among othe effects are compared in four cases each using combinations of fleet of individually modeled reactors with 1-month or 3-month time steps. There are noticeable differences in results for the different cases. The larges differences occur during periods of constrained reactor fuel availability This and similar work can help improve the quality of fuel cycle analysi generally There is significant uncertainty associated deploying new nuclear technologie such as time-frames for technology availability and the cost of buildin advanced reactors

Systems-Level Synthetic Biology for Advanced Biofuel Production

Energy Technology Data Exchange (ETDEWEB)

Ruffing, Anne [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jensen, Travis J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Strickland, Lucas Marshall [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Meserole, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tallant, David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-03-01

Cyanobacteria have been shown to be capable of producing a variety of advanced biofuels; however, product yields remain well below those necessary for large scale production. New genetic tools and high throughput metabolic engineering techniques are needed to optimize cyanobacterial metabolisms for enhanced biofuel production. Towards this goal, this project advances the development of a multiple promoter replacement technique for systems-level optimization of gene expression in a model cyanobacterial host: Synechococcus sp. PCC 7002. To realize this multiple-target approach, key capabilities were developed, including a high throughput detection method for advanced biofuels, enhanced transformation efficiency, and genetic tools for Synechococcus sp. PCC 7002. Moreover, several additional obstacles were identified for realization of this multiple promoter replacement technique. The techniques and tools developed in this project will help to enable future efforts in the advancement of cyanobacterial biofuels.

Multi-Objective Optimization of a Turbofan for an Advanced, Single-Aisle Transport

Science.gov (United States)

Berton, Jeffrey J.; Guynn, Mark D.

2012-01-01

Considerable interest surrounds the design of the next generation of single-aisle commercial transports in the Boeing 737 and Airbus A320 class. Aircraft designers will depend on advanced, next-generation turbofan engines to power these airplanes. The focus of this study is to apply single- and multi-objective optimization algorithms to the conceptual design of ultrahigh bypass turbofan engines for this class of aircraft, using NASA s Subsonic Fixed Wing Project metrics as multidisciplinary objectives for optimization. The independent design variables investigated include three continuous variables: sea level static thrust, wing reference area, and aerodynamic design point fan pressure ratio, and four discrete variables: overall pressure ratio, fan drive system architecture (i.e., direct- or gear-driven), bypass nozzle architecture (i.e., fixed- or variable geometry), and the high- and low-pressure compressor work split. Ramp weight, fuel burn, noise, and emissions are the parameters treated as dependent objective functions. These optimized solutions provide insight to the ultrahigh bypass engine design process and provide information to NASA program management to help guide its technology development efforts.

Good Manufacturing Practices (GMP) manufacturing of advanced therapy medicinal products: a novel tailored model for optimizing performance and estimating costs.

Science.gov (United States)

Abou-El-Enein, Mohamed; Römhild, Andy; Kaiser, Daniel; Beier, Carola; Bauer, Gerhard; Volk, Hans-Dieter; Reinke, Petra

2013-03-01

Advanced therapy medicinal products (ATMP) have gained considerable attention in academia due to their therapeutic potential. Good Manufacturing Practice (GMP) principles ensure the quality and sterility of manufacturing these products. We developed a model for estimating the manufacturing costs of cell therapy products and optimizing the performance of academic GMP-facilities. The "Clean-Room Technology Assessment Technique" (CTAT) was tested prospectively in the GMP facility of BCRT, Berlin, Germany, then retrospectively in the GMP facility of the University of California-Davis, California, USA. CTAT is a two-level model: level one identifies operational (core) processes and measures their fixed costs; level two identifies production (supporting) processes and measures their variable costs. The model comprises several tools to measure and optimize performance of these processes. Manufacturing costs were itemized using adjusted micro-costing system. CTAT identified GMP activities with strong correlation to the manufacturing process of cell-based products. Building best practice standards allowed for performance improvement and elimination of human errors. The model also demonstrated the unidirectional dependencies that may exist among the core GMP activities. When compared to traditional business models, the CTAT assessment resulted in a more accurate allocation of annual expenses. The estimated expenses were used to set a fee structure for both GMP facilities. A mathematical equation was also developed to provide the final product cost. CTAT can be a useful tool in estimating accurate costs for the ATMPs manufactured in an optimized GMP process. These estimates are useful when analyzing the cost-effectiveness of these novel interventions. Copyright © 2013 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Rational design and optimization of downstream processes of virus particles for biopharmaceutical applications: current advances.

Science.gov (United States)

Vicente, Tiago; Mota, José P B; Peixoto, Cristina; Alves, Paula M; Carrondo, Manuel J T

2011-01-01

The advent of advanced therapies in the pharmaceutical industry has moved the spotlight into virus-like particles and viral vectors produced in cell culture holding great promise in a myriad of clinical targets, including cancer prophylaxis and treatment. Even though a couple of cases have reached the clinic, these products have yet to overcome a number of biological and technological challenges before broad utilization. Concerning the manufacturing processes, there is significant research focusing on the optimization of current cell culture systems and, more recently, on developing scalable downstream processes to generate material for pre-clinical and clinical trials. We review the current options for downstream processing of these complex biopharmaceuticals and underline current advances on knowledge-based toolboxes proposed for rational optimization of their processing. Rational tools developed to increase the yet scarce knowledge on the purification processes of complex biologicals are discussed as alternative to empirical, "black-boxed" based strategies classically used for process development. Innovative methodologies based on surface plasmon resonance, dynamic light scattering, scale-down high-throughput screening and mathematical modeling for supporting ion-exchange chromatography show great potential for a more efficient and cost-effective process design, optimization and equipment prototyping. Copyright © 2011 Elsevier Inc. All rights reserved.

Discrete particle swarm optimization for identifying community structures in signed social networks.

Science.gov (United States)

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

Technology-design-manufacturing co-optimization for advanced mobile SoCs

Science.gov (United States)

Yang, Da; Gan, Chock; Chidambaram, P. R.; Nallapadi, Giri; Zhu, John; Song, S. C.; Xu, Jeff; Yeap, Geoffrey

2014-03-01

How to maintain the Moore's Law scaling beyond the 193 immersion resolution limit is the key question semiconductor industry needs to answer in the near future. Process complexity will undoubtfully increase for 14nm node and beyond, which brings both challenges and opportunities for technology development. A vertically integrated design-technologymanufacturing co-optimization flow is desired to better address the complicated issues new process changes bring. In recent years smart mobile wireless devices have been the fastest growing consumer electronics market. Advanced mobile devices such as smartphones are complex systems with the overriding objective of providing the best userexperience value by harnessing all the technology innovations. Most critical system drivers are better system performance/power efficiency, cost effectiveness, and smaller form factors, which, in turns, drive the need of system design and solution with More-than-Moore innovations. Mobile system-on-chips (SoCs) has become the leading driver for semiconductor technology definition and manufacturing. Here we highlight how the co-optimization strategy influenced architecture, device/circuit, process technology and package, in the face of growing process cost/complexity and variability as well as design rule restrictions.

Summary of SMIRT20 Preconference Topical Workshop - Identifying Structural Issues in Advanced Reactors

International Nuclear Information System (INIS)

Richins, William; Novascone, Stephen; O'Brien, Cheryl

2009-01-01

The Idaho National Laboratory (INL, USA) and IASMiRT sponsored an international forum Nov 5-6, 2008 in Porvoo, Finland for nuclear industry, academic, and regulatory representatives to identify structural issues in current and future advanced reactor design, especially for extreme conditions and external threats. The purpose of this Topical Workshop was to articulate research, engineering, and regulatory Code development needs. The topics addressed by the Workshop were selected to address critical industry needs specific to advanced reactor structures that have long lead times and can be the subject of future SMiRT technical sessions. The topics were; (1) structural/materials needs for extreme conditions and external threats in contemporary (Gen. III) and future (Gen. IV and NGNP) advanced reactors and (2) calibrating simulation software and methods that address topic 1. The workshop discussions and research needs identified are presented. The Workshop successfully produced interactive discussion on the two topics resulting in a list of research and technology needs. It is recommended that IASMiRT communicate the results of the discussion to industry and researchers to encourage new ideas and projects. In addition, opportunities exist to retrieve research reports and information that currently exists, and encourage more international cooperation and collaboration. It is recommended that IASMiRT continue with an off-year workshop series on select topics.

Optimization of Friction Stir Welding Tool Advance Speed via Monte-Carlo Simulation of the Friction Stir Welding Process.

Science.gov (United States)

Fraser, Kirk A; St-Georges, Lyne; Kiss, Laszlo I

2014-04-30

Recognition of the friction stir welding process is growing in the aeronautical and aero-space industries. To make the process more available to the structural fabrication industry (buildings and bridges), being able to model the process to determine the highest speed of advance possible that will not cause unwanted welding defects is desirable. A numerical solution to the transient two-dimensional heat diffusion equation for the friction stir welding process is presented. A non-linear heat generation term based on an arbitrary piecewise linear model of friction as a function of temperature is used. The solution is used to solve for the temperature distribution in the Al 6061-T6 work pieces. The finite difference solution of the non-linear problem is used to perform a Monte-Carlo simulation (MCS). A polynomial response surface (maximum welding temperature as a function of advancing and rotational speed) is constructed from the MCS results. The response surface is used to determine the optimum tool speed of advance and rotational speed. The exterior penalty method is used to find the highest speed of advance and the associated rotational speed of the tool for the FSW process considered. We show that good agreement with experimental optimization work is possible with this simplified model. Using our approach an optimal weld pitch of 0.52 mm/rev is obtained for 3.18 mm thick AA6061-T6 plate. Our method provides an estimate of the optimal welding parameters in less than 30 min of calculation time.

Novel Handover Optimization with a Coordinated Contiguous Carrier Aggregation Deployment Scenario in LTE-Advanced Systems

Directory of Open Access Journals (Sweden)

Ibraheem Shayea

2016-01-01

Full Text Available The carrier aggregation (CA technique and Handover Parameters Optimization (HPO function have been introduced in LTE-Advanced systems to enhance system performance in terms of throughput, coverage area, and connection stability and to reduce management complexity. Although LTE-Advanced has benefited from the CA technique, the low spectral efficiency and high ping-pong effect with high outage probabilities in conventional Carrier Aggregation Deployment Scenarios (CADSs have become major challenges for cell edge User Equipment (UE. Also, the existing HPO algorithms are not optimal for selecting the appropriate handover control parameters (HCPs. This paper proposes two solutions by deploying a Coordinated Contiguous-CADS (CC-CADS and a Novel Handover Parameters Optimization algorithm that is based on the Weight Performance Function (NHPO-WPF. The CC-CADS uses two contiguous component carriers (CCs that have two different beam directions. The NHPO-WPF automatically adjusts the HCPs based on the Weight Performance Function (WPF, which is evaluated as a function of the Signal-to-Interference Noise Ratio (SINR, cell load, and UE’s velocity. Simulation results show that the CC-CADS and the NHPO-WPF algorithm provide significant enhancements in system performance over that of conventional CADSs and HPO algorithms from the literature, respectively. The integration of both solutions achieves even better performance than scenarios in which each solution is considered independently.

Computational modeling, optimization and manufacturing simulation of advanced engineering materials

CERN Document Server

2016-01-01

This volume presents recent research work focused in the development of adequate theoretical and numerical formulations to describe the behavior of advanced engineering materials.  Particular emphasis is devoted to applications in the fields of biological tissues, phase changing and porous materials, polymers and to micro/nano scale modeling. Sensitivity analysis, gradient and non-gradient based optimization procedures are involved in many of the chapters, aiming at the solution of constitutive inverse problems and parameter identification. All these relevant topics are exposed by experienced international and inter institutional research teams resulting in a high level compilation. The book is a valuable research reference for scientists, senior undergraduate and graduate students, as well as for engineers acting in the area of computational material modeling.

Design and Performance Optimizations of Advanced Erosion-Resistant Low Conductivity Thermal Barrier Coatings for Rotorcraft Engines

Science.gov (United States)

Zhu, Dongming; Miller, Robert A.; Kuczmarski, Maria A.

2012-01-01

Thermal barrier coatings will be more aggressively designed to protect gas turbine engine hot-section components in order to meet future rotorcraft engine higher fuel efficiency and lower emission goals. For thermal barrier coatings designed for rotorcraft turbine airfoil applications, further improved erosion and impact resistance are crucial for engine performance and durability, because the rotorcraft are often operated in the most severe sand erosive environments. Advanced low thermal conductivity and erosion-resistant thermal barrier coatings are being developed, with the current emphasis being placed on thermal barrier coating toughness improvements using multicomponent alloying and processing optimization approaches. The performance of the advanced thermal barrier coatings has been evaluated in a high temperature erosion burner rig and a laser heat-flux rig to simulate engine erosion and thermal gradient environments. The results have shown that the coating composition and architecture optimizations can effectively improve the erosion and impact resistance of the coating systems, while maintaining low thermal conductivity and cyclic oxidation durability

Evolutionary optimization and game strategies for advanced multi-disciplinary design applications to aeronautics and UAV design

CERN Document Server

Periaux, Jacques; Lee, Dong Seop Chris

2015-01-01

Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with c...

Optimization and experimental validation of a thermal cycle that maximizes entropy coefficient fisher identifiability for lithium iron phosphate cells

Science.gov (United States)

Mendoza, Sergio; Rothenberger, Michael; Hake, Alison; Fathy, Hosam

2016-03-01

This article presents a framework for optimizing the thermal cycle to estimate a battery cell's entropy coefficient at 20% state of charge (SOC). Our goal is to maximize Fisher identifiability: a measure of the accuracy with which a parameter can be estimated. Existing protocols in the literature for estimating entropy coefficients demand excessive laboratory time. Identifiability optimization makes it possible to achieve comparable accuracy levels in a fraction of the time. This article demonstrates this result for a set of lithium iron phosphate (LFP) cells. We conduct a 24-h experiment to obtain benchmark measurements of their entropy coefficients. We optimize a thermal cycle to maximize parameter identifiability for these cells. This optimization proceeds with respect to the coefficients of a Fourier discretization of this thermal cycle. Finally, we compare the estimated parameters using (i) the benchmark test, (ii) the optimized protocol, and (iii) a 15-h test from the literature (by Forgez et al.). The results are encouraging for two reasons. First, they confirm the simulation-based prediction that the optimized experiment can produce accurate parameter estimates in 2 h, compared to 15-24. Second, the optimized experiment also estimates a thermal time constant representing the effects of thermal capacitance and convection heat transfer.

Plant protection system optimization studies to mitigate consequences of large breaks in the Advanced Neutron Source Reactor

International Nuclear Information System (INIS)

Khayat, M.I.; March-Leuba, J.

1993-01-01

This paper documents some of the optimization studies performed to maximize the performance of the engineered safety features and scram systems to mitigate the consequences of large breaks in the primary cooling system of the Advanced Neutron Source (ANS) Reactor

Design and optimization of components and processes for plasma sources in advanced material treatments

OpenAIRE

Rotundo, Fabio

2012-01-01

The research activities described in the present thesis have been oriented to the design and development of components and technological processes aimed at optimizing the performance of plasma sources in advanced in material treatments. Consumables components for high definition plasma arc cutting (PAC) torches were studied and developed. Experimental activities have in particular focussed on the modifications of the emissive insert with respect to the standard electrode configuration, whi...

Advanced Electrocardiography Can Identify Occult Cardiomyopathy in Doberman Pinschers

Science.gov (United States)

Spiljak, M.; Petric, A. Domanjko; Wilberg, M.; Olsen, L. H.; Stepancic, A.; Schlegel, T. T.; Starc, V.

2011-01-01

Recently, multiple advanced resting electrocardiographic (A-ECG) techniques have improved the diagnostic value of short-duration ECG in detection of dilated cardiomyopathy (DCM) in humans. This study investigated whether 12-lead A-ECG recordings could accurately identify the occult phase of DCM in dogs. Short-duration (3-5 min) high-fidelity 12-lead ECG recordings were obtained from 31 privately-owned, clinically healthy Doberman Pinschers (5.4 +/- 1.7 years, 11/20 males/females). Dogs were divided into 2 groups: 1) 19 healthy dogs with normal echocardiographic M-mode measurements: left ventricular internal diameter in diastole (LVIDd . 47mm) and in systole (LVIDs . 38mm) and normal 24-hour ECG recordings (100 VPCs/24h; 1/12 dogs had only abnormal 24-hour ECG recordings (>100 VPCs/24h). ECG recordings were evaluated via custom software programs to calculate multiple parameters of high-frequency (HF) QRS ECG, heart rate variability, QT variability, waveform complexity and 3-D ECG. Student's t-tests determined 19 ECG parameters that were significantly different (P canine DCM as five selected ECG parameters can with reasonable accuracy identify occult DCM in Doberman Pinschers. Future extensive clinical studies need to clarify if 12-lead A-ECG could be useful as an additional screening test for canine DCM.

Integrated Circuit Conception: A Wire Optimization Technic Reducing Interconnection Delay in Advanced Technology Nodes

Directory of Open Access Journals (Sweden)

Mohammed Darmi

2017-10-01

Full Text Available As we increasingly use advanced technology nodes to design integrated circuits (ICs, physical designers and electronic design automation (EDA providers are facing multiple challenges, firstly, to honor all physical constraints coming with cutting-edge technologies and, secondly, to achieve expected quality of results (QoR. An advanced technology should be able to bring better performances with minimum cost whatever the complexity. A high effort to develop out-of-the-box optimization techniques is more than needed. In this paper, we will introduce a new routing technique, with the objective to optimize timing, by only acting on routing topology, and without impacting the IC Area. In fact, the self-aligned double patterning (SADP technology offers an important difference on layer resistance between SADP and No-SADP layers; this property will be taken as an advantage to drive the global router to use No-SADP less resistive layers for critical nets. To prove the benefit on real test cases, we will use Mentor Graphics’ physical design EDA tool Nitro-SoC™ and several 7 nm technology node designs. The experiments show that worst negative slack (WNS and total negative slack (TNS improved up to 13% and 56%, respectively, compared to the baseline flow.

Optimization and Optimal Control

CERN Document Server

Chinchuluun, Altannar; Enkhbat, Rentsen; Tseveendorj, Ider

2010-01-01

During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and due to the rapid development of these fields, there are no other recent publications on the same topics. Key features: Provides a collection of selected contributions giving a state-of-the-art accou

Optimizing the wind power generation in low wind speed areas using an advanced hybrid RBF neural network coupled with the HGA-GSA optimization method

Energy Technology Data Exchange (ETDEWEB)

Assareh, Ehsanolah; Poultangari, Iman [Dezful Branch, Islamic Azad University, Dezful (Iran, Islamic Republic of); Tandis, Emad [Mechanical Engineering Department, University of Jundi Shapor, Dezful (Iran, Islamic Republic of); Nedael, Mojtaba [Dept. of Energy Engineering, Graduate School of the Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran (Iran, Islamic Republic of)

2016-10-15

Enhancing the energy production from wind power in low-wind areas has always been a fundamental subject of research in the field of wind energy industry. In the first phase of this research, an initial investigation was performed to evaluate the potential of wind in south west of Iran. The initial results indicate that the wind potential in the studied location is not sufficient enough and therefore the investigated region is identified as a low wind speed area. In the second part of this study, an advanced optimization model was presented to regulate the torque in the wind generators. For this primary purpose, the torque of wind turbine is adjusted using a Proportional and integral (PI) control system so that at lower speeds of the wind, the power generated by generator is enhanced significantly. The proposed model uses the RBF neural network to adjust the net obtained gains of the PI controller for the purpose of acquiring the utmost electricity which is produced through the generator. Furthermore, in order to edify and instruct the neural network, the optimal data set is obtained by a Hybrid genetic algorithm along with a gravitational search algorithm (HGA-GSA). The proposed method is evaluated by using a 5MW wind turbine manufactured by National Renewable Energy Laboratory (NREL). Final results of this study are indicative of the satisfactory and successful performance of the proposed investigated model.

Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.

Science.gov (United States)

Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

2015-01-01

Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature - integrin β4 (ITGB4) - was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.

Plasma Profile and Shape Optimization for the Advanced Tokamak Power Plant, ARIES-AT

International Nuclear Information System (INIS)

Kessel, C.E.; Mau, T.K.; Jardin, S.C.; Najmabadi, F.

2001-01-01

An advanced tokamak plasma configuration is developed based on equilibrium, ideal-MHD stability, bootstrap current analysis, vertical stability and control, and poloidal-field coil analysis. The plasma boundaries used in the analysis are forced to coincide with the 99% flux surface from the free-boundary equilibrium. Using an accurate bootstrap current model and external current-drive profiles from ray-tracing calculations in combination with optimized pressure profiles, beta(subscript N) values above 7.0 have been obtained. The minimum current drive requirement is found to lie at a lower beta(subscript N) of 5.4. The external kink mode is stabilized by a tungsten shell located at 0.33 times the minor radius and a feedback system. Plasma shape optimization has led to an elongation of 2.2 and triangularity of 0.9 at the separatrix. Vertical stability could be achieved by a combination of tungsten shells located at 0.33 times the minor radius and feedback control coils located behind the shield. The poloidal-field coils were optimized in location and current, providing a maximum coil current of 8.6 MA. These developments have led to a simultaneous reduction in the power plant major radius and toroidal field

Optimally setting up directed searches for continuous gravitational waves in Advanced LIGO O1 data

Science.gov (United States)

Ming, Jing; Papa, Maria Alessandra; Krishnan, Badri; Prix, Reinhard; Beer, Christian; Zhu, Sylvia J.; Eggenstein, Heinz-Bernd; Bock, Oliver; Machenschalk, Bernd

2018-02-01

In this paper we design a search for continuous gravitational waves from three supernova remnants: Vela Jr., Cassiopeia A (Cas A) and G347.3. These systems might harbor rapidly rotating neutron stars emitting quasiperiodic gravitational radiation detectable by the advanced LIGO detectors. Our search is designed to use the volunteer computing project Einstein@Home for a few months and assumes the sensitivity and duty cycles of the advanced LIGO detectors during their first science run. For all three supernova remnants, the sky positions of their central compact objects are well known but the frequency and spin-down rates of the neutron stars are unknown which makes the searches computationally limited. In a previous paper we have proposed a general framework for deciding on what target we should spend computational resources and in what proportion, what frequency and spin-down ranges we should search for every target, and with what search setup. Here we further expand this framework and apply it to design a search directed at detecting continuous gravitational wave signals from the most promising three supernova remnants identified as such in the previous work. Our optimization procedure yields broad frequency and spin-down searches for all three objects, at an unprecedented level of sensitivity: The smallest detectable gravitational wave strain h0 for Cas A is expected to be 2 times smaller than the most sensitive upper limits published to date, and our proposed search, which was set up and ran on the volunteer computing project Einstein@Home, covers a much larger frequency range.

Advances in stochastic and deterministic global optimization

CERN Document Server

Zhigljavsky, Anatoly; Žilinskas, Julius

2016-01-01

Current research results in stochastic and deterministic global optimization including single and multiple objectives are explored and presented in this book by leading specialists from various fields. Contributions include applications to multidimensional data visualization, regression, survey calibration, inventory management, timetabling, chemical engineering, energy systems, and competitive facility location. Graduate students, researchers, and scientists in computer science, numerical analysis, optimization, and applied mathematics will be fascinated by the theoretical, computational, and application-oriented aspects of stochastic and deterministic global optimization explored in this book. This volume is dedicated to the 70th birthday of Antanas Žilinskas who is a leading world expert in global optimization. Professor Žilinskas's research has concentrated on studying models for the objective function, the development and implementation of efficient algorithms for global optimization with single and mu...

Advanced fuel for fast breeder reactors: Fabrication and properties and their optimization

International Nuclear Information System (INIS)

1988-06-01

The present design for FBR fuel rods includes usually MOX fuel pellets cladded into stainless steel tubes, together with UO 2 axial blanket and stainless steel hexagonal wrappers. Mixed carbide, nitride and metallic fuels have been tested as alternative fuels in test reactors. Among others, the objectives to develop these alternative fuels are to gain a high breeding ratio, short doubling time and high linear ratings. Fuel rod and assembly designers are now concentrating on finding the combination of optimized fuel, cladding and wrapper materials which could result in improvement of fuel operational reliability under high burnups and load-follow mode of operation. The purpose of the meeting was to review the experience of advanced FBR fuel fabrication technology, its properties before, under and after irradiation, peculiarities of the back-end of the nuclear fuel cycle, and to outline future trends. As a result of the panel discussion, the recommendations on future Agency activities in the area of advanced FBR fuels were developed. A separate abstract was prepared for each of the 10 presentations of this meeting. Refs, figs and tabs

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

OpenAIRE

Ahmet Demir; Utku kose

2017-01-01

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...

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.

Challenges in Optimizing a Prostate Carcinoma Binding Peptide, Identified through the Phage Display Technology

Directory of Open Access Journals (Sweden)

Jürgen Debus

2011-02-01

Full Text Available The transfer of peptides identified through the phage display technology to clinical applications is difficult. Major drawbacks are the metabolic degradation and label instability. The aim of our work is the optimization of DUP-1, a peptide which was identified by phage display to specifically target human prostate carcinoma. To investigate the influence of chelate conjugation, DOTA was coupled to DUP-1 and labeling was performed with 111In. To improve serum stability cyclization of DUP-1 and targeted D-amino acid substitution were carried out. Alanine scanning was performed for identification of the binding site and based on the results peptide fragments were chemically synthesized. The properties of modified ligands were investigated in in vitro binding and competition assays. In vivo biodistribution studies were carried out in mice, carrying human prostate tumors subcutaneously. DOTA conjugation resulted in different cellular binding kinetics, rapid in vivo renal clearance and increased tumor-to-organ ratios. Cyclization and D-amino acid substitution increased the metabolic stability but led to binding affinity decrease. Fragment investigation indicated that the sequence NRAQDY might be significant for target-binding. Our results demonstrate challenges in optimizing peptides, identified through phage display libraries, and show that careful investigation of modified derivatives is necessary in order to improve their characteristics.

Advanced Functional Polymers for Increasing the Stability of Organic Photovoltaics

DEFF Research Database (Denmark)

Bundgaard, Eva; Helgesen, Martin; Carlé, Jon Eggert

2013-01-01

The development of new advanced polymers for improving the stability of OPV is reviewed. Two main degradation pathways for the OPV active layer are identified: photochemically initiated reactions primarily starting in the side chains and morphological changes that degrade the important nanostruct......The development of new advanced polymers for improving the stability of OPV is reviewed. Two main degradation pathways for the OPV active layer are identified: photochemically initiated reactions primarily starting in the side chains and morphological changes that degrade the important...... nanostructure. Chemical units can be introduced that impart an increased stability. Similarly, the morphological degradation of the optimal nanostructure can be reduced. Active polymers and blends with acceptor material are used to create nanoparticle links with controlled size. Most of these advanced polymers...

Advanced Harmony Search with Ant Colony Optimization for Solving the Traveling Salesman Problem

Directory of Open Access Journals (Sweden)

Ho-Yoeng Yun

2013-01-01

Full Text Available We propose a novel heuristic algorithm based on the methods of advanced Harmony Search and Ant Colony Optimization (AHS-ACO to effectively solve the Traveling Salesman Problem (TSP. The TSP, in general, is well known as an NP-complete problem, whose computational complexity increases exponentially by increasing the number of cities. In our algorithm, Ant Colony Optimization (ACO is used to search the local optimum in the solution space, followed by the use of the Harmony Search to escape the local optimum determined by the ACO and to move towards a global optimum. Experiments were performed to validate the efficiency of our algorithm through a comparison with other algorithms and the optimum solutions presented in the TSPLIB. The results indicate that our algorithm is capable of generating the optimum solution for most instances in the TSPLIB; moreover, our algorithm found better solutions in two cases (kroB100 and pr144 when compared with the optimum solution presented in the TSPLIB.

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

Design optimization of JT-60SU for steady-state advanced operation

International Nuclear Information System (INIS)

Ushigusa, K.; Kurita, G.; Toyoshima, N.

2001-01-01

Design optimization of JT-60SU has been done for a steady-state advanced operation. A transport code simulation indicates that a fully non-inductive reversed shear plasmas with fractions of 70% of the bootstrap current and 30% of beam driven current can be sustained for more than 1,000s without any additional control. Investigations have been progressed on MHD stability, vertical positional stability and dynamics of the vertical displacement events. Significant progress has been achieved in the R and D of Nb 3 Al superconducting wires, low induced activation material (Fe-Cr-Mn steel). A design improvement has been made in TF coils to reduce a local stress on radial disk. Dynamic behaviors of the tokamak machine have been analyzed at emergency events such as an earthquake. (author)

De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locally advanced breast cancer

Directory of Open Access Journals (Sweden)

Wu Xiwei

2012-03-01

Full Text Available Abstract Background MicroRNAs (miRNAs have been recently detected in the circulation of cancer patients, where they are associated with clinical parameters. Discovery profiling of circulating small RNAs has not been reported in breast cancer (BC, and was carried out in this study to identify blood-based small RNA markers of BC clinical outcome. Methods The pre-treatment sera of 42 stage II-III locally advanced and inflammatory BC patients who received neoadjuvant chemotherapy (NCT followed by surgical tumor resection were analyzed for marker identification by deep sequencing all circulating small RNAs. An independent validation cohort of 26 stage II-III BC patients was used to assess the power of identified miRNA markers. Results More than 800 miRNA species were detected in the circulation, and observed patterns showed association with histopathological profiles of BC. Groups of circulating miRNAs differentially associated with ER/PR/HER2 status and inflammatory BC were identified. The relative levels of selected miRNAs measured by PCR showed consistency with their abundance determined by deep sequencing. Two circulating miRNAs, miR-375 and miR-122, exhibited strong correlations with clinical outcomes, including NCT response and relapse with metastatic disease. In the validation cohort, higher levels of circulating miR-122 specifically predicted metastatic recurrence in stage II-III BC patients. Conclusions Our study indicates that certain miRNAs can serve as potential blood-based biomarkers for NCT response, and that miR-122 prevalence in the circulation predicts BC metastasis in early-stage patients. These results may allow optimized chemotherapy treatments and preventive anti-metastasis interventions in future clinical applications.

Fusion of optimized indicators from Advanced Driver Assistance Systems (ADAS) for driver drowsiness detection.

Science.gov (United States)

Daza, Iván García; Bergasa, Luis Miguel; Bronte, Sebastián; Yebes, Jose Javier; Almazán, Javier; Arroyo, Roberto

2014-01-09

This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study.

Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS for Driver Drowsiness Detection

Directory of Open Access Journals (Sweden)

Iván G. Daza

2014-01-01

Full Text Available This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS. An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study.

Advanced compiler design and implementation

CERN Document Server

Muchnick, Steven S

1997-01-01

From the Foreword by Susan L. Graham: This book takes on the challenges of contemporary languages and architectures, and prepares the reader for the new compiling problems that will inevitably arise in the future. The definitive book on advanced compiler design This comprehensive, up-to-date work examines advanced issues in the design and implementation of compilers for modern processors. Written for professionals and graduate students, the book guides readers in designing and implementing efficient structures for highly optimizing compilers for real-world languages. Covering advanced issues in fundamental areas of compiler design, this book discusses a wide array of possible code optimizations, determining the relative importance of optimizations, and selecting the most effective methods of implementation. * Lays the foundation for understanding the major issues of advanced compiler design * Treats optimization in-depth * Uses four case studies of commercial compiling suites to illustrate different approache...

BRAIN Journal - Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm

OpenAIRE

Ahmet Demir; Utku Kose

2016-01-01

ABSTRACT 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 Sc...

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 ...

Indoor environment and energy consumption optimization using field measurements and building energy simulation

DEFF Research Database (Denmark)

Christensen, Jørgen Erik; Chasapis, Kleanthis; Gazovic, Libor

2015-01-01

Modern buildings are usually equipped with advanced climate conditioning systems to ensure comfort of their occupants. However, analysis of their actual operation usually identifies large potential for improvements with respect to their efficiency. Present study investigated potential for improve......, which was used for optimization of building’s performance. Proposed optimization scenarios bring 21-37% reduction on heating consumption and thermal comfort improvement by 7-12%. The approach (procedure) can help to optimize building operation and shorten the adjustment period....

Improved Broadband Liner Optimization Applied to the Advanced Noise Control Fan

Science.gov (United States)

Nark, Douglas M.; Jones, Michael G.; Sutliff, Daniel L.; Ayle, Earl; Ichihashi, Fumitaka

2014-01-01

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more desirable. This paper describes improvements to a previously established broadband acoustic liner optimization process using the Advanced Noise Control Fan rig as a demonstrator. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom designs are carried through design, fabrication, and testing to validate the efficacy of the design process. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of these liner designs. This study also provides an application for demonstrating the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and Pareto filters.

Directory of Open Access Journals (Sweden)

Carlos Pozo

Full Text Available Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and Pareto filters.

Science.gov (United States)

Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Sorribas, Albert; Jiménez, Laureano

2012-01-01

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the

Optimization of time distribution for studying the course modules on advanced training of health care administrators

Directory of Open Access Journals (Sweden)

Dorovskaya A.l.

2015-06-01

Full Text Available The research objective is rational (optimal time management in studying the course modules on Advanced Training of Health Care Administrators. Materials and methods. We conducted expert survey of 73 healthcare administrators from medical organizations of Saratov region. Branch-and-bound method was used for rescheduling the educational program. Results. Both direct and inverse problems have been solved. The direct one refers to time distribution for each module of the advanced Training of Healthcare Administrators course so that the total score is maximum and each module is marked not lower than "satisfactory". The inverse one resulted in achieving minimal time characteristics for varieties of average score. Conclusion. The offered approach allows to solve problems of managing time given for education.

Waste incineration models for operation optimization. Phase 1: Advanced measurement equipment for improved operation of waste fired plants; Affaldsforbraendingsmodeller til driftsoptimering. Fase 1: Avanceret maeleudstyr til forbedret drift af affaldsfyrede anlaeg

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-06-01

This report describes results from the PSO projects ELTRA-5294 and ELTRA-5348: Waste incineration models for operation optimization. Phase 1, and Advanced measurement equipment for improved operation of waste fired plants. Phase 1. The two projects form the first step in a project course build on a long-term vision of a fully automatic system using a wide range of advanced measurement data, advanced dynamic models for prediction of operation and advanced regulation methods for optimization of the operation of waste incinerator plants. (BA)

Advancing PWR fuel to meet customer needs

Energy Technology Data Exchange (ETDEWEB)

Kramer, F W

1987-03-01

Since the introduction of the Optimized Fuel Assembly (OFA) for PWRs in the late 1970s, Westinghouse has continued to work with the utility customers to identify the greatest needs for further advance in fuel performance and reliability. The major customer requirements include longer fuel cycle at lower costs, increased fuel discharge burn-up, enhanced operating flexibility, all accompanied by even greater reliability. In response to these needs, Westinghouse developed Vantage 5 PWR fuel. To optimize reactor operations, Vantage 5 fuel features distinct advantages: integral fuel burnable absorbers, axial and radial blankets, intermediate flow mixers, a removable top nozzle, and assembly modifications to accommodate increased discharge burn-up.

Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...

Science.gov (United States)

With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th

Identifying Core Competencies to Advance Female Professors' Careers: An Exploratory Study in United States Academia

Science.gov (United States)

Seo, Ga-eun; Hedayati Mehdiabadi, Amir; Huang, Wenhao

2017-01-01

This exploratory study aims to identify the core competencies necessary to successfully advance the careers of female associate professors in higher education. To ascertain these core career competencies, a critical incident interview technique was employed. One-to-one semi-structured interviews with six female full professors at a major research…

Plasma profile and shape optimization for the advanced tokamak power plant, ARIES-AT

International Nuclear Information System (INIS)

Kessel, C.E.; Mau, T.K.; Jardin, S.C.; Najmabadi, F.

2006-01-01

An advanced tokamak plasma configuration is developed based on equilibrium, ideal MHD stability, bootstrap current analysis, vertical stability and control, and poloidal field coil analysis. The plasma boundaries used in the analysis are forced to coincide with the 99% flux surface from the free-boundary equilibrium. Using an accurate bootstrap current model and external current drive profiles from ray tracing calculations in combination with optimized pressure profiles, β N values above 7.0 have been obtained. The minimum current drive requirement is found to lie at a lower β N of 6.0. The external kink mode is stabilized by a tungsten shell located at 0.33 times the minor radius and a feedback system. Plasma shape optimization has led to an elongation of 2.2 and triangularity of 0.9 at the separatrix. Vertical stability could be achieved by a combination of tungsten shells located at 0.33 times the minor radius and feedback control coils located behind the shield. The poloidal field coils were optimized in location and current, providing a maximum coil current of 8.6 MA. These developments have led to a simultaneous reduction in the power plant major radius and toroidal field from those found in a previous study [S.C. Jardin, C.E. Kessel, C.G. Bathke, D.A. Ehst, T.K. Mau, F. Najmabadi, T.W. Petrie, the ARIES Team, Physics basis for a reversed shear tokamak power plant, Fusion Eng. Design 38 (1997) 27

Co-Optimization of Fuels & Engines: Fuel Blendstocks with the Potential to Optimize Future Gasoline Engine Performance; Identification of Five Chemical Families for Detailed Evaluation

Energy Technology Data Exchange (ETDEWEB)

Farrell, John T [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Holladay, John [Pacific Northwest National Laboratory; Wagner, Robert [Oak Ridge National Laboratory

2018-04-18

The U.S. Department of Energy's (DOE's) Co-Optimization of Fuels & Engines (Co-Optima) initiative is conducting the early-stage research needed to accelerate the market introduction of advanced fuel and engine technologies. The research includes both spark-ignition (SI) and compression-ignition (CI) combustion approaches, targeting applications that impact the entire on-road fleet (light-, medium-, and heavy-duty vehicles). The initiative's major goals include significant improvements in vehicle fuel economy, lower-cost pathways to reduce emissions, and leveraging diverse U.S. fuel resources. A key objective of Co-Optima's research is to identify new blendstocks that enhance current petroleum blending components, increase blendstock diversity, and provide refiners with increased flexibility to blend fuels with the key properties required to optimize advanced internal combustion engines. This report identifies eight representative blendstocks from five chemical families that have demonstrated the potential to increase boosted SI engine efficiency, meet key fuel quality requirements, and be viable for production at commercial scale by 2025-2030.

Optimizing a three-element core design for the Advanced Neutron Source Reactor

International Nuclear Information System (INIS)

West, C.D.

1995-01-01

Source of neutrons in the proposed Advanced Neutron Source facility is a multipurpose research reactor providing 5-10 times the flux, for neutron beams, of the best existing facilities. Baseline design for the reactor core, based on the ''no new inventions'' rule, was an assembly of two annular fuel elements similar to those used in the Oak Ridge and Grenoble high flux reactors, containing highly enriched U silicide particles. DOE commissioned a study of the use of medium- or low-enriched U; a three-element core design was studied as a means to provide extra volume to accommodate the additional U compound required when the fissionable 235 U has to be diluted with 238 U to reduce the enrichment. This paper describes the design and optimization of that three-element core

Identifying the sociological implications of the main aspects affecting the optimal sporting career development

OpenAIRE

2014-01-01

M.Phil. (Sport Management) This study is strengthened by several studies that have indicated that the dualist nature of student-athletes is problematic, as well as the management thereof. The study aimed to identify the sociological implications of the main aspects affecting the optimal sporting career development in athletics (throwers) at University of Johannesburg Sport, and offers recommendations for managing student-athletes. The methods utilized for this study included: i) self-desig...

Identifying relationships between the professional culture of pharmacy, pharmacists' personality traits, and the provision of advanced pharmacy services.

Science.gov (United States)

Rosenthal, Meagen; Tsao, Nicole W; Tsuyuki, Ross T; Marra, Carlo A

2016-01-01

Legislative changes are affording pharmacists the opportunity to provide more advanced pharmacy services. However, many pharmacists have not yet been able to provide these services sustainably. Research from implementation science suggests that before sustained change in pharmacy can be achieved an improved understanding of pharmacy context, through the professional culture of pharmacy and pharmacists' personality traits, is required. The primary objective of this study was to investigate possible relationships between cultural factors, and personality traits, and the uptake of advanced practice opportunities by pharmacists in British Columbia, Canada. The study design was a cross-sectional survey of registered, and practicing, pharmacists from one Canadian province. The survey gauged respondents' characteristics, practice setting, and the provision of advanced pharmacy services, and contained the Organizational Culture Profile (OCP), a measure of professional culture, as well as the Big Five Inventory (BFI), a measure of personality traits. A total of 945 completed survey instruments were returned. The majority of respondents were female (61%), the average age of respondents was 42 years (SD: 12), and the average number of years in practice was 19 (SD: 12). A significant positive relationship was identified for respondents perceiving greater value in the OCP factors competitiveness and innovation and providing a higher number of all advanced services. A positive relationship was observed for respondents scoring higher on the BFI traits extraversion and the immunizations provided, and agreeableness and openness and medication reviews completed. This is the first work to identify statistically significant relationships between the OCP and BFI, and the provision of advanced pharmacy services. As such, this work serves as a starting place from which to develop more detailed insight into how the professional culture of pharmacy and pharmacists personality traits may

Advanced exergetic analysis of five natural gas liquefaction processes

International Nuclear Information System (INIS)

Vatani, Ali; Mehrpooya, Mehdi; Palizdar, Ali

2014-01-01

Highlights: • Advanced exergetic analysis was investigated for five LNG processes. • Avoidable/unavoidable and endogenous/exogenous irreversibilities were calculated. • Advanced exergetic analysis identifies the potentials for improving the system. - Abstract: Conventional exergy analysis cannot identify portion of inefficiencies which can be avoided. Also this analysis does not have ability to calculate a portion of exergy destruction which has been produced through performance of a component alone. In this study advanced exergetic analysis was performed for five mixed refrigerant LNG processes and four parts of irreversibility (avoidable/unavoidable) and (endogenous/exogenous) were calculated for the components with high inefficiencies. The results showed that portion of endogenous exergy destruction in the components is higher than the exogenous one. In fact interactions among the components do not affect the inefficiencies significantly. Also this analysis showed that structural optimization cannot be useful to decrease the overall process irreversibilities. In compressors high portion of the exergy destruction is related to the avoidable one, thus they have high potential to improve. But in multi stream heat exchangers and air coolers, unavoidable inefficiencies were higher than the other parts. Advanced exergetic analysis can identify the potentials and strategies to improve thermodynamic performance of energy intensive processes

Launch Vehicle Design and Optimization Methods and Priority for the Advanced Engineering Environment

Science.gov (United States)

Rowell, Lawrence F.; Korte, John J.

2003-01-01

NASA's Advanced Engineering Environment (AEE) is a research and development program that will improve collaboration among design engineers for launch vehicle conceptual design and provide the infrastructure (methods and framework) necessary to enable that environment. In this paper, three major technical challenges facing the AEE program are identified, and three specific design problems are selected to demonstrate how advanced methods can improve current design activities. References are made to studies that demonstrate these design problems and methods, and these studies will provide the detailed information and check cases to support incorporation of these methods into the AEE. This paper provides background and terminology for discussing the launch vehicle conceptual design problem so that the diverse AEE user community can participate in prioritizing the AEE development effort.

Design of future municipal wastewater treatment plants: A mathematical approach to manage complexity and identify optimal solutions

DEFF Research Database (Denmark)

Bozkurt, Hande; Quaglia, Alberto; Gernaey, Krist

The increasing number of alternative wastewater treatment (WWT) technologies and stricter effluent requirements imposed by regulations make the early stage decision making for WWTP layout design, which is currently based on expert decisions and previous experiences, much harder. This paper...... therefore proposes a new approach based on mathematical programming to manage the complexity of the problem and generate/identify novel and optimal WWTP layouts for municipal/domestic wastewater treatment. Towards this end, after developing a database consisting of primary, secondary and tertiary WWT...... solved to obtain the optimal WWT network and the optimal wastewater and sludge flow through the network. The tool is evaluated on a case study, which was chosen as the Benchmark Simulation Model no.1 (BSM1) and many retrofitting options for obtaining a cost-effective treatment were investigated...

Nomogram for 30-day morbidity after primary cytoreductive surgery for advanced stage ovarian cancer.

Science.gov (United States)

Nieuwenhuyzen-de Boer, G M; Gerestein, C G; Eijkemans, M J C; Burger, C W; Kooi, G S

2016-01-01

Extensive surgical procedures to achieve maximal cytoreduction in patients with advanced stage epithelial ovarian cancer (EOC) are inevitably associated with postoperative morbidity and mortality. This study aimed to identify preoperative predictors of 30-day morbidity after primary cytoreductive surgery for advanced stage EOC and to develop a nomogram for individual risk assessment. Patients in The Netherlands who underwent primary cytoreductive surgery for advanced stage EOC between January 2004 and December 2007. All peri- and postoperative complications within 30 days after surgery were registered and classified. To investigate predictors of 30-day morbidity, a Cox proportional hazard model with backward stepwise elimination was utilized. The identified predictors were entered into a nomogram. The main outcome was to identify parameters that predict operative risk. 293 patients entered the study protocol. Optimal cytoreduction was achieved in 136 (46%) patients. Thirty-day morbidity was seen in 99 (34%) patients. Morbidity could be predicted by age (p = 0.033; OR 1.024), preoperative hemoglobin (p = 0.194; OR 0.843), and WHO performance status (p = 0.015; OR 1.821) with a optimism-corrected c-statistic of 0.62. Determinants co-morbidity status, serum CA125 level, platelet count, and presence of ascites were comparable in both groups. Thirty-day morbidity after primary cytoreductive surgery for advanced stage EOC could be predicted by age, hemoglobin, and WHO performance status. The generated nomogram could be valuable for predicting operative risk in the individual patient.

Optimization of wind turbine rotors - using advanced aerodynamic and aeroelastic models and numerical optimization

DEFF Research Database (Denmark)

Døssing, Mads

of very large machines introduces new problems in the practical design, and optimization tools are necessary. These must combine the dynamic eects of both aerodynamics and structure in an integrated optimization environment. This is referred to as aeroelastic optimization. The Ris DTU optimization...... software HAWTOPT has been used in this project. The quasi-steady aerodynamic module have been improved with a corrected blade element momentum method. A structure module has also been developed which lays out the blade structural properties. This is done in a simplied way allowing fast conceptual design...... studies and with focus on the overall properties relevant for the aeroelastic properties. Aeroelastic simulations in the time domain were carried out using the aeroelastic code HAWC2. With these modules coupled to HAWTOPT, optimizations have been made. In parallel with the developments of the mentioned...

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. 

Optimization of wind turbine rotors - using advanced aerodynamic and aeroelastic models and numerical optimization

Energy Technology Data Exchange (ETDEWEB)

Doessing, M.

2011-05-15

During the last decades the annual energy produced by wind turbines has increased dramatically and wind turbines are now available in the 5MW range. Turbines in this range are constantly being developed and it is also being investigated whether turbines as large as 10-20MW are feasible. The design of very large machines introduces new problems in the practical design, and optimization tools are necessary. These must combine the dynamic effects of both aerodynamics and structure in an integrated optimization environment. This is referred to as aeroelastic optimization. The Risoe DTU optimization software HAWTOPT has been used in this project. The quasi-steady aerodynamic module have been improved with a corrected blade element momentum method. A structure module has also been developed which lays out the blade structural properties. This is done in a simplified way allowing fast conceptual design studies and with focus on the overall properties relevant for the aeroelastic properties. Aeroelastic simulations in the time domain were carried out using the aeroelastic code HAWC2. With these modules coupled to HAWTOPT, optimizations have been made. In parallel with the developments of the mentioned numerical modules, focus has been on analysis and a fundamental understanding of the key parameters in wind turbine design. This has resulted in insight and an effective design methodology is presented. Using the optimization environment a 5MW wind turbine rotor has been optimized for reduced fatigue loads due to apwise bending moments. Among other things this has indicated that airfoils for wind turbine blades should have a high lift coefficient. The design methodology proved to be stable and a help in the otherwise challenging task of numerical aeroelastic optimization. (Author)

A probabilistic approach for optimal sensor allocation in structural health monitoring

International Nuclear Information System (INIS)

Azarbayejani, M; Reda Taha, M M; El-Osery, A I; Choi, K K

2008-01-01

Recent advances in sensor technology promote using large sensor networks to efficiently and economically monitor, identify and quantify damage in structures. In structural health monitoring (SHM) systems, the effectiveness and reliability of the sensor network are crucial to determine the optimal number and locations of sensors in SHM systems. Here, we suggest a probabilistic approach for identifying the optimal number and locations of sensors for SHM. We demonstrate a methodology to establish the probability distribution function that identifies the optimal sensor locations such that damage detection is enhanced. The approach is based on using the weights of a neural network trained from simulations using a priori knowledge about damage locations and damage severities to generate a normalized probability distribution function for optimal sensor allocation. We also demonstrate that the optimal sensor network can be related to the highest probability of detection (POD). The redundancy of the proposed sensor network is examined using a 'leave one sensor out' analysis. A prestressed concrete bridge is selected as a case study to demonstrate the effectiveness of the proposed method. The results show that the proposed approach can provide a robust design for sensor networks that are more efficient than a uniform distribution of sensors on a structure

A Multivariate Quality Loss Function Approach for Optimization of Spinning Processes

Science.gov (United States)

Chakraborty, Shankar; Mitra, Ankan

2018-05-01

Recent advancements in textile industry have given rise to several spinning techniques, such as ring spinning, rotor spinning etc., which can be used to produce a wide variety of textile apparels so as to fulfil the end requirements of the customers. To achieve the best out of these processes, they should be utilized at their optimal parametric settings. However, in presence of multiple yarn characteristics which are often conflicting in nature, it becomes a challenging task for the spinning industry personnel to identify the best parametric mix which would simultaneously optimize all the responses. Hence, in this paper, the applicability of a new systematic approach in the form of multivariate quality loss function technique is explored for optimizing multiple quality characteristics of yarns while identifying the ideal settings of two spinning processes. It is observed that this approach performs well against the other multi-objective optimization techniques, such as desirability function, distance function and mean squared error methods. With slight modifications in the upper and lower specification limits of the considered quality characteristics, and constraints of the non-linear optimization problem, it can be successfully applied to other processes in textile industry to determine their optimal parametric settings.

LTE-Advanced Radio and Network Optimization

DEFF Research Database (Denmark)

Velez, Fernando J.; Sousa, Sofia; Flores, Jessica Acevedo

2015-01-01

In cellular optimization, the UL and DL the values from carrier-to-noise-plus-interference ratio (CNIR) from/at the mobile station are very important parameters. From a detailed analysis of its variation with the coverage and reuse distances for different values of the Channel Quality Indicator (...

Design and Optimization of a Composite Canard Control Surface of an Advanced Fighter Aircraft under Static Loading

Directory of Open Access Journals (Sweden)

Shrivastava Sachin

2015-01-01

Full Text Available The minimization of weight and maximization of payload is an ever challenging design procedure for air vehicles. The present study has been carried out with an objective to redesign control surface of an advanced all-metallic fighter aircraft. In this study, the structure made up of high strength aluminum, titanium and ferrous alloys has been attempted to replace by carbon fiber composite (CFC skin, ribs and stiffeners. This study presents an approach towards development of a methodology for optimization of first-ply failure index (FI in unidirectional fibrous laminates using Genetic-Algorithms (GA under quasi-static loading. The GAs, by the application of its operators like reproduction, cross-over, mutation and elitist strategy, optimize the ply-orientations in laminates so as to have minimum FI of Tsai-Wu first-ply failure criterion. The GA optimization procedure has been implemented in MATLAB and interfaced with commercial software ABAQUS using python scripting. FI calculations have been carried out in ABAQUS with user material subroutine (UMAT. The GA's application gave reasonably well-optimized ply-orientations combination at a faster convergence rate. However, the final optimized sequence of ply-orientations is obtained by tweaking the sequences given by GA's based on industrial practices and experience, whenever needed. The present study of conversion of an all metallic structure to partial CFC structure has led to 12% of weight reduction. Therefore, the approach proposed here motivates designer to use CFC with a confidence.

Performance analysis and optimization of an advanced pharmaceutical wastewater treatment plant through a visual basic software tool (PWWT.VB).

Science.gov (United States)

Pal, Parimal; Thakura, Ritwik; Chakrabortty, Sankha

2016-05-01

A user-friendly, menu-driven simulation software tool has been developed for the first time to optimize and analyze the system performance of an advanced continuous membrane-integrated pharmaceutical wastewater treatment plant. The software allows pre-analysis and manipulation of input data which helps in optimization and shows the software performance visually on a graphical platform. Moreover, the software helps the user to "visualize" the effects of the operating parameters through its model-predicted output profiles. The software is based on a dynamic mathematical model, developed for a systematically integrated forward osmosis-nanofiltration process for removal of toxic organic compounds from pharmaceutical wastewater. The model-predicted values have been observed to corroborate well with the extensive experimental investigations which were found to be consistent under varying operating conditions like operating pressure, operating flow rate, and draw solute concentration. Low values of the relative error (RE = 0.09) and high values of Willmott-d-index (d will = 0.981) reflected a high degree of accuracy and reliability of the software. This software is likely to be a very efficient tool for system design or simulation of an advanced membrane-integrated treatment plant for hazardous wastewater.

Optimization of the Phase Advance Between RHIC Interaction Points

CERN Document Server

Tomas, Rogelio

2005-01-01

We consider the scenario of having two identical Interaction Points (IPs) in the Relativistic Heavy Ion Collider (RHIC). The strengths of beam-beam resonances strongly depend on the phase advance between these two IPs and therefore certain phase advances could improve beam lifetime and luminosity. We compute the dynamic aperture as function of the phase advance between these IPs to find the optimum settings. The beam-beam interaction is treated in the weak-strong approximation and a complete non-linear model of the lattice is used. For the current RHIC proton working point (0.69,0.685) the design lattice is found to have the optimum phase advance. However this is not the case for other working points.

Development and Utilization of mathematical Optimization in Advanced Fuel Cycle Systems Analysis

International Nuclear Information System (INIS)

Turinsky, Paul; Hays, Ross

2011-01-01

Over the past sixty years, a wide variety of nuclear power technologies have been theorized, investigated and tested to various degrees. These technologies, if properly applied, could provide a stable, long-term, economical source of CO2-free electric power. However, the recycling of nuclear fuel introduces a degree of coupling between reactor systems which must be accounted for when making long term strategic plans. This work investigates the use of a simulated annealing optimization algorithm coupled together with the VISION fuel cycle simulation model in order to identify attractive strategies from economic, evironmental, non-proliferation and waste-disposal perspectives, which each have associated an objective function. The simulated annealing optimization algorithm works by perturbing the fraction of new reactor capacity allocated to each available reactor type (using a set of heuristic rules) then evaluating the resulting deployment scenario outcomes using the VISION model and the chosen objective functions. These new scenarios, which are either accepted or rejected according the the Metropolis Criterion, are then used as the basis for further perturbations. By repeating this process several thousand times, a family of near-optimal solutions are obtained. Preliminary results from this work using a two-step, Once-through LWR to Full-recycle/FRburner deployment scenario with exponentially increasing electric demand indicate that the algorithm is capable of finding reactor deployment profiles that reduce the long-term-heat waste disposal burden relative to an initial reference scenario. Further work is under way to refine the current results and to extend them to include the other objective functions and to examine the optimization trade-offs that exist between these different objectives.

Development and Utilization of mathematical Optimization in Advanced Fuel Cycle Systems Analysis

Energy Technology Data Exchange (ETDEWEB)

Turinsky, Paul; Hays, Ross

2011-09-02

Over the past sixty years, a wide variety of nuclear power technologies have been theorized, investigated and tested to various degrees. These technologies, if properly applied, could provide a stable, long-term, economical source of CO2-free electric power. However, the recycling of nuclear fuel introduces a degree of coupling between reactor systems which must be accounted for when making long term strategic plans. This work investigates the use of a simulated annealing optimization algorithm coupled together with the VISION fuel cycle simulation model in order to identify attractive strategies from economic, evironmental, non-proliferation and waste-disposal perspectives, which each have associated an objective function. The simulated annealing optimization algorithm works by perturbing the fraction of new reactor capacity allocated to each available reactor type (using a set of heuristic rules) then evaluating the resulting deployment scenario outcomes using the VISION model and the chosen objective functions. These new scenarios, which are either accepted or rejected according the the Metropolis Criterion, are then used as the basis for further perturbations. By repeating this process several thousand times, a family of near-optimal solutions are obtained. Preliminary results from this work using a two-step, Once-through LWR to Full-recycle/FRburner deployment scenario with exponentially increasing electric demand indicate that the algorithm is capable of nding reactor deployment pro les that reduce the long-term-heat waste disposal burden relative to an initial reference scenario. Further work is under way to re ne the current results and to extend them to include the other objective functions and to examine the optimization trade-o s that exist between these di erent objectives.

Optimized ex-ovo culturing of chick embryos to advanced stages of development.

Science.gov (United States)

Cloney, Kellie; Franz-Odendaal, Tamara Anne

2015-01-24

Research in anatomy, embryology, and developmental biology has largely relied on the use of model organisms. In order to study development in live embryos model organisms, such as the chicken, are often used. The chicken is an excellent model organism due to its low cost and minimal maintenance, however they present observational challenges because they are enclosed in an opaque eggshell. In order to properly view the embryo as it develops, the shell must be windowed or removed. Both windowing and ex ovo techniques have been developed to assist researchers in the study of embryonic development. However, each of the methods has limitations and challenges. Here, we present a simple, optimized ex ovo culture technique for chicken embryos that enables the observation of embryonic development from stage HH 19 into late stages of development (HH 40), when many organs have developed. This technique is easy to adopt in both undergraduate classes and more advanced research laboratories where embryo manipulations are conducted.

Full space device optimization for solar cells.

Science.gov (United States)

Baloch, Ahmer A B; Aly, Shahzada P; Hossain, Mohammad I; El-Mellouhi, Fedwa; Tabet, Nouar; Alharbi, Fahhad H

2017-09-20

Advances in computational materials have paved a way to design efficient solar cells by identifying the optimal properties of the device layers. Conventionally, the device optimization has been governed by single or double descriptors for an individual layer; mostly the absorbing layer. However, the performance of the device depends collectively on all the properties of the material and the geometry of each layer in the cell. To address this issue of multi-property optimization and to avoid the paradigm of reoccurring materials in the solar cell field, a full space material-independent optimization approach is developed and presented in this paper. The method is employed to obtain an optimized material data set for maximum efficiency and for targeted functionality for each layer. To ensure the robustness of the method, two cases are studied; namely perovskite solar cells device optimization and cadmium-free CIGS solar cell. The implementation determines the desirable optoelectronic properties of transport mediums and contacts that can maximize the efficiency for both cases. The resulted data sets of material properties can be matched with those in materials databases or by further microscopic material design. Moreover, the presented multi-property optimization framework can be extended to design any solid-state device.

Design and analysis challenges for advanced nuclear fuel

International Nuclear Information System (INIS)

Klepfer, H.; Abdollahian, D.; Dias, A.; Durston, C.; Eisenhart, L.; Engel, R.; Gilmore, P.; Rank, P.; Kjaer-Pedersen, N.; Sorensen, J.; Yang, R.; Agee, L.

2004-01-01

Significant changes have been incorporated in the light water reactor (LWR) fuel designs now being offered, and advanced fuel designs are currently being developed for the existing and the next generation of reactor designs. These advanced fuel design configurations are intended to offer utilities major economic gains, including: (1) improved fuel characteristics through optimized hydrogen to uranium ratio within the core; (2) increased capacity factor by allowing longer operating cycles, which is implemented by increasing the fuel enrichment and the amount and distribution of burnable poison, gadolinia, boron, or erbium within the fuel assembly to achieve higher discharge burnup; and (3) increased plant power output, if it can be accommodated by the balance of plant, by increasing the power density of the fuel assembly. The authors report here work being done to identify emerging technical issues in support of utility industry evaluations of advanced fuel designs. (author)

vProtein: identifying optimal amino acid complements from plant-based foods.

Directory of Open Access Journals (Sweden)

Peter J Woolf

Full Text Available BACKGROUND: Indispensible amino acids (IAAs are used by the body in different proportions. Most animal-based foods provide these IAAs in roughly the needed proportions, but many plant-based foods provide different proportions of IAAs. To explore how these plant-based foods can be better used in human nutrition, we have created the computational tool vProtein to identify optimal food complements to satisfy human protein needs. METHODS: vProtein uses 1251 plant-based foods listed in the United States Department of Agriculture standard release 22 database to determine the quantity of each food or pair of foods required to satisfy human IAA needs as determined by the 2005 daily recommended intake. The quantity of food in a pair is found using a linear programming approach that minimizes total calories, total excess IAAs, or the total weight of the combination. RESULTS: For single foods, vProtein identifies foods with particularly balanced IAA patterns such as wheat germ, quinoa, and cauliflower. vProtein also identifies foods with particularly unbalanced IAA patterns such as macadamia nuts, degermed corn products, and wakame seaweed. Although less useful alone, some unbalanced foods provide unusually good complements, such as Brazil nuts to legumes. Interestingly, vProtein finds no statistically significant bias toward grain/legume pairings for protein complementation. These analyses suggest that pairings of plant-based foods should be based on the individual foods themselves instead of based on broader food group-food group pairings. Overall, the most efficient pairings include sweet corn/tomatoes, apple/coconut, and sweet corn/cherry. The top pairings also highlight the utility of less common protein sources such as the seaweeds laver and spirulina, pumpkin leaves, and lambsquarters. From a public health perspective, many of the food pairings represent novel, low cost food sources to combat malnutrition. Full analysis results are available online

Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

Science.gov (United States)

Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

MO-FG-207-00: Technological Advances in PET/MR Imaging

International Nuclear Information System (INIS)

2015-01-01

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee

MO-FG-207-00: Technological Advances in PET/MR Imaging

Energy Technology Data Exchange (ETDEWEB)

NONE

2015-06-15

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

Nomogram for suboptimal cytoreduction at primary surgery for advanced stage ovarian cancer.

Science.gov (United States)

Gerestein, Cornelis G; Eijkemans, Marinus J; Bakker, Jeanette; Elgersma, Otto E; van der Burg, Maria E L; Kooi, Geertruida S; Burger, Curt W

2011-11-01

Maximal cytoreduction to minimal residual tumor is the most important determinant of prognosis in patients with advanced stage epithelial ovarian cancer (EOC). Preoperative prediction of suboptimal cytoreduction, defined as residual tumor >1 cm, could guide treatment decisions and improve counseling. The objective of this study was to identify predictive computed tomographic (CT) scan and clinical parameters for suboptimal cytoreduction at primary cytoreductive surgery for advanced stage EOC and to generate a nomogram with the identified parameters, which would be easy to use in daily clinical practice. Between October 2005 and December 2008, all patients with primary surgery for suspected advanced stage EOC at six participating teaching hospitals in the South Western part of the Netherlands entered the study protocol. To investigate independent predictors of suboptimal cytoreduction, a Cox proportional hazard model with backward stepwise elimination was utilized. One hundred and fifteen patients with FIGO stage III/IV EOC entered the study protocol. Optimal cytoreduction was achieved in 52 (45%) patients. A suboptimal cytoreduction was predicted by preoperative blood platelet count (p=0.1990; odds ratio (OR)=1.002), diffuse peritoneal thickening (DPT) (p=0.0074; OR=3.021), and presence of ascites on at least two thirds of CT scan slices (p=0.0385; OR=2.294) with a for-optimism corrected c-statistic of 0.67. Suboptimal cytoreduction was predicted by preoperative platelet count, DPT and presence of ascites. The generated nomogram can, after external validation, be used to estimate surgical outcome and to identify those patients, who might benefit from alternative treatment approaches.

Ten years of "Optimal Therapy in Advanced Ovarian Cancer. Update" meeting.

Science.gov (United States)

Poveda, A

2008-01-01

The International Symposium on Advanced Ovarian Cancer: Optimal Therapy was founded by Dr. Andrés Poveda and Prof. Jan B. Vermorken, and each edition has been directed by them. The 6th edition was held on March 2, 2007. This symposium is organized every other year by GEICO (Grupo Español de Investigación de Cáncer de Ovario/Spanish Ovarian Cancer Research Group), under the auspices of the Spanish Society of Medical Oncology (SEOM), the Gynecologic Cancer Intergroup (GCIG), and the European Society of Medical Oncology (ESMO) Educational Committee for its Medical Oncology Recertification Approval (ESMO/MORA) Program. One hundred and fifty people attended the symposium's 1st edition, held in 1996. Since then, the interest in this meeting has increased. Last year, almost three hundred people coming not only from Spain but also from Europe, North and Latin America, Asia, and Australia were present in the symposium. This is a great challenge for us. Some important international cooperative groups from Europe, America, and Australia collaborate with this symposium, such as GOG, NCIC, EORTC, AGO, Scottish Group, ICON, GINECO, NSGO, ANZGOG, and others.

Optimizing the regimes of the Advanced LIGO gravitational wave detector for multiple source types

International Nuclear Information System (INIS)

Kondrashov, I. S.; Simakov, D. A.; Khalili, F. Ya.; Danilishin, S. L.

2008-01-01

We developed algorithms which allow us to find regimes of the signal-recycled Fabry-Perot-Michelson interferometer [for example, the Advanced Laser Interferometric Gravitational Wave Observatory (LIGO)], optimized concurrently for two (binary inspirals + bursts) and three (binary inspirals + bursts + millisecond pulsars) types of gravitational wave sources. We show that there exists a relatively large area in the interferometer parameters space where the detector sensitivity to the first two kinds of sources differs only by a few percent from the maximal ones for each kind of source. In particular, there exists a specific regime where this difference is ≅0.5% for both of them. Furthermore, we show that even more multipurpose regimes are also possible that provide significant sensitivity gain for millisecond pulsars with only minor sensitivity degradation for binary inspirals and bursts.

Advanced CANDU reactors fuel analysis through optimal fuel management at approach to refuelling equilibrium

International Nuclear Information System (INIS)

Tingle, C.P.; Bonin, H.W.

1999-01-01

The analysis of alternate CANDU fuels along with natural uranium-based fuel was carried out from the view point of optimal in-core fuel management at approach to refuelling equilibrium. The alternate fuels considered in the present work include thorium containing oxide mixtures (MOX), plutonium-based MOX, and Pressurised Water Reactor (PWR) spent fuel recycled in CANDU reactors (Direct Use of spent PWR fuel in CANDU (DUPIC)); these are compared with the usual natural UO 2 fuel. The focus of the study is on the 'Approach to Refuelling Equilibrium' period which immediately follows the initial commissioning of the reactor. The in-core fuel management problem for this period is treated as an optimization problem in which the objective function is the refuelling frequency to be minimized by adjusting the following decision variables: the channel to be refuelled next, the time of the refuelling and the number of fresh fuel bundles to be inserted in the channel. Several constraints are also included in the optimisation problem which is solved using Perturbation Theory. Both the present 37-rod CANDU fuel bundle and the proposed CANFLEX bundle designs are part of this study. The results include the time to reach refuelling equilibrium from initial start-up of the reactor, the average discharge burnup, the average refuelling frequency and the average channel and bundle powers relative to natural UO 2 . The model was initially tested and the average discharge burnup for natural UO 2 came within 2% of the industry accepted 199 MWh/kgHE. For this type of fuel, the optimization exercise predicted the savings of 43 bundles per full power year. In addition to producing average discharge burnups and other parameters for the advanced fuels investigated, the optimisation model also evidenced some problem areas like high power densities for fuels such as the DUPIC. Perturbation Theory has proven itself to be an accurate and valuable optimization tool in predicting the time between

Identifying and addressing specific student difficulties in advanced thermal physics

Science.gov (United States)

Smith, Trevor I.

As part of an ongoing multi-university research study on student understanding of concepts in thermal physics at the upper division, I identified several student difficulties with topics related to heat engines (especially the Carnot cycle), as well as difficulties related to the Boltzmann factor. In an effort to address these difficulties, I developed two guided-inquiry worksheet activities (a.k.a. tutorials) for use in advanced undergraduate thermal physics courses. Both tutorials seek to improve student understanding of the utility and physical background of a particular mathematical expression. One tutorial focuses on a derivation of Carnot's theorem regarding the limit on thermodynamic efficiency, starting from the Second Law of Thermodynamics. The other tutorial helps students gain an appreciation for the origin of the Boltzmann factor and when it is applicable; focusing on the physical justification of its mathematical derivation, with emphasis on the connections between probability, multiplicity, entropy, and energy. Student understanding of the use and physical implications of Carnot's theorem and the Boltzmann factor was assessed using written surveys both before and after tutorial instruction within the advanced thermal physics courses at the University of Maine and at other institutions. Classroom tutorial sessions at the University of Maine were videotaped to allow in-depth scrutiny of student successes and failures following tutorial prompts. I also interviewed students on various topics related to the Boltzmann factor to gain a more complete picture of their understanding and inform tutorial revisions. Results from several implementations of my tutorials at the University of Maine indicate that students did not have a robust understanding of these physical principles after lectures alone, and that they gain a better understanding of relevant topics after tutorial instruction; Fisher's exact tests yield statistically significant improvement at the

Multi-net optimization of VLSI interconnect

CERN Document Server

Moiseev, Konstantin; Wimer, Shmuel

2015-01-01

This book covers layout design and layout migration methodologies for optimizing multi-net wire structures in advanced VLSI interconnects. Scaling-dependent models for interconnect power, interconnect delay and crosstalk noise are covered in depth, and several design optimization problems are addressed, such as minimization of interconnect power under delay constraints, or design for minimal delay in wire bundles within a given routing area. A handy reference or a guide for design methodologies and layout automation techniques, this book provides a foundation for physical design challenges of interconnect in advanced integrated circuits.  • Describes the evolution of interconnect scaling and provides new techniques for layout migration and optimization, focusing on multi-net optimization; • Presents research results that provide a level of design optimization which does not exist in commercially-available design automation software tools; • Includes mathematical properties and conditions for optimal...

Co-Optimization of Fuels and Engines

Energy Technology Data Exchange (ETDEWEB)

Farrell, John

2016-04-11

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a new DOE initiative focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) are designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, ten national laboratories, and numerous industry and academic partners to simultaneously tackle fuel and engine research and development (R&D) to maximize energy savings and on-road vehicle performance while dramatically reducing transportation-related petroleum consumption and greenhouse gas (GHG) emissions. This multi-year project will provide industry with the scientific underpinnings required to move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions. This presentation provides an overview of the initiative and reviews recent progress focused on both advanced spark-ignition and compression-ignition approaches.

Advanced Variance Reduction Strategies for Optimizing Mesh Tallies in MAVRIC

International Nuclear Information System (INIS)

Peplow, Douglas E.; Blakeman, Edward D; Wagner, John C

2007-01-01

More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficiently optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS)

Optimization of programming parameters in children with the advanced bionics cochlear implant.

Science.gov (United States)

Baudhuin, Jacquelyn; Cadieux, Jamie; Firszt, Jill B; Reeder, Ruth M; Maxson, Jerrica L

2012-05-01

Cochlear implants provide access to soft intensity sounds and therefore improved audibility for children with severe-to-profound hearing loss. Speech processor programming parameters, such as threshold (or T-level), input dynamic range (IDR), and microphone sensitivity, contribute to the recipient's program and influence audibility. When soundfield thresholds obtained through the speech processor are elevated, programming parameters can be modified to improve soft sound detection. Adult recipients show improved detection for low-level sounds when T-levels are set at raised levels and show better speech understanding in quiet when wider IDRs are used. Little is known about the effects of parameter settings on detection and speech recognition in children using today's cochlear implant technology. The overall study aim was to assess optimal T-level, IDR, and sensitivity settings in pediatric recipients of the Advanced Bionics cochlear implant. Two experiments were conducted. Experiment 1 examined the effects of two T-level settings on soundfield thresholds and detection of the Ling 6 sounds. One program set T-levels at 10% of most comfortable levels (M-levels) and another at 10 current units (CUs) below the level judged as "soft." Experiment 2 examined the effects of IDR and sensitivity settings on speech recognition in quiet and noise. Participants were 11 children 7-17 yr of age (mean 11.3) implanted with the Advanced Bionics High Resolution 90K or CII cochlear implant system who had speech recognition scores of 20% or greater on a monosyllabic word test. Two T-level programs were compared for detection of the Ling sounds and frequency modulated (FM) tones. Differing IDR/sensitivity programs (50/0, 50/10, 70/0, 70/10) were compared using Ling and FM tone detection thresholds, CNC (consonant-vowel nucleus-consonant) words at 50 dB SPL, and Hearing in Noise Test for Children (HINT-C) sentences at 65 dB SPL in the presence of four-talker babble (+8 signal

Measuring the influence of a mental health training module on the therapeutic optimism of advanced nurse practitioner students in the United Kingdom.

Science.gov (United States)

Hemingway, Steve; Rogers, Melanie; Elsom, Stephen

2014-03-01

To evaluate the influence of a mental health training module on the therapeutic optimism of advanced nurse practitioner (ANP) students in primary care (family practice). Three cohorts of ANPs who undertook a Mental Health Problems in Primary Care Module as part of their MSc ANP (primary care) run by the University of Huddersfield completed the Elsom Therapeutic Optimism Scale (ETOS), in a pre- and postformat. The ETOS is a 10-item, self-administered scale, which has been used to evaluate therapeutic optimism previously in mental health professionals. All three cohorts who completed the scale showed an improvement in their therapeutic optimism scores. With stigma having such a detrimental effect for people diagnosed with a mental health problem, ANPs who are more mental health literate facilitated by education and training in turn facilitates them to have the skills and confidence to engage and inspire hope for the person diagnosed with mental health problems. ©2013 The Author(s) ©2013 American Association of Nurse Practitioners.

Free-boundary simulations of ITER advanced scenarios

International Nuclear Information System (INIS)

Besseghir, K.

2013-06-01

The successful operation of ITER advanced scenarios is likely to be a major step forward in the development of controlled fusion as a power production source. ITER advanced scenarios raise specific challenges that are not encountered in presently-operated tokamaks. In this thesis, it is argued that ITER advanced operation may benefit from optimal control techniques. Optimal control ensures high performance operation while guaranteeing tokamak integrity. The application of optimal control techniques for ITER operation is assessed and it is concluded that robust optimisation is appropriate for ITER operation of advanced scenarios. Real-time optimisation schemes are discussed and it is concluded that the necessary conditions of optimality tracking approach may potentially be appropriate for ITER operation, thus offering a viable closed-loop optimal control approach. Simulations of ITER advanced operation are necessary in order to assess the present ITER design and uncover the main difficulties that may be encountered during advanced operation. The DINA-CH and CRONOS full tokamak simulator is used to simulate the operation of the ITER hybrid and steady-state scenarios. It is concluded that the present ITER design is appropriate for performing a hybrid scenario pulse lasting more than 1000 sec, with a flat-top plasma current of 12 MA, and a fusion gain of Q ≅ 8. Similarly, a steady-state scenario without internal transport barrier, with a flat-top plasma current of 10 MA, and with a fusion gain of Q ≅ 5 can be realised using the present ITER design. The sensitivity of the advanced scenarios with respect to transport models and physical assumption is assessed using CRONOS. It is concluded that the hybrid scenario and the steady-state scenario are highly sensitive to the L-H transition timing, to the value of the confinement enhancement factor, to the heating and current drive scenario during ramp-up, and, to a lesser extent, to the density peaking and pedestal

Free-boundary simulations of ITER advanced scenarios

Energy Technology Data Exchange (ETDEWEB)

Besseghir, K.

2013-06-15

The successful operation of ITER advanced scenarios is likely to be a major step forward in the development of controlled fusion as a power production source. ITER advanced scenarios raise specific challenges that are not encountered in presently-operated tokamaks. In this thesis, it is argued that ITER advanced operation may benefit from optimal control techniques. Optimal control ensures high performance operation while guaranteeing tokamak integrity. The application of optimal control techniques for ITER operation is assessed and it is concluded that robust optimisation is appropriate for ITER operation of advanced scenarios. Real-time optimisation schemes are discussed and it is concluded that the necessary conditions of optimality tracking approach may potentially be appropriate for ITER operation, thus offering a viable closed-loop optimal control approach. Simulations of ITER advanced operation are necessary in order to assess the present ITER design and uncover the main difficulties that may be encountered during advanced operation. The DINA-CH and CRONOS full tokamak simulator is used to simulate the operation of the ITER hybrid and steady-state scenarios. It is concluded that the present ITER design is appropriate for performing a hybrid scenario pulse lasting more than 1000 sec, with a flat-top plasma current of 12 MA, and a fusion gain of Q ≅ 8. Similarly, a steady-state scenario without internal transport barrier, with a flat-top plasma current of 10 MA, and with a fusion gain of Q ≅ 5 can be realised using the present ITER design. The sensitivity of the advanced scenarios with respect to transport models and physical assumption is assessed using CRONOS. It is concluded that the hybrid scenario and the steady-state scenario are highly sensitive to the L-H transition timing, to the value of the confinement enhancement factor, to the heating and current drive scenario during ramp-up, and, to a lesser extent, to the density peaking and pedestal

Use of advanced modeling techniques to optimize thermal packaging designs.

Science.gov (United States)

Formato, Richard M; Potami, Raffaele; Ahmed, Iftekhar

2010-01-01

Through a detailed case study the authors demonstrate, for the first time, the capability of using advanced modeling techniques to correctly simulate the transient temperature response of a convective flow-based thermal shipper design. The objective of this case study was to demonstrate that simulation could be utilized to design a 2-inch-wall polyurethane (PUR) shipper to hold its product box temperature between 2 and 8 °C over the prescribed 96-h summer profile (product box is the portion of the shipper that is occupied by the payload). Results obtained from numerical simulation are in excellent agreement with empirical chamber data (within ±1 °C at all times), and geometrical locations of simulation maximum and minimum temperature match well with the corresponding chamber temperature measurements. Furthermore, a control simulation test case was run (results taken from identical product box locations) to compare the coupled conduction-convection model with a conduction-only model, which to date has been the state-of-the-art method. For the conduction-only simulation, all fluid elements were replaced with "solid" elements of identical size and assigned thermal properties of air. While results from the coupled thermal/fluid model closely correlated with the empirical data (±1 °C), the conduction-only model was unable to correctly capture the payload temperature trends, showing a sizeable error compared to empirical values (ΔT > 6 °C). A modeling technique capable of correctly capturing the thermal behavior of passively refrigerated shippers can be used to quickly evaluate and optimize new packaging designs. Such a capability provides a means to reduce the cost and required design time of shippers while simultaneously improving their performance. Another advantage comes from using thermal modeling (assuming a validated model is available) to predict the temperature distribution in a shipper that is exposed to ambient temperatures which were not bracketed

Advanced Gradient Based Optimization Techniques Applied on Sheet Metal Forming

International Nuclear Information System (INIS)

Endelt, Benny; Nielsen, Karl Brian

2005-01-01

The computational-costs for finite element simulations of general sheet metal forming processes are considerable, especially measured in time. In combination with optimization, the performance of the optimization algorithm is crucial for the overall performance of the system, i.e. the optimization algorithm should gain as much information about the system in each iteration as possible. Least-square formulation of the object function is widely applied for solution of inverse problems, due to the superior performance of this formulation.In this work focus will be on small problems which are defined as problems with less than 1000 design parameters; as the majority of real life optimization and inverse problems, represented in literature, can be characterized as small problems, typically with less than 20 design parameters.We will show that the least square formulation is well suited for two classes of inverse problems; identification of constitutive parameters and process optimization.The scalability and robustness of the approach are illustrated through a number of process optimizations and inverse material characterization problems; tube hydro forming, two step hydro forming, flexible aluminum tubes, inverse identification of material parameters

ACR-700 advanced technologies

International Nuclear Information System (INIS)

Tapping, R.L.; Turner, C.W.; Yu, S.K.W.; Olmstead, R.; Speranzini, R.A.

2004-01-01

A successful advanced reactor plant will have optimized economics including reduced operating and maintenance costs, improved performance, and enhanced safety. Incorporating improvements based on advanced technologies ensures cost, safety and operational competitiveness of the ACR-700. These advanced technologies include modern configuration management; construction technologies; operational technology for the control centre and information systems for plant monitoring and analysis. This paper summarizes the advanced technologies used to achieve construction and operational improvements to enhance plant economic competitiveness, advances in the operational technology used for reactor control, and presents the development of the Smart CANDU suite of tools and its application to existing operating reactors and to the ACR-700. (author)

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 ...

Practical mathematical optimization basic optimization theory and gradient-based algorithms

CERN Document Server

Snyman, Jan A

2018-01-01

This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are presented with emphasis on gradient-based numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradient-based methods. This second edition addresses further advancements of gradient-only optimization strategies to handle discontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies and numerical optimization using Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and dir...

Optimizing Aspect-Oriented Mechanisms for Embedded Applications

Science.gov (United States)

Hundt, Christine; Stöhr, Daniel; Glesner, Sabine

As applications for small embedded mobile devices are getting larger and more complex, it becomes inevitable to adopt more advanced software engineering methods from the field of desktop application development. Aspect-oriented programming (AOP) is a promising approach due to its advanced modularization capabilities. However, existing AOP languages tend to add a substantial overhead in both execution time and code size which restricts their practicality for small devices with limited resources. In this paper, we present optimizations for aspect-oriented mechanisms at the level of the virtual machine. Our experiments show that these optimizations yield a considerable performance gain along with a reduction of the code size. Thus, our optimizations establish the base for using advanced aspect-oriented modularization techniques for developing Java applications on small embedded devices.

Optimal cut points for quality of life questionnaire-core 30 (QLQ-C30) scales: utility for clinical trials and updates of prognostic systems in advanced hepatocellular carcinoma.

Science.gov (United States)

Diouf, Momar; Bonnetain, Franck; Barbare, Jean-Claude; Bouché, Olivier; Dahan, Laetitia; Paoletti, Xavier; Filleron, Thomas

2015-01-01

Health-related quality of life (QoL) has been validated as a prognostic factor for cancer patients; however, to be used in routine practice, QoL scores must be dichotomized. Cutoff points are usually based on arbitrary percentile values. We aimed to identify optimal cutoff points for six QoL scales and to quantify their added utility in the performance of four prognostic classifications in patients with hepatocellular carcinoma (HCC). We reanalyzed data of 271 patients with advanced HCC recruited between July 2002 and October 2003 from 79 institutions in France in the CHOC trial, designed to assess the efficacy of long-acting octreotide. QoL was assessed with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (QLQ-C30). The scores ranged from 0 to 100. Identification of optimal cutoff points was based on the method of Faraggi and Simon [Stat Med 1996;15:2203-2213]. Improvement in the performance of prognostic classifications was studied with Harrell's C-index, the net reclassification improvement (NRI), and integrated discrimination improvement (IDI). We found that optimal cutoff points were 50 for global health, 58.33 for physical functioning, 66.67 for role functioning, 66.67 for fatigue, 0 for dyspnea, and 33.33 for diarrhea. The addition of QoL and clinical factors improved the performance of all four prognostic classifications, with improvement in the range of 0.02-0.09 for the C-index, 0.24-0.78 for 3-month NRI, and 0.02-0.10 for IDI. These cutoff values for QoL scales can be useful to identify HCC patients with very poor prognosis and thus improve design of clinical trials and treatment adjustment for these patients. ©AlphaMed Press.

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.

An Advanced Coupled Genetic Algorithm for Identifying Unknown Moving Loads on Bridge Decks

Directory of Open Access Journals (Sweden)

Sang-Youl Lee

2014-01-01

Full Text Available This study deals with an inverse method to identify moving loads on bridge decks using the finite element method (FEM and a coupled genetic algorithm (c-GA. We developed the inverse technique using a coupled genetic algorithm that can make global solution searches possible as opposed to classical gradient-based optimization techniques. The technique described in this paper allows us to not only detect the weight of moving vehicles but also find their moving velocities. To demonstrate the feasibility of the method, the algorithm is applied to a bridge deck model with beam elements. In addition, 1D and 3D finite element models are simulated to study the influence of measurement errors and model uncertainty between numerical and real structures. The results demonstrate the excellence of the method from the standpoints of computation efficiency and avoidance of premature convergence.

Advanced hardware design for error correcting codes

CERN Document Server

Coussy, Philippe

2015-01-01

This book provides thorough coverage of error correcting techniques. It includes essential basic concepts and the latest advances on key topics in design, implementation, and optimization of hardware/software systems for error correction. The book’s chapters are written by internationally recognized experts in this field. Topics include evolution of error correction techniques, industrial user needs, architectures, and design approaches for the most advanced error correcting codes (Polar Codes, Non-Binary LDPC, Product Codes, etc). This book provides access to recent results, and is suitable for graduate students and researchers of mathematics, computer science, and engineering. • Examines how to optimize the architecture of hardware design for error correcting codes; • Presents error correction codes from theory to optimized architecture for the current and the next generation standards; • Provides coverage of industrial user needs advanced error correcting techniques.

An optimization methodology for identifying robust process integration investments under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden); Patriksson, Michael [Department of Mathematical Sciences, Chalmers University of Technology and Department of Mathematical Sciences, University of Gothenburg, SE-412 96 Goeteborg (Sweden)

2009-02-15

Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

An optimization methodology for identifying robust process integration investments under uncertainty

International Nuclear Information System (INIS)

Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith; Patriksson, Michael

2009-01-01

Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)

European advanced driver training programs: Reasons for optimism

Directory of Open Access Journals (Sweden)

Simon Washington

2011-03-01

This paper reviews the predominant features and empirical evidence surrounding post licensing advanced driver training programs focused on novice drivers. A clear articulation of differences between the renewed and current US advanced driver training programs is provided. While the individual quantitative evaluations range from marginally to significantly effective in reducing novice driver crash risk, they have been criticized for evaluation deficiencies ranging from small sample sizes to confounding variables to lack of exposure metrics. Collectively, however, the programs sited in the paper suggest at least a marginally positive effect that needs to be validated with further studies. If additional well controlled studies can validate these programs, a pilot program in the US should be considered.

Technological advances for interrogating the human kinome.

Science.gov (United States)

Baharani, Akanksha; Trost, Brett; Kusalik, Anthony; Napper, Scott

2017-02-08

There is increasing appreciation among researchers and clinicians of the value of investigating biology and pathobiology at the level of cellular kinase (kinome) activity. Kinome analysis provides valuable opportunity to gain insights into complex biology (including disease pathology), identify biomarkers of critical phenotypes (including disease prognosis and evaluation of therapeutic efficacy), and identify targets for therapeutic intervention through kinase inhibitors. The growing interest in kinome analysis has fueled efforts to develop and optimize technologies that enable characterization of phosphorylation-mediated signaling events in a cost-effective, high-throughput manner. In this review, we highlight recent advances to the central technologies currently available for kinome profiling and offer our perspectives on the key challenges remaining to be addressed. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Giga-Voxel Structural Optimization

DEFF Research Database (Denmark)

Aage, Niels; Andreassen, Erik; Lazarov, Boyan Stefanov

2017-01-01

The optimal topology of large structural systems has until now been concerned with the design of individual parts and not that of complete assemblies. However, due to recent advances in numerical algorithms tailored for large scale structural optimization this limitation can now be circumvented....... In this work we present several examplesdisplaying how high resolution topology optimization can be used to obtain new, as well as already known, insight within the field of structural optimization. To demonstrate the capabilities of the developed framework we apply it to the design of the supporting structure...... topology optimization provides new insight and possible weight savings forfuture aircraft designs....

The Theory of Optimal Taxation

DEFF Research Database (Denmark)

Sørensen, Peter Birch

The paper discusses the implications of optimal tax theory for the debates on uniform commodity taxation and neutral capital income taxation. While strong administrative and political economy arguments in favor of uniform and neutral taxation remain, recent advances in optimal tax theory suggest...... that the information needed to implement the differentiated taxation prescribed by optimal tax theory may be easier to obtain than previously believed. The paper also points to the strong similarity between optimal commodity tax rules and the rules for optimal source-based capital income taxation...

The theory of optimal taxation

DEFF Research Database (Denmark)

Sørensen, Peter Birch

2007-01-01

The paper discusses the implications of optimal tax theory for the debates on uniform commodity taxation and neutral capital income taxation. While strong administrative and political economy arguments in favor of uniform and neutral taxation remain, recent advances in optimal tax theory suggest...... that the information needed to implement the differentiated taxation prescribed by optimal tax theory may be easier to obtain than previously believed. The paper also points to the strong similarity between optimal commodity tax rules and the rules for optimal source-based capital income taxation...

Identifying the optimal depth for mussel suspended culture in shallow and turbid environments

DEFF Research Database (Denmark)

Filgueira, Ramón; Grant, Jon; Petersen, Jens Kjerulf

2017-01-01

on farm productivity, farmers must position the cultured biomass at the appropriate depth to benefit from or mitigate the impact of this resuspended material. A combination of field measurements, a 1-D vertical resuspension model and a bioenergetic model for mussels based on Dynamic Energy Budget (DEB...... particles for cultured bivalves. The effect of resuspended material on bivalve bioenergetics and growth is a function of the quality and concentration of resuspended particles and background diet in the water column. Given the potential for positive or negative impacts on bivalve growth and consequently......) theory has been carried out for a mussel farm in Skive Fjord, a shallow Danish fjord, with the aim of identifying the optimal depth for culture. Observations at the farm location revealed that horizontal advection is more important than vertical resuspension during periods with predominant Eastern winds...

Risk management of energy system for identifying optimal power mix with financial-cost minimization and environmental-impact mitigation under uncertainty

International Nuclear Information System (INIS)

Nie, S.; Li, Y.P.; Liu, J.; Huang, Charley Z.

2017-01-01

An interval-stochastic risk management (ISRM) method is launched to control the variability of the recourse cost as well as to capture the notion of risk in stochastic programming. The ISRM method can examine various policy scenarios that are associated with economic penalties under uncertainties presented as probability distributions and interval values. An ISRM model is then formulated to identify the optimal power mix for the Beijing's energy system. Tradeoffs between risk and cost are evaluated, indicating any change in targeted cost and risk level would yield different expected costs. Results reveal that the inherent uncertainty of system components and risk attitude of decision makers have significant effects on the city's energy-supply and electricity-generation schemes as well as system cost and probabilistic penalty. Results also disclose that import electricity as a recourse action to compensate the local shortage would be enforced. The import electricity would increase with a reduced risk level; under every risk level, more electricity would be imported with an increased demand. The findings can facilitate the local authority in identifying desired strategies for the city's energy planning and management in association with financial-cost minimization and environmental-impact mitigation. - Highlights: • Interval-stochastic risk management method is launched to identify optimal power mix. • It is advantageous in capturing the notion of risk in stochastic programming. • Results reveal that risk attitudes can affect optimal power mix and financial cost. • Developing renewable energies would enhance the sustainability of energy management. • Import electricity as an action to compensate the local shortage would be enforced.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

Science.gov (United States)

Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

2016-01-01

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

Directory of Open Access Journals (Sweden)

Nadia Said

Full Text Available Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Sensitivity Analysis and Optimization of the Nuclear Fuel Cycle: A Systematic Approach

Science.gov (United States)

Passerini, Stefano

For decades, nuclear energy development was based on the expectation that recycling of the fissionable materials in the used fuel from today's light water reactors into advanced (fast) reactors would be implemented as soon as technically feasible in order to extend the nuclear fuel resources. More recently, arguments have been made for deployment of fast reactors in order to reduce the amount of higher actinides, hence the longevity of radioactivity, in the materials destined to a geologic repository. The cost of the fast reactors, together with concerns about the proliferation of the technology of extraction of plutonium from used LWR fuel as well as the large investments in construction of reprocessing facilities have been the basis for arguments to defer the introduction of recycling technologies in many countries including the US. In this thesis, the impacts of alternative reactor technologies on the fuel cycle are assessed. Additionally, metrics to characterize the fuel cycles and systematic approaches to using them to optimize the fuel cycle are presented. The fuel cycle options of the 2010 MIT fuel cycle study are re-examined in light of the expected slower rate of growth in nuclear energy today, using the CAFCA (Code for Advanced Fuel Cycle Analysis). The Once Through Cycle (OTC) is considered as the base-line case, while advanced technologies with fuel recycling characterize the alternative fuel cycle options available in the future. The options include limited recycling in L WRs and full recycling in fast reactors and in high conversion LWRs. Fast reactor technologies studied include both oxide and metal fueled reactors. Additional fuel cycle scenarios presented for the first time in this work assume the deployment of innovative recycling reactor technologies such as the Reduced Moderation Boiling Water Reactors and Uranium-235 initiated Fast Reactors. A sensitivity study focused on system and technology parameters of interest has been conducted to test

A computational technique to identify the optimal stiffness matrix for a discrete nuclear fuel assembly model

International Nuclear Information System (INIS)

Park, Nam-Gyu; Kim, Kyoung-Joo; Kim, Kyoung-Hong; Suh, Jung-Min

2013-01-01

Highlights: ► An identification method of the optimal stiffness matrix for a fuel assembly structure is discussed. ► The least squares optimization method is introduced, and a closed form solution of the problem is derived. ► The method can be expanded to the system with the limited number of modes. ► Identification error due to the perturbed mode shape matrix is analyzed. ► Verification examples show that the proposed procedure leads to a reliable solution. -- Abstract: A reactor core structural model which is used to evaluate the structural integrity of the core contains nuclear fuel assembly models. Since the reactor core consists of many nuclear fuel assemblies, the use of a refined fuel assembly model leads to a considerable amount of computing time for performing nonlinear analyses such as the prediction of seismic induced vibration behaviors. The computational time could be reduced by replacing the detailed fuel assembly model with a simplified model that has fewer degrees of freedom, but the dynamic characteristics of the detailed model must be maintained in the simplified model. Such a model based on an optimal design method is proposed in this paper. That is, when a mass matrix and a mode shape matrix are given, the optimal stiffness matrix of a discrete fuel assembly model can be estimated by applying the least squares minimization method. The verification of the method is completed by comparing test results and simulation results. This paper shows that the simplified model's dynamic behaviors are quite similar to experimental results and that the suggested method is suitable for identifying reliable mathematical model for fuel assemblies

Workshop on Computational Optimization

CERN Document Server

2015-01-01

Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2013. It presents recent advances in computational optimization. The volume includes important real life problems like parameter settings for controlling processes in bioreactor, resource constrained project scheduling, problems arising in transport services, error correcting codes, optimal system performance and energy consumption and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others.

Motion feedback in advanced driving manoeuvres

NARCIS (Netherlands)

Correia Grácio, B.; Wentink, M.; Feenstra, P.J; Mulder, M.; Paassen M.M. van; Bles, W.

2009-01-01

During advanced driving manoeuvres, drivers can be hypothesized to use all the available cues to optimize their performance. Fixed-base simulators are commonly used for training of these advanced driving manoeuvres, despite the fact that motion cues are not present. In this experiment we hypothesize

An outline of a model-based expert system to identify optimal remedial strategies for restoring contaminated acquatic ecosystems: The project ``moira``

Energy Technology Data Exchange (ETDEWEB)

Appelgren, A.; Bergstrom, U. [Studsvik Eco and AB, Nykoping (Sweden); Brittain, J. [Oslo Univ. (Norway). LFI Zoological Museum; Gallego Diaz, E. [Madrid Universidad Politecnica (Spain). Dept. de Ingenieria Nuclear; Hakanson, L. [KEMA Nuclear, Arnhem (Niger); Monte, L. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Ambiente

1996-10-01

The present report describes the fundamental principles of the research programme MOIRA (a model based computerized system for management support to Identify optimal remedial strategies for Restoring radionuclide contaminated Aquatic ecosystems and drainage areas) financed by the EC (European Community) (Contract N F14P-CT96-0036). The interventions to restore radionuclides contaminated aquatic systems may result in detrimental ecological, social and economical effects. Decision makers must carefully evaluate these impacts. The main aim of the MOIRA project is the development of an expert system based on validated models predicting the evolution of the radioactive contamination of fresh water systems following countermeasure applications and their relevant ecological, social and economical impacts. The expert system will help decision makers, that are not necessarily gifted with experience in environmental modeling, to identify optimal remedial strategies for restoring contaminated fresh water systems.

An outline of a model-based expert system to identify optimal remedial strategies for restoring contaminated aquatic ecosystems: the project MOIRA

International Nuclear Information System (INIS)

Appelgren, A.; Bergstrom, U.; Brittain, J.; Monte, L.

1996-10-01

The present report describes the fundamental principles of the research programme MOIRA (a model based computerized system for management support to Identify optimal remedial strategies for Restoring radionuclide contaminated Aquatic ecosystems and drainage areas) financed by the EC (European Community) (Contract N F14P-CT96-0036). The interventions to restore radionuclides contaminated aquatic systems may result in detrimental ecological, social and economical effects. Decision makers must carefully evaluate these impacts. The main aim of the MOIRA project is the development of an expert system based on validated models predicting the evolution of the radioactive contamination of fresh water systems following countermeasure applications and their relevant ecological, social and economical impacts. The expert system will help decision makers, that are not necessarily gifted with experience in environmental modeling, to identify optimal remedial strategies for restoring contaminated fresh water systems

Recent experience with multidisciplinary analysis and optimization in advanced aircraft design

Science.gov (United States)

Dollyhigh, Samuel M.; Sobieszczanski-Sobieski, Jaroslaw

1990-01-01

The task of modern aircraft design has always been complicated due to the number of intertwined technical factors from the various engineering disciplines. Furthermore, this complexity has been rapidly increasing by the development of such technologies as aeroelasticity tailored materials and structures, active control systems, integrated propulsion/airframe controls, thrust vectoring, and so on. Successful designs that achieve maximum advantage from these new technologies require a thorough understanding of the physical phenomena and the interactions among these phenomena. A study commissioned by the Aeronautical Sciences and Evaluation Board of the National Research Council has gone so far as to identify technology integration as a new discipline from which many future aeronautical advancements will arise. Regardless of whether one considers integration as a new discipline or not, it is clear to all engineers involved in aircraft design and analysis that better methods are required. In the past, designers conducted parametric studies in which a relatively small number of principal characteristics were varied to determine the effect on design requirements which were themselves often diverse and contradictory. Once a design was chosen, it then passed through the various engineers' disciplines whose principal task was to make the chosen design workable. Working in a limited design space, the discipline expert sometimes improved the concept, but more often than not, the result was in the form of a penalty to make the original concept workable. If an insurmountable problem was encountered, the process began over. Most design systems that attempt to account for disciplinary interactions have large empirical elements and reliance on past experience is a poor guide in obtaining maximum utilizations of new technologies. Further compounding the difficulty of design is that as the aeronautical sciences have matured, the discipline specialist's area of research has generally

Cooperative Research and Development for Advanced Microturbines Program on Advanced Integrated Microturbine System

Energy Technology Data Exchange (ETDEWEB)

Michael J. Bowman

2007-05-30

The Advanced Integrated Microturbine Systems (AIMS) project was kicked off in October of 2000 to develop the next generation microturbine system. The overall objective of the project was to develop a design for a 40% electrical efficiency microturbine system and demonstrate many of the enabling technologies. The project was initiated as a collaborative effort between several units of GE, Elliott Energy Systems, Turbo Genset, Oak Ridge National Lab and Kyocera. Since the inception of the project the partners have changed but the overall direction of the project has stayed consistent. The project began as a systems study to identify design options to achieve the ultimate goal of 40% electrical efficiency. Once the optimized analytical design was identified for the 40% system, it was determined that a 35% efficient machine would be capable of demonstrating many of the advanced technologies within the given budget and timeframe. The items that would not be experimentally demonstrated were fully produced ceramic parts. However, to understand the requirements of these ceramics, an effort was included in the project to experimentally evaluate candidate materials in representative conditions. The results from this effort would clearly identify the challenges and improvement required of these materials for the full design. Following the analytical effort, the project was dedicated to component development and testing. Each component and subsystem was designed with the overall system requirements in mind and each tested to the fullest extent possible prior to being integrated together. This method of component development and evaluation helps to minimize the technical risk of the project. Once all of the components were completed, they were assembled into the full system and experimentally evaluated.

Optimal anthropometric measures and thresholds to identify undiagnosed type 2 diabetes in three major Asian ethnic groups.

Science.gov (United States)

Alperet, Derrick Johnston; Lim, Wei-Yen; Mok-Kwee Heng, Derrick; Ma, Stefan; van Dam, Rob M

2016-10-01

To identify optimal anthropometric measures and cutoffs to identify undiagnosed diabetes mellitus (UDM) in three major Asian ethnic groups (Chinese, Malays, and Asian-Indians). Cross-sectional data were analyzed from 14,815 ethnic Chinese, Malay, and Asian-Indian participants of the Singapore National Health Surveys, which included anthropometric measures and an oral glucose tolerance test. Receiver operating characteristic curve analyses were used with calculation of the area under the curve (AUC) to evaluate the performance of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHTR) for the identification of UDM. BMI performed significantly worse (AUCMEN  = 0.70; AUCWOMEN  = 0.75) than abdominal measures, whereas WHTR (AUCMEN  = 0.76; AUCWOMEN  = 0.79) was among the best performing measures in both sexes and all ethnic groups. Anthropometric measures performed better in Chinese than in Asian-Indian participants for the identification of UDM. A WHTR cutoff of 0.52 appeared optimal with a sensitivity of 76% in men and 73% in women and a specificity of 63% in men and 70% in women. Although ethnic differences were observed in the performance of anthropometric measures for the identification of UDM, abdominal adiposity measures generally performed better than BMI, and WHTR performed best in all Asian ethnic groups. © 2016 The Obesity Society.

An advanced control system for the optimal operation and management of medium size power systems with a large penetration from renewable power sources

Energy Technology Data Exchange (ETDEWEB)

Nogaret, E.; Stavrakakis, G.; Kariniotakis, G. [Ecole de Mines de Paris, Centre d`Energetique, Sophia-Antipolis (France)] [and others

1997-10-01

An advanced control system for the optimal operation and management of autonomous wind-diesel systems is presented. This system minimises the production costs through an on-line optimal scheduling of the power units, which takes into account the technical constraints of the diesel units, as well as short-term forecasts of the load and renewable resources. The power system security is maximised through on-line security assessment modules, which enable the power system to withstand sudden changes in the production of the renewable sources. The control system was evaluated using data from the island of Lemnos, where it has been installed and operated since January 1995. (Author)

Decomposition with thermoeconomic isolation applied to the optimal synthesis/design and operation of an advanced tactical aircraft system

International Nuclear Information System (INIS)

Rancruel, Diego F.; Spakovsky, Michael R. von

2006-01-01

A decomposition methodology based on the concept of 'thermoeconomic isolation' and applied to the synthesis/design and operational optimization of an advanced tactical fighter aircraft is the focus of this paper. The total system is composed of six sub-systems of which five participate with degrees of freedom (493) in the optimization. They are the propulsion sub-system (PS), the environmental control sub-system (ECS), the fuel loop subsystem (FLS), the vapor compression and Polyalphaolefin (PAO) loops sub-system (VC/PAOS), and the airframe sub-system (AFS). The sixth subsystem comprises the expendable and permanent payloads as well as the equipment group. For each of the first five, detailed thermodynamic, geometric, physical, and aerodynamic models at both design and off-design were formulated and implemented. The most promising set of aircraft sub-system and system configurations were then determined based on both an energy integration and aerodynamic performance analysis at each stage of the mission (including the transient ones). Conceptual, time, and physical decomposition were subsequently applied to the synthesis/design and operational optimization of these aircraft configurations as well as to the highly dynamic process of heat generation and dissipation internal to the subsystems. The physical decomposition strategy used (i.e. Iterative Local-Global Optimization-ILGO) is the first to successfully closely approach the theoretical condition of 'thermoeconomic isolation' when applied to highly complex, highly dynamic non-linear systems. Developed at our Center for Energy Systems research, it has been effectively applied to a number of complex stationary and transportation applications

Decomposition with thermoeconomic isolation applied to the optimal synthesis/design and operation of an advanced tactical aircraft system

Energy Technology Data Exchange (ETDEWEB)

Rancruel, Diego F. [Center for Energy Systems Research, Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060 (United States); Spakovsky, Michael R. von [Center for Energy Systems Research, Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060 (United States)]. E-mail: vonspako@vt.edu

2006-12-15

A decomposition methodology based on the concept of 'thermoeconomic isolation' and applied to the synthesis/design and operational optimization of an advanced tactical fighter aircraft is the focus of this paper. The total system is composed of six sub-systems of which five participate with degrees of freedom (493) in the optimization. They are the propulsion sub-system (PS), the environmental control sub-system (ECS), the fuel loop subsystem (FLS), the vapor compression and Polyalphaolefin (PAO) loops sub-system (VC/PAOS), and the airframe sub-system (AFS). The sixth subsystem comprises the expendable and permanent payloads as well as the equipment group. For each of the first five, detailed thermodynamic, geometric, physical, and aerodynamic models at both design and off-design were formulated and implemented. The most promising set of aircraft sub-system and system configurations were then determined based on both an energy integration and aerodynamic performance analysis at each stage of the mission (including the transient ones). Conceptual, time, and physical decomposition were subsequently applied to the synthesis/design and operational optimization of these aircraft configurations as well as to the highly dynamic process of heat generation and dissipation internal to the subsystems. The physical decomposition strategy used (i.e. Iterative Local-Global Optimization-ILGO) is the first to successfully closely approach the theoretical condition of 'thermoeconomic isolation' when applied to highly complex, highly dynamic non-linear systems. Developed at our Center for Energy Systems research, it has been effectively applied to a number of complex stationary and transportation applications.

OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE - A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING

Energy Technology Data Exchange (ETDEWEB)

Arnis Judzis

2003-01-01

This document details the progress to date on the ''OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE -- A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING'' contract for the quarter starting October 2002 through December 2002. Even though we are awaiting the optimization portion of the testing program, accomplishments included the following: (1) Smith International participated in the DOE Mud Hammer program through full scale benchmarking testing during the week of 4 November 2003. (2) TerraTek acknowledges Smith International, BP America, PDVSA, and ConocoPhillips for cost-sharing the Smith benchmarking tests allowing extension of the contract to add to the benchmarking testing program. (3) Following the benchmark testing of the Smith International hammer, representatives from DOE/NETL, TerraTek, Smith International and PDVSA met at TerraTek in Salt Lake City to review observations, performance and views on the optimization step for 2003. (4) The December 2002 issue of Journal of Petroleum Technology (Society of Petroleum Engineers) highlighted the DOE fluid hammer testing program and reviewed last years paper on the benchmark performance of the SDS Digger and Novatek hammers. (5) TerraTek's Sid Green presented a technical review for DOE/NETL personnel in Morgantown on ''Impact Rock Breakage'' and its importance on improving fluid hammer performance. Much discussion has taken place on the issues surrounding mud hammer performance at depth conditions.

Co-Optimization of Fuels and Engines (Co-Optima) -- Introduction

Energy Technology Data Exchange (ETDEWEB)

Farrell, John T [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wagner, Robert [Oak Ridge National Laboratory; Holladay, John [Pacific Northwest National Laboratory

2017-08-11

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a U.S. Department of Energy (DOE) effort funded by both the Vehicle and Bioenergy Technology Offices. The overall goal of the effort is to identify the combinations of fuel properties and engine characteristics that maximize efficiency, independent of production pathway or fuel composition, and accelerate commercialization of these technologies. Multiple research efforts are underway focused on both spark-ignition and compression-ignition strategies applicable across the entire light, medium, and heavy-duty fleet. A key objective of Co-Optima's research is to identify new blendstocks that enhance current petroleum blending components, increase blendstock diversity, and provide refiners with increased flexibility to blend fuels with the key properties required to optimize advanced internal combustion engines. In addition to fuels and engines R&D, the initiative is guided by analyses assessing the near-term commercial feasibility of new blendstocks based on economics, environmental performance, compatibility, and large-scale production viability. This talk will provide an overview of the Co-Optima effort.

Fifty years of chasing lizards: new insights advance optimal escape theory.

Science.gov (United States)

Samia, Diogo S M; Blumstein, Daniel T; Stankowich, Theodore; Cooper, William E

2016-05-01

Systematic reviews and meta-analyses often examine data from diverse taxa to identify general patterns of effect sizes. Meta-analyses that focus on identifying generalisations in a single taxon are also valuable because species in a taxon are more likely to share similar unique constraints. We conducted a comprehensive phylogenetic meta-analysis of flight initiation distance in lizards. Flight initiation distance (FID) is a common metric used to quantify risk-taking and has previously been shown to reflect adaptive decision-making. The past decade has seen an explosion of studies focused on quantifying FID in lizards, and, because lizards occur in a wide range of habitats, are ecologically diverse, and are typically smaller and differ physiologically from the better studied mammals and birds, they are worthy of detailed examination. We found that variables that reflect the costs or benefits of flight (being engaged in social interactions, having food available) as well as certain predator effects (predator size and approach speed) had large effects on FID in the directions predicted by optimal escape theory. Variables that were associated with morphology (with the exception of crypsis) and physiology had relatively small effects, whereas habitat selection factors typically had moderate to large effect sizes. Lizards, like other taxa, are very sensitive to the costs of flight. © 2015 Cambridge Philosophical Society.

Optimal economic and environment operation of micro-grid power systems

International Nuclear Information System (INIS)

Elsied, Moataz; Oukaour, Amrane; Gualous, Hamid; Lo Brutto, Ottavio A.

2016-01-01

Highlights: • Real-time energy management system for Micro-Grid power systems is introduced. • The management system considered cost objective function and emission constraints. • The optimization problem is solved using Binary Particle Swarm Algorithm. • Advanced real-time interface libraries are used to run the optimization code. - Abstract: In this paper, an advanced real-time energy management system is proposed in order to optimize micro-grid performance in a real-time operation. The proposed strategy of the management system capitalizes on the power of binary particle swarm optimization algorithm to minimize the energy cost and carbon dioxide and pollutant emissions while maximizing the power of the available renewable energy resources. Advanced real-time interface libraries are used to run the optimization code. The simulation results are considered for three different scenarios considering the complexity of the proposed problem. The proposed management system along with its control system is experimentally tested to validate the simulation results obtained from the optimization algorithm. The experimental results highlight the effectiveness of the proposed management system for micro-grids operation.

Advance care planning in 21st century Australia: a systematic review and appraisal of online advance care directive templates against national framework criteria.

Science.gov (United States)

Luckett, Tim; Bhattarai, Priyanka; Phillips, Jane; Agar, Meera; Currow, David; Krastev, Yordanka; Davidson, Patricia M

2015-11-01

A drive to promote advance care planning at a population level has led to a proliferation of online advance care directive (ACD) templates but little information to guide consumer choice. The current study aimed to appraise the quality of online ACD templates promoted for use in Australia. A systematic review of online Australian ACD templates was conducted in February 2014. ACD templates were identified via Google searches, and quality was independently appraised by two reviewers against criteria from the 2011 report A National Frameworkfor Advance Care Directives. Bias either towards or against future medical treatment was assessed using criteria designed to limit subjectivity. Fourteen online ACD templates were included, all of which were available only in English. Templates developed by Southern Cross University best met the framework criteria. One ACD template was found to be biased against medical treatment--the Dying with Dignity Victoria Advance Healthcare Directive. More research is needed to understand how online resources can optimally elicit and record consumers' individual preferences for future care. Future iterations of the framework should address online availability and provide a simple rating system to inform choice and drive quality improvement.

Optimal control applications in electric power systems

CERN Document Server

Christensen, G S; Soliman, S A

1987-01-01

Significant advances in the field of optimal control have been made over the past few decades. These advances have been well documented in numerous fine publications, and have motivated a number of innovations in electric power system engineering, but they have not yet been collected in book form. Our purpose in writing this book is to provide a description of some of the applications of optimal control techniques to practical power system problems. The book is designed for advanced undergraduate courses in electric power systems, as well as graduate courses in electrical engineering, applied mathematics, and industrial engineering. It is also intended as a self-study aid for practicing personnel involved in the planning and operation of electric power systems for utilities, manufacturers, and consulting and government regulatory agencies. The book consists of seven chapters. It begins with an introductory chapter that briefly reviews the history of optimal control and its power system applications and also p...

Workshop on Computational Optimization

CERN Document Server

2016-01-01

This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2014, held at Warsaw, Poland, September 7-10, 2014. The book presents recent advances in computational optimization. The volume includes important real problems like parameter settings for controlling processes in bioreactor and other processes, resource constrained project scheduling, infection distribution, molecule distance geometry, quantum computing, real-time management and optimal control, bin packing, medical image processing, localization the abrupt atmospheric contamination source and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.

Radiation protection optimization. Advances in practical implementation

International Nuclear Information System (INIS)

1989-01-01

Within the Community, protection against the dangers of ionizing radiation is regulated in conformity with the provisions of two Council Directives. One is of general application for all activities involving a hazard arising from ionizing radiation and lays down the basic safety standards for the health protection of the general public and workers against the dangers of ionizing radiation. The other is derived from the abovementioned one and lays down the basic measures for the radiation protection of persons undergoing medical examination or treatment. The Commission, in collaboration with the Spanish Ministerio de Sanidad y Consumo, the Consejo de Seguridad Nuclear and the Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas, organized on 12, 13 and 14 September 1988 in Madrid, the third scientific seminar on the optimization principle (Alara) which is a key element of the two abovementioned Council Directives. The seminar allowed an analysis of the progress made since the previous seminars of 1979 and 1983, in the practical implementation of the optimization principle, in relation to the design and operation of nuclear and industrial installations, natural radioactivity, medical practices and countermeasures. The report contains the 20 original contributions presented and some general considerations on the results of the seminar

BWR Assembly Optimization for Minor Actinide Recycling

Energy Technology Data Exchange (ETDEWEB)

G. Ivan Maldonado; John M. Christenson; J.P. Renier; T.F. Marcille; J. Casal

2010-03-22

The Primary objective of the proposed project is to apply and extend the latest advancements in LWR fuel management optimization to the design of advanced boiling water reactor (BWR) fuel assemblies specifically for the recycling of minor actinides (MAs).

Optimal Market Design

NARCIS (Netherlands)

Boone, J.; Goeree, J.K.

2010-01-01

This paper introduces three methodological advances to study the optimal design of static and dynamic markets. First, we apply a mechanism design approach to characterize all incentive-compatible market equilibria. Second, we conduct a normative analysis, i.e. we evaluate alternative competition and

Identifying the optimal depth for mussel suspended culture in shallow and turbid environments

Science.gov (United States)

Filgueira, Ramón; Grant, Jon; Petersen, Jens Kjerulf

2018-02-01

Bivalve aquaculture is commonly carried out in shallow water systems, which are susceptible to resuspension of benthic particulate matter by natural processes such as tidal currents, winds and wave action, as well as human activity. The resuspended material can alter the availability of food particles for cultured bivalves. The effect of resuspended material on bivalve bioenergetics and growth is a function of the quality and concentration of resuspended particles and background diet in the water column. Given the potential for positive or negative impacts on bivalve growth and consequently on farm productivity, farmers must position the cultured biomass at the appropriate depth to benefit from or mitigate the impact of this resuspended material. A combination of field measurements, a 1-D vertical resuspension model and a bioenergetic model for mussels based on Dynamic Energy Budget (DEB) theory has been carried out for a mussel farm in Skive Fjord, a shallow Danish fjord, with the aim of identifying the optimal depth for culture. Observations at the farm location revealed that horizontal advection is more important than vertical resuspension during periods with predominant Eastern winds. In addition, high background seston in the water column reduces the impact of resuspension on the available food for mussels. The simulation of different scenarios in terms of food availability suggested minimal effects of resuspension on mussel growth. Based on this finding and the fact that phytoplankton concentration, the main food source for mussels, is usually higher in the upper part of the water column, suspended culture in the top 3 m of the water column seems to be the optimal practice to produce mussels in Skive Fjord.

Center for Advanced Computational Technology

Science.gov (United States)

Noor, Ahmed K.

2000-01-01

The Center for Advanced Computational Technology (ACT) was established to serve as a focal point for diverse research activities pertaining to application of advanced computational technology to future aerospace systems. These activities include the use of numerical simulations, artificial intelligence methods, multimedia and synthetic environments, and computational intelligence, in the modeling, analysis, sensitivity studies, optimization, design and operation of future aerospace systems. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The Center has four specific objectives: 1) conduct innovative research on applications of advanced computational technology to aerospace systems; 2) act as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); 3) help in identifying future directions of research in support of the aeronautical and space missions of the twenty-first century; and 4) help in the rapid transfer of research results to industry and in broadening awareness among researchers and engineers of the state-of-the-art in applications of advanced computational technology to the analysis, design prototyping and operations of aerospace and other high-performance engineering systems. In addition to research, Center activities include helping in the planning and coordination of the activities of a multi-center team of NASA and JPL researchers who are developing an intelligent synthesis environment for future aerospace systems; organizing workshops and national symposia; as well as writing state-of-the-art monographs and NASA special publications on timely topics.

Optimization and Logistics Challenges in the Enterprise

CERN Document Server

Chaovalitwongse, Wanpracha; Pardalos, Panos M

2009-01-01

Presents advances in supply chain and logistics research and computational optimization that apply to a collaborative environment in the enterprise. This book intends to bridge the gap between operations research and mathematical optimization research from the academic arena with industrial practice

Optimization of large-scale industrial systems : an emerging method

Energy Technology Data Exchange (ETDEWEB)

Hammache, A.; Aube, F.; Benali, M.; Cantave, R. [Natural Resources Canada, Varennes, PQ (Canada). CANMET Energy Technology Centre

2006-07-01

This paper reviewed optimization methods of large-scale industrial production systems and presented a novel systematic multi-objective and multi-scale optimization methodology. The methodology was based on a combined local optimality search with global optimality determination, and advanced system decomposition and constraint handling. The proposed method focused on the simultaneous optimization of the energy, economy and ecology aspects of industrial systems (E{sup 3}-ISO). The aim of the methodology was to provide guidelines for decision-making strategies. The approach was based on evolutionary algorithms (EA) with specifications including hybridization of global optimality determination with a local optimality search; a self-adaptive algorithm to account for the dynamic changes of operating parameters and design variables occurring during the optimization process; interactive optimization; advanced constraint handling and decomposition strategy; and object-oriented programming and parallelization techniques. Flowcharts of the working principles of the basic EA were presented. It was concluded that the EA uses a novel decomposition and constraint handling technique to enhance the Pareto solution search procedure for multi-objective problems. 6 refs., 9 figs.

Mass Spectrometry-Based Methods for Identifying Oxidized Proteins in Disease: Advances and Challenges

Directory of Open Access Journals (Sweden)

Ivan Verrastro

2015-04-01

Full Text Available Many inflammatory diseases have an oxidative aetiology, which leads to oxidative damage to biomolecules, including proteins. It is now increasingly recognized that oxidative post-translational modifications (oxPTMs of proteins affect cell signalling and behaviour, and can contribute to pathology. Moreover, oxidized proteins have potential as biomarkers for inflammatory diseases. Although many assays for generic protein oxidation and breakdown products of protein oxidation are available, only advanced tandem mass spectrometry approaches have the power to localize specific oxPTMs in identified proteins. While much work has been carried out using untargeted or discovery mass spectrometry approaches, identification of oxPTMs in disease has benefitted from the development of sophisticated targeted or semi-targeted scanning routines, combined with chemical labeling and enrichment approaches. Nevertheless, many potential pitfalls exist which can result in incorrect identifications. This review explains the limitations, advantages and challenges of all of these approaches to detecting oxidatively modified proteins, and provides an update on recent literature in which they have been used to detect and quantify protein oxidation in disease.

Identifying Dieters Who Will Develop an Eating Disorder: A Prospective, Population-Based Study

Science.gov (United States)

Fairburn, Christopher G.; Cooper, Zafra; Doll, Helen A.; Davies, Beverley A.

2010-01-01

Objective The aims of the study were to identify the characteristics of the dieters most at risk of subsequently developing an eating disorder and to evaluate the feasibility of using a brief questionnaire to identify such dieters in advance. Method A general population cohort of 2,992 young women who were dieting was identified. On four occasions over the subsequent 2 years, this cohort was sent a questionnaire concerning eating habits and attitudes. Participants whose responses suggested that they had developed an eating disorder were interviewed to establish their true case status. The baseline questionnaires of those who did and did not subsequently develop an eating disorder were compared to identify features that predicted future case status. Results One hundred four of the dieters developed an eating disorder of clinical severity during the 2 years of follow-up. Their baseline questionnaire scores differed in many respects from those who had not developed an eating disorder. Items associated with developing an eating disorder were selected by using three different statistical methods. A simple case-predicting instrument based on one of five items scoring above an optimal cut point had a sensitivity of 71% and a specificity of 72% (overall efficiency of 72%). Conclusions Dieters who will develop an eating disorder within the next 2 years have distinctive features. It is feasible to identify them in advance with reasonable efficiency with a brief questionnaire. This questionnaire could be incorporated into routine health assessments, thereby identifying those at high risk. PMID:16330587

Hydrologic Process-oriented Optimization of Electrical Resistivity Tomography

Science.gov (United States)

Hinnell, A.; Bechtold, M.; Ferre, T. A.; van der Kruk, J.

2010-12-01

Electrical resistivity tomography (ERT) is commonly used in hydrologic investigations. Advances in joint and coupled hydrogeophysical inversion have enhanced the quantitative use of ERT to construct and condition hydrologic models (i.e. identify hydrologic structure and estimate hydrologic parameters). However the selection of which electrical resistivity data to collect and use is often determined by a combination of data requirements for geophysical analysis, intuition on the part of the hydrogeophysicist and logistical constraints of the laboratory or field site. One of the advantages of coupled hydrogeophysical inversion is the direct link between the hydrologic model and the individual geophysical data used to condition the model. That is, there is no requirement to collect geophysical data suitable for independent geophysical inversion. The geophysical measurements collected can be optimized for estimation of hydrologic model parameters rather than to develop a geophysical model. Using a synthetic model of drip irrigation we evaluate the value of individual resistivity measurements to describe the soil hydraulic properties and then use this information to build a data set optimized for characterizing hydrologic processes. We then compare the information content in the optimized data set with the information content in a data set optimized using a Jacobian sensitivity analysis.

Optimal networks of future gravitational-wave telescopes

Science.gov (United States)

Raffai, Péter; Gondán, László; Heng, Ik Siong; Kelecsényi, Nándor; Logue, Josh; Márka, Zsuzsa; Márka, Szabolcs

2013-08-01

We aim to find the optimal site locations for a hypothetical network of 1-3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ˜58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms).

BWR Assembly Optimization for Minor Actinide Recycling

International Nuclear Information System (INIS)

Maldonado, G. Ivan; Christenson, John M.; Renier, J.P.; Marcille, T.F.; Casal, J.

2010-01-01

The Primary objective of the proposed project is to apply and extend the latest advancements in LWR fuel management optimization to the design of advanced boiling water reactor (BWR) fuel assemblies specifically for the recycling of minor actinides (MAs). A top-level objective of the Advanced Fuel Cycle Systems Analysis program element of the DOE NERI program is to investigate spent fuel treatment and recycling options for current light water reactors (LWRs). Accordingly, this project targets to expand the traditional scope of nuclear fuel management optimization into the following two complementary specific objectives: (1) To develop a direct coupling between the pin-by-pin within-bundle loading control variables and core-wide (bundle-by-bundle) optimization objectives, (2) to extend the methodology developed to explicitly encompass control variables, objectives, and constraints designed to maximize minor actinide incineration in BWR bundles and cycles. The first specific objective is projected to 'uncover' dormant thermal margin made available by employing additional degrees of freedom within the optimization process, while the addition of minor actinides is expected to 'consume' some of the uncovered thermal margin. Therefore, a key underlying goal of this project is to effectively invest some of the uncovered thermal margin into achieving the primary objective.

Outline of the advanced boiling water reactor (ABWR)

International Nuclear Information System (INIS)

Hucik, S.A.; Imaoka, T.; Minematsu, A.; Takashima, Y.

1986-01-01

The fundamental design of the Advanced Boiling Water Reactor (ABWR) was completed in December 1985. This design represents the next generation of Boiling Water Reactors (BWR) to be introduced into commercial operation in the 1990s. The ABWR is the result of the continuing evolution of the BWR, incorporating state-of-the-art technologies and many new improvements based on an extensive accumulation of world-wide experience through design, construction and operation of BWRs. The ABWR development program was initiated in 1978, with subsequent design and test and development programs started in 1981. Most of the development and verification tests of the new features have been completed. The ABWR development objective focused on an optimized selection of advanced technologies and proven BWR technologies. The ABWR objectives were specific improvements such as operating and safety margins, enhanced availability and capacity factor, and reduced occupational exposure while at the same time achieving significant cost reduction in both capital and operating costs. The ABWR is characterized by an improved NSSS including ten internal recirculation pumps, fine motion electric-hydraulic control rod drives, optimized safety and auxiliary systems, advanced control and instrumentation systems, improved turbine-generator with moisture/separator reheater with plant output increased to 1350 MWe, and an integrated reinforced concrete containment vessel and compact Reactor and Turbine Building design. The turbine system also included improvements in the Turbine-Generator, feedwater/heater system, and condensate treatment systems. The radwaste system was also optimized taking advantage of the plant design improvements and advances in radwaste technology. The ABWR is a truly optimal design which utilizes advanced technologies, capabilities, performance improvements, and yet provides an economic advantage. (author)

Advances in Optimizing Weather Driven Electric Power Systems.

Science.gov (United States)

Clack, C.; MacDonald, A. E.; Alexander, A.; Dunbar, A. D.; Xie, Y.; Wilczak, J. M.

2014-12-01

The importance of weather-driven renewable energies for the United States (and global) energy portfolio is growing. The main perceived problems with weather-driven renewable energies are their intermittent nature, low power density, and high costs. The National Energy with Weather System Simulator (NEWS) is a mathematical optimization tool that allows the construction of weather-driven energy sources that will work in harmony with the needs of the system. For example, it will match the electric load, reduce variability, decrease costs, and abate carbon emissions. One important test run included existing US carbon-free power sources, natural gas power when needed, and a High Voltage Direct Current power transmission network. This study shows that the costs and carbon emissions from an optimally designed national system decrease with geographic size. It shows that with achievable estimates of wind and solar generation costs, that the US could decrease its carbon emissions by up to 80% by the early 2030s, without an increase in electric costs. The key requirement would be a 48 state network of HVDC transmission, creating a national market for electricity not possible in the current AC grid. These results were found without the need for storage. Further, we tested the effect of changing natural gas fuel prices on the optimal configuration of the national electric power system. Another test that was carried out was an extension to global regions. The extension study shows that the same properties found in the US study extend to the most populous regions of the planet. The extra test is a simplified version of the US study, and is where much more research can be carried out. We compare our results to other model results.

Application of Advanced Particle Swarm Optimization Techniques to Wind-thermal Coordination

DEFF Research Database (Denmark)

Singh, Sri Niwas; Østergaard, Jacob; Yadagiri, J.

2009-01-01

wind-thermal coordination algorithm is necessary to determine the optimal proportion of wind and thermal generator capacity that can be integrated into the system. In this paper, four versions of Particle Swarm Optimization (PSO) techniques are proposed for solving wind-thermal coordination problem...

Application of the advanced engineering environment for optimization energy consumption in designed vehicles

Science.gov (United States)

Monica, Z.; Sękala, A.; Gwiazda, A.; Banaś, W.

2016-08-01

Nowadays a key issue is to reduce the energy consumption of road vehicles. In particular solution one could find different strategies of energy optimization. The most popular but not sophisticated is so called eco-driving. In this strategy emphasized is particular behavior of drivers. In more sophisticated solution behavior of drivers is supported by control system measuring driving parameters and suggesting proper operation of the driver. The other strategy is concerned with application of different engineering solutions that aid optimization the process of energy consumption. Such systems take into consideration different parameters measured in real time and next take proper action according to procedures loaded to the control computer of a vehicle. The third strategy bases on optimization of the designed vehicle taking into account especially main sub-systems of a technical mean. In this approach the optimal level of energy consumption by a vehicle is obtained by synergetic results of individual optimization of particular constructional sub-systems of a vehicle. It is possible to distinguish three main sub-systems: the structural one the drive one and the control one. In the case of the structural sub-system optimization of the energy consumption level is related with the optimization or the weight parameter and optimization the aerodynamic parameter. The result is optimized body of a vehicle. Regarding the drive sub-system the optimization of the energy consumption level is related with the fuel or power consumption using the previously elaborated physical models. Finally the optimization of the control sub-system consists in determining optimal control parameters.

Identifying optimal postmarket surveillance strategies for medical and surgical devices: implications for policy, practice and research.

Science.gov (United States)

Gagliardi, Anna R; Umoquit, Muriah; Lehoux, Pascale; Ross, Sue; Ducey, Ariel; Urbach, David R

2013-03-01

Non-drug technologies offer many benefits, but have been associated with adverse events, prompting calls for improved postmarket surveillance. There is little empirical research to guide the development of such a system. The purpose of this study was to identify optimal postmarket surveillance strategies for medical and surgical devices. Qualitative methods were used for sampling, data collection and analysis. Stakeholders from Canada and the USA representing different roles and perspectives were first interviewed to identify examples and characteristics of different surveillance strategies. These stakeholders and others they recommended were then assembled at a 1-day nominal group meeting to discuss and prioritise the components of a postmarket device surveillance system, and research needed to achieve such a system. Consultations were held with 37 participants, and 47 participants attended the 1-day meeting. They recommended a multicomponent system including reporting by facilities, clinicians and patients, supported with some external surveillance for validation and real-time trials for high-risk devices. Many considerations were identified that constitute desirable characteristics of, and means by which to implement such a system. An overarching network was envisioned to broker linkages, establish a shared minimum dataset, and support communication and decision making. Numerous research questions were identified, which could be pursued in tandem with phased implementation of the system. These findings provide unique guidance for establishing a device safety network that is based on existing initiatives, and could be expanded and evaluated in a prospective, phased fashion as it was developed.

The Theory of Optimal Taxation

DEFF Research Database (Denmark)

Sørensen, Peter Birch

The theory of optimal taxation has often been criticized for being of little practical policy relevance, due to a lack of robust theoretical results. This paper argues that recent advances in optimal tax theory has made that theory easier to apply and may help to explain some current trends...... in international tax policy. Covering the taxation of labour income and capital income as well as indirect taxation, the paper also illustrates how some of the key results in optimal tax theory may be derived in a simple, heuristic manner....

Topology optimization and digital assembly of advanced space-frame structures

DEFF Research Database (Denmark)

Søndergaard, Asbjørn; Amir, Oded; Michael, Knauss

2014-01-01

this paper presents a novel method for integrated design, optimization and fabrication of optimized space-frame structures in an autonomous, digital process. Comparative numerical studies are presented, demonstrating achievable mass reduction by application of the method by comparison to equivalent...... to normative space truss designs and dimensions. As such, a principal digital fabrication and assembly scheme is developed, where an architectural design methodology relative to the described process is established, and the proposed process demonstrated through scaled digital fabrication experiments....

Advanced Accelerators for Medical Applications

Science.gov (United States)

Uesaka, Mitsuru; Koyama, Kazuyoshi

We review advanced accelerators for medical applications with respect to the following key technologies: (i) higher RF electron linear accelerator (hereafter “linac”); (ii) optimization of alignment for the proton linac, cyclotron and synchrotron; (iii) superconducting magnet; (iv) laser technology. Advanced accelerators for medical applications are categorized into two groups. The first group consists of compact medical linacs with high RF, cyclotrons and synchrotrons downsized by optimization of alignment and superconducting magnets. The second group comprises laser-based acceleration systems aimed of medical applications in the future. Laser plasma electron/ion accelerating systems for cancer therapy and laser dielectric accelerating systems for radiation biology are mentioned. Since the second group has important potential for a compact system, the current status of the established energy and intensity and of the required stability are given.

Optimal routing of coordinated aircraft to Identify moving surface contacts

Science.gov (United States)

2017-06-01

either model for any asset’s route. Its inclusion may eliminate arcs that could be part of an optimal route for an asset. As such, it should be...Arma Aérea.” Revista general de Marina 8: 319–332. http://www.armada.mde.es/archivo/rgm/ 2016/08/2016_08.pdf. Marine Traffic. n.d. “Density maps

Estimating of aquifer parameters from the single-well water-level measurements in response to advancing longwall mine by using particle swarm optimization

Science.gov (United States)

Buyuk, Ersin; Karaman, Abdullah

2017-04-01

We estimated transmissivity and storage coefficient values from the single well water-level measurements positioned ahead of the mining face by using particle swarm optimization (PSO) technique. The water-level response to the advancing mining face contains an semi-analytical function that is not suitable for conventional inversion shemes because the partial derivative is difficult to calculate . Morever, the logaritmic behaviour of the model create difficulty for obtaining an initial model that may lead to a stable convergence. The PSO appears to obtain a reliable solution that produce a reasonable fit between water-level data and model function response. Optimization methods have been used to find optimum conditions consisting either minimum or maximum of a given objective function with regard to some criteria. Unlike PSO, traditional non-linear optimization methods have been used for many hydrogeologic and geophysical engineering problems. These methods indicate some difficulties such as dependencies to initial model, evolution of the partial derivatives that is required while linearizing the model and trapping at local optimum. Recently, Particle swarm optimization (PSO) became the focus of modern global optimization method that is inspired from the social behaviour of birds of swarms, and appears to be a reliable and powerful algorithms for complex engineering applications. PSO that is not dependent on an initial model, and non-derivative stochastic process appears to be capable of searching all possible solutions in the model space either around local or global optimum points.

Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

Science.gov (United States)

Poitras, Travis; Villarreal, Miguel; Waller, Eric K.; Nauman, Travis; Miller, Mark E.; Duniway, Michael C.

2018-01-01

Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

Strategic targeting of advance care planning interventions: the Goldilocks phenomenon.

Science.gov (United States)

Billings, J Andrew; Bernacki, Rachelle

2014-04-01

Strategically selecting patients for discussions and documentation about limiting life-sustaining treatments-choosing the right time along the end-of-life trajectory for such an intervention and identifying patients at high risk of facing end-of-life decisions-can have a profound impact on the value of advance care planning (ACP) efforts. Timing is important because the completion of an advance directive (AD) too far from or too close to the time of death can lead to end-of-life decisions that do not optimally reflect the patient's values, goals, and preferences: a poorly chosen target patient population that is unlikely to need an AD in the near future may lead to patients making unrealistic, hypothetical choices, while assessing preferences in the emergency department or hospital in the face of a calamity is notoriously inadequate. Because much of the currently studied ACP efforts have led to a disappointingly small proportion of patients eventually benefitting from an AD, careful targeting of the intervention should also improve the efficacy of such projects. A key to optimal timing and strategic selection of target patients for an ACP program is prognostication, and we briefly highlight prognostication tools and studies that may point us toward high-value AD interventions.

Optimal networks of future gravitational-wave telescopes

International Nuclear Information System (INIS)

Raffai, Péter; Márka, Zsuzsa; Márka, Szabolcs; Gondán, László; Kelecsényi, Nándor; Heng, Ik Siong; Logue, Josh

2013-01-01

We aim to find the optimal site locations for a hypothetical network of 1–3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ∼58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms). (paper)

Advances in nuclear science and technology

CERN Document Server

Greebler, Paul

1968-01-01

Advances in Nuclear Science and Technology Volume 4 provides information pertinent to the fundamental aspects of advanced reactor concepts. This book discusses the advances in various areas of general applicability, including modern perturbation theory, optimal control theory, and industrial application of ionizing radiations.Organized into seven chapters, this volume begins with an overview of the technology of sodium-cooled fast breeder power reactors and gas-cooled power reactors. This text then examines the key role of reactor safety in the development of fast breeder reactors. Other chapt

Analytical methods of optimization

CERN Document Server

Lawden, D F

2006-01-01

Suitable for advanced undergraduates and graduate students, this text surveys the classical theory of the calculus of variations. It takes the approach most appropriate for applications to problems of optimizing the behavior of engineering systems. Two of these problem areas have strongly influenced this presentation: the design of the control systems and the choice of rocket trajectories to be followed by terrestrial and extraterrestrial vehicles.Topics include static systems, control systems, additional constraints, the Hamilton-Jacobi equation, and the accessory optimization problem. Prereq

NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

Science.gov (United States)

Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

2015-10-15

In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to

Bio-Inspired Optimization of Sustainable Energy Systems: A Review

Directory of Open Access Journals (Sweden)

Yu-Jun Zheng

2013-01-01

Full Text Available Sustainable energy development always involves complex optimization problems of design, planning, and control, which are often computationally difficult for conventional optimization methods. Fortunately, the continuous advances in artificial intelligence have resulted in an increasing number of heuristic optimization methods for effectively handling those complicated problems. Particularly, algorithms that are inspired by the principles of natural biological evolution and/or collective behavior of social colonies have shown a promising performance and are becoming more and more popular nowadays. In this paper we summarize the recent advances in bio-inspired optimization methods, including artificial neural networks, evolutionary algorithms, swarm intelligence, and their hybridizations, which are applied to the field of sustainable energy development. Literature reviewed in this paper shows the current state of the art and discusses the potential future research trends.

CFD-based optimization in plastics extrusion

Science.gov (United States)

Eusterholz, Sebastian; Elgeti, Stefanie

2018-05-01

This paper presents novel ideas in numerical design of mixing elements in single-screw extruders. The actual design process is reformulated as a shape optimization problem, given some functional, but possibly inefficient initial design. Thereby automatic optimization can be incorporated and the design process is advanced, beyond the simulation-supported, but still experience-based approach. This paper proposes concepts to extend a method which has been developed and validated for die design to the design of mixing-elements. For simplicity, it focuses on single-phase flows only. The developed method conducts forward-simulations to predict the quasi-steady melt behavior in the relevant part of the extruder. The result of each simulation is used in a black-box optimization procedure based on an efficient low-order parameterization of the geometry. To minimize user interaction, an objective function is formulated that quantifies the products' quality based on the forward simulation. This paper covers two aspects: (1) It reviews the set-up of the optimization framework as discussed in [1], and (2) it details the necessary extensions for the optimization of mixing elements in single-screw extruders. It concludes with a presentation of first advances in the unsteady flow simulation of a metering and mixing section with the SSMUM [2] using the Carreau material model.

The optimal blood glucose level for critically ill adult patients.

Science.gov (United States)

Lv, Shaoning; Ross, Paul; Tori, Kathleen

2017-09-01

Glycaemic control is recognized as one of the important aspects in managing critically ill patients. Both hyperglycaemia and hypoglycaemia independently increase the risk of patient mortality. Hence, the identification of optimal glycaemic control is of paramount importance in the management of critically ill patients. The aim of this literature review is to examine the current status of glycaemic control in critically ill adult patients. This literature review will focus on randomized controlled trials comparing intensive insulin therapy to conventional insulin therapy, with an objective to identify optimal blood glucose level targets for critically ill adult patients. A literature review was conducted to identify large randomized controlled trials for the optimal targeted blood glucose level for critically ill adult patients published since 2000. A total of eight studies fulfilled the selection criteria of this review. With current human and technology resources, the results of the studies support commencing glycaemic control once the blood glucose level of critically ill patients reaches 10 mmol/L and maintaining this level between 8 mmol/L and 10 mmol/L. This literature review provides a recommendation for targeting the optimal blood glucose level for critically ill patients within moderate blood glucose level target range (8-10 mmol/L). The need for uniformed glucometrics for unbiased reporting and further research for optimal blood glucose target is required, especially in light of new technological advancements in closed-loop insulin delivery and monitoring devices. This literature review has revealed a need to call for consensus in the measurement and reporting of glycaemic control using standardized glucometrics. © 2017 British Association of Critical Care Nurses.

High Fidelity Multi-Objective Design Optimization of a Downscaled Cusped Field Thruster

Directory of Open Access Journals (Sweden)

Thomas Fahey

2017-11-01

Full Text Available The Cusped Field Thruster (CFT concept has demonstrated significantly improved performance over the Hall Effect Thruster and the Gridded Ion Thruster; however, little is understood about the complexities of the interactions and interdependencies of the geometrical, magnetic and ion beam properties of the thruster. This study applies an advanced design methodology combining a modified power distribution calculation and evolutionary algorithms assisted by surrogate modeling to a multi-objective design optimization for the performance optimization and characterization of the CFT. Optimization is performed for maximization of performance defined by five design parameters (i.e., anode voltage, anode current, mass flow rate, and magnet radii, simultaneously aiming to maximize three objectives; that is, thrust, efficiency and specific impulse. Statistical methods based on global sensitivity analysis are employed to assess the optimization results in conjunction with surrogate models to identify key design factors with respect to the three design objectives and additional performance measures. The research indicates that the anode current and the Outer Magnet Radius have the greatest effect on the performance parameters. An optimal value for the anode current is determined, and a trend towards maximizing anode potential and mass flow rate is observed.

Optimization of Premix Powders for Tableting Use.

Science.gov (United States)

Todo, Hiroaki; Sato, Kazuki; Takayama, Kozo; Sugibayashi, Kenji

2018-05-08

Direct compression is a popular choice as it provides the simplest way to prepare the tablet. It can be easily adopted when the active pharmaceutical ingredient (API) is unstable in water or to thermal drying. An optimal formulation of preliminary mixed powders (premix powders) is beneficial if prepared in advance for tableting use. The aim of this study was to find the optimal formulation of the premix powders composed of lactose (LAC), cornstarch (CS), and microcrystalline cellulose (MCC) by using statistical techniques. Based on the "Quality by Design" concept, a (3,3)-simplex lattice design consisting of three components, LAC, CS, and MCC was employed to prepare the model premix powders. Response surface method incorporating a thin-plate spline interpolation (RSM-S) was applied for estimation of the optimum premix powders for tableting use. The effect of tablet shape identified by the surface curvature on the optimization was investigated. The optimum premix powder was effective when the premix was applied to a small quantity of API, although the function of premix was limited in the case of the formulation of large amount of API. Statistical techniques are valuable to exploit new functions of well-known materials such as LAC, CS, and MCC.

Identifying Strategic Scientific Opportunities

Science.gov (United States)

As NCI's central scientific strategy office, CRS collaborates with the institute's divisions, offices, and centers to identify research opportunities to advance NCI's vision for the future of cancer research.

Well-posed optimization problems

CERN Document Server

Dontchev, Asen L

1993-01-01

This book presents in a unified way the mathematical theory of well-posedness in optimization. The basic concepts of well-posedness and the links among them are studied, in particular Hadamard and Tykhonov well-posedness. Abstract optimization problems as well as applications to optimal control, calculus of variations and mathematical programming are considered. Both the pure and applied side of these topics are presented. The main subject is often introduced by heuristics, particular cases and examples. Complete proofs are provided. The expected knowledge of the reader does not extend beyond textbook (real and functional) analysis, some topology and differential equations and basic optimization. References are provided for more advanced topics. The book is addressed to mathematicians interested in optimization and related topics, and also to engineers, control theorists, economists and applied scientists who can find here a mathematical justification of practical procedures they encounter.

Identifying and Managing Undue Influence From Family Members in End-of-Life Decisions for Patients With Advanced Cancer.

Science.gov (United States)

Baker, Francis X; Gallagher, Colleen M

2017-10-01

Undue influence from family members of patients with advanced cancer remains a serious ethical problem in end-of-life decision making. Despite the wealth of articles discussing the problem of undue influence, little has been written by way of practical guidance to help clinicians identify and effectively manage situations of undue influence. This article briefly lays out how to identify and manage situations of undue influence sensitively and effectively. We explain how undue influence may present itself in the clinic and distinguish it from ethically permissible expressions of relational autonomy. In addition, we lay out a process by which any clinician suspecting undue influence may gather additional information and, if necessary, conduct a family meeting to address the undue influence. It is our hope that by providing clinicians at all levels of patient care with such guidance, they will feel empowered to respond to cases of undue influence when they arise.

Matlab enhanced multi-threaded tomography optimization sequence (MEMTOS)

International Nuclear Information System (INIS)

Lum, Edward S.; Pope, Chad L.

2016-01-01

Highlights: • Monte Carlo simulation of spent nuclear fuel assembly neutron computed tomography. • Optimized parallel calculations conducted from within the MATLAB environment. • Projection difference technique used to identify anomalies in spent nuclear fuel assemblies. - Abstract: One challenge associated with spent nuclear fuel assemblies is the lack of non-destructive analysis techniques to determine if fuel pins have been removed or replaced or if there are significant defects associated with fuel pins deep within a fuel assembly. Neutron computed tomography is a promising technique for addressing these qualitative issues. Monte Carlo simulation of spent nuclear fuel neutron computed tomography allows inexpensive process investigation and optimization. The main purpose of this work is to provide a fully automated advanced simulation framework for the analysis of spent nuclear fuel inspection using neutron computed tomography. The simulation framework, called Matlab Enhanced Multi-Threaded Tomography Optimization Sequence (MEMTOS) not only automates the simulation process, but also generates superior tomography image results. MEMTOS is written in the MATLAB scripting language and addresses file management, parallel Monte Carlo execution, results extraction, and tomography image generation. This paper describes the mathematical basis for neutron computed tomography, the Monte Carlo technique used to simulate neutron computed tomography, and the overall tomography simulation optimization algorithm. Sequence results presented include overall simulation speed enhancement, tomography and image results obtained for Experimental Breeder Reactor II spent fuel assemblies and light water reactor fuel assemblies. Optimization using a projection difference technique are also described.

Hope, optimism and survival in a randomised trial of chemotherapy for metastatic colorectal cancer.

Science.gov (United States)

Schofield, Penelope E; Stockler, M R; Zannino, D; Tebbutt, N C; Price, T J; Simes, R J; Wong, N; Pavlakis, N; Ransom, D; Moylan, E; Underhill, C; Wyld, D; Burns, I; Ward, R; Wilcken, N; Jefford, M

2016-01-01

Psychological responses to cancer are widely believed to affect survival. We investigated associations between hope, optimism, anxiety, depression, health utility and survival in patients starting first-line chemotherapy for metastatic colorectal cancer. Four hundred twenty-nine subjects with metastatic colorectal cancer in a randomised controlled trial of chemotherapy completed baseline questionnaires assessing the following: hopefulness, optimism, anxiety and depression and health utility. Hazard ratios (HRs) and P values were calculated with Cox models for overall survival (OS) and progression-free survival (PFS) in univariable and multivariable analyses. Median follow-up was 31 months. Univariable analyses showed that OS was associated negatively with depression (HR 2.04, P optimism, anxiety or hopefulness. PFS was not associated with hope, optimism, anxiety or depression in any analyses. Depression and health utility, but not optimism, hope or anxiety, were associated with survival after controlling for known prognostic factors in patients with advanced colorectal cancer. Further research is required to understand the nature of the relationship between depression and survival. If a causal mechanism is identified, this may lead to interventional possibilities.

A multi-factor GIS method to identify optimal geographic locations for electric vehicle (EV) charging stations

Science.gov (United States)

Zhang, Yongqin; Iman, Kory

2018-05-01

Fuel-based transportation is one of the major contributors to poor air quality in the United States. Electric Vehicle (EV) is potentially the cleanest transportation technology to our environment. This research developed a spatial suitability model to identify optimal geographic locations for installing EV charging stations for travelling public. The model takes into account a variety of positive and negative factors to identify prime locations for installing EV charging stations in Wasatch Front, Utah, where automobile emission causes severe air pollution due to atmospheric inversion condition near the valley floor. A walkable factor grid was created to store index scores from input factor layers to determine prime locations. 27 input factors including land use, demographics, employment centers etc. were analyzed. Each factor layer was analyzed to produce a summary statistic table to determine the site suitability. Potential locations that exhibit high EV charging usage were identified and scored. A hot spot map was created to demonstrate high, moderate, and low suitability areas for installing EV charging stations. A spatially well distributed EV charging system was then developed, aiming to reduce "range anxiety" from traveling public. This spatial methodology addresses the complex problem of locating and establishing a robust EV charging station infrastructure for decision makers to build a clean transportation infrastructure, and eventually improve environment pollution.

Genetic Optimization Algorithm for Metabolic Engineering Revisited

Directory of Open Access Journals (Sweden)

Tobias B. Alter

2018-05-01

Full Text Available To date, several independent methods and algorithms exist for exploiting constraint-based stoichiometric models to find metabolic engineering strategies that optimize microbial production performance. Optimization procedures based on metaheuristics facilitate a straightforward adaption and expansion of engineering objectives, as well as fitness functions, while being particularly suited for solving problems of high complexity. With the increasing interest in multi-scale models and a need for solving advanced engineering problems, we strive to advance genetic algorithms, which stand out due to their intuitive optimization principles and the proven usefulness in this field of research. A drawback of genetic algorithms is that premature convergence to sub-optimal solutions easily occurs if the optimization parameters are not adapted to the specific problem. Here, we conducted comprehensive parameter sensitivity analyses to study their impact on finding optimal strain designs. We further demonstrate the capability of genetic algorithms to simultaneously handle (i multiple, non-linear engineering objectives; (ii the identification of gene target-sets according to logical gene-protein-reaction associations; (iii minimization of the number of network perturbations; and (iv the insertion of non-native reactions, while employing genome-scale metabolic models. This framework adds a level of sophistication in terms of strain design robustness, which is exemplarily tested on succinate overproduction in Escherichia coli.

Evaluation of the applicability of existing nuclear power plant regulatory requirements in the U.S. to advanced small modular reactors.

Energy Technology Data Exchange (ETDEWEB)

LaChance, Jeffrey L.; Wheeler, Timothy A.; Farnum, Cathy Ottinger; Middleton, Bobby D.; Jordan, Sabina Erteza; Duran, Felicia Angelica; Baum, Gregory A.

2013-05-01

The current wave of small modular reactor (SMR) designs all have the goal of reducing the cost of management and operations. By optimizing the system, the goal is to make these power plants safer, cheaper to operate and maintain, and more secure. In particular, the reduction in plant staffing can result in significant cost savings. The introduction of advanced reactor designs and increased use of advanced automation technologies in existing nuclear power plants will likely change the roles, responsibilities, composition, and size of the crews required to control plant operations. Similarly, certain security staffing requirements for traditional operational nuclear power plants may not be appropriate or necessary for SMRs due to the simpler, safer and more automated design characteristics of SMRs. As a first step in a process to identify where regulatory requirements may be met with reduced staffing and therefore lower cost, this report identifies the regulatory requirements and associated guidance utilized in the licensing of existing reactors. The potential applicability of these regulations to advanced SMR designs is identified taking into account the unique features of these types of reactors.

Advanced technologies in biodiesel new advances in designed and optimized catalysts

CERN Document Server

Islam, Aminul

2015-01-01

The inadequacy of fossil fuel is the main driving force of the future sustainable energy around the world. Since heterogeneous catalysis is used in chemical industry for biodiesel production, achieving optimal catalytic performance is a significant issue for chemical engineers and chemists. Enormous attention has been placed in recent years on the selection of heterogeneous catalyst in biodiesel industry, where the catalyst could be facilitated highly selective toward desired products, easily handled, separated from the reaction medium, and subsequently reused. This book stresses an overview on the contributions of tailored solid acid and base catalysts to catalytic biodiesel synthesis, and the in uences of heterogeneous catalyst properties on biodiesel yield in order to develop a better understanding of catalyst design for the green production process as well as practical applications in the biodiesel industry.

A Review of Design Optimization Methods for Electrical Machines

Directory of Open Access Journals (Sweden)

Gang Lei

2017-11-01

Full Text Available Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines.

UES: an optimization software package for power and energy

International Nuclear Information System (INIS)

Vohryzek, J.; Havlena, V.; Findejs, J.; Jech, J.

2004-01-01

Unified Energy Solutions components are designed to meet specific requirements of the electric utilities, industrial power units, and district heating (combined heat and power) plants. The optimization objective is to operate the plant with maximum process efficiency and operational profit under the constraints imposed by technology and environmental impacts. Software applications for advanced control real-time optimization may provide a low-cost, high return alternative to expensive boiler retrofits for improving operational profit as well as reducing emissions. Unified Energy Solutions (UES) software package is a portfolio of advanced control and optimization components running on top of the standard process regulatory and control system. The objective of the UES is to operate the plant with maximum achievable profit (maximum efficiency) under the constraints imposed by technology (life-time consumption, asset health) and environmental impacts (CO and NO x emissions). Fast responsiveness to varying economic conditions and integration of real-time optimization and operator decision support (off-line) features are critical for operation in real-time economy. Optimization Features are targeted to combustion process, heat and power load allocation to parallel resources, electric power delivery and ancillary services. Optimization Criteria include increased boiler thermal efficiency, maintaining emission limits, economic load allocation of the heat and generation sources. State-of-the-art advanced control algorithms use model based predictive control principles and provide superior response in transient states. Individual software modules support open control platforms and communication protocols. UES can be implemented on a wide range of distributed control systems. Typical achievable benefits include heat and power production costs savings, increased effective boiler operation range, optimized flue gas emissions, optimized production capacity utilization, optimized

[Research advances in identifying nitrate pollution sources of water environment by using nitrogen and oxygen stable isotopes].

Science.gov (United States)

Mao, Wei; Liang, Zhi-wei; Li, Wei; Zhu, Yao; Yanng, Mu-yi; Jia, Chao-jie

2013-04-01

Water body' s nitrate pollution has become a common and severe environmental problem. In order to ensure human health and water environment benign evolution, it is of great importance to effectively identify the nitrate pollution sources of water body. Because of the discrepant composition of nitrogen and oxygen stable isotopes in different sources of nitrate in water body, nitrogen and oxygen stable isotopes can be used to identify the nitrate pollution sources of water environment. This paper introduced the fractionation factors of nitrogen and oxygen stable isotopes in the main processes of nitrogen cycling and the composition of these stable isotopes in main nitrate sources, compared the advantages and disadvantages of five pre-treatment methods for analyzing the nitrogen and oxygen isotopes in nitrate, and summarized the research advances in this aspect into three stages, i. e. , using nitrogen stable isotope alone, using nitrogen and oxygen stable isotopes simultaneously, and combining with mathematical models. The future research directions regarding the nitrate pollution sources identification of water environment were also discussed.

Prediction of 30-day morbidity after primary cytoreductive surgery for advanced stage ovarian cancer.

Science.gov (United States)

Gerestein, C G; Nieuwenhuyzen-de Boer, G M; Eijkemans, M J; Kooi, G S; Burger, C W

2010-01-01

Treatment in advanced stage epithelial ovarian cancer (EOC) is based on primary cytoreductive surgery followed by platinum-based chemotherapy. Successful cytoreduction to minimal residual tumour burden is the most important determinant of prognosis. However, extensive surgical procedures to achieve maximal debulking are inevitably associated with postoperative morbidity and mortality. The objective of this study is to determine predictors of 30-day morbidity after primary cytoreductive surgery for advanced stage EOC. All patients in the South Western part of the Netherlands who underwent primary cytoreductive surgery for advanced stage EOC between January 2004 and December 2007 were identified from the Rotterdam Cancer Registry database. All peri- and postoperative complications within 30 days after surgery were registered and classified according to the definitions of the National Surgical Quality Improvement Programme (NSQIP). To investigate independent predictors of 30-day morbidity, a Cox proportional hazards model with backward stepwise elimination was utilised. The identified predictors were entered into a nomogram. Two hundred and ninety-three patients entered the study protocol. Optimal cytoreduction was achieved in 136 (46%) patients. 30-day morbidity was seen in 99 (34%) patients. Postoperative morbidity could be predicted by age (P=0.007; odds ratio [OR] 1.034), WHO performance status (P=0.046; OR 1.757), extent of surgery (P=0.1308; OR=2.101), and operative time (P=0.017; OR 1.007) with an optimism corrected c-statistic of 0.68. 30-day morbidity could be predicted by age, WHO performance status, operative time and extent of surgery. The generated nomogram could be valuable for predicting operative risk in the individual patient.

Evaluation of the Reliability of Electronic Medical Record Data in Identifying Comorbid Conditions among Patients with Advanced Non-Small Cell Lung Cancer

International Nuclear Information System (INIS)

Muehlenbein, C. E.; Lawson, A.; Pohl, G.; Hoverman, R.; Gruschkus, S. K.; Forsyth, M.; Chen, C.; Lopez, W.; Hartnett, H. J.

2011-01-01

Traditional methods for identifying co morbidity data in EMRs have relied primarily on costly and time-consuming manual chart review. The purpose of this study was to validate a strategy of electronically searching EMR data to identify co morbidities among cancer patients. Methods. Advanced stage NSCLC patients ( N = 2,513) who received chemotherapy from 7/1/2006 to 6/30/2008 were identified using iKnowMed, US Oncology's proprietary oncology-specific EMR system. EMR data were searched for documentation of co morbidities common to advanced stage cancer patients. The search was conducted by a series of programmatic queries on standardized information including concomitant illnesses, patient history, review of systems, and diagnoses other than cancer. The validity of the co morbidity information that we derived from the EMR search was compared to the chart review gold standard in a random sample of 450 patients for whom the EMR search yielded no indication of co morbidities. Negative predictive values were calculated. Results. The overall prevalence of co morbidities of 22%. Overall negative predictive value was 0.92 in the 450 patients randomly sampled patients (36 of 450 were found to have evidence of co morbidities on chart review). Conclusion. Results of this study suggest that efficient queries/text searches of EMR data may provide reliable data on co morbid conditions among cancer patients.

MO-FG-207-01: Technological Advances and Challenges: Experience with the First Integrated Whole-Body PET/MRI

Energy Technology Data Exchange (ETDEWEB)

Laforest, R. [Washington University School of Medicine (United States)

2015-06-15

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

MO-FG-207-01: Technological Advances and Challenges: Experience with the First Integrated Whole-Body PET/MRI

International Nuclear Information System (INIS)

Laforest, R.

2015-01-01

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee

Optimization by GRASP greedy randomized adaptive search procedures

CERN Document Server

Resende, Mauricio G C

2016-01-01

This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristic that has enjoyed wide success in practice with a broad range of applications to real-world combinatorial optimization problems. The state-of-the-art coverage and carefully crafted pedagogical style lends this book highly accessible as an introductory text not only to GRASP, but also to combinatorial optimization, greedy algorithms, local search, and path-relinking, as well as to heuristics and metaheuristics, in general. The focus is on algorithmic and computational aspects of applied optimization with GRASP with emphasis given to the end-user, providing sufficient information on the broad spectrum of advances in applied optimization with GRASP. For the more advanced reader, chapters on hybridization with path-relinking and parallel and continuous GRASP present these topics in a clear and concise fashion. Additionally, the book offers a very complete annotated bibliography of GRASP and combinatorial optimizat...

Optimization in liner shipping

DEFF Research Database (Denmark)

Brouer, Berit Dangaard; Karsten, Christian Vad; Pisinger, David

2017-01-01

Seaborne trade is the lynchpin in almost every international supply chain, and about 90% of non-bulk cargo worldwide is transported by container. In this survey we give an overview of data-driven optimization problems in liner shipping. Research in liner shipping is motivated by a need for handling...... still more complex decision problems, based on big data sets and going across several organizational entities. Moreover, liner shipping optimization problems are pushing the limits of optimization methods, creating a new breeding ground for advanced modelling and solution methods. Starting from liner...... shipping network design, we consider the problem of container routing and speed optimization. Next, we consider empty container repositioning and stowage planning as well as disruption management. In addition, the problem of bunker purchasing is considered in depth. In each section we give a clear problem...

Handbook of simulation optimization

CERN Document Server

Fu, Michael C

2014-01-01

The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science,...

Advanced Architectures for Astrophysical Supercomputing

Science.gov (United States)

Barsdell, B. R.; Barnes, D. G.; Fluke, C. J.

2010-12-01

Astronomers have come to rely on the increasing performance of computers to reduce, analyze, simulate and visualize their data. In this environment, faster computation can mean more science outcomes or the opening up of new parameter spaces for investigation. If we are to avoid major issues when implementing codes on advanced architectures, it is important that we have a solid understanding of our algorithms. A recent addition to the high-performance computing scene that highlights this point is the graphics processing unit (GPU). The hardware originally designed for speeding-up graphics rendering in video games is now achieving speed-ups of O(100×) in general-purpose computation - performance that cannot be ignored. We are using a generalized approach, based on the analysis of astronomy algorithms, to identify the optimal problem-types and techniques for taking advantage of both current GPU hardware and future developments in computing architectures.

Uncertainty quantification using evidence theory in multidisciplinary design optimization

International Nuclear Information System (INIS)

Agarwal, Harish; Renaud, John E.; Preston, Evan L.; Padmanabhan, Dhanesh

2004-01-01

Advances in computational performance have led to the development of large-scale simulation tools for design. Systems generated using such simulation tools can fail in service if the uncertainty of the simulation tool's performance predictions is not accounted for. In this research an investigation of how uncertainty can be quantified in multidisciplinary systems analysis subject to epistemic uncertainty associated with the disciplinary design tools and input parameters is undertaken. Evidence theory is used to quantify uncertainty in terms of the uncertain measures of belief and plausibility. To illustrate the methodology, multidisciplinary analysis problems are introduced as an extension to the epistemic uncertainty challenge problems identified by Sandia National Laboratories. After uncertainty has been characterized mathematically the designer seeks the optimum design under uncertainty. The measures of uncertainty provided by evidence theory are discontinuous functions. Such non-smooth functions cannot be used in traditional gradient-based optimizers because the sensitivities of the uncertain measures are not properly defined. In this research surrogate models are used to represent the uncertain measures as continuous functions. A sequential approximate optimization approach is used to drive the optimization process. The methodology is illustrated in application to multidisciplinary example problems

Patient perspectives on the optimal start of renal replacement therapy.

Science.gov (United States)

Henry, Shayna L; Munoz-Plaza, Corrine; Garcia Delgadillo, Jazmine; Mihara, Nichole K; Rutkowski, Mark P

2017-09-01

Healthcare systems and providers are encouraged to prepare their patients with advanced chronic kidney disease (CKD) for a planned start to renal replacement therapies (RRT). Less well understood are the socioemotional experiences surrounding the optimal start of RRT versus suboptimal haemodialysis (HD) starts with a central catheter. To characterise the experiences of patients beginning RRT. Qualitative, semi-structured phone interviews. A total of 168 patients with stage 5 CKD initiating RRT in an integrated, capitated learning healthcare system. Qualitative data from patients were collected as part of a quality improvement initiative to better understand patient-reported themes concerning preparation for RRT, patients' perceptions of their transition to dialysis and why sub-optimal starts for RRT occur within our healthcare system. Dual review and verification was used to identify key phrases and themes within and across each domain, using both deductive a priori codes generated by the interview guide and grounded discovery of emergent themes. From the patient perspective, preparing for RRT is an experience rooted in deep feelings of fear. In addition, a number of key factors contributed to patients' preparation (or failure to prepare) for RRT. While the education provided by our system was viewed as adequate overall, patients often felt that their emotional and psychosocial needs went unmet, regardless of whether or not, they experienced an optimal dialysis start. Future efforts should incorporate additional strategies for helping patients with advanced CKD achieve emotional and psychological safety while preparing for RRT. © 2017 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Intelligent flame analysis for an optimized combustion

Energy Technology Data Exchange (ETDEWEB)

Stephan Peper; Dirk Schmidt [ABB Utilities GmbH, Mainheimm (Germany)

2003-07-01

One of the primary challenges in the area of process control is to ensure that many competing optimization goals are accomplished at the same time and be considered in time. This paper describes a successful approach through the use of an advanced pattern recognition technology and intelligent optimization tool modeling combustion processes more precisely and optimizing them based on a holistic view. 17 PowerPoint slides are also available in the proceedings. 5 figs., 1 tab.

Pyomo optimization modeling in Python

CERN Document Server

Hart, William E; Watson, Jean-Paul; Woodruff, David L; Hackebeil, Gabriel A; Nicholson, Bethany L; Siirola, John D

2017-01-01

This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming. Pyomo is an open source software package fo...

Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non-Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235.

Science.gov (United States)

Ohri, Nitin; Duan, Fenghai; Snyder, Bradley S; Wei, Bo; Machtay, Mitchell; Alavi, Abass; Siegel, Barry A; Johnson, Douglas W; Bradley, Jeffrey D; DeNittis, Albert; Werner-Wasik, Maria; El Naqa, Issam

2016-06-01

In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on (18)F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Patients with locally advanced NSCLC underwent (18)F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient's primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address overfitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan-Meier curves and log-rank testing were used to compare outcomes among patient groups. Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm(3), and the optimal SumMean cutpoint for tumors above 93.3 cm(3) was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non–Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235

Science.gov (United States)

Ohri, Nitin; Duan, Fenghai; Snyder, Bradley S.; Wei, Bo; Machtay, Mitchell; Alavi, Abass; Siegel, Barry A.; Johnson, Douglas W.; Bradley, Jeffrey D.; DeNittis, Albert; Werner-Wasik, Maria; El Naqa, Issam

2016-01-01

In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on 18F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non–small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Methods Patients with locally advanced NSCLC underwent 18F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient’s primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address over-fitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan–Meier curves and log-rank testing were used to compare outcomes among patient groups. Results Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm3, and the optimal Sum-Mean cutpoint for tumors above 93.3 cm3 was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted. PMID:26912429

Today and tomorrow on optimization of structural systems. Kozo system saitekika no genjo to shorai

Energy Technology Data Exchange (ETDEWEB)

1992-07-20

It has been 30 years since a conception structurally optimized design method'' was advocated as a new structural design system which links three factors; mathematical programming, a finite element method, and computers. This paper summarizes the current states in the optimizing technologies in Japan and views over their future, with reference mainly to the two symposiums held in the past as an activity of the subcommittee for structural system optimization in the Japan Society of Civil Engineers. The summary covers the following matters: Optimizing algorithms for structural designs, fuzzy theories, practical use of expert systems and AI, maintenance and management systems for structures, vibration control, shock resistant designs, inverse problems and structure identifying problems, and designs of underground and off-shore structures. For instance, examples of bridge designs include a minimum mass design on a pedestrians' bridge incorporating vibration sensitivities into restricting conditions, comparisons of economics in suspension bridges using a multi-stage determination method, and many others. Optimizing technologies are believed to advance greatly in the future and be used as a very routine design tool. 145 refs., 1 fig., 3 tabs.

Optimization and management in manufacturing engineering resource collaborative optimization and management through the Internet of Things

CERN Document Server

Liu, Xinbao; Liu, Lin; Cheng, Hao; Zhou, Mi; Pardalos, Panos M

2017-01-01

Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book. Recent advances in information technology have transformed the use of resources and data exchange, often leading to management and optimization problems attributable to technology limitations and strong market competition. This book discusses several problems and concepts which makes significant connections in the areas of information sharing, organization management, resource operations, and performance assessment. Geared toward practitioners and researchers, this treatment deepens the understanding between resource collaborative management and advanced information technology. Those in manufacturing will utilize the numerous mathematical models and methods offered to solve practical problems related to cutting stock, supply chain scheduling, and inventory management.  Academics and students with a basic knowledge of manufacturing, c...

Patients' understanding of treatment goals and disease course and their relationship with optimism, hope, and quality of life: a preliminary study among advanced breast cancer outpatients before receiving palliative treatment.

Science.gov (United States)

Soylu, Cem; Babacan, Taner; Sever, Ali R; Altundag, Kadri

2016-08-01

The aims of this study were to explore advanced breast cancer patients' knowledge of treatment intent and expectation of illness course and to evaluate their relationship with optimism, hope, and quality of life (QoL). Patients with advanced breast cancer (n = 55) who were treated in the ambulatory clinic of the University of Hacettepe were included in the study. They completed Life Orientation Scale, The Hope Scale, and the European Organization for Research and Treatment of Cancer Quality of Life questionnaires. The data regarding the knowledge of illness progression and the perceptions of therapy intent were assessed using self-administered open-ended questionnaires that were answered by the patients. The data revealed that 58.2 % of the patients had an inaccurate perception of treatment intent, believing the aim of treatment was cure, whereas only 38.2 % of the patients had a realistic expectation that their disease may remain stable or may progress over a year. In addition, the awareness of disease progression and perception of goals of treatment was significantly related to hope and optimism scores but not to QoL. A large proportion of patients diagnosed with advanced breast cancer believed that their treatment was "curative", and they would improve within a year. Findings of our study suggest that patients with inaccurate perception of treatment intent and unrealistic expectation of prognosis have higher hope and optimism scores than those who do not, but there were no significant differences in terms of global health status.

Advanced metaheuristic algorithms for laser optimization

International Nuclear Information System (INIS)

Tomizawa, H.

2010-01-01

A laser is one of the most important experimental tools. In synchrotron radiation field, lasers are widely used for experiments with Pump-Probe techniques. Especially for Xray-FELs, a laser has important roles as a seed light source or photo-cathode-illuminating light source to generate a high brightness electron bunch. The controls of laser pulse characteristics are required for many kinds of experiments. However, the laser should be tuned and customized for each requirement by laser experts. The automatic tuning of laser is required to realize with some sophisticated algorithms. The metaheuristic algorithm is one of the useful candidates to find one of the best solutions as acceptable as possible. The metaheuristic laser tuning system is expected to save our human resources and time for the laser preparations. I have shown successful results on a metaheuristic algorithm based on a genetic algorithm to optimize spatial (transverse) laser profiles and a hill climbing method extended with a fuzzy set theory to choose one of the best laser alignments automatically for each experimental requirement. (author)

Kinematic Optimization in Birds, Bats and Ornithopters

Science.gov (United States)

Reichert, Todd

Birds and bats employ a variety of advanced wing motions in the efficient production of thrust. The purpose of this thesis is to quantify the benefit of these advanced wing motions, determine the optimal theoretical wing kinematics for a given flight condition, and to develop a methodology for applying the results in the optimal design of flapping-wing aircraft (ornithopters). To this end, a medium-fidelity, combined aero-structural model has been developed that is capable of simulating the advanced kinematics seen in bird flight, as well as the highly non-linear structural deformations typical of high-aspect ratio wings. Five unique methods of thrust production observed in natural species have been isolated, quantified and thoroughly investigated for their dependence on Reynolds number, airfoil selection, frequency, amplitude and relative phasing. A gradient-based optimization algorithm has been employed to determined the wing kinematics that result in the minimum required power for a generalized aircraft or species in any given flight condition. In addition to the theoretical work, with the help of an extended team, the methodology was applied to the design and construction of the world's first successful human-powered ornithopter. The Snowbird Human-Powered Ornithopter, is used as an example aircraft to show how additional design constraints can pose limits on the optimal kinematics. The results show significant trends that give insight into the kinematic operation of natural species. The general result is that additional complexity, whether it be larger twisting deformations or advanced wing-folding mechanisms, allows for the possibility of more efficient flight. At its theoretical optimum, the efficiency of flapping-wings exceeds that of current rotors and propellers, although these efficiencies are quite difficult to achieve in practice.

Advanced digital PWR plant protection system based on optimal estimation theory

International Nuclear Information System (INIS)

Tylee, J.L.

1981-04-01

An advanced plant protection system for the Loss-of-Fluid Test (LOFT) reactor plant is described and evaluated. The system, based on a Kalman filter estimator, is capable of providing on-line estimates of such critical variables as fuel and cladding temperature, departure from nucleate boiling ratio, and maximum linear heat generation rate. The Kalman filter equations are presented, as is a description of the LOFT plant dynamic model inherent in the filter. Simulation results demonstrate the performance of the advanced system

Application of response surface methodology for optimization of natural organic matter degradation by UV/H2O2 advanced oxidation process.

Science.gov (United States)

Rezaee, Reza; Maleki, Afshin; Jafari, Ali; Mazloomi, Sajad; Zandsalimi, Yahya; Mahvi, Amir H

2014-01-01

In this research, the removal of natural organic matter from aqueous solutions using advanced oxidation processes (UV/H2O2) was evaluated. Therefore, the response surface methodology and Box-Behnken design matrix were employed to design the experiments and to determine the optimal conditions. The effects of various parameters such as initial concentration of H2O2 (100-180 mg/L), pH (3-11), time (10-30 min) and initial total organic carbon (TOC) concentration (4-10 mg/L) were studied. Analysis of variance (ANOVA), revealed a good agreement between experimental data and proposed quadratic polynomial model (R(2) = 0.98). Experimental results showed that with increasing H2O2 concentration, time and decreasing in initial TOC concentration, TOC removal efficiency was increased. Neutral and nearly acidic pH values also improved the TOC removal. Accordingly, the TOC removal efficiency of 78.02% in terms of the independent variables including H2O2 concentration (100 mg/L), pH (6.12), time (22.42 min) and initial TOC concentration (4 mg/L) were optimized. Further confirmation tests under optimal conditions showed a 76.50% of TOC removal and confirmed that the model is accordance with the experiments. In addition TOC removal for natural water based on response surface methodology optimum condition was 62.15%. This study showed that response surface methodology based on Box-Behnken method is a useful tool for optimizing the operating parameters for TOC removal using UV/H2O2 process.

Hierarchthis: An Interactive Interface for Identifying Mission-Relevant Components of the Advanced Multi-Mission Operations System

Science.gov (United States)

Litomisky, Krystof

2012-01-01

Even though NASA's space missions are many and varied, there are some tasks that are common to all of them. For example, all spacecraft need to communicate with other entities, and all spacecraft need to know where they are. These tasks use tools and services that can be inherited and reused between missions, reducing systems engineering effort and therefore reducing cost.The Advanced Multi-Mission Operations System, or AMMOS, is a collection of multimission tools and services, whose development and maintenance are funded by NASA. I created HierarchThis, a plugin designed to provide an interactive interface to help customers identify mission-relevant tools and services. HierarchThis automatically creates diagrams of the AMMOS database, and then allows users to show/hide specific details through a graphical interface. Once customers identify tools and services they want for a specific mission, HierarchThis can automatically generate a contract between the Multimission Ground Systems and Services Office, which manages AMMOS, and the customer. The document contains the selected AMMOS components, along with their capabilities and satisfied requirements. HierarchThis reduces the time needed for the process from service selections to having a mission-specific contract from the order of days to the order of minutes.

Advanced Horizontal Well Recirculation Systems for Geothermal Energy Recovery in Sedimentary and Crystalline Formations

Energy Technology Data Exchange (ETDEWEB)

Bruno, Mike S. [Terralog Technologies USA, Inc., Calgary (Canada); Detwiler, Russell L. [Terralog Technologies USA, Inc., Calgary (Canada); Lao, Kang [Terralog Technologies USA, Inc., Calgary (Canada); Serajian, Vahid [Terralog Technologies USA, Inc., Calgary (Canada); Elkhoury, Jean [Terralog Technologies USA, Inc., Calgary (Canada); Diessl, Julia [Terralog Technologies USA, Inc., Calgary (Canada); White, Nicky [Terralog Technologies USA, Inc., Calgary (Canada)

2012-12-13

There is increased recognition that geothermal energy resources are more widespread than previously thought, with potential for providing a significant amount of sustainable clean energy worldwide. Recent advances in drilling, completion, and production technology from the oil and gas industry can now be applied to unlock vast new geothermal resources, with some estimates for potential electricity generation from geothermal energy now on the order of 2 million megawatts. The primary objectives of this DOE research effort are to develop and document optimum design configurations and operating practices to produce geothermal power from hot permeable sedimentary and crystalline formations using advanced horizontal well recirculation systems. During Phase I of this research project Terralog Technologies USA and The University of California, Irvine (UCI), have completed preliminary investigations and documentation of advanced design concepts for paired horizontal well recirculation systems, optimally configured for geothermal energy recovery in permeable sedimentary and crystalline formations of varying structure and material properties. We have also identified significant geologic resources appropriate for application of such technology. The main challenge for such recirculation systems is to optimize both the design configuration and the operating practices for cost-effective geothermal energy recovery. These will be strongly influenced by sedimentary formation properties, including thickness and dip, temperature, thermal conductivity, heat capacity, permeability, and porosity; and by working fluid properties.

Automation method to identify the geological structure of seabed using spatial statistic analysis of echo sounding data

Science.gov (United States)

Kwon, O.; Kim, W.; Kim, J.

2017-12-01

Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics

NonLinear Parallel OPtimization Tool, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The technological advancement proposed is a novel large-scale Noninear Parallel OPtimization Tool (NLPAROPT). This software package will eliminate the computational...

Identifying optimal models to represent biochemical systems.

Directory of Open Access Journals (Sweden)

Mochamad Apri

Full Text Available Biochemical systems involving a high number of components with intricate interactions often lead to complex models containing a large number of parameters. Although a large model could describe in detail the mechanisms that underlie the system, its very large size may hinder us in understanding the key elements of the system. Also in terms of parameter identification, large models are often problematic. Therefore, a reduced model may be preferred to represent the system. Yet, in order to efficaciously replace the large model, the reduced model should have the same ability as the large model to produce reliable predictions for a broad set of testable experimental conditions. We present a novel method to extract an "optimal" reduced model from a large model to represent biochemical systems by combining a reduction method and a model discrimination method. The former assures that the reduced model contains only those components that are important to produce the dynamics observed in given experiments, whereas the latter ensures that the reduced model gives a good prediction for any feasible experimental conditions that are relevant to answer questions at hand. These two techniques are applied iteratively. The method reveals the biological core of a model mathematically, indicating the processes that are likely to be responsible for certain behavior. We demonstrate the algorithm on two realistic model examples. We show that in both cases the core is substantially smaller than the full model.

Optimization with PDE constraints ESF networking program 'OPTPDE'

CERN Document Server

2014-01-01

This book on PDE Constrained Optimization contains contributions on the mathematical analysis and numerical solution of constrained optimal control and optimization problems where a partial differential equation (PDE) or a system of PDEs appears as an essential part of the constraints. The appropriate treatment of such problems requires a fundamental understanding of the subtle interplay between optimization in function spaces and numerical discretization techniques and relies on advanced methodologies from the theory of PDEs and numerical analysis as well as scientific computing. The contributions reflect the work of the European Science Foundation Networking Programme ’Optimization with PDEs’ (OPTPDE).

Optimizing the electrical excitation of an atmospheric pressure plasma advanced oxidation process.

Science.gov (United States)

Olszewski, P; Li, J F; Liu, D X; Walsh, J L

2014-08-30

The impact of pulse-modulated generation of atmospheric pressure plasma on the efficiency of organic dye degradation has been investigated. Aqueous samples of methyl orange were exposed to low temperature air plasma and the degradation efficiency was determined by absorbance spectroscopy. The plasma was driven at a constant frequency of 35kHz with a duty cycle of 25%, 50%, 75% and 100%. Relative concentrations of dissolved nitrogen oxides, pH, conductivity and the time evolution of gas phase ozone were measured to identify key parameters responsible for the changes observed in degradation efficiency. The results indicate that pulse modulation significantly improved dye degradation efficiency, with a plasma pulsed at 25% duty showing a two-fold enhancement. Additionally, pulse modulation led to a reduction in the amount of nitrate contamination added to the solution by the plasma. The results clearly demonstrate that optimization of the electrical excitation of the plasma can enhance both degradation efficiency and the final water quality. Copyright © 2014 Elsevier B.V. All rights reserved.

Selection of the optimal radiotherapy technique for locally advanced hepatocellular carcinoma

International Nuclear Information System (INIS)

Lee, Ik-Jae; Seong, Jinsil; Koom, Woong-Sub; Kim, Yong-Bae; Jeon, Byeong-Chul; Kim, Joo-Ho; Han, Kwang-Hyub

2011-01-01

Various techniques are available for radiotherapy of hepatocellular carcinoma, including three-dimensional conformal radiotherapy, linac-based intensity-modulated radiotherapy and helical tomotherapy. The purpose of this study was to determine the optimal radiotherapy technique for hepatocellular carcinoma. Between 2006 and 2007, 12 patients underwent helical tomotherapy for locally advanced hepatocellular carcinoma. Helical tomotherapy computerized radiotherapy planning was compared with the best computerized radiotherapy planning for three-dimensional conformal radiotherapy and linac-based intensity-modulated radiotherapy for the delivery of 60 Gy in 30 fractions. Tumor coverage was assessed by conformity index, radical dose homogeneity index and moderated dose homogeneity index. Computerized radiotherapy planning was also compared according to the tumor location. Tumor coverage was shown to be significantly superior with helical tomotherapy as assessed by conformity index and moderated dose homogeneity index (P=0.002 and 0.03, respectively). Helical tomotherapy showed significantly lower irradiated liver volume at 40, 50 and 60 Gy (V40, V50 and V60, P=0.04, 0.03 and 0.01, respectively). On the contrary, the dose-volume of three-dimensional conformal radiotherapy at V20 was significantly smaller than those of linac-based intensity-modulated radiotherapy and helical tomotherapy in the remaining liver (P=0.03). Linac-based intensity-modulated radiotherapy showed better sparing of the stomach compared with helical tomotherapy in the case of separated lesions in both lobes (12.3 vs. 24.6 Gy). Helical tomotherapy showed the high dose-volume exposure to the left kidney due to helical delivery in the right lobe lesion. Helical tomotherapy achieved the best tumor coverage of the remaining normal liver. However, helical tomotherapy showed much exposure to the remaining liver at the lower dose region and left kidney. (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.

Application of Spatial Data Modeling Systems, Geographical Information Systems (GIS), and Transportation Routing Optimization Methods for Evaluating Integrated Deployment of Interim Spent Fuel Storage Installations and Advanced Nuclear Plants

International Nuclear Information System (INIS)

Mays, Gary T.; Belles, Randy; Cetiner, Mustafa Sacit; Howard, Rob L.; Liu, Cheng; Mueller, Don; Omitaomu, Olufemi A.; Peterson, Steven K.; Scaglione, John M.

2012-01-01

The objective of this siting study work is to support DOE in evaluating integrated advanced nuclear plant and ISFSI deployment options in the future. This study looks at several nuclear power plant growth scenarios that consider the locations of existing and planned commercial nuclear power plants integrated with the establishment of consolidated interim spent fuel storage installations (ISFSIs). This research project is aimed at providing methodologies, information, and insights that inform the process for determining and optimizing candidate areas for new advanced nuclear power generation plants and consolidated ISFSIs to meet projected US electric power demands for the future.

Application of Spatial Data Modeling Systems, Geographical Information Systems (GIS), and Transportation Routing Optimization Methods for Evaluating Integrated Deployment of Interim Spent Fuel Storage Installations and Advanced Nuclear Plants

Energy Technology Data Exchange (ETDEWEB)

Mays, Gary T [ORNL; Belles, Randy [ORNL; Cetiner, Sacit M [ORNL; Howard, Rob L [ORNL; Liu, Cheng [ORNL; Mueller, Don [ORNL; Omitaomu, Olufemi A [ORNL; Peterson, Steven K [ORNL; Scaglione, John M [ORNL

2012-06-01

The objective of this siting study work is to support DOE in evaluating integrated advanced nuclear plant and ISFSI deployment options in the future. This study looks at several nuclear power plant growth scenarios that consider the locations of existing and planned commercial nuclear power plants integrated with the establishment of consolidated interim spent fuel storage installations (ISFSIs). This research project is aimed at providing methodologies, information, and insights that inform the process for determining and optimizing candidate areas for new advanced nuclear power generation plants and consolidated ISFSIs to meet projected US electric power demands for the future.

Reliability and optimization of structural systems

International Nuclear Information System (INIS)

Thoft-Christensen, P.

1987-01-01

The proceedings contain 28 papers presented at the 1st working conference. The working conference was organized by the IFIP Working Group 7.5. The proceedings also include 4 papers which were submitted, but for various reasons not presented at the working conference. The working conference was attended by 50 participants from 18 countries. The conference was the first scientific meeting of the new IFIP Working Group 7.5 on 'Reliability and Optimization of Structural Systems'. The purpose of the Working Group 7.5 is to promote modern structural system optimization and reliability theory, to advance international cooperation in the field of structural system optimization and reliability theory, to stimulate research, development and application of structural system optimization and reliability theory, to further the dissemination and exchange of information on reliability and optimization of structural system optimization and reliability theory, and to encourage education in structural system optimization and reliability theory. (orig./HP)

Development of Optimal Water-Resources Management Strategies for Kaidu-Kongque Watershed under Multiple Uncertainties

Directory of Open Access Journals (Sweden)

Y. Zhou

2013-01-01

Full Text Available In this study, an interval-stochastic fractile optimization (ISFO model is advanced for developing optimal water-resources management strategies under multiple uncertainties. The ISFO model can not only handle uncertainties presented in terms of probability distributions and intervals with possibility distribution boundary, but also quantify subjective information (i.e., expected system benefit preference and risk-averse attitude from different decision makers. The ISFO model is then applied to a real case of water-resources systems planning in Kaidu-kongque watershed, China, and a number of scenarios with different ecological water-allocation policies under varied p-necessity fractiles are analyzed. Results indicate that different policies for ecological water allocation can lead to varied water supplies, economic penalties, and system benefits. The solutions obtained can help decision makers identify optimized water-allocation alternatives, alleviate the water supply-demand conflict, and achieve socioeconomic and ecological sustainability, particularly when limited water resources are available for multiple competing users.

MO-FG-207-02: Technological Advances and Challenges: Experience with Time-Of-Flight PET Combined with 3-Tesla MRI

International Nuclear Information System (INIS)

Jansen, F.

2015-01-01

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee

MO-FG-207-02: Technological Advances and Challenges: Experience with Time-Of-Flight PET Combined with 3-Tesla MRI

Energy Technology Data Exchange (ETDEWEB)

Jansen, F. [GE Healthcare (United Kingdom)

2015-06-15

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

Plant protection system optimization studies to mitigate consequences of large breaks in the advanced neutron source reactor

International Nuclear Information System (INIS)

Khayat, M.I.; March-Leuba, J.

1993-01-01

This paper documents some of the optimization studies performed to maximize the performance of the engineered safety features and scram systems to mitigate the consequences of large breaks in the primary cooling system of the advanced neutron source (ANS) reactor. The ANS is a new basic and applied research facility based on a powerful steady-state research reactor that provides beams of neutrons for measurements and experiments in the field of material science and engineering, biology, chemistry, material analysis, and nuclear science. To achieve the high neutron fluxes for these state-of-the-art experiments, the ANS design has a very high power density core (330 MW fission with an active volume of 67.6 ell) surrounded by a large heavy-water reflector, where most neutrons are moderated. This design maximizes the number of neutrons available for experiments but results in a low heat capacity core that creates unique challenges to the design of the plant protection system

Dependability of self-optimizing mechatronic systems

CERN Document Server

Rammig, Franz; Schäfer, Wilhelm; Sextro, Walter

2014-01-01

Intelligent technical systems, which combine mechanical, electrical and software engineering with control engineering and advanced mathematics, go far beyond the state of the art in mechatronics and open up fascinating perspectives. Among these systems are so-called self-optimizing systems, which are able to adapt their behavior autonomously and flexibly to changing operating conditions. Self-optimizing systems create high value for example in terms of energy and resource efficiency as well as reliability. The Collaborative Research Center 614 "Self-optimizing Concepts and Structures in Mechanical Engineering" pursued the long-term aim to open up the active paradigm of self-optimization for mechanical engineering and to enable others to develop self-optimizing systems. This book is directed to researchers and practitioners alike. It provides a design methodology for the development of self-optimizing systems consisting of a reference process, methods, and tools. The reference process is divided into two phase...

Optimization in engineering models and algorithms

CERN Document Server

Sioshansi, Ramteen

2017-01-01

This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering ...

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

Advances in LWD pressure measurements: smart, time optimized pretests and on demand real-time transmission applications

Energy Technology Data Exchange (ETDEWEB)

Serafim, Robson; Ferraris, Paolo [Schlumberger, Rio de Janeiro, RJ (Brazil)

2008-07-01

The StethoScope Logging While Drilling (LWD) Pressure Measurement, introduced in Brazil in 2005, has been extensively used in deep water environment to provide reservoir pressure and mobility in real-time. In the last three years the StethoScope service was further enhanced to allow better real time monitoring using a larger transmission rate, higher RT data resolution and remote visualization. In order to guarantee stable formation pressures with a limited test duration under a wide range of conditions, Time Optimized Pretests (TOP) were developed. These tests adjust automatically drawdown and buildup parameters as a function of formation characteristics (pressure/mobility) without requiring any input from the operator. On-demand frame (ODF), an advanced telemetry triggered automatically during the pressure tests, allowed to increase equivalent transmission rate and resolution and to include quality indices computed downhole. This paper is focused on the TOP and ODF Field Test results in Brazil, which proved to be useful and reliable options for better real-time decisions together with remote monitoring visualization implemented by the RTMonitor program. (author)

Association between frequent cardiac resynchronization therapy optimization and long-term clinical response: a post hoc analysis of the Clinical Evaluation on Advanced Resynchronization (CLEAR) pilot study

Science.gov (United States)

Delnoy, Peter Paul; Ritter, Philippe; Naegele, Herbert; Orazi, Serafino; Szwed, Hanna; Zupan, Igor; Goscinska-Bis, Kinga; Anselme, Frederic; Martino, Maria; Padeletti, Luigi

2013-01-01

Aims The long-term clinical value of the optimization of atrioventricular (AVD) and interventricular (VVD) delays in cardiac resynchronization therapy (CRT) remains controversial. We studied retrospectively the association between the frequency of AVD and VVD optimization and 1-year clinical outcomes in the 199 CRT patients who completed the Clinical Evaluation on Advanced Resynchronization study. Methods and results From the 199 patients assigned to CRT-pacemaker (CRT-P) (New York Heart Association, NYHA, class III/IV, left ventricular ejection fraction failure-related hospitalization, NYHA functional class, and Quality of Life score, at 1 year. Systematic CRT optimization was associated with a higher percentage of improved patients based on the composite endpoint (85% in Group 1 vs. 61% in Group 2, P < 0.001), with fewer deaths (3% in Group 1 vs. 14% in Group 2, P = 0.014) and fewer hospitalizations (8% in Group 1 vs. 23% in Group 2, P = 0.007), at 1 year. Conclusion These results further suggest that AVD and VVD frequent optimization (at implant, at 3 and 6 months) is associated with improved long-term clinical response in CRT-P patients. PMID:23493410

Completing advance directives for health care decisions: getting to yes.

Science.gov (United States)

Shewchuk, T R

1998-09-01

The concept of advance directives for health care decision making has been judicially condoned, legislatively promoted, and systematically implemented by health care institutions, yet the execution rate of advance directives remains low. Physicians should discuss with their patients advance care planning generally and end-of-life issues specifically, preferably when patients are in good health and not when they face an acute medical crisis. The physician-hospital relationship poses particular challenges for the optimal implementation of advance directives that must be addressed. Hospital administrators must improve education of patients and physicians on the value of such documents as well as internal mechanisms to ensure better implementation of directives. Health insurance plans may be better able to ensure optimal gathering and implementation of directives. Patients must become more familiar and more comfortable with advance care planning and the reality of death and dying issues. Full acceptance of the value of directives ultimately rests on achieving full participation of all involved--providers, patients, families, and payors--in this most profound process.

Co-Optimization of Internal Combustion Engines and Biofuels

Energy Technology Data Exchange (ETDEWEB)

McCormick, Robert L.

2016-03-08

The development of advanced engines has significant potential advantages in reduced aftertreatment costs for air pollutant emission control, and just as importantly for efficiency improvements and associated greenhouse gas emission reductions. There are significant opportunities to leverage fuel properties to create more optimal engine designs for both advanced spark-ignition and compression-ignition combustion strategies. The fact that biofuel blendstocks offer a potentially low-carbon approach to fuel production, leads to the idea of optimizing the entire fuel production-utilization value chain as a system from the standpoint of life cycle greenhouse gas emissions. This is a difficult challenge that has yet to be realized. This presentation will discuss the relationship between chemical structure and critical fuel properties for more efficient combustion, survey the properties of a range of biofuels that may be produced in the future, and describe the ongoing challenges of fuel-engine co-optimization.

Parameter Identification with the Random Perturbation Particle Swarm Optimization Method and Sensitivity Analysis of an Advanced Pressurized Water Reactor Nuclear Power Plant Model for Power Systems

Directory of Open Access Journals (Sweden)

Li Wang

2017-02-01

Full Text Available The ability to obtain appropriate parameters for an advanced pressurized water reactor (PWR unit model is of great significance for power system analysis. The attributes of that ability include the following: nonlinear relationships, long transition time, intercoupled parameters and difficult obtainment from practical test, posed complexity and difficult parameter identification. In this paper, a model and a parameter identification method for the PWR primary loop system were investigated. A parameter identification process was proposed, using a particle swarm optimization (PSO algorithm that is based on random perturbation (RP-PSO. The identification process included model variable initialization based on the differential equations of each sub-module and program setting method, parameter obtainment through sub-module identification in the Matlab/Simulink Software (Math Works Inc., Natick, MA, USA as well as adaptation analysis for an integrated model. A lot of parameter identification work was carried out, the results of which verified the effectiveness of the method. It was found that the change of some parameters, like the fuel temperature and coolant temperature feedback coefficients, changed the model gain, of which the trajectory sensitivities were not zero. Thus, obtaining their appropriate values had significant effects on the simulation results. The trajectory sensitivities of some parameters in the core neutron dynamic module were interrelated, causing the parameters to be difficult to identify. The model parameter sensitivity could be different, which would be influenced by the model input conditions, reflecting the parameter identifiability difficulty degree for various input conditions.

Advanced thermal barrier coatings for operation in high hydrogen content fueled gas turbines.

Energy Technology Data Exchange (ETDEWEB)

Sampath, Sanjay [Stony Brook Univ., NY (United States)

2015-04-02

and resulted in improved TBC lifetimes. Processing based approaches of identifying optimal processing regimes deploying advanced in-situ coating property measurements and in-flight diagnostic tools were used to develop process maps for bond coats. Having established a framework for the bond coat processing using the HVOF process, effort were channeled towards fabrication of APS and VPS bond coats with the same material composition. Comparative evaluation of the three deposition processes with regard to their microstrcuture , surface profiles and TBC performance were carried out and provided valuable insights into factors that require concurrent consideration for the development of bond coats for advanced TBC systems. Over the course of this program several advancements were made on the development of durable thermal barrier coatings. Process optimization techniques were utilized to identify processing regimes for both conventional YSZ as well as other TBC compositions such as Gadolinium Zirconate and other Co-doped materials. Measurement of critical properties for these formed the initial stages of the program to identify potential challenges in their implementation as part of a TBC system. High temperature thermal conductivity measurements as well as sintering behavior of both YSZ and GDZ coatings were evaluated as part of initial efforts to undersand the influence of processing on coating properties. By effectively linking fundamental coating properties of fracture toughness and elastic modulus to the cyclic performance of coatings, a durability strategy for APS YSZ coatings was developed. In order to meet the goals of fabricating a multimaterial TBC system further research was carried out on the development of a gradient thermal conductivity model and the evaluation of sintering behavior of multimaterial coatings. Layer optimization for desired properties in the multimaterial TBC was achieved by an iterative feedback approach utilizing process maps and in-situ and

Optimal dynamic detection of explosives

Energy Technology Data Exchange (ETDEWEB)

Moore, David Steven [Los Alamos National Laboratory; Mcgrane, Shawn D [Los Alamos National Laboratory; Greenfield, Margo T [Los Alamos National Laboratory; Scharff, R J [Los Alamos National Laboratory; Rabitz, Herschel A [PRINCETON UNIV; Roslund, J [PRINCETON UNIV

2009-01-01

The detection of explosives is a notoriously difficult problem, especially at stand-off distances, due to their (generally) low vapor pressure, environmental and matrix interferences, and packaging. We are exploring optimal dynamic detection to exploit the best capabilities of recent advances in laser technology and recent discoveries in optimal shaping of laser pulses for control of molecular processes to significantly enhance the standoff detection of explosives. The core of the ODD-Ex technique is the introduction of optimally shaped laser pulses to simultaneously enhance sensitivity of explosives signatures while reducing the influence of noise and the signals from background interferents in the field (increase selectivity). These goals are being addressed by operating in an optimal nonlinear fashion, typically with a single shaped laser pulse inherently containing within it coherently locked control and probe sub-pulses. With sufficient bandwidth, the technique is capable of intrinsically providing orthogonal broad spectral information for data fusion, all from a single optimal pulse.

Identifying the optimal supply temperature in district heating networks - A modelling approach

DEFF Research Database (Denmark)

Mohammadi, Soma; Bojesen, Carsten

2014-01-01

of this study is to develop a model for thermo-hydraulic calculation of low temperature DH system. The modelling is performed with emphasis on transient heat transfer in pipe networks. The pseudo-dynamic approach is adopted to model the District Heating Network [DHN] behaviour which estimates the temperature...... dynamically while the flow and pressure are calculated on the basis of steady state conditions. The implicit finite element method is applied to simulate the transient temperature behaviour in the network. Pipe network heat losses, pressure drop in the network and return temperature to the plant...... are calculated in the developed model. The model will serve eventually as a basis to find out the optimal supply temperature in an existing DHN in later work. The modelling results are used as decision support for existing DHN; proposing possible modifications to operate at optimal supply temperature....

Control parameter optimization for AP1000 reactor using Particle Swarm Optimization

International Nuclear Information System (INIS)

Wang, Pengfei; Wan, Jiashuang; Luo, Run; Zhao, Fuyu; Wei, Xinyu

2016-01-01

Highlights: • The PSO algorithm is applied for control parameter optimization of AP1000 reactor. • Key parameters of the MSHIM control system are optimized. • Optimization results are evaluated though simulations and quantitative analysis. - Abstract: The advanced mechanical shim (MSHIM) core control strategy is implemented in the AP1000 reactor for core reactivity and axial power distribution control simultaneously. The MSHIM core control system can provide superior reactor control capabilities via automatic rod control only. This enables the AP1000 to perform power change operations automatically without the soluble boron concentration adjustments. In this paper, the Particle Swarm Optimization (PSO) algorithm has been applied for the parameter optimization of the MSHIM control system to acquire better reactor control performance for AP1000. System requirements such as power control performance, control bank movement and AO control constraints are reflected in the objective function. Dynamic simulations are performed based on an AP1000 reactor simulation platform in each iteration of the optimization process to calculate the fitness values of particles in the swarm. The simulation platform is developed in Matlab/Simulink environment with implementation of a nodal core model and the MSHIM control strategy. Based on the simulation platform, the typical 10% step load decrease transient from 100% to 90% full power is simulated and the objective function used for control parameter tuning is directly incorporated in the simulation results. With successful implementation of the PSO algorithm in the control parameter optimization of AP1000 reactor, four key parameters of the MSHIM control system are optimized. It has been demonstrated by the calculation results that the optimized MSHIM control system parameters can improve the reactor power control capability and reduce the control rod movement without compromising AO control. Therefore, the PSO based optimization

Physics and safety of advanced research reactors

International Nuclear Information System (INIS)

Boening, K.; Hardt, P. von der

1987-01-01

Advanced research reactor concepts are presently being developed in order to meet the neutron-based research needs of the nineties. Among these research reactors, which are characterized by an average power density of 1-10 MW per liter, highest priority is now generally given to the 'beam tube reactors'. These provide very high values of the thermal neutron flux (10 14 -10 16 cm -2 s -1 ) in a large volume outside of the reactor core, which can be used for sample irradiations and, in particular, for neutron scattering experiments. The paper first discusses the 'inverse flux trap concept' and the main physical aspects of the design and optimization of beam tube reactors. After that two examples of advanced research reactor projects are described which may be considered as two opposite extremes with respect to the physical optimization principle just mentioned. The present situation concerning cross section libraries and neutronic computer codes is more or less satisfactory. The safety analyses of advanced research reactors can largely be updated from those of current new designs, partially taking advantage of the immense volume of work done for power reactors. The paper indicates a few areas where generic problems for advanced research reactor safety are to be solved. (orig.)

8th Workshop on Computational Optimization

CERN Document Server

2016-01-01

This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2015. It presents recent advances in computational optimization. The volume includes important real life problems like parameter settings for controlling processes in bioreactor, control of ethanol production, minimal convex hill with application in routing algorithms, graph coloring, flow design in photonic data transport system, predicting indoor temperature, crisis control center monitoring, fuel consumption of helicopters, portfolio selection, GPS surveying and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics, medicine and other domains can be formulated as optimization problems. .

Practice parameters facilitating adoption of advanced technologies for enhancing neuropsychological assessment paradigms.

Science.gov (United States)

Parsons, Thomas D; McMahan, Timothy; Kane, Robert

2018-01-01

Clinical neuropsychologists have long underutilized computer technologies for neuropsychological assessment. Given the rapid advances in technology (e.g. virtual reality; tablets; iPhones) and the increased accessibility in the past decade, there is an on-going need to identify optimal specifications for advanced technologies while minimizing potential sources of error. Herein, we discuss concerns raised by a joint American Academy of Clinical Neuropsychology/National Academy of Neuropsychology position paper. Moreover, we proffer parameters for the development and use of advanced technologies in neuropsychological assessments. We aim to first describe software and hardware configurations that can impact a computerized neuropsychological assessment. This is followed by a description of best practices for developers and practicing neuropsychologists to minimize error in neuropsychological assessments using advanced technologies. We also discuss the relevance of weighing potential computer error in light of possible errors associated with traditional testing. Throughout there is an emphasis on the need for developers to provide bench test results for their software's performance on various devices and minimum specifications (documented in manuals) for the hardware (e.g. computer, monitor, input devices) in the neuropsychologist's practice. Advances in computerized assessment platforms offer both opportunities and challenges. The challenges can appear daunting but are a manageable and require informed consumers who can appreciate the issues and ask pertinent questions in evaluating their options.

Portfolio Optimization and Mortgage Choice

Directory of Open Access Journals (Sweden)

Maj-Britt Nordfang

2017-01-01

Full Text Available This paper studies the optimal mortgage choice of an investor in a simple bond market with a stochastic interest rate and access to term life insurance. The study is based on advances in stochastic control theory, which provides analytical solutions to portfolio problems with a stochastic interest rate. We derive the optimal portfolio of a mortgagor in a simple framework and formulate stylized versions of mortgage products offered in the market today. This allows us to analyze the optimal investment strategy in terms of optimal mortgage choice. We conclude that certain extreme investors optimally choose either a traditional fixed rate mortgage or an adjustable rate mortgage, while investors with moderate risk aversion and income prefer a mix of the two. By matching specific investor characteristics to existing mortgage products, our study provides a better understanding of the complex and yet restricted mortgage choice faced by many household investors. In addition, the simple analytical framework enables a detailed analysis of how changes to market, income and preference parameters affect the optimal mortgage choice.

Advances in transport phenomena 2011

CERN Document Server

2014-01-01

This new volume of the annual review “Advances in Transport Phenomena” series contains three in-depth review articles on the microfluidic fabrication of vesicles, the dielectrophoresis field-flow fractionation for continuous-flow separation of particles and cells in microfluidic devices, and the thermodynamic analysis and optimization of heat exchangers, respectively.

Development of optimized advanced austenitic steels (II). Evaluation of out-of-pile testing results of the test fuel claddings

Energy Technology Data Exchange (ETDEWEB)

Uwaba, Tomoyuki; Mizuta, Shunji; Ukai, Shigeharu [Japan Nuclear Cycle Development Inst., Oarai, Ibaraki (Japan). Oarai Engineering Center

2000-03-01

14Cr-25Ni optimized advanced austenitic steels have been developed to improve the swelling resistance of 15Cr-20Ni austenitic stainless steels used for FBR fuel cladding. In this improvement, Ti, Nb, V and P were dissolved into 14Cr-25Ni matrix by means of the high-temperature solution treatment to make finely distributed and stabilized precipitates in the operation. Furthermore, at the final stage of cold-working, cold-working level increased and residual stress was reduced. In this study, as fabricated microstructure observation, solubility of alloying elements and grain size test in the manufacturing process were evaluated. Following results were obtained. (1) Spherical precipitates were observed in the grain. Most of them were identified as complexed carbide-nitride [Ti,Nb(C,N)] by EDX analysis. (2) The dissolved percentages of Ti and Ni in the matrix were about 70% and 30% respectively. Undissolved Ti and Nb may react with undissolved carbon and precipitate as MC carbides. (3) High-temperature solution treatment is effective for the sufficient solubility of alloying elements, but it is likely to induce very large grains, which is the cause of defective signal in the ultrasonic alloy testing. The results of the grain size test showed that the large grain size is reduced in low Nb (0.1wt%) alloy compared with the standard alloy (0.2wt% Nb), and the effectiveness for the grain size control by reducing the Nb content was confirmed. Also, it was suggested that the intermediate heat treatment and cold work conditions would possibly avoid the occurrence of the large grain at the final heat treatment. (author)

Software for industrial consumers electrical energy tariff optimal selection

OpenAIRE

Simona Ardelean; A. Ceclan; L. Czumbil; D. D. Micu; E. Simion

2008-01-01

This paper briefly presents someelectrical energy management techniques andproposes a software product dedicated forautomatic choose of the optimal tariff structure forindustrial consumers. The optimal choose ofelectrical energy invoicing model proves to be anefficient way to bring quality and economies in anycompanies administration. Advanced description ofthe proposed software is also presented.

Intensity-modulated radiation therapy (IMRT) for locally advanced paranasal sinus tumors: incorporating clinical decisions in the optimization process

International Nuclear Information System (INIS)

Tsien, Christina; Eisbruch, Avraham; McShan, Daniel; Kessler, Marc; Marsh, Robin C.; Fraass, Benedick

2003-01-01

Purpose: Intensity-modulated radiotherapy (IMRT) plans require decisions about priorities and tradeoffs among competing goals. This study evaluates the incorporation of various clinical decisions into the optimization system, using locally advanced paranasal sinus tumors as a model. Methods and Materials: Thirteen patients with locally advanced paranasal sinus tumors were retrospectively replanned using inverse planning. Two clinical decisions were assumed: (1) Spare both optic pathways (OP), or (2) Spare only the contralateral OP. In each case, adequate tumor coverage (treated to 70 Gy in 35 fractions) was required. Two beamlet IMRT plans were thus developed for each patient using a class solution cost function. By altering one key variable at a time, different levels of risk of OP toxicity and planning target volume (PTV) compromise were compared in a systematic manner. The resulting clinical tradeoffs were analyzed using dosimetric criteria, tumor control probability (TCP), equivalent uniform dose (EUD), and normal tissue complication probability. Results: Plan comparisons representing the two clinical decisions (sparing both OP and sparing only the contralateral OP), with respect to minimum dose, TCP, V 95 , and EUD, demonstrated small, yet statistically significant, differences. However, when individual cases were analyzed further, significant PTV underdosage (>5%) was present in most cases for plans sparing both OP. In 6/13 cases (46%), PTV underdosage was between 5% and 15%, and in 3 cases (23%) was greater than 15%. By comparison, adequate PTV coverage was present in 8/13 cases (62%) for plans sparing only the contralateral OP. Mean target EUD comparisons between the two plans (including 9 cases where a clinical tradeoff between PTV coverage and OP sparing was required) were similar: 68.6 Gy and 69.1 Gy, respectively (p=0.02). Mean TCP values for those 9 cases were 56.5 vs. 61.7, respectively (p=0.006). Conclusions: In IMRT plans for paranasal sinus tumors

Co-Optimization of Fuels and Engines

Energy Technology Data Exchange (ETDEWEB)

Farrell, John

2016-03-24

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a new DOE initiative focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) are designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, ten national laboratories, and numerous industry and academic partners to simultaneously tackle fuel and engine research and development (R&D) to maximize energy savings and on-road vehicle performance while dramatically reducing transportation-related petroleum consumption and greenhouse gas (GHG) emissions. This multi-year project will provide industry with the scientific underpinnings required to move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions. This presentation provides an overview of the project.

Optimization of investments in gas networks

International Nuclear Information System (INIS)

Andre, J.

2010-09-01

The natural gas networks require very important investments to cope with a still growing demand and to satisfy the new regulatory constraints. The gas market deregulation imposed to the gas network operators, first, transparency rules of a natural monopoly to justify their costs and ultimately their tariffs, and, second, market fluidity objectives in order to facilitate access for competition to the end-users. These major investments are the main reasons for the use of optimization techniques aiming at reducing the costs. Due to the discrete choices (investment location, limited choice of additional capacities, timing) crossed with physical non linear constraints (flow/pressures relations in the pipe or operating ranges of compressors), the programs to solve are Large Mixed Non Linear Programs (MINLP). As these types of programs are known to be hard to solve exactly in polynomial times (NP-hard), advanced optimization methods have to be implemented to obtain realistic results. The objectives of this thesis are threefold. First, one states several investment problems modeling of natural gas networks from industrial world motivations. Second, one identifies the most suitable methods and algorithms to the formulated problems. Third, one exposes the main advantages and drawbacks of these methods with the help of numerical applications on real cases. (author)

Advanced interface modelling of n-Si/HNO3 doped graphene solar cells to identify pathways to high efficiency

Science.gov (United States)

Zhao, Jing; Ma, Fa-Jun; Ding, Ke; Zhang, Hao; Jie, Jiansheng; Ho-Baillie, Anita; Bremner, Stephen P.

2018-03-01

In graphene/silicon solar cells, it is crucial to understand the transport mechanism of the graphene/silicon interface to further improve power conversion efficiency. Until now, the transport mechanism has been predominantly simplified as an ideal Schottky junction. However, such an ideal Schottky contact is never realised experimentally. According to literature, doped graphene shows the properties of a semiconductor, therefore, it is physically more accurate to model graphene/silicon junction as a Heterojunction. In this work, HNO3-doped graphene/silicon solar cells were fabricated with the power conversion efficiency of 9.45%. Extensive characterization and first-principles calculations were carried out to establish an advanced technology computer-aided design (TCAD) model, where p-doped graphene forms a straddling heterojunction with the n-type silicon. In comparison with the simple Schottky junction models, our TCAD model paves the way for thorough investigation on the sensitivity of solar cell performance to graphene properties like electron affinity. According to the TCAD heterojunction model, the cell performance can be improved up to 22.5% after optimizations of the antireflection coatings and the rear structure, highlighting the great potentials for fabricating high efficiency graphene/silicon solar cells and other optoelectronic devices.

Mirror Advanced Reactor Study interim design report

Energy Technology Data Exchange (ETDEWEB)

1983-04-01

The status of the design of a tenth-of-a-kind commercial tandem-mirror fusion reactor is described at the midpoint of a two-year study. When completed, the design is to serve as a strategic goal for the mirror fusion program. The main objectives of the Mirror Advanced Reactor Study (MARS) are: (1) to design an attractive tandem-mirror fusion reactor producing electricity and synfuels (in alternate versions), (2) to identify key development and technology needs, and (3) to exploit the potential of fusion for safety, low activation, and simple disposal of radioactive waste. In the first year we have emphasized physics and engineering of the central cell and physics of the end cell. Design optimization and trade studies are continuing, and we expect additional modifications in the end cells to further improve the performance of the final design.

Mirror Advanced Reactor Study interim design report

International Nuclear Information System (INIS)

1983-04-01

The status of the design of a tenth-of-a-kind commercial tandem-mirror fusion reactor is described at the midpoint of a two-year study. When completed, the design is to serve as a strategic goal for the mirror fusion program. The main objectives of the Mirror Advanced Reactor Study (MARS) are: (1) to design an attractive tandem-mirror fusion reactor producing electricity and synfuels (in alternate versions), (2) to identify key development and technology needs, and (3) to exploit the potential of fusion for safety, low activation, and simple disposal of radioactive waste. In the first year we have emphasized physics and engineering of the central cell and physics of the end cell. Design optimization and trade studies are continuing, and we expect additional modifications in the end cells to further improve the performance of the final design

Reaction kinetics of hydrazine neutralization in steam generator wet lay-up solution: Identifying optimal degradation conditions

International Nuclear Information System (INIS)

Schildermans, Kim; Lecocq, Raphael; Girasa, Emmanuel

2012-09-01

During a nuclear power plant outage, hydrazine is used as an oxygen scavenger in the steam generator lay-up solution. However, due to the carcinogenic effects of hydrazine, more stringent discharge limits are or will be imposed in the environmental permits. Hydrazine discharge could even be prohibited. Consequently, hydrazine alternatives or hydrazine degradation before discharge is needed. This paper presents the laboratory tests performed to characterize the reaction kinetics of hydrazine neutralization using bleach or hydrogen peroxide, catalyzed with either copper sulfate (CuSO 4 ) or potassium permanganate (KMnO 4 ). The tests are performed on two standard steam generator lay-up solutions based on different pH control agents: ammonia or ethanolamine. Different neutralization conditions are tested by varying temperature, oxidant addition, and catalyst concentration, among others, in order to identify the optimal parameters for hydrazine neutralization in a steam generator wet lay-up solution. (authors)

Multicriteria Optimization in Intensity-Modulated Radiation Therapy Treatment Planning for Locally Advanced Cancer of the Pancreatic Head

International Nuclear Information System (INIS)

Hong, Theodore S.; Craft, David L.; Carlsson, Fredrik; Bortfeld, Thomas R.

2008-01-01

Purpose: Intensity-modulated radiation therapy (IMRT) affords the potential to decrease radiation therapy-associated toxicity by creating highly conformal dose distributions. However, the inverse planning process can create a suboptimal plan despite meeting all constraints. Multicriteria optimization (MCO) may reduce the time-consuming iteration loop necessary to develop a satisfactory plan while providing information regarding trade-offs between different treatment planning goals. In this exploratory study, we examine the feasibility and utility of MCO in physician plan selection in patients with locally advanced pancreatic cancer (LAPC). Methods and Materials: The first 10 consecutive patients with LAPC treated with IMRT were evaluated. A database of plans (Pareto surface) was created that met the inverse planning goals. The physician then navigated to an 'optimal' plan from the point on the Pareto surface at which kidney dose was minimized. Results: Pareto surfaces were created for all 10 patients. A physician was able to select a plan from the Pareto surface within 10 minutes for all cases. Compared with the original (treated) IMRT plans, the plan selected from the Pareto surface had a lower stomach mean dose in 9 of 10 patients, although often at the expense of higher kidney dose than with the treated plan. Conclusion: The MCO is feasible in patients with LAPC and allows the physician to choose a satisfactory plan quickly. Generally, when given the opportunity, the physician will choose a plan with a lower stomach dose. The MCO enables a physician to provide greater active clinical input into the IMRT planning process

COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U

Energy Technology Data Exchange (ETDEWEB)

Sun, Y.; Borland, Michael

2017-06-25

Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.

A process insight repository supporting process optimization

OpenAIRE

Vetlugin, Andrey

2012-01-01

Existing solutions for analysis and optimization of manufacturing processes, such as online analysis processing or statistical calculations, have shortcomings that limit continuous process improvements. In particular, they lack means of storing and integrating the results of analysis. This makes the valuable information that can be used for process optimizations used only once and then disposed. The goal of the Advanced Manufacturing Analytics (AdMA) research project is to design an integrate...

Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

Energy Technology Data Exchange (ETDEWEB)

Svensson, Elin [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden)], E-mail: elin.svensson@chalmers.se; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)

2009-03-15

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives.

Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty. A pulp mill example

Energy Technology Data Exchange (ETDEWEB)

Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)

2009-03-15

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, doi:10.1016/j.enpol.2008.10.023] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives. (author)

Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty-A pulp mill example

International Nuclear Information System (INIS)

Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith

2009-01-01

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO 2 emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO 2 emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives

Review of design optimization methods for turbomachinery aerodynamics

Science.gov (United States)

Li, Zhihui; Zheng, Xinqian

2017-08-01

In today's competitive environment, new turbomachinery designs need to be not only more efficient, quieter, and ;greener; but also need to be developed at on much shorter time scales and at lower costs. A number of advanced optimization strategies have been developed to achieve these requirements. This paper reviews recent progress in turbomachinery design optimization to solve real-world aerodynamic problems, especially for compressors and turbines. This review covers the following topics that are important for optimizing turbomachinery designs. (1) optimization methods, (2) stochastic optimization combined with blade parameterization methods and the design of experiment methods, (3) gradient-based optimization methods for compressors and turbines and (4) data mining techniques for Pareto Fronts. We also present our own insights regarding the current research trends and the future optimization of turbomachinery designs.

Interaction patterns between parents with advanced cancer and their adolescent children.

Science.gov (United States)

Sheehan, Denice Kopchak; Draucker, Claire Burke

2011-10-01

Advanced cancer profoundly affects those with the illness and their families. The interaction patterns between parents with advanced cancer and their adolescent children are likely to influence how a family experiences a parent's dying process. There is little information on such interactions. This study aimed to develop an explanatory model that explains interaction patterns between parents with advanced cancer and their adolescent children and to identify strategies to prepare children for their lives after a parent dies. Semi-structured interviews were conducted with 9 parents with advanced cancer, 7 of their spouses/partners, and 10 of their adolescent children. The interviews were recorded, transcribed verbatim, and analyzed using a constructionist grounded theory approach. Twenty-six family participants were interviewed. Their main concern was not having enough time together. In response, they described a four-stage process for optimizing the time they had left together: coming to know our time together is limited, spending more time together, extending our time together, and giving up our time together to end the suffering. The adolescents and their ill parents did not change their interaction patterns until they realized their time together was limited by the advanced cancer. Then they spent more time together to make things easier for each other. Time was of great importance to the parents and adolescents; all the participants structured their stories in relation to the concept of time. The model reflects the dynamic process by which families continuously adapt their relationships in the face of advanced cancer. 2010 John Wiley & Sons, Ltd.

Imaging evidence and recommendations for traumatic brain injury: advanced neuro- and neurovascular imaging techniques.

Science.gov (United States)

Wintermark, M; Sanelli, P C; Anzai, Y; Tsiouris, A J; Whitlow, C T

2015-02-01

Neuroimaging plays a critical role in the evaluation of patients with traumatic brain injury, with NCCT as the first-line of imaging for patients with traumatic brain injury and MR imaging being recommended in specific settings. Advanced neuroimaging techniques, including MR imaging DTI, blood oxygen level-dependent fMRI, MR spectroscopy, perfusion imaging, PET/SPECT, and magnetoencephalography, are of particular interest in identifying further injury in patients with traumatic brain injury when conventional NCCT and MR imaging findings are normal, as well as for prognostication in patients with persistent symptoms. These advanced neuroimaging techniques are currently under investigation in an attempt to optimize them and substantiate their clinical relevance in individual patients. However, the data currently available confine their use to the research arena for group comparisons, and there remains insufficient evidence at the time of this writing to conclude that these advanced techniques can be used for routine clinical use at the individual patient level. TBI imaging is a rapidly evolving field, and a number of the recommendations presented will be updated in the future to reflect the advances in medical knowledge. © 2015 by American Journal of Neuroradiology.

Impact of Chaos Functions on Modern Swarm Optimizers.

Directory of Open Access Journals (Sweden)

E Emary

Full Text Available Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates the impact of using chaos-based control of exploration/exploitation rates against using the systematic native control. Three modern algorithms were used in the study namely grey wolf optimizer (GWO, antlion optimizer (ALO and moth-flame optimizer (MFO in the domain of machine learning for feature selection. Results on a set of standard machine learning data using a set of assessment indicators prove advance in optimization algorithm performance when using variational repeated periods of declined exploration rates over using systematically decreased exploration rates.

New multigrid solver advances in TOPS

International Nuclear Information System (INIS)

Falgout, R D; Brannick, J; Brezina, M; Manteuffel, T; McCormick, S

2005-01-01

In this paper, we highlight new multigrid solver advances in the Terascale Optimal PDE Simulations (TOPS) project in the Scientific Discovery Through Advanced Computing (SciDAC) program. We discuss two new algebraic multigrid (AMG) developments in TOPS: the adaptive smoothed aggregation method (αSA) and a coarse-grid selection algorithm based on compatible relaxation (CR). The αSA method is showing promising results in initial studies for Quantum Chromodynamics (QCD) applications. The CR method has the potential to greatly improve the applicability of AMG

Gradient Optimization for Analytic conTrols - GOAT

Science.gov (United States)

Assémat, Elie; Machnes, Shai; Tannor, David; Wilhelm-Mauch, Frank

Quantum optimal control becomes a necessary step in a number of studies in the quantum realm. Recent experimental advances showed that superconducting qubits can be controlled with an impressive accuracy. However, most of the standard optimal control algorithms are not designed to manage such high accuracy. To tackle this issue, a novel quantum optimal control algorithm have been introduced: the Gradient Optimization for Analytic conTrols (GOAT). It avoids the piecewise constant approximation of the control pulse used by standard algorithms. This allows an efficient implementation of very high accuracy optimization. It also includes a novel method to compute the gradient that provides many advantages, e.g. the absence of backpropagation or the natural route to optimize the robustness of the control pulses. This talk will present the GOAT algorithm and a few applications to transmons systems.

Optimal Taxation and Social Insurance in a Lifetime Perspective

DEFF Research Database (Denmark)

Bovenberg, A. Lans; Sørensen, Peter Birch

Advances in information technology have improved the administrative feasibility of redistribution based on lifetime earnings recorded at the time of retirement. We study optimal lifetime income taxation and social insurance in an economy in which redistributive taxation and social insurance serve...... to insure (ex ante) against skill heterogeneity as well as disability risk. Optimal disability benefits rise with previous earnings so that public transfers depend not only on current earnings but also on earnings in the past. Hence, lifetime taxation rather than annual taxation is optimal. The optimal tax...

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

Science.gov (United States)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Steady State Advanced Tokamak (SSAT): The mission and the machine

International Nuclear Information System (INIS)

Thomassen, K.; Goldston, R.; Nevins, B.; Neilson, H.; Shannon, T.; Montgomery, B.

1992-03-01

Extending the tokamak concept to the steady state regime and pursuing advances in tokamak physics are important and complementary steps for the magnetic fusion energy program. The required transition away from inductive current drive will provide exciting opportunities for advances in tokamak physics, as well as important impetus to drive advances in fusion technology. Recognizing this, the Fusion Policy Advisory Committee and the US National Energy Strategy identified the development of steady state tokamak physics and technology, and improvements in the tokamak concept, as vital elements in the magnetic fusion energy development plan. Both called for the construction of a steady state tokamak facility to address these plan elements. Advances in physics that produce better confinement and higher pressure limits are required for a similar unit size reactor. Regimes with largely self-driven plasma current are required to permit a steady-state tokamak reactor with acceptable recirculating power. Reliable techniques of disruption control will be needed to achieve the availability goals of an economic reactor. Thus the central role of this new tokamak facility is to point the way to a more attractive demonstration reactor (DEMO) than the present data base would support. To meet the challenges, we propose a new ''Steady State Advanced Tokamak'' (SSAT) facility that would develop and demonstrate optimized steady state tokamak operating mode. While other tokamaks in the world program employ superconducting toroidal field coils, SSAT would be the first major tokamak to operate with a fully superconducting coil set in the elongated, divertor geometry planned for ITER and DEMO

Optimized ventilation-on-demand (VOD)

Energy Technology Data Exchange (ETDEWEB)

Masse, M. [Simsmart Technologies Inc., Brossard, PQ (Canada); Cervinka, A. [Newtrax Technologies Inc., Montreal, PQ (Canada)

2008-07-01

This presentation described how the combination of 2 innovative technologies can help optimize mine ventilation. Newtrax Technologies has developed a self-contained battery-powered wireless electronic system designed to operate in harsh industrial environments, including underground mines. Simsmart Technologies has created an advanced process and control simulation based design tool used in industrial applications, including mine ventilation systems. This presentation described the system components and how they work. These included the wireless mesh network designed for dynamic diesel machinery tracking and operating status monitoring; the real-time ventilation model and fan speed optimizer; the OPC server for information interchange; the OPC linkage to existing control infrastructure; a human machine interface that provide data archiving capability; live MS-Excel to interrogate the simulation, controls and optimizer; and, the battery-powered network mesh that provides SCADA functionality to route optimized setpoints. Details of the user interface were also provided. 1 tab., 20 figs.

Convex analysis and global optimization

CERN Document Server

Tuy, Hoang

2016-01-01

This book presents state-of-the-art results and methodologies in modern global optimization, and has been a staple reference for researchers, engineers, advanced students (also in applied mathematics), and practitioners in various fields of engineering. The second edition has been brought up to date and continues to develop a coherent and rigorous theory of deterministic global optimization, highlighting the essential role of convex analysis. The text has been revised and expanded to meet the needs of research, education, and applications for many years to come. Updates for this new edition include: · Discussion of modern approaches to minimax, fixed point, and equilibrium theorems, and to nonconvex optimization; · Increased focus on dealing more efficiently with ill-posed problems of global optimization, particularly those with hard constraints;

Optimization and industry new frontiers

CERN Document Server

Korotkikh, Victor

2003-01-01

Optimization from Human Genes to Cutting Edge Technologies The challenges faced by industry today are so complex that they can only be solved through the help and participation of optimization ex­ perts. For example, many industries in e-commerce, finance, medicine, and engineering, face several computational challenges due to the mas­ sive data sets that arise in their applications. Some of the challenges include, extended memory algorithms and data structures, new program­ ming environments, software systems, cryptographic protocols, storage devices, data compression, mathematical and statistical methods for knowledge mining, and information visualization. With advances in computer and information systems technologies, and many interdisci­ plinary efforts, many of the "data avalanche challenges" are beginning to be addressed. Optimization is the most crucial component in these efforts. Nowadays, the main task of optimization is to investigate the cutting edge frontiers of these technologies and systems ...

Advanced LIGO low-latency searches

Science.gov (United States)

Kanner, Jonah; LIGO Scientific Collaboration, Virgo Collaboration

2016-06-01

Advanced LIGO recently made the first detection of gravitational waves from merging binary black holes. The signal was first identified by a low-latency analysis, which identifies gravitational-wave transients within a few minutes of data collection. More generally, Advanced LIGO transients are sought with a suite of automated tools, which collectively identify events, evaluate statistical significance, estimate source position, and attempt to characterize source properties. This low-latency effort is enabling a broad multi-messenger approach to the science of compact object mergers and other transients. This talk will give an overview of the low-latency methodology and recent results.

Handbook on modelling for discrete optimization

CERN Document Server

Pitsoulis, Leonidas; Williams, H

2006-01-01

The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this. It has long been recognized that "modelling" is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It will be done in an academic handbook treatment...

Optimal control novel directions and applications

CERN Document Server

Aronna, Maria; Kalise, Dante

2017-01-01

Focusing on applications to science and engineering, this book presents the results of the ITN-FP7 SADCO network’s innovative research in optimization and control in the following interconnected topics: optimality conditions in optimal control, dynamic programming approaches to optimal feedback synthesis and reachability analysis, and computational developments in model predictive control. The novelty of the book resides in the fact that it has been developed by early career researchers, providing a good balance between clarity and scientific rigor. Each chapter features an introduction addressed to PhD students and some original contributions aimed at specialist researchers. Requiring only a graduate mathematical background, the book is self-contained. It will be of particular interest to graduate and advanced undergraduate students, industrial practitioners and to senior scientists wishing to update their knowledge.

Identifying and prioritizing indicators and effective solutions to optimization the use of wood in construction classical furniture by using AHP (Case study of Qom

Directory of Open Access Journals (Sweden)

Mohammad Ghofrani

2017-02-01

Full Text Available AbstractThe aim of this study was to identify and prioritize the indicators and provide effective solutions to optimize the use of wood in construction classical furniture using the analytic hierarchy process (case study in Qom. For this purpose, studies and results of other researchers and interviews with experts, the factors affecting the optimization of wood consumption were divided into 4 main categories and 23 sub-indicators. The importance of the sub after getting feedback furniture producers were determined by AHP. The results show that the original surface design and human resources are of great importance. In addition, among 23 sub-effective optimization of the use of wood in construction classical furniture, ergonomics, style, skill training and inlaid in classical furniture industry in order to weight the value of 0/247, 0/181, 0/124 and 0/087 are of paramount importance and the method of use of force specialist solutions were a priority.

Identifying factors for optimal development of health-related websites: a delphi study among experts and potential future users.

Science.gov (United States)

Schneider, Francine; van Osch, Liesbeth; de Vries, Hein

2012-02-14

The Internet has become a popular medium for offering tailored and targeted health promotion programs to the general public. However, suboptimal levels of program use in the target population limit the public health impact of these programs. Optimizing program development is considered as one of the main processes to increase usage rates. To distinguish factors potentially related to optimal development of health-related websites by involving both experts and potential users. By considering and incorporating the opinions of experts and potential users in the development process, involvement in the program is expected to increase, consequently resulting in increased appreciation, lower levels of attrition, and higher levels of sustained use. We conducted a systematic three-round Delphi study through the Internet. Both national and international experts (from the fields of health promotion, health psychology, e-communication, and technical Web design) and potential users were invited via email to participate. During this study an extensive list of factors potentially related to optimal development of health-related websites was identified, by focusing on factors related to layout, general and risk information provision, questionnaire use, additional services, and ease of use. Furthermore, we assessed the extent to which experts and potential users agreed on the importance of these factors. Differences as well as similarities among experts and potentials users were deduced. In total, 20 of 62 contacted experts participated in the first round (32% response rate); 60 of 200 contacted experts (30% response rate) and 210 potential users (95% response rate) completed the second-round questionnaire, and 32 of 60 contacted experts completed the third round (53% response rate). Results revealed important factors consented upon by experts and potential users (eg, ease of use, clear structure, and detailed health information provision), as well as differences regarding

Defining defect specifications to optimize photomask production and requalification

Science.gov (United States)

Fiekowsky, Peter

2006-10-01

Reducing defect repairs and accelerating defect analysis is becoming more important as the total cost of defect repairs on advanced masks increases. Photomask defect specs based on printability, as measured on AIMS microscopes has been used for years, but the fundamental defect spec is still the defect size, as measured on the photomask, requiring the repair of many unprintable defects. ADAS, the Automated Defect Analysis System from AVI is now available in most advanced mask shops. It makes the use of pure printability specs, or "Optimal Defect Specs" practical. This software uses advanced algorithms to eliminate false defects caused by approximations in the inspection algorithm, classify each defect, simulate each defect and disposition each defect based on its printability and location. This paper defines "optimal defect specs", explains why they are now practical and economic, gives a method of determining them and provides accuracy data.

High FDG uptake areas on pre-radiotherapy PET/CT identify preferential sites of local relapse after chemoradiotherapy for locally advanced oesophageal cancer

Energy Technology Data Exchange (ETDEWEB)

Calais, Jeremie; Lemarignier, Charles; Vera, Pierre [Henri Becquerel Cancer Center and Rouen University Hospital, Nuclear Medicine Department, Rouen (France); University of Rouen, QuantIF-LITIS (Equipe d' Accueil 4108-FR CNRS 3638), Faculty of Medicine, Rouen (France); Dubray, Bernard [University of Rouen, QuantIF-LITIS (Equipe d' Accueil 4108-FR CNRS 3638), Faculty of Medicine, Rouen (France); Centre Henri Becquerel and Rouen University Hospital, Department of Radiotherapy and Medical Physics, Rouen (France); Nkhali, Lamyaa; Thureau, Sebastien; Modzelewski, Romain; Gardin, Isabelle [Henri Becquerel Cancer Center and Rouen University Hospital, Nuclear Medicine Department, Rouen (France); University of Rouen, QuantIF-LITIS (Equipe d' Accueil 4108-FR CNRS 3638), Faculty of Medicine, Rouen (France); Centre Henri Becquerel and Rouen University Hospital, Department of Radiotherapy and Medical Physics, Rouen (France); Di Fiore, Frederic [Rouen University Hospital, Department of Gastroenterology, Rouen (France); Rouen University Hospital, Department of Oncology, Henri Becquerel Cancer Center, IRON, Rouen (France); Michel, Pierre [Rouen University Hospital, Department of Gastroenterology, Rouen (France)

2015-05-01

The high failure rates in the radiotherapy (RT) target volume suggest that patients with locally advanced oesophageal cancer (LAOC) would benefit from increased total RT doses. High 2-deoxy-2-[{sup 18}F]fluoro-D-glucose (FDG) uptake (hotspot) on pre-RT FDG positron emission tomography (PET)/CT has been reported to identify intra-tumour sites at increased risk of relapse after RT in non-small cell lung cancer and in rectal cancer. Our aim was to confirm these observations in patients with LAOC and to determine the optimal maximum standardized uptake value (SUV{sub max}) threshold to delineate smaller RT target volumes that would facilitate RT dose escalation without impaired tolerance. The study included 98 consecutive patients with LAOC treated by chemoradiotherapy (CRT). All patients underwent FDG PET/CT at initial staging and during systematic follow-up in a single institution. FDG PET/CT acquisitions were coregistered on the initial CT scan. Various subvolumes within the initial tumour (30, 40, 50, 60, 70, 80 and 90 % SUV{sub max} thresholds) and in the subsequent local recurrence (LR, 40 and 90 % SUV{sub max} thresholds) were pasted on the initial CT scan and compared[Dice, Jaccard, overlap fraction (OF), common volume/baseline volume, common volume/recurrent volume]. Thirty-five patients had LR. The initial metabolic tumour volume was significantly higher in LR tumours than in the locally controlled tumours (mean 25.4 vs 14.2 cc; p = 0.002). The subvolumes delineated on initial PET/CT with a 30-60 % SUV{sub max} threshold were in good agreement with the recurrent volume at 40 % SUV{sub max} (OF = 0.60-0.80). The subvolumes delineated on initial PET/CT with a 30-60 % SUV{sub max} threshold were in good to excellent agreement with the core volume (90 % SUV{sub max}) of the relapse (common volume/recurrent volume and OF indices 0.61-0.89). High FDG uptake on pretreatment PET/CT identifies tumour subvolumes that are at greater risk of recurrence after CRT in

Optimization of Large-Scale Structural Systems

DEFF Research Database (Denmark)

Jensen, F. M.

solutions to small problems with one or two variables to the optimization of large structures such as bridges, ships and offshore structures. The methods used for salving these problems have evolved from being classical differential calculus and calculus of variation to very advanced numerical techniques...

HIV-associated neurocognitive disorders: recent advances in pathogenesis, biomarkers, and treatment [version 1; referees: 4 approved

Directory of Open Access Journals (Sweden)

Antonia Carroll

2017-03-01

Full Text Available HIV-associated neurocognitive disorders (HAND remain prevalent despite plasma viral suppression by antiretroviral agents. In fact, the prevalence of milder subtypes of cognitive impairment is increasing. Neuropsychologic testing remains the “gold standard” of diagnosis; however, this is time consuming and costly in a resource-poor environment. Recently developed screening tools, such as CogState and the revised HIV dementia scale, have very good sensitivity and specificity in the more severe stages of HAND. However, questions remain regarding the utility of, optimal population for, and insensitivity of tests in mild HAND. Recognition of ongoing viral persistence and the inflammatory milieu in the central nervous system (CNS has advanced our understanding of the pathogenesis of HAND and facilitated the development of biomarkers of CNS disease. The importance of the monocyte-macrophage lineage cell and the astrocyte as viral reservoirs, HIV viral proteins, self-perpetuating CNS inflammation, and CCR5 chemokine receptor neurotropism has been identified. Whilst biomarkers demonstrate monocyte activation, inflammation, and neuronal injury, they remain limited in their clinical utility. The improved understanding of pathogenic mechanisms has led to novel approaches to the treatment of HAND; however, despite these advances, the optimal management is still undefined.

Advances in Male Contraception

Science.gov (United States)

Page, Stephanie T.; Amory, John K.; Bremner, William J.

2008-01-01

Despite significant advances in contraceptive options for women over the last 50 yr, world population continues to grow rapidly. Scientists and activists alike point to the devastating environmental impacts that population pressures have caused, including global warming from the developed world and hunger and disease in less developed areas. Moreover, almost half of all pregnancies are still unwanted or unplanned. Clearly, there is a need for expanded, reversible, contraceptive options. Multicultural surveys demonstrate the willingness of men to participate in contraception and their female partners to trust them to do so. Notwithstanding their paucity of options, male methods including vasectomy and condoms account for almost one third of contraceptive use in the United States and other countries. Recent international clinical research efforts have demonstrated high efficacy rates (90–95%) for hormonally based male contraceptives. Current barriers to expanded use include limited delivery methods and perceived regulatory obstacles, which stymie introduction to the marketplace. However, advances in oral and injectable androgen delivery are cause for optimism that these hurdles may be overcome. Nonhormonal methods, such as compounds that target sperm motility, are attractive in their theoretical promise of specificity for the reproductive tract. Gene and protein array technologies continue to identify potential targets for this approach. Such nonhormonal agents will likely reach clinical trials in the near future. Great strides have been made in understanding male reproductive physiology; the combined efforts of scientists, clinicians, industry and governmental funding agencies could make an effective, reversible, male contraceptive an option for family planning over the next decade. PMID:18436704

Toward Optimal Transport Networks

Science.gov (United States)

Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

2008-01-01

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Towards Optimality in Online Learning – The OLeCenT Approach

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Carl Beckford

2017-06-01

Full Text Available Higher Education Institutions (HEIs employ Learning Management Systems (LMSs primarily for greater efficiency, profitability, technological advancement or survival. The predominantly used LMSs, Moodle and Blackboard account for in excess of 60% usage by the top HEIs. However, the individual international regions do not necessarily bear the percentages of the overall total. Gaps are identified in optimality in course delivery within online learning when one studies LMSs and their functionalities. Advanced Distributed Learning (ADL Initiative which was established to standardize and modernize training and education management and delivery, developed and recommended usage of Sharable Content Object Reference Model (SCORM 2004 and later versions. SCORM 2004 which provides for flexibility in sequencing and navigation for learner-centric course delivery is not supported in any version of the more prevalently used LMSs. It is believed that most people have a preferred way in processing information. We propose codifying one or more Learning Style Instruments (LSIs, diagnosing the preferred teaching approach(es and dominant/existing learning styles within a batch of learners, then providing course delivery as a best-fit per learner. As a proof of concept, OLeCenT allows the input of one or more course learning paths with real-time learning and automatic reconfiguration of the course path where a new trend or pattern is identified. OLeCenT identified disparity in teaching-learning and provided a mechanism towards improving online learner-centric course delivery. OLeCenT also identified comparative levels of similarities among learners and instructors even where they are deemed to be of different teaching-learning styles/mechanisms.

Some Studies on Forming Optimization with Genetic Algorithm

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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.

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)

A Global Network Alignment Method Using Discrete Particle Swarm Optimization.

Science.gov (United States)

Huang, Jiaxiang; Gong, Maoguo; Ma, Lijia

2016-10-19

Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations. The particle statuses and status updating rules are redefined in a discrete form by using permutation. A seed-and-extend strategy is employed to guide the searching for the superior alignment. The proposed initialization method "seeds" matches with high sequence similarity into the alignment, which guarantees the functional coherence of the mapping nodes. A greedy local search method is designed as the "extension" procedure to iteratively optimize the edge conservations. PSONA is compared with several state-of-art methods on ten network pairs combined by five species. The experimental results demonstrate that the proposed aligner can map the proteins with high functional coherence and can be used as a booster to effectively refine the well-studied aligners.

Optimal design of the heat pipe using TLBO (teaching–learning-based optimization) algorithm

International Nuclear Information System (INIS)

Rao, R.V.; More, K.C.

2015-01-01

Heat pipe is a highly efficient and reliable heat transfer component. It is a closed container designed to transfer a large amount of heat in system. Since the heat pipe operates on a closed two-phase cycle, the heat transfer capacity is greater than for solid conductors. Also, the thermal response time is less than with solid conductors. The three major elemental parts of the rotating heat pipe are: a cylindrical evaporator, a truncated cone condenser, and a fixed amount of working fluid. In this paper, a recently proposed new stochastic advanced optimization algorithm called TLBO (Teaching–Learning-Based Optimization) algorithm is used for single objective as well as multi-objective design optimization of heat pipe. It is easy to implement, does not make use of derivatives and it can be applied to unconstrained or constrained problems. Two examples of heat pipe are presented in this paper. The results of application of TLBO algorithm for the design optimization of heat pipe are compared with the NPGA (Niched Pareto Genetic Algorithm), GEM (Grenade Explosion Method) and GEO (Generalized External optimization). It is found that the TLBO algorithm has produced better results as compared to those obtained by using NPGA, GEM and GEO algorithms. - Highlights: • The TLBO (Teaching–Learning-Based Optimization) algorithm is used for the design and optimization of a heat pipe. • Two examples of heat pipe design and optimization are presented. • The TLBO algorithm is proved better than the other optimization algorithms in terms of results and the convergence

Thermodynamic analysis of multicomponent distillation columns: identifying optimal feed conditions

Directory of Open Access Journals (Sweden)

M. L.O. Maia

2000-12-01

Full Text Available A new methodology for the optimisation of feed conditions as well as the calculation of minimum reflux ratio of distillation columns is presented. The reversible profile approach used for saturated liquid feeds is extended to consider other feed conditions. For flashed feed, the liquid fraction of the feed stream is used to compute the column pinch conditions and the minimum reflux ratio. The modifications required for subcooled liquid and superheated vapor feed are discussed, and a procedure to estimate the minimum reflux for those conditions is proposed. The methodology presented allows the identification of the optimal feed condition, without having to resort to a full stage-by-stage procedure.

Advanced liquid metal reactor plant control system

International Nuclear Information System (INIS)

Dayal, Y.; Wagner, W.; Zizzo, D.; Carroll, D.

1993-01-01

The modular Advanced Liquid Metal Reactor (ALMR) power plant is controlled by an advanced state-of-the-art control system designed to facilitate plant operation, optimize availability, and protect plant investment. The control system features a high degree of automatic control and extensive amount of on-line diagnostics and operator aids. It can be built with today's control technology, and has the flexibility of adding new features that benefit plant operation and reduce O ampersand M costs as the technology matures

Divertor design through shape optimization

International Nuclear Information System (INIS)

Dekeyser, W.; Baelmans, M.; Reiter, D.

2012-01-01

Due to the conflicting requirements, complex physical processes and large number of design variables, divertor design for next step fusion reactors is a challenging problem, often relying on large numbers of computationally expensive numerical simulations. In this paper, we attempt to partially automate the design process by solving an appropriate shape optimization problem. Design requirements are incorporated in a cost functional which measures the performance of a certain design. By means of changes in the divertor shape, which in turn lead to changes in the plasma state, this cost functional can be minimized. Using advanced adjoint methods, optimal solutions are computed very efficiently. The approach is illustrated by designing divertor targets for optimal power load spreading, using a simplified edge plasma model (copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Advanced Vadose Zone Simulations Using TOUGH

Energy Technology Data Exchange (ETDEWEB)

Finsterle, S.; Doughty, C.; Kowalsky, M.B.; Moridis, G.J.; Pan,L.; Xu, T.; Zhang, Y.; Pruess, K.

2007-02-01

The vadose zone can be characterized as a complex subsurfacesystem in which intricate physical and biogeochemical processes occur inresponse to a variety of natural forcings and human activities. Thismakes it difficult to describe, understand, and predict the behavior ofthis specific subsurface system. The TOUGH nonisothermal multiphase flowsimulators are well-suited to perform advanced vadose zone studies. Theconceptual models underlying the TOUGH simulators are capable ofrepresenting features specific to the vadose zone, and of addressing avariety of coupled phenomena. Moreover, the simulators are integratedinto software tools that enable advanced data analysis, optimization, andsystem-level modeling. We discuss fundamental and computationalchallenges in simulating vadose zone processes, review recent advances inmodeling such systems, and demonstrate some capabilities of the TOUGHsuite of codes using illustrative examples.

Advanced Manufacture of Spiral Bevel and Hypoid Gears

Directory of Open Access Journals (Sweden)

Vilmos Simon

2016-11-01

Full Text Available In this study, an advanced method for the manufacture of spiral bevel and hypoid gears on CNC hypoid generators is proposed. The optmal head-cutter geometry and machine tool settings are determined to introduce the optimal tooth surface modifications into the teeth of spiral bevel and hypoid gears. The aim of these tooth surface modifications is to simultaneously reduce the tooth contact pressure and the transmission errors, to maximize the EHD load carrying capacity of the oil film, and to minimize power losses in the oil film. The proposed advanced method for the manufacture of spiral bevel and hypoid gears is based on machine tool setting variation on the cradle-type generator conducted by optimal polynomial functions and on the use of a CNC hypoid generator. An algorithm is developed for the execution of motions on the CNC hypoid generator using the optimal relations on the cradle-type machine. Effectiveness of the method was demonstrated by using spiral bevel and hypoid gear examples. Significant improvements in the operating characteristics of the gear pairs are achieved.

Application of Response Surface Methodology for Optimizing Oil ...

African Journals Online (AJOL)

Application of Response Surface Methodology for Optimizing Oil Extraction Yield From ... AFRICAN JOURNALS ONLINE (AJOL) · Journals · Advanced Search ... from tropical almond seed by the use of response surface methodology (RSM).

Cross-study analysis of gene expression data for intermediate neuroblastoma identifies two biological subtypes

International Nuclear Information System (INIS)

Warnat, Patrick; Oberthuer, André; Fischer, Matthias; Westermann, Frank; Eils, Roland; Brors, Benedikt

2007-01-01

Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome

Licensing and advanced fuel designs

International Nuclear Information System (INIS)

Davidson, S.L.; Novendstern, E.H.

1991-01-01

For the past 15 years, Westinghouse has been actively involved in the development and licensing of fuel designs that contain major advanced features. These designs include the optimized fuel assembly, The VANTAGE 5 fuel assembly, the VANTAGE 5H, and most recently the VANTAGE+ fuel assembly. Each of these designs was supported by extensive experimental data, safety evaluations, and design efforts and required intensive interaction with the US Nuclear Regulatory Commission (NRC) during the review and approval process. This paper presents a description of the licensing approach and how it was utilized by the utilities to facilitate the licensing applications of the advanced fuel designs for their plants. The licensing approach described in this paper has been successfully applied to four major advanced fuel design changes ∼40 plant-specific applications, and >350 cycle-specific reloads in the past 15 years

ESTIMATION OF SURVIVAL IN PATIENTS WITH ADVANCED OVARIAN CANCER – ABSTRACT OF THE RESEARCH PROJECT

Directory of Open Access Journals (Sweden)

Špela Smrkolj

2018-02-01

Full Text Available Background: Morbidity and mortality caused by cancer persist to be an important health problem world- wide and in the European Union member states as well. In Slovenia, most ovarian cancer cases are detected in advanced stages, hence a rather high mortality rate. Aims: The purpose of this research project is to analyze the primary cytoreduction in the patients with advanced ovarian cancer. The main objective of the project is to assess the use of lap- aroscopy in the prediction of optimal cytoreduction in these patients. Applicative research project ‘Estimation of survial in patients with advanced ovarian can- cer based on primary laparoscopical assessment of optimal cytoreduction’ (L3-2371 was approved and has been financed by the Slovene Research Agency and co-financed by the Ministry of Health of RS; Duration: May 1, 2009–April 30, 2012. Methods: The research project will consist of retrospective and prospective study. In all the patients with advanced ovarian cancer managed at the Department of Obstetrics and Gynecol- ogy, University Medical Centre Ljubljana in the years 2003–2008, and in whom optimal primary cytoreduction was made using either laparoscopy or laparotomy, certain clinical and pathomorphological factors will be compared, and the effects of all analyzed factors on the outcome of treatment assessed. In the prospective study, we will aim at assessing the use of laparoscopy in the prediction of optimal cytoreduction in all newly detected cases using a laparoscopy-based score (Fagotti’s scoring system. Conclusions: The standard management of advanced ovarian cancer patients consists of primary surgical optimal and/or suboptimal cytoreduction followed by aggressive cytotoxic chemotherapy. In line with our experience and with that published most recently, laparoscopy seems to be a promising method with which we will attempt to most accurately assess the optimal cytoreduction in surgical treatment of ovarian cancer patients.

Breeding rootstocks for Prunus species: Advances in genetic and genomics of peach and cherry as a model

Directory of Open Access Journals (Sweden)

Verónica Guajardo

2015-08-01

Full Text Available Prunus rootstock is an important choice in optimizing productivity of grafted cultivars. Nevertheless, many Prunus rootstocks are notoriously intolerant to hypoxia which is caused by waterlogging and/or heavy soils. There is no available information to help select Prunus rootstocks that are tolerant to stress conditions such as root hypoxia caused by excess moisture. Information from genetic maps has demonstrated a high level of synteny among Prunus species, and this suggests that they all share a similar genomic structure. It should be possible to identify the genetic determinants involved in tolerance to hypoxia and other traits in Prunus rootstocks by applying methods to identify regions of the genome involved in the expression of important traits; these have been developed mainly in peach which is the model species for the genus. Molecular markers that are tightly linked to major genes would be useful in marker-assisted selection (MAS to optimize new rootstock selection. This article provides insight on the advances in the development of molecular markers, genetic maps, and gene identification in Prunus, mainly in peach; the aim is to provide a general approach for identifying the genetic determinants of hypoxia stress in rootstocks.

Germinal Center Optimization Applied to Neural Inverse Optimal Control for an All-Terrain Tracked Robot

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Carlos Villaseñor

2017-12-01

Full Text Available Nowadays, there are several meta-heuristics algorithms which offer solutions for multi-variate optimization problems. These algorithms use a population of candidate solutions which explore the search space, where the leadership plays a big role in the exploration-exploitation equilibrium. In this work, we propose to use a Germinal Center Optimization algorithm (GCO which implements temporal leadership through modeling a non-uniform competitive-based distribution for particle selection. GCO is used to find an optimal set of parameters for a neural inverse optimal control applied to all-terrain tracked robot. In the Neural Inverse Optimal Control (NIOC scheme, a neural identifier, based on Recurrent High Orden Neural Network (RHONN trained with an extended kalman filter algorithm, is used to obtain a model of the system, then, a control law is design using such model with the inverse optimal control approach. The RHONN identifier is developed without knowledge of the plant model or its parameters, on the other hand, the inverse optimal control is designed for tracking velocity references. Applicability of the proposed scheme is illustrated using simulations results as well as real-time experimental results with an all-terrain tracked robot.

Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization

Science.gov (United States)

Meyn, Larry A.

2018-01-01

One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use

Time-optimal control with finite bandwidth

Science.gov (United States)

Hirose, M.; Cappellaro, P.

2018-04-01

Time-optimal control theory provides recipes to achieve quantum operations with high fidelity and speed, as required in quantum technologies such as quantum sensing and computation. While technical advances have achieved the ultrastrong driving regime in many physical systems, these capabilities have yet to be fully exploited for the precise control of quantum systems, as other limitations, such as the generation of higher harmonics or the finite response time of the control apparatus, prevent the implementation of theoretical time-optimal control. Here we present a method to achieve time-optimal control of qubit systems that can take advantage of fast driving beyond the rotating wave approximation. We exploit results from time-optimal control theory to design driving protocols that can be implemented with realistic, finite-bandwidth control fields, and we find a relationship between bandwidth limitations and achievable control fidelity.

Development of GEM detector for plasma diagnostics application: simulations addressing optimization of its performance

Science.gov (United States)

Chernyshova, M.; Malinowski, K.; Kowalska-Strzęciwilk, E.; Czarski, T.; Linczuk, P.; Wojeński, A.; Krawczyk, R. D.

2017-12-01

The advanced Soft X-ray (SXR) diagnostics setup devoted to studies of the SXR plasma emissivity is at the moment a highly relevant and important for ITER/DEMO application. Especially focusing on the energy range of tungsten emission lines, as plasma contamination by W and its transport in the plasma must be understood and monitored for W plasma-facing material. The Gas Electron Multiplier, with a spatial and energy-resolved photon detecting chamber, based SXR radiation detection system under development by our group may become such a diagnostic setup considering and solving many physical, technical and technological aspects. This work presents the results of simulations aimed to optimize a design of the detector's internal chamber and its performance. The study of the effect of electrodes alignment allowed choosing the gap distances which maximizes electron transmission and choosing the optimal magnitudes of the applied electric fields. Finally, the optimal readout structure design was identified suitable to collect a total formed charge effectively, basing on the range of the simulated electron cloud at the readout plane which was in the order of ~ 2 mm.

The Theory of Optimal Taxation: What is the Policy Relevance?

OpenAIRE

Birch Sørensen, Peter

2006-01-01

The paper discusses the implications of optimal tax theory for the debates on uniform commodity taxation and neutral capital income taxation. While strong administrative and political economy arguments in favor of uniform and neutral taxation remain, recent advances in optimal tax theory suggest that the information needed to implement the differentiated taxation prescribed by optimal tax theory may be easier to obtain than previously believed. The paper also points to the strong similarity b...

Optimization and control methods in industrial engineering and construction

CERN Document Server

Wang, Xiangyu

2014-01-01

This book presents recent advances in optimization and control methods with applications to industrial engineering and construction management. It consists of 15 chapters authored by recognized experts in a variety of fields including control and operation research, industrial engineering, and project management. Topics include numerical methods in unconstrained optimization, robust optimal control problems, set splitting problems, optimum confidence interval analysis, a monitoring networks optimization survey, distributed fault detection, nonferrous industrial optimization approaches, neural networks in traffic flows, economic scheduling of CCHP systems, a project scheduling optimization survey, lean and agile construction project management, practical construction projects in Hong Kong, dynamic project management, production control in PC4P, and target contracts optimization.   The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and c...

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.

Advances in iterative methods

International Nuclear Information System (INIS)

Beauwens, B.; Arkuszewski, J.; Boryszewicz, M.

1981-01-01

Results obtained in the field of linear iterative methods within the Coordinated Research Program on Transport Theory and Advanced Reactor Calculations are summarized. The general convergence theory of linear iterative methods is essentially based on the properties of nonnegative operators on ordered normed spaces. The following aspects of this theory have been improved: new comparison theorems for regular splittings, generalization of the notions of M- and H-matrices, new interpretations of classical convergence theorems for positive-definite operators. The estimation of asymptotic convergence rates was developed with two purposes: the analysis of model problems and the optimization of relaxation parameters. In the framework of factorization iterative methods, model problem analysis is needed to investigate whether the increased computational complexity of higher-order methods does not offset their increased asymptotic convergence rates, as well as to appreciate the effect of standard relaxation techniques (polynomial relaxation). On the other hand, the optimal use of factorization iterative methods requires the development of adequate relaxation techniques and their optimization. The relative performances of a few possibilities have been explored for model problems. Presently, the best results have been obtained with optimal diagonal-Chebyshev relaxation

Targeted Structural Optimization with Additive Manufacturing of Metals

Science.gov (United States)

Burt, Adam; Hull, Patrick

2015-01-01

The recent advances in additive manufacturing (AM) of metals have now improved the state-of-the-art such that traditionally non-producible parts can be readily produced in a cost-effective way. Because of these advances in manufacturing technology, structural optimization techniques are well positioned to supplement and advance this new technology. The goal of this project is to develop a structural design, analysis, and optimization framework combined with AM to significantly light-weight the interior of metallic structures while maintaining the selected structural properties of the original solid. This is a new state-of-the-art capability to significantly reduce mass, while maintaining the structural integrity of the original design, something that can only be done with AM. In addition, this framework will couple the design, analysis, and fabrication process, meaning that what has been designed directly represents the produced part, thus closing the loop on the design cycle and removing human iteration between design and fabrication. This fundamental concept has applications from light-weighting launch vehicle components to in situ resource fabrication.

Optimizing main-memory join on modern hardware

OpenAIRE

Boncz, Peter; Manegold, Stefan; Kersten, Martin

2002-01-01

textabstractIn the past decade, the exponential growth in commodity CPUs speed has far outpaced advances in memory latency. A second trend is that CPU performance advances are not only brought by increased clock rate, but also by increasing parallelism inside the CPU. Current database systems have not yet adapted to these trends, and show poor utilization of both CPU and memory resources on current hardware. In this article, we show how these resources can be optimized for large joins and tra...

Advances in waveform-agile sensing for tracking

CERN Document Server

Sira, Sandeep Prasad

2009-01-01

Recent advances in sensor technology and information processing afford a new flexibility in the design of waveforms for agile sensing. Sensors are now developed with the ability to dynamically choose their transmit or receive waveforms in order to optimize an objective cost function. This has exposed a new paradigm of significant performance improvements in active sensing: dynamic waveform adaptation to environment conditions, target structures, or information features. The manuscript provides a review of recent advances in waveform-agile sensing for target tracking applications. A dynamic wav

Quality assurance for high dose rate brachytherapy treatment planning optimization: using a simple optimization to verify a complex optimization

International Nuclear Information System (INIS)

Deufel, Christopher L; Furutani, Keith M

2014-01-01

As dose optimization for high dose rate brachytherapy becomes more complex, it becomes increasingly important to have a means of verifying that optimization results are reasonable. A method is presented for using a simple optimization as quality assurance for the more complex optimization algorithms typically found in commercial brachytherapy treatment planning systems. Quality assurance tests may be performed during commissioning, at regular intervals, and/or on a patient specific basis. A simple optimization method is provided that optimizes conformal target coverage using an exact, variance-based, algebraic approach. Metrics such as dose volume histogram, conformality index, and total reference air kerma agree closely between simple and complex optimizations for breast, cervix, prostate, and planar applicators. The simple optimization is shown to be a sensitive measure for identifying failures in a commercial treatment planning system that are possibly due to operator error or weaknesses in planning system optimization algorithms. Results from the simple optimization are surprisingly similar to the results from a more complex, commercial optimization for several clinical applications. This suggests that there are only modest gains to be made from making brachytherapy optimization more complex. The improvements expected from sophisticated linear optimizations, such as PARETO methods, will largely be in making systems more user friendly and efficient, rather than in finding dramatically better source strength distributions. (paper)

Advancing tuberculosis drug regimen development through innovative quantitative translational pharmacology methods and approaches.

Science.gov (United States)

Hanna, Debra; Romero, Klaus; Schito, Marco

2017-03-01

The development of novel tuberculosis (TB) multi-drug regimens that are more efficacious and of shorter duration requires a robust drug development pipeline. Advances in quantitative modeling and simulation can be used to maximize the utility of patient-level data from prior and contemporary clinical trials, thus optimizing study design for anti-TB regimens. This perspective article highlights the work of seven project teams developing first-in-class translational and quantitative methodologies that aim to inform drug development decision-making, dose selection, trial design, and safety assessments, in order to achieve shorter and safer therapies for patients in need. These tools offer the opportunity to evaluate multiple hypotheses and provide a means to identify, quantify, and understand relevant sources of variability, to optimize translation and clinical trial design. When incorporated into the broader regulatory sciences framework, these efforts have the potential to transform the development paradigm for TB combination development, as well as other areas of global health. Copyright © 2016. Published by Elsevier Ltd.

A novel optimization method, Gravitational Search Algorithm (GSA), for PWR core optimization

International Nuclear Information System (INIS)

Mahmoudi, S.M.; Aghaie, M.; Bahonar, M.; Poursalehi, N.

2016-01-01

Highlights: • The Gravitational Search Algorithm (GSA) is introduced. • The advantage of GSA is verified in Shekel’s Foxholes. • Reload optimizing in WWER-1000 and WWER-440 cases are performed. • Maximizing K eff , minimizing PPFs and flattening power density is considered. - Abstract: In-core fuel management optimization (ICFMO) is one of the most challenging concepts of nuclear engineering. In recent decades several meta-heuristic algorithms or computational intelligence methods have been expanded to optimize reactor core loading pattern. This paper presents a new method of using Gravitational Search Algorithm (GSA) for in-core fuel management optimization. The GSA is constructed based on the law of gravity and the notion of mass interactions. It uses the theory of Newtonian physics and searcher agents are the collection of masses. In this work, at the first step, GSA method is compared with other meta-heuristic algorithms on Shekel’s Foxholes problem. In the second step for finding the best core, the GSA algorithm has been performed for three PWR test cases including WWER-1000 and WWER-440 reactors. In these cases, Multi objective optimizations with the following goals are considered, increment of multiplication factor (K eff ), decrement of power peaking factor (PPF) and power density flattening. It is notable that for neutronic calculation, PARCS (Purdue Advanced Reactor Core Simulator) code is used. The results demonstrate that GSA algorithm have promising performance and could be proposed for other optimization problems of nuclear engineering field.

Aero-Acoustic-Structural Optimization Analysis and Testing, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This proposal effort is concerned with the development of a novel multidisciplinary optimization scheme and computer software for the effective design of advanced...

Advanced methods in diagnosis and therapy

International Nuclear Information System (INIS)

1987-01-01

This important meeting covers the following topics: use and optimization of monoclonal antibobies in oncology: - Tumor markers: Clinical follow-up of patients through tumor marker serum determinations. - Cancer and medical imaging: The use of monoclonal antibodies in immunoscintigraphy. - Immunoradiotherapy: Monoclonal antibodies as therapeutic vectors. Advanced methods in diagnosis: - Contribution of monoclonal antibodies in modern immunochemistry (RIA, EIA). - Interest of monoclonal antibody in immunohistochemical pathology diagnosis. - In vitro diagnosis future prospects: with receptors and oncogenes. - Immunofluoroassay: a new sensitive immunoanalytical procedure with broad applications. Recent advances in brachitherapy: - Interest of computer processing. Blood products irradiation: - Interest in transfusion and bone marrow transplantations [fr

Supply-Chain Optimization Template

Science.gov (United States)

Quiett, William F.; Sealing, Scott L.

2009-01-01

The Supply-Chain Optimization Template (SCOT) is an instructional guide for identifying, evaluating, and optimizing (including re-engineering) aerospace- oriented supply chains. The SCOT was derived from the Supply Chain Council s Supply-Chain Operations Reference (SCC SCOR) Model, which is more generic and more oriented toward achieving a competitive advantage in business.

Optimization of prophylaxis for hemophilia A.

Directory of Open Access Journals (Sweden)

Robert D Herbert

Full Text Available Prophylactic injections of factor VIII reduce the incidence of bleeds and slow the development of joint damage in people with hemophilia. The aim of this study was to identify optimal person-specific prophylaxis regimens for children with hemophilia A.Analytic and numerical methods were used to identify prophylaxis regimens which maximize the time for which plasma factor VIII concentrations exceed a threshold, maximize the lowest plasma factor VIII concentrations, and minimize risk of bleeds.It was demonstrated analytically that, for any injection schedule, the regimen that maximizes the lowest factor VIII concentration involves sharing doses between injections so that all of the trough concentrations in a prophylaxis cycle are equal. Numerical methods were used to identify optimal prophylaxis schedules and explore the trade-offs between efficacy and acceptability of different prophylaxis regimens. The prophylaxis regimen which minimizes risk of bleeds depends on the person's pattern of physical activity and may differ greatly from prophylaxis regimens that optimize pharmacokinetic parameters. Prophylaxis regimens which minimize risk of bleeds also differ from prophylaxis regimens that are typically prescribed. Predictions about which regimen is optimal are sensitive to estimates of the effects on risk of bleeds of factor VIII concentration and physical activity.The methods described here can be used to identify optimal, person-specific prophylaxis regimens for children with hemophilia A.

Optimization of stabilized leachate treatment using ozone/persulfate in the advanced oxidation process

International Nuclear Information System (INIS)

Abu Amr, Salem S.; Aziz, Hamidi Abdul; Adlan, Mohd Nordin

2013-01-01

Highlights: ► Ozone and persulfate reagent (O 3 /S 2 O 8 2- ) was used to treat stabilized leachate. ► Central composite design (CCD) with response surface methodology (RSM) was applied. ► Operating variables including ozone and persulfate dosage, pH variance, and reaction time. ► Optimum removal of COD, color, and NH 3 –N was 72%, 96%, and 76%, respectively. ► A good value of ozone consumption (OC) obtained with 0.60 (kg O 3 /kg COD). - Abstract: The objective of this study was to investigate the performance of employing persulfate reagent in the advanced oxidation of ozone to treat stabilized landfill leachate in an ozone reactor. A central composite design (CCD) with response surface methodology (RSM) was applied to evaluate the relationships between operating variables, such as ozone and persulfate dosages, pH, and reaction time, to identify the optimum operating conditions. Quadratic models for the following four responses proved to be significant with very low probabilities ( 3 –N, and ozone consumption (OC). The obtained optimum conditions included a reaction time of 210 min, 30 g/m 3 ozone, 1 g/1 g COD 0 /S 2 O 8 2- ratio, and pH 10. The experimental results were corresponded well with predicted models (COD, color, and NH 3 –N removal rates of 72%, 96%, and 76%, respectively, and 0.60 (kg O 3 /kg COD OC). The results obtained in the stabilized leachate treatment were compared with those from other treatment processes, such as ozone only and persulfate S 2 O 8 2- only, to evaluate its effectiveness. The combined method (i.e., O 3 /S 2 O 8 2- ) achieved higher removal efficiencies for COD, color, and NH 3 –N compared with other studied applications. Furthermore, the new method is more efficient than ozone/Fenton in advanced oxidation process in the treatment of the same studied leachate

An Indirect Simulation-Optimization Model for Determining Optimal TMDL Allocation under Uncertainty

Directory of Open Access Journals (Sweden)

Feng Zhou

2015-11-01

Full Text Available An indirect simulation-optimization model framework with enhanced computational efficiency and risk-based decision-making capability was developed to determine optimal total maximum daily load (TMDL allocation under uncertainty. To convert the traditional direct simulation-optimization model into our indirect equivalent model framework, we proposed a two-step strategy: (1 application of interval regression equations derived by a Bayesian recursive regression tree (BRRT v2 algorithm, which approximates the original hydrodynamic and water-quality simulation models and accurately quantifies the inherent nonlinear relationship between nutrient load reductions and the credible interval of algal biomass with a given confidence interval; and (2 incorporation of the calibrated interval regression equations into an uncertain optimization framework, which is further converted to our indirect equivalent framework by the enhanced-interval linear programming (EILP method and provides approximate-optimal solutions at various risk levels. The proposed strategy was applied to the Swift Creek Reservoir’s nutrient TMDL allocation (Chesterfield County, VA to identify the minimum nutrient load allocations required from eight sub-watersheds to ensure compliance with user-specified chlorophyll criteria. Our results indicated that the BRRT-EILP model could identify critical sub-watersheds faster than the traditional one and requires lower reduction of nutrient loadings compared to traditional stochastic simulation and trial-and-error (TAE approaches. This suggests that our proposed framework performs better in optimal TMDL development compared to the traditional simulation-optimization models and provides extreme and non-extreme tradeoff analysis under uncertainty for risk-based decision making.

Advanced methods for the analysis, design, and optimization of SMA-based aerostructures

International Nuclear Information System (INIS)

Hartl, D J; Lagoudas, D C; Calkins, F T

2011-01-01

Engineers continue to apply shape memory alloys to aerospace actuation applications due to their high energy density, robust solid-state actuation, and silent and shock-free operation. Past design and development of such actuators relied on experimental trial and error and empirically derived graphical methods. Over the last two decades, however, it has been repeatedly demonstrated that existing SMA constitutive models can capture stabilized SMA transformation behaviors with sufficient accuracy. This work builds upon past successes and suggests a general framework by which predictive tools can be used to assess the responses of many possible design configurations in an automated fashion. By applying methods of design optimization, it is shown that the integrated implementation of appropriate analysis tools can guide engineers and designers to the best design configurations. A general design optimization framework is proposed for the consideration of any SMA component or assembly of such components that applies when the set of design variables includes many members. This is accomplished by relying on commercially available software and utilizing tools already well established in the design optimization community. Such tools are combined with finite element analysis (FEA) packages that consider a multitude of structural effects. The foundation of this work is a three-dimensional thermomechanical constitutive model for SMAs applicable for arbitrarily shaped bodies. A reduced-order implementation also allows computationally efficient analysis of structural components such as wires, rods, beams and shells. The use of multiple optimization schemes, the consideration of assembled components, and the accuracy of the implemented constitutive model in full and reduced-order forms are all demonstrated

The aerodynamic design of an advanced rotor airfoil

Science.gov (United States)

Blackwell, J. A., Jr.; Hinson, B. L.

1978-01-01

An advanced rotor airfoil, designed utilizing supercritical airfoil technology and advanced design and analysis methodology is described. The airfoil was designed subject to stringent aerodynamic design criteria for improving the performance over the entire rotor operating regime. The design criteria are discussed. The design was accomplished using a physical plane, viscous, transonic inverse design procedure, and a constrained function minimization technique for optimizing the airfoil leading edge shape. The aerodynamic performance objectives of the airfoil are discussed.

Advances in fragment-based drug discovery platforms.

Science.gov (United States)

Orita, Masaya; Warizaya, Masaichi; Amano, Yasushi; Ohno, Kazuki; Niimi, Tatsuya

2009-11-01

Fragment-based drug discovery (FBDD) has been established as a powerful alternative and complement to traditional high-throughput screening techniques for identifying drug leads. At present, this technique is widely used among academic groups as well as small biotech and large pharmaceutical companies. In recent years, > 10 new compounds developed with FBDD have entered clinical development, and more and more attention in the drug discovery field is being focused on this technique. Under the FBDD approach, a fragment library of relatively small compounds (molecular mass = 100 - 300 Da) is screened by various methods and the identified fragment hits which normally weakly bind to the target are used as starting points to generate more potent drug leads. Because FBDD is still a relatively new drug discovery technology, further developments and optimizations in screening platforms and fragment exploitation can be expected. This review summarizes recent advances in FBDD platforms and discusses the factors important for the successful application of this technique. Under the FBDD approach, both identifying the starting fragment hit to be developed and generating the drug lead from that starting fragment hit are important. Integration of various techniques, such as computational technology, X-ray crystallography, NMR, surface plasmon resonance, isothermal titration calorimetry, mass spectrometry and high-concentration screening, must be applied in a situation-appropriate manner.

6 Sigma project advance

International Nuclear Information System (INIS)

2002-12-01

This book deals with 6 sigma project advance which introduces 6 sigma project in Changwon special steel, how is failure accepted? CTQ selection which is starting line, definition of performance standard, measurement system check on reliability of measurement data, check of process capacity for current level, establishment of target, optimal design and performance of application, practice of management system for maintain of improved result, CTQ selection, check of measurement system and practice of management system.

Class and Home Problems: Optimization Problems

Science.gov (United States)

Anderson, Brian J.; Hissam, Robin S.; Shaeiwitz, Joseph A.; Turton, Richard

2011-01-01

Optimization problems suitable for all levels of chemical engineering students are available. These problems do not require advanced mathematical techniques, since they can be solved using typical software used by students and practitioners. The method used to solve these problems forces students to understand the trends for the different terms…

A supercomputing application for reactors core design and optimization

International Nuclear Information System (INIS)

Hourcade, Edouard; Gaudier, Fabrice; Arnaud, Gilles; Funtowiez, David; Ammar, Karim

2010-01-01

Advanced nuclear reactor designs are often intuition-driven processes where designers first develop or use simplified simulation tools for each physical phenomenon involved. Through the project development, complexity in each discipline increases and implementation of chaining/coupling capabilities adapted to supercomputing optimization process are often postponed to a further step so that task gets increasingly challenging. In the context of renewal in reactor designs, project of first realization are often run in parallel with advanced design although very dependant on final options. As a consequence, the development of tools to globally assess/optimize reactor core features, with the on-going design methods accuracy, is needed. This should be possible within reasonable simulation time and without advanced computer skills needed at project management scale. Also, these tools should be ready to easily cope with modeling progresses in each discipline through project life-time. An early stage development of multi-physics package adapted to supercomputing is presented. The URANIE platform, developed at CEA and based on the Data Analysis Framework ROOT, is very well adapted to this approach. It allows diversified sampling techniques (SRS, LHS, qMC), fitting tools (neuronal networks...) and optimization techniques (genetic algorithm). Also data-base management and visualization are made very easy. In this paper, we'll present the various implementing steps of this core physics tool where neutronics, thermo-hydraulics, and fuel mechanics codes are run simultaneously. A relevant example of optimization of nuclear reactor safety characteristics will be presented. Also, flexibility of URANIE tool will be illustrated with the presentation of several approaches to improve Pareto front quality. (author)

Optimal ratio of cash and non-cash payments

Directory of Open Access Journals (Sweden)

Galina S. Panova

2014-01-01

Full Text Available Analysis of the present condition and prospects of development of the monetary sector of the Russian economy. Quantitative parameters of aggregate turnover, including the value of cash and non-cash it. Researched issues restricting cash advance industry in Russia and other countries; the problems encountered by foreign States in imposing administrative limits on cash payments; provides specific recommendations and identified risks imposing such restrictions in Russia. The article deals with topical issues of optimization of structure of aggregate turnover. Analyzing the development of money turnover, the role and the place of cash in the economy, the author explored the basic approaches to the determination and regulation of money turnover, proposed a new approach to ensure transparency in money flows. Particularly promising cash flow optimization are: a measures aimed at improving the cash turnover (including maintaining the stability of the national currency, improving the procedures for issuing and withdrawing money from circulation, determine the optimal structure of monetary aggregates, etc. and b development of cashless money turnover. The author's position is presented on the future of the scientific basis and practical realization of the optimal ratio of cash and cashless money turnover in Russia and other countries. In particular, felt the need to increase information transparency, openness international information exchange in order to improve monetary policy by countries at the national and international level. To develop common approaches (models of the analysis and forecasting of financial markets, as well as the establishment of an international coordination centre responsible for the collection, verification and access to public information databases for the cross-country studies of banking and financial and monetary sphere.

Treatment of an actual slaughterhouse wastewater by integration of biological and advanced oxidation processes: Modeling, optimization, and cost-effectiveness analysis.

Science.gov (United States)

Bustillo-Lecompte, Ciro Fernando; Mehrvar, Mehrab

2016-11-01

Biological and advanced oxidation processes are combined to treat an actual slaughterhouse wastewater (SWW) by a sequence of an anaerobic baffled reactor, an aerobic activated sludge reactor, and a UV/H2O2 photoreactor with recycle in continuous mode at laboratory scale. In the first part of this study, quadratic modeling along with response surface methodology are used for the statistical analysis and optimization of the combined process. The effects of the influent total organic carbon (TOC) concentration, the flow rate, the pH, the inlet H2O2 concentration, and their interaction on the overall treatment efficiency, CH4 yield, and H2O2 residual in the effluent of the photoreactor are investigated. The models are validated at different operating conditions using experimental data. Maximum TOC and total nitrogen (TN) removals of 91.29 and 86.05%, respectively, maximum CH4 yield of 55.72%, and minimum H2O2 residual of 1.45% in the photoreactor effluent were found at optimal operating conditions. In the second part of this study, continuous distribution kinetics is applied to establish a mathematical model for the degradation of SWW as a function of time. The agreement between model predictions and experimental values indicates that the proposed model could describe the performance of the combined anaerobic-aerobic-UV/H2O2 processes for the treatment of SWW. In the final part of the study, the optimized combined anaerobic-aerobic-UV/H2O2 processes with recycle were evaluated using a cost-effectiveness analysis to minimize the retention time, the electrical energy consumption, and the overall incurred treatment costs required for the efficient treatment of slaughterhouse wastewater effluents. Copyright © 2016 Elsevier Ltd. All rights reserved.

MULTI-OBJECTIVE ONLINE OPTIMIZATION OF BEAM LIFETIME AT APS

Energy Technology Data Exchange (ETDEWEB)

Sun, Yipeng

2017-06-25

In this paper, online optimization of beam lifetime at the APS (Advanced Photon Source) storage ring is presented. A general genetic algorithm (GA) is developed and employed for some online optimizations in the APS storage ring. Sextupole magnets in 40 sectors of the APS storage ring are employed as variables for the online nonlinear beam dynamics optimization. The algorithm employs several optimization objectives and is designed to run with topup mode or beam current decay mode. Up to 50\\% improvement of beam lifetime is demonstrated, without affecting the transverse beam sizes and other relevant parameters. In some cases, the top-up injection efficiency is also improved.

Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zamzam, Admed S. [University of Minnesota; Sidiropoulos, Nicholas D. [University of Minnesota; Taylor, Josh A. [University of Toronto

2018-01-12

This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.

Leveraging advances in biology to design biomaterials

Science.gov (United States)

Darnell, Max; Mooney, David J.

2017-12-01

Biomaterials have dramatically increased in functionality and complexity, allowing unprecedented control over the cells that interact with them. From these engineering advances arises the prospect of improved biomaterial-based therapies, yet practical constraints favour simplicity. Tools from the biology community are enabling high-resolution and high-throughput bioassays that, if incorporated into a biomaterial design framework, could help achieve unprecedented functionality while minimizing the complexity of designs by identifying the most important material parameters and biological outputs. However, to avoid data explosions and to effectively match the information content of an assay with the goal of the experiment, material screens and bioassays must be arranged in specific ways. By borrowing methods to design experiments and workflows from the bioprocess engineering community, we outline a framework for the incorporation of next-generation bioassays into biomaterials design to effectively optimize function while minimizing complexity. This framework can inspire biomaterials designs that maximize functionality and translatability.

Determining the optimal approach to identifying individuals with chronic obstructive pulmonary disease: The DOC study.

Science.gov (United States)

Ronaldson, Sarah J; Dyson, Lisa; Clark, Laura; Hewitt, Catherine E; Torgerson, David J; Cooper, Brendan G; Kearney, Matt; Laughey, William; Raghunath, Raghu; Steele, Lisa; Rhodes, Rebecca; Adamson, Joy

2018-06-01

Early identification of chronic obstructive pulmonary disease (COPD) results in patients receiving appropriate management for their condition at an earlier stage in their disease. The determining the optimal approach to identifying individuals with chronic obstructive pulmonary disease (DOC) study was a case-finding study to enhance early identification of COPD in primary care, which evaluated the diagnostic accuracy of a series of simple lung function tests and symptom-based case-finding questionnaires. Current smokers aged 35 or more were invited to undertake a series of case-finding tools, which comprised lung function tests (specifically, spirometry, microspirometry, peak flow meter, and WheezoMeter) and several case-finding questionnaires. The effectiveness of these tests, individually or in combination, to identify small airways obstruction was evaluated against the gold standard of spirometry, with the quality of spirometry tests assessed by independent overreaders. The study was conducted with general practices in the Yorkshire and Humberside area, in the UK. Six hundred eighty-one individuals met the inclusion criteria, with 444 participants completing their study appointments. A total of 216 (49%) with good-quality spirometry readings were included in the analysis. The most effective case-finding tools were found to be the peak flow meter alone, the peak flow meter plus WheezoMeter, and microspirometry alone. In addition to the main analysis, where the severity of airflow obstruction was based on fixed ratios and percent of predicted values, sensitivity analyses were conducted by using lower limit of normal values. This research informs the choice of test for COPD identification; case-finding by use of the peak flow meter or microspirometer could be used routinely in primary care for suspected COPD patients. Only those testing positive to these tests would move on to full spirometry, thereby reducing unnecessary spirometric testing. © 2018 John Wiley

Advanced computational biology methods identify molecular switches for malignancy in an EGF mouse model of liver cancer.

Directory of Open Access Journals (Sweden)

Philip Stegmaier

Full Text Available The molecular causes by which the epidermal growth factor receptor tyrosine kinase induces malignant transformation are largely unknown. To better understand EGFs' transforming capacity whole genome scans were applied to a transgenic mouse model of liver cancer and subjected to advanced methods of computational analysis to construct de novo gene regulatory networks based on a combination of sequence analysis and entrained graph-topological algorithms. Here we identified transcription factors, processes, key nodes and molecules to connect as yet unknown interacting partners at the level of protein-DNA interaction. Many of those could be confirmed by electromobility band shift assay at recognition sites of gene specific promoters and by western blotting of nuclear proteins. A novel cellular regulatory circuitry could therefore be proposed that connects cell cycle regulated genes with components of the EGF signaling pathway. Promoter analysis of differentially expressed genes suggested the majority of regulated transcription factors to display specificity to either the pre-tumor or the tumor state. Subsequent search for signal transduction key nodes upstream of the identified transcription factors and their targets suggested the insulin-like growth factor pathway to render the tumor cells independent of EGF receptor activity. Notably, expression of IGF2 in addition to many components of this pathway was highly upregulated in tumors. Together, we propose a switch in autocrine signaling to foster tumor growth that was initially triggered by EGF and demonstrate the knowledge gain form promoter analysis combined with upstream key node identification.

Optimal FDG PET/CT volumetric parameters for risk stratification in patients with locally advanced non-small cell lung cancer: results from the ACRIN 6668/RTOG 0235 trial

Energy Technology Data Exchange (ETDEWEB)

Salavati, Ali [Hospital of the University of Pennsylvania, Department of Radiology, Philadelphia, PA (United States); University of Minnesota, Department of Radiology, Minneapolis, MN (United States); Duan, Fenghai [Brown University School of Public Health, Department of Biostatistics and Center for Statistical Sciences, Providence, RI (United States); Snyder, Bradley S. [Brown University School of Public Health, Center for Statistical Sciences, Providence, RI (United States); Wei, Bo [Emory University, Department of Biostatistics, Rollins School of Public Health, Atlanta, GA (United States); Houshmand, Sina; Alavi, Abass [Hospital of the University of Pennsylvania, Department of Radiology, Philadelphia, PA (United States); Khiewvan, Benjapa [Hospital of the University of Pennsylvania, Department of Radiology, Philadelphia, PA (United States); Mahidol University, Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine Siriraj Hospital, Bangkok (Thailand); Opanowski, Adam [ACR Center for Research and Innovation, American College of Radiology, Philadelphia, PA (United States); Simone, Charles B. [University of Maryland Medical Center, Department of Radiation Oncology, Baltimore, MD (United States); Siegel, Barry A. [Washington University School of Medicine, Mallinckrodt Institute of Radiology and the Alvin J. Siteman Cancer Center, St, Louis, MO (United States); Machtay, Mitchell [Case Western Reserve University and University Hospitals Case Medical Center, Department of Radiation Oncology, Cleveland, OH (United States)

2017-11-15

In recent years, multiple studies have demonstrated the value of volumetric FDG-PET/CT parameters as independent prognostic factors in patients with non-small cell lung cancer (NSCLC). We aimed to determine the optimal cut-off points of pretreatment volumetric FDG-PET/CT parameters in predicting overall survival (OS) in patients with locally advanced NSCLC and to recommend imaging biomarkers appropriate for routine clinical applications. Patients with inoperable stage IIB/III NSCLC enrolled in ACRIN 6668/RTOG 0235 were included. Pretreatment FDG-PET scans were quantified using semiautomatic adaptive contrast-oriented thresholding and local-background partial-volume-effect-correction algorithms. For each patient, the following indices were measured: metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, SUVmean, partial-volume-corrected TLG (pvcTLG), and pvcSUVmean for the whole-body, primary tumor, and regional lymph nodes. The association between each index and patient outcome was assessed using Cox proportional hazards regression. Optimal cut-off points were estimated using recursive binary partitioning in a conditional inference framework and used in Kaplan-Meier curves with log-rank testing. The discriminatory ability of each index was examined using time-dependent receiver operating characteristic (ROC) curves and corresponding area under the curve (AUC(t)). The study included 196 patients. Pretreatment whole-body and primary tumor MTV, TLG, and pvcTLG were independently prognostic of OS. Optimal cut-off points were 175.0, 270.9, and 35.5 cm{sup 3} for whole-body TLG, pvcTLG, and MTV, and were 168.2, 239.8, and 17.4 cm{sup 3} for primary tumor TLG, pvcTLG, and MTV, respectively. In time-dependent ROC analysis, AUC(t) for MTV and TLG were uniformly higher than that of SUV measures over all time points. Primary tumor and whole-body parameters demonstrated similar patterns of separation for those patients above versus below the optimal cut

Applied probability models with optimization applications

CERN Document Server

Ross, Sheldon M

1992-01-01

Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process, renewal theory, Markov chains, inventory theory, Brownian motion and continuous time optimization models, much more. Problems and references at chapter ends. ""Excellent introduction."" - Journal of the American Statistical Association. Bibliography. 1970 edition.

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

Directory of Open Access Journals (Sweden)

Kirshna Kumar

2017-12-01

Full Text Available Energy efficiency is a significant characteristic of battery-run devices such as sensors, RFID and mobile phones. In the present scenario, this is the most prominent requirement that must be served while introducing a communication protocol for an IoT environment. IoT network success and performance enhancement depend heavily on optimization of energy consumption that enhance the lifetime of IoT nodes and the network. In this context, this paper presents a comprehensive review on energy efficiency techniques used in IoT environments. The techniques proposed by researchers have been categorized based on five different layers of the energy architecture of IoT. These five layers are named as sensing, local processing and storage, network/communication, cloud processing and storage, and application. Specifically, the significance of energy efficiency in IoT environments is highlighted. A taxonomy is presented for the classification of related literature on energy efficient techniques in IoT environments. Following the taxonomy, a critical review of literature is performed focusing on major functional models, strengths and weaknesses. Open research challenges related to energy efficiency in IoT are identified as future research directions in the area. The survey should benefit IoT industry practitioners and researchers, in terms of augmenting the understanding of energy efficiency and its IoT-related trends and issues.

Identifying non-technical skills and barriers for improvement of teamwork in cardiac arrest teams

DEFF Research Database (Denmark)

Andersen, P.O.; Jensen, Michael Kammer; Lippert, A.

2010-01-01

Background: The application of non-technical skills (NTSs) in health care has previously been described in other health-care educational programmes. NTSs are behavioural principles such as leadership, task distribution and communication. The aim of this study was to identify NTSs suitable...... for improving team performance in multi-professional cardiac arrest teams, and to describe barriers to the use and implementation of such NTSs by using a qualitative method. Methods: Individual semi-structured interviews were conducted with 11 Danish Advanced Life Support instructors during the period April...... 2006 to November 2006. Interviews were focussed on barriers and recommendations for teamwork in the cardiac arrest team, optimal policy for improvement of resuscitation training and clinical practice, use of cognitive aids and adoption of European Resuscitation Council (ERC) Guidelines 2005. Interviews...

Identifying optimal agricultural countermeasure strategies for a hypothetical contamination scenario using the strategy model

International Nuclear Information System (INIS)

Cox, G.; Beresford, N.A.; Alvarez-Farizo, B.; Oughton, D.; Kis, Z.; Eged, K.; Thorring, H.; Hunt, J.; Wright, S.; Barnett, C.L.; Gil, J.M.; Howard, B.J.; Crout, N.M.J.

2005-01-01

A spatially implemented model designed to assist the identification of optimal countermeasure strategies for radioactively contaminated regions is described. Collective and individual ingestion doses for people within the affected area are estimated together with collective exported ingestion dose. A range of countermeasures are incorporated within the model, and environmental restrictions have been included as appropriate. The model evaluates the effectiveness of a given combination of countermeasures through a cost function which balances the benefit obtained through the reduction in dose with the cost of implementation. The optimal countermeasure strategy is the combination of individual countermeasures (and when and where they are implemented) which gives the lowest value of the cost function. The model outputs should not be considered as definitive solutions, rather as interactive inputs to the decision making process. As a demonstration the model has been applied to a hypothetical scenario in Cumbria (UK). This scenario considered a published nuclear power plant accident scenario with a total deposition of 1.7 x 10 14 , 1.2 x 10 13 , 2.8 x 10 10 and 5.3 x 10 9 Bq for Cs-137, Sr-90, Pu-239/240 and Am-241, respectively. The model predicts that if no remediation measures were implemented the resulting collective dose would be approximately 36 000 person-Sv (predominantly from 137 Cs) over a 10-year period post-deposition. The optimal countermeasure strategy is predicted to avert approximately 33 000 person-Sv at a cost of approximately pound 160 million. The optimal strategy comprises a mixture of ploughing, AFCF (ammonium-ferric hexacyano-ferrate) administration, potassium fertiliser application, clean feeding of livestock and food restrictions. The model recommends specific areas within the contaminated area and time periods where these measures should be implemented

Neoadjuvant Chemotherapy for Advanced Epithelial Ovarian Cancer

International Nuclear Information System (INIS)

Avendano Juan; Buitrago, Giancarlo; Ramos, Pedro; Suescun Oscar

2010-01-01

Objective: To describe the experience at the National Cancer Institute (NCI) on the use of neoadjuvant chemotherapy as primary treatment for epithelial ovarian cancer among patients in stages IIIC and IV. Methods: We conducted a descriptive retrospective study (case series type) of patients diagnosed with epithelial ovarian cancer in stages IIIC and IV, treated at the NCI from January 1, 2003 to December 31,2006, who underwent neoadjuvant chemotherapy as primary treatment. Demographic characteristics and clinical outcomes are described. Results: Seventeen patients who fulfilled the above mentioned criteria were selected. Once neoadjuvant chemotherapy ended, 5 patients (29.4%) achieved complete or partial clinical response; 4 (23.8%) remained in stable condition, and 8 (47.6%) showed signs of progressive illness. Interval debulking surgery was performed on objective response patients. Maximum cytoreduction was achieved in 5 patients (100%); first relapse was reported at month 18 of follow-up; 2 disease-free survivors were identified in December, 2007; 8 (49%) reported some degree of non-severe chemotherapy-related toxicity. No mortality was related to chemotherapy, no post surgical complications were observed and no patient required advanced support management. Conclusions: Neoadjuvant chemotherapy, followed by optimal interval debulking surgery among selected patients, can be an alternative treatment for advanced epithelial ovarian cancer among women with irresecability or the critically ill. Further studies with improved design are required to confirm these findings.

Analyses of Methods and Algorithms for Modelling and Optimization of Biotechnological Processes

Directory of Open Access Journals (Sweden)

Stoyan Stoyanov

2009-08-01

Full Text Available A review of the problems in modeling, optimization and control of biotechnological processes and systems is given in this paper. An analysis of existing and some new practical optimization methods for searching global optimum based on various advanced strategies - heuristic, stochastic, genetic and combined are presented in the paper. Methods based on the sensitivity theory, stochastic and mix strategies for optimization with partial knowledge about kinetic, technical and economic parameters in optimization problems are discussed. Several approaches for the multi-criteria optimization tasks are analyzed. The problems concerning optimal controls of biotechnological systems are also discussed.

Efficacy and safety of endocrine monotherapy as first-line treatment for hormone-sensitive advanced breast cancer: A network meta-analysis.

Science.gov (United States)

Zhang, Jingwen; Huang, Yanhong; Wang, Changyi; He, Yuanfang; Zheng, Shukai; Wu, Kusheng

2017-08-01

Endocrine therapy was recommended as the preferred first-line treatment for hormone receptor-positive (HR+, i.e., ER+ and/or PgR+), human epidermal growth factor receptor-2-negative (HER2-) postmenopausal advanced breast cancer (ABC), but which endocrine monotherapy is optimal lacks consensus. We aimed to identify the optimal endocrine monotherapy with a network meta-analysis. We performed a network meta-analysis for a comprehensive analysis of 6 first-line endocrine monotherapies (letrozole, anastrozole, exemestane, tamoxifen, fulvestrant 250 mg and 500 mg) for HR+ HER2- metastatic or locally advanced breast cancer in postmenopausal patients. The main outcomes were objective response rate (ORR), time to progression (TTP), and progression-free survival (PFS). Secondary outcomes were adverse events. We identified 27 articles of 8 randomized controlled trials including 3492 patients in the network meta-analysis. For ORR, the treatments ranked in descending order of effectiveness were letrozole > exemestane > anastrozole > fulvestrant 500 mg > tamoxifen > fulvestrant 250 mg. For TTP/PFS, the order was fulvestrant 500 mg > letrozole > anastrozole > exemestane > tamoxifen > fulvestrant 250 mg. We directly compared adverse events and found that tamoxifen produced more hot flash events than fulvestrant 250 mg. Fulvestrant 500 mg and letrozole might be optimal first-line endocrine monotherapy choices for HR+ HER2- ABC because of efficacious ORR and TTP/PFS, with a favorable tolerability profile. However, direct comparisons among endocrine monotherapies in the first-line therapy setting are still required to robustly demonstrate any differences among these endocrine agents. Clinical choices should also depend on the specific disease situation and duration of endocrine therapy.

3rd World Congress on Global Optimization in Engineering & Science

CERN Document Server

Ruan, Ning; Xing, Wenxun; WCGO-III; Advances in Global Optimization

2015-01-01

This proceedings volume addresses advances in global optimization—a multidisciplinary research field that deals with the analysis, characterization, and computation of global minima and/or maxima of nonlinear, non-convex, and nonsmooth functions in continuous or discrete forms. The volume contains selected papers from the third biannual World Congress on Global Optimization in Engineering & Science (WCGO), held in the Yellow Mountains, Anhui, China on July 8-12, 2013. The papers fall into eight topical sections: mathematical programming; combinatorial optimization; duality theory; topology optimization; variational inequalities and complementarity problems; numerical optimization; stochastic models and simulation; and complex simulation and supply chain analysis.

Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

Science.gov (United States)

Crown, William; Buyukkaramikli, Nasuh; Thokala, Praveen; Morton, Alec; Sir, Mustafa Y; Marshall, Deborah A; Tosh, Jon; Padula, William V; Ijzerman, Maarten J; Wong, Peter K; Pasupathy, Kalyan S

2017-03-01

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Physics challenges for advanced fuel cycle assessment

Energy Technology Data Exchange (ETDEWEB)

Giuseppe Palmiotti; Massimo Salvatores; Gerardo Aliberti

2014-06-01

Advanced fuel cycles and associated optimized reactor designs will require substantial improvements in key research area to meet new and more challenging requirements. The present paper reviews challenges and issues in the field of reactor and fuel cycle physics. Typical examples are discussed with, in some cases, original results.

Physics challenges for advanced fuel cycle assessment

Energy Technology Data Exchange (ETDEWEB)

Salvatores, Massimo; Aliberti, Gerardo; Palmiotti, Giuseppe

2014-06-17

Advanced fuel cycles and associated optimized reactor designs will require substantial improvements in key research area to meet new and more challenging requirements. The present paper reviews challenges and issues in the field of reactor and fuel cycle physics. Typical examples are discussed with, in some cases, original results.

Synthetic biology advances for pharmaceutical production

OpenAIRE

Breitling, Rainer; Takano, Eriko

2015-01-01

Synthetic biology enables a new generation of microbial engineering for the biotechnological production of pharmaceuticals and other high-value chemicals. This review presents an overview of recent advances in the field, describing new computational and experimental tools for the discovery, optimization and production of bioactive molecules, and outlining progress towards the application of these tools to pharmaceutical production systems.

Healthcare Provider Views on Transitioning From Task Shifting to Advanced Practice Nursing in Tanzania.

Science.gov (United States)

Mboineki, Joanes Faustine; Zhang, Weihong

The Tanzanian health sector suffers from shortages of healthcare workers as well as uneven distribution of healthcare workers in urban and rural areas. Task shifting-delegation of tasks from professionals to other healthcare team members with less training, such as medical attendants-is practiced, compromising quality of care. Advanced practice nursing is underutilized. The purpose of this study was to explore the views of nurses and physicians on current responses to shortages of healthcare workers and the potential for utilization of advanced practice nurses. A descriptive, qualitative design was used. Purposeful sampling was used to select 20 participants. An in-depth interview guide was used to obtain information. Interviews were conducted in Swahili or English. Content analysis was used to identify themes. Shortage of human resources in rural primary healthcare facilities was identified as a major rationale for implementation of the advanced practice nurse practitioner role because the current health providers in rural health facilities are less trained and doctors are not ready to work in these settings. Opposition from physicians is expected during the course of implementing the nurse practitioner role. Professional bodies and government should reach consensus before the implementation of this role in such a way that they should agree on scope and standards of practice of nurse practitioners in Tanzania. Shortage of human resources for health is greater in rural primary healthcare facilities. Task shifting in Tanzania is neither effective nor legally recognized. Transition to advanced practice nursing roles-particularly the nurse practitioner role-can facilitate provision of optimal care. Nurse practitioners should be prepared to work in rural primary healthcare facilities.

Optimization of Antivirus Software

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available The paper describes the main techniques used in development of computer antivirus software applications. For this particular category of software, are identified and defined optimum criteria that helps determine which solution is better and what are the objectives of the optimization process. From the general viewpoint of software optimization are presented methods and techniques that are applied at code development level. Regarding the particularities of antivirus software, the paper analyzes some of the optimization concepts applied to this category of applications

Advances and Challenges in Treatment of Locally Advanced Rectal Cancer

Science.gov (United States)

Smith, J. Joshua; Garcia-Aguilar, Julio

2015-01-01

Dramatic improvements in the outcomes of patients with rectal cancer have occurred over the past 30 years. Advances in surgical pathology, refinements in surgical techniques and instrumentation, new imaging modalities, and the widespread use of neoadjuvant therapy have all contributed to these improvements. Several questions emerge as we learn of the benefits or lack thereof for components of the current multimodality treatment in subgroups of patients with nonmetastatic locally advanced rectal cancer (LARC). What is the optimal surgical technique for distal rectal cancers? Do all patients need postoperative chemotherapy? Do all patients need radiation? Do all patients need surgery, or is a nonoperative, organ-preserving approach warranted in selected patients? Answering these questions will lead to more precise treatment regimens, based on patient and tumor characteristics, that will improve outcomes while preserving quality of life. However, the idea of shifting the treatment paradigm (chemoradiotherapy, total mesorectal excision, and adjuvant therapy) currently applied to all patients with LARC to a more individually tailored approach is controversial. The paradigm shift toward organ preservation in highly selected patients whose tumors demonstrate clinical complete response to neoadjuvant treatment is also controversial. Herein, we highlight many of the advances and resultant controversies that are likely to dominate the research agenda for LARC in the modern era. PMID:25918296

Traveling wave accelerating structures with a large phase advance

International Nuclear Information System (INIS)

Paramonov, V.V.

2012-01-01

The cells RF parameters for the well known Disk Loaded Waveguide (DLW) are considered in higher pass bands of TM01 wave, providing operating phase advance between 180 o - 1230 o per cell. With an appropriate shape optimization and some additional elements proposed traveling wave structures with such large phase advance overlap the classical first band DLW in RF efficiency. Examples of proposed structures together with RF and dispersion properties are presented.

WiMAX network performance monitoring & optimization

DEFF Research Database (Denmark)

Zhang, Qi; Dam, H

2008-01-01

frequency reuse, capacity planning, proper network dimensioning, multi-class data services and so on. Furthermore, as a small operator we also want to reduce the demand for sophisticated technicians and man labour hours. To meet these critical demands, we design a generic integrated network performance......In this paper we present our WiMAX (worldwide interoperability for microwave access) network performance monitoring and optimization solution. As a new and small WiMAX network operator, there are many demanding issues that we have to deal with, such as limited available frequency resource, tight...... this integrated network performance monitoring and optimization system in our WiMAX networks. This integrated monitoring and optimization system has such good flexibility and scalability that individual function component can be used by other operators with special needs and more advanced function components can...

Identifying the Optimal Offshore Areas for Wave Energy Converter Deployments in Taiwanese Waters Based on 12-Year Model Hindcasts

Directory of Open Access Journals (Sweden)

Hung-Ju Shih

2018-02-01

Full Text Available A 12-year sea-state hindcast for Taiwanese waters, covering the period from 2005 to 2016, was conducted using a fully coupled tide-surge-wave model. The hindcasts of significant wave height and peak period were employed to estimate the wave power resources in the waters surrounding Taiwan. Numerical simulations based on unstructured grids were converted to structured grids with a resolution of 25 × 25 km. The spatial distribution maps of offshore annual mean wave power were created for each year and for the 12-year period. Waters with higher wave power density were observed off the northern, northeastern, southeastern (south of Green Island and southeast of Lanyu and southern coasts of Taiwan. Five energetic sea areas with spatial average annual total wave energy density of 60–90 MWh/m were selected for further analysis. The 25 × 25 km square grids were then downscaled to resolutions of 5 × 5 km, and five 5 × 5 km optimal areas were identified for wave energy converter deployments. The spatial average annual total wave energy yields at the five optimal areas (S1–(S5 were estimated to be 64.3, 84.1, 84.5, 111.0 and 99.3 MWh/m, respectively. The prevailing wave directions for these five areas lie between east and northeast.

A Joint Report on PSA for New and Advanced Reactors

International Nuclear Information System (INIS)

2013-01-01

This report addresses the application of Probabilistic Safety Assessment (PSA) to new and advanced nuclear reactors. As far as advanced reactors are concerned, the objectives were to characterize the ability of current PSA technology to address key questions regarding the development, acceptance and licensing of advanced reactor designs, to characterize the potential value of advanced PSA methods and tools for application to advanced reactors, and to develop recommendations for any needed developments regarding PSA for these reactors. As far as the design and commissioning of new nuclear power plants is concerned, the objectives were to identify and characterize current practices regarding the role of PSA, to identify key technical issues regarding PSA, lessons learned and issues requiring further work; to develop recommendations regarding the use of PSA, and to identify future international cooperative work on the identified issues. In order to reach these objectives, questionnaires had been sent to participating countries and organisations

Advanced HVAC System for Smart Grid

Energy Technology Data Exchange (ETDEWEB)

Whalen, Scott A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Corbin, Charles D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-03-06

Rocky Research (Boulder City, NV) has developed an advanced roof top air conditioning unit (RTU) with the potential for providing smart grid functions such as regulation services and PV integration. The RTU contains advanced technologies that have been demonstrated to enable 1) improved coefficient of performance (COP) during start-up transients, 2) improved steady-state efficiency, and 3) blending of DC and AC power with high conversion efficiency. Technologies incorporated by Rocky Research include a pulsing thermal expansion valve (PTXV) to dynamically optimize refrigerant flow, a variable frequency drive (VFD) for the compressor, and on-board integrated power conversion electronics for inverting and blending DC and AC power.

Multi-Objective Optimization in Physical Synthesis of Integrated Circuits

CERN Document Server

A Papa, David

2013-01-01

This book introduces techniques that advance the capabilities and strength of modern software tools for physical synthesis, with the ultimate goal to improve the quality of leading-edge semiconductor products.  It provides a comprehensive introduction to physical synthesis and takes the reader methodically from first principles through state-of-the-art optimizations used in cutting edge industrial tools. It explains how to integrate chip optimizations in novel ways to create powerful circuit transformations that help satisfy performance requirements. Broadens the scope of physical synthesis optimization to include accurate transformations operating between the global and local scales; Integrates groups of related transformations to break circular dependencies and increase the number of circuit elements that can be jointly optimized to escape local minima;  Derives several multi-objective optimizations from first observations through complete algorithms and experiments; Describes integrated optimization te...

Optimization of surface maintenance

International Nuclear Information System (INIS)

Oeverland, E.

1990-01-01

The present conference paper deals with methods of optimizing the surface maintenance of steel-made offshore installations. The paper aims at identifying important approaches to the problems regarding the long-range planning of an economical and cost effective maintenance program. The methods of optimization are based on the obtained experiences from the maintenance of installations on the Norwegian continental shelf. 3 figs

Process optimization and insecticidal activity of alkaloids from the ...

African Journals Online (AJOL)

Process optimization and insecticidal activity of alkaloids from the root bark of Catalpa ovata G. Don by response surface methodology. ... Tropical Journal of Pharmaceutical Research. Journal Home · ABOUT THIS JOURNAL · Advanced ...

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

Advanced optimization of permanent magnet wigglers using a genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Hajima, Ryoichi [Univ. of Tokyo (Japan)

1995-12-31

In permanent magnet wigglers, magnetic imperfection of each magnet piece causes field error. This field error can be reduced or compensated by sorting magnet pieces in proper order. We showed a genetic algorithm has good property for this sorting scheme. In this paper, this optimization scheme is applied to the case of permanent magnets which have errors in the direction of field. The result shows the genetic algorithm is superior to other algorithms.

Advanced optimization of permanent magnet wigglers using a genetic algorithm

International Nuclear Information System (INIS)

Hajima, Ryoichi

1995-01-01

In permanent magnet wigglers, magnetic imperfection of each magnet piece causes field error. This field error can be reduced or compensated by sorting magnet pieces in proper order. We showed a genetic algorithm has good property for this sorting scheme. In this paper, this optimization scheme is applied to the case of permanent magnets which have errors in the direction of field. The result shows the genetic algorithm is superior to other algorithms

Electric power systems advanced forecasting techniques and optimal generation scheduling

CERN Document Server

Catalão, João P S

2012-01-01

Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

Confirming the timing of phase-based costing in oncology studies: a case example in advanced melanoma.

Science.gov (United States)

Atkins, Michael; Coutinho, Anna D; Nunna, Sasikiran; Gupte-Singh, Komal; Eaddy, Michael

2018-02-01

The utilization of healthcare services and costs among patients with cancer is often estimated by the phase of care: initial, interim, or terminal. Although their durations are often set arbitrarily, we sought to establish data-driven phases of care using joinpoint regression in an advanced melanoma population as a case example. A retrospective claims database study was conducted to assess the costs of advanced melanoma from distant metastasis diagnosis to death during January 2010-September 2014. Joinpoint regression analysis was applied to identify the best-fitting points, where statistically significant changes in the trend of average monthly costs occurred. To identify the initial phase, average monthly costs were modeled from metastasis diagnosis to death; and were modeled backward from death to metastasis diagnosis for the terminal phase. Points of monthly cost trend inflection denoted ending and starting points. The months between represented the interim phase. A total of 1,671 patients with advanced melanoma who died met the eligibility criteria. Initial phase was identified as the 5-month period starting with diagnosis of metastasis, after which there was a sharp, significant decline in monthly cost trend (monthly percent change [MPC] = -13.0%; 95% CI = -16.9% to -8.8%). Terminal phase was defined as the 5-month period before death (MPC = -14.0%; 95% CI = -17.6% to -10.2%). The claims-based algorithm may under-estimate patients due to misclassifications, and may over-estimate terminal phase costs because hospital and emergency visits were used as a death proxy. Also, recently approved therapies were not included, which may under-estimate advanced melanoma costs. In this advanced melanoma population, optimal duration of the initial and terminal phases of care was 5 months immediately after diagnosis of metastasis and before death, respectively. Joinpoint regression can be used to provide data-supported phase of cancer care durations, but

Optimization of Heat Exchangers for Intercooled Recuperated Aero Engines

Directory of Open Access Journals (Sweden)

Dimitrios Misirlis

2017-03-01

Full Text Available In the framework of the European research project LEMCOTEC, a section was devoted to the further optimization of the recuperation system of the Intercooled Recuperated Aero engine (IRA engine concept, of MTU Aero Engines AG. This concept is based on an advanced thermodynamic cycle combining both intercooling and recuperation. The present work is focused only on the recuperation process. This is carried out through a system of heat exchangers mounted inside the hot-gas exhaust nozzle, providing fuel economy and reduced pollutant emissions. The optimization of the recuperation system was performed using computational fluid dynamics (CFD computations, experimental measurements and thermodynamic cycle analysis for a wide range of engine operating conditions. A customized numerical tool was developed based on an advanced porosity model approach. The heat exchangers were modeled as porous media of predefined heat transfer and pressure loss behaviour and could also incorporate major and critical heat exchanger design decisions in the CFD computations. The optimization resulted in two completely new innovative heat exchanger concepts, named as CORN (COnical Recuperative Nozzle and STARTREC (STraight AnnulaR Thermal RECuperator, which provided significant benefits in terms of fuel consumption, pollutants emission and weight reduction compared to more conventional heat exchanger designs, thus proving that further optimization potential for this technology exists.

Optimization problem in quantum cryptography

International Nuclear Information System (INIS)

Brandt, Howard E

2003-01-01

A complete optimization was recently performed, yielding the maximum information gain by a general unitary entangling probe in the four-state protocol of quantum cryptography. A larger set of optimum probe parameters was found than was known previously from an incomplete optimization. In the present work, a detailed comparison is made between the complete and incomplete optimizations. Also, a new set of optimum probe parameters is identified for the four-state protocol

Superlattice design for optimal thermoelectric generator performance

Science.gov (United States)

Priyadarshi, Pankaj; Sharma, Abhishek; Mukherjee, Swarnadip; Muralidharan, Bhaskaran

2018-05-01

We consider the design of an optimal superlattice thermoelectric generator via the energy bandpass filter approach. Various configurations of superlattice structures are explored to obtain a bandpass transmission spectrum that approaches the ideal ‘boxcar’ form, which is now well known to manifest the largest efficiency at a given output power in the ballistic limit. Using the coherent non-equilibrium Green’s function formalism coupled self-consistently with the Poisson’s equation, we identify such an ideal structure and also demonstrate that it is almost immune to the deleterious effect of self-consistent charging and device variability. Analyzing various superlattice designs, we conclude that superlattice with a Gaussian distribution of the barrier thickness offers the best thermoelectric efficiency at maximum power. It is observed that the best operating regime of this device design provides a maximum power in the range of 0.32–0.46 MW/m 2 at efficiencies between 54%–43% of Carnot efficiency. We also analyze our device designs with the conventional figure of merit approach to counter support the results so obtained. We note a high zT el   =  6 value in the case of Gaussian distribution of the barrier thickness. With the existing advanced thin-film growth technology, the suggested superlattice structures can be achieved, and such optimized thermoelectric performances can be realized.

Free Energy-Based Virtual Screening and Optimization of RNase H Inhibitors of HIV-1 Reverse Transcriptase.

Science.gov (United States)

Zhang, Baofeng; D'Erasmo, Michael P; Murelli, Ryan P; Gallicchio, Emilio

2016-09-30

We report the results of a binding free energy-based virtual screening campaign of a library of 77 α-hydroxytropolone derivatives against the challenging RNase H active site of the reverse transcriptase (RT) enzyme of human immunodeficiency virus-1. Multiple protonation states, rotamer states, and binding modalities of each compound were individually evaluated. The work involved more than 300 individual absolute alchemical binding free energy parallel molecular dynamics calculations and over 1 million CPU hours on national computing clusters and a local campus computational grid. The thermodynamic and structural measures obtained in this work rationalize a series of characteristics of this system useful for guiding future synthetic and biochemical efforts. The free energy model identified key ligand-dependent entropic and conformational reorganization processes difficult to capture using standard docking and scoring approaches. Binding free energy-based optimization of the lead compounds emerging from the virtual screen has yielded four compounds with very favorable binding properties, which will be the subject of further experimental investigations. This work is one of the few reported applications of advanced-binding free energy models to large-scale virtual screening and optimization projects. It further demonstrates that, with suitable algorithms and automation, advanced-binding free energy models can have a useful role in early-stage drug-discovery programs.

Optimal Implantation Depth and Adherence to Guidelines on Permanent Pacing to Improve the Results of Transcatheter Aortic Valve Replacement With the Medtronic CoreValve System: The CoreValve Prospective, International, Post-Market ADVANCE-II Study.

Science.gov (United States)

Petronio, Anna S; Sinning, Jan-Malte; Van Mieghem, Nicolas; Zucchelli, Giulio; Nickenig, Georg; Bekeredjian, Raffi; Bosmans, Johan; Bedogni, Francesco; Branny, Marian; Stangl, Karl; Kovac, Jan; Schiltgen, Molly; Kraus, Stacia; de Jaegere, Peter

2015-05-01

The aim of the CoreValve prospective, international, post-market ADVANCE-II study was to define the rates of conduction disturbances and permanent pacemaker implantation (PPI) after transcatheter aortic valve replacement with the Medtronic CoreValve System (Minneapolis, Minnesota) using optimized implantation techniques and application of international guidelines on cardiac pacing. Conduction disturbances are a frequent complication of transcatheter aortic valve replacement. The rates of PPI in the published reports vary according to bioprosthesis type and the indications for PPI. The primary endpoint was the 30-day incidence of PPI with Class I/II indications when the Medtronic CoreValve System was implanted at an optimal depth (≤6 mm below the aortic annulus). The timing and resolution of all new-onset conduction disturbances were analyzed. A total of 194 patients were treated. The overall rate of PPI for Class I/II indications was 18.2%. An optimal depth was reached in 43.2% of patients, with a nonsignificantly lower incidence of PPI in patients with depths ≤6 mm, compared with those with deeper implants (13.3% vs. 21.1%; p = 0.14). In a paired analysis, new-onset left bundle branch block and first-degree atrioventricular block occurred in 45.4% and 39.0% of patients, respectively, and resolved spontaneously within 30 days in 43.2% and 73.9%, respectively. In patients with new PPI, the rate of intrinsic sinus rhythm increased from 25.9% at 7 days to 59.3% at 30 days (p = 0.004). Optimal Medtronic CoreValve System deployment and adherence to international guidelines on cardiac pacing are associated with a lower rate of new PPI after transcatheter aortic valve replacement, compared with results reported in previous studies. (CoreValve Advance-II Study: Prospective International Post-Market Study [ADVANCE II]; NCT01624870). Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Advanced sorting technologies for optimal wood products and woody biomass utilization

Science.gov (United States)

Xiping Wang

2012-01-01

Forest materials represent great potential for advancing our goals in the 21st century for sustainable building, energy independence, and carbon sequestration. A critical component of an improved system for producing bioproducts and bioenergr from forest materials is the ability to sort trees, stems, and logs into end-product categories that represent their highest...

Advanced tools for modeling, design and optimization of wind turbine systems

DEFF Research Database (Denmark)

Iov, F.; Hansen, A.D.; Jauch, C.

2005-01-01

As wind turbine technology and control has advanced over the last decade, this has led to a high penetration of wind turbines into the power system. Whether it be for a large wind turbine or an offshore wind farm with hundreds of MW power capacity, the electrical system has become more and more i...

COMMUNICATION: Toward closed-loop optimization of deep brain stimulation for Parkinson's disease: concepts and lessons from a computational model

Science.gov (United States)

Feng, Xiao-jiang; Greenwald, Brian; Rabitz, Herschel; Shea-Brown, Eric; Kosut, Robert

2007-06-01

Deep brain stimulation (DBS) of the subthalamic nucleus with periodic, high-frequency pulse trains is an increasingly standard therapy for advanced Parkinson's disease. Here, we propose that a closed-loop global optimization algorithm may identify novel DBS waveforms that could be more effective than their high-frequency counterparts. We use results from a computational model of the Parkinsonian basal ganglia to illustrate general issues relevant to eventual clinical or experimental tests of such an algorithm. Specifically, while the relationship between DBS characteristics and performance is highly complex, global search methods appear able to identify novel and effective waveforms with convergence rates that are acceptably fast to merit further investigation in laboratory or clinical settings.

Advancing grate-firing for greater environmental impacts and efficiency for decentralized biomass/wastes combustion

DEFF Research Database (Denmark)

Yin, Chungen; Li, Shuangshuang

2017-01-01

to well suit decentralized biomass and municipal/industrial wastes combustion. This paper discusses with concrete examples how to advance grate-firing for greater efficiency and environmental impacts, e.g., use of advanced secondary air system, flue gas recycling and optimized grate assembly, which...

Finite Element Multidisciplinary Optimization Simulation of Flight Vehicles, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The proposed effort is concerned with the development of a novel optimization scheme and computer software for the effective design of advanced aerospace vehicles....

Optimal growth when environmental quality is a research asset

DEFF Research Database (Denmark)

Groth, Christian; Ricci, Francesco

2011-01-01

We advance an original assumption whereby a good state of the environment positively affects labor productivity in R&D such that deteriorating environmental quality negatively impacts R&D. We study the implications of this assumption for the optimal solution in an R&D-based model of growth, where......, we find that it is optimal to re-allocate employment to R&D in line with productivity changes. If environmental quality recovers only partially from pollution, R&D effort optimally begins above its long-run level, then progressively declines to a minimum and eventually increases to its steady...

Synthetic biology advances for pharmaceutical production

Science.gov (United States)

Breitling, Rainer; Takano, Eriko

2015-01-01

Synthetic biology enables a new generation of microbial engineering for the biotechnological production of pharmaceuticals and other high-value chemicals. This review presents an overview of recent advances in the field, describing new computational and experimental tools for the discovery, optimization and production of bioactive molecules, and outlining progress towards the application of these tools to pharmaceutical production systems. PMID:25744872

Advancing Physics evaluated

Science.gov (United States)

Ogborn, Jon

2003-07-01

The first phase of an evaluation of the new AS/A-level course Advancing Physics, sponsored by the Institute of Physics, is now complete. It shows that the course has achieved very high satisfaction ratings from teachers of the course, and that a majority of these teachers see it as achieving its main aims. The first phase of the evaluation was designed to pinpoint aspects of Advancing Physics that offer scope for improvement. Two such aspects have been identified: course planning and use of the CD-ROM material, and arrangements for coursework in the examination.

Optimization of up-flow anaerobic sludge blanket reactor for ...

African Journals Online (AJOL)

Optimization of up-flow anaerobic sludge blanket reactor for treatment of composite ... AFRICAN JOURNALS ONLINE (AJOL) · Journals · Advanced Search ... Granules grown in the bottom part of UASB reactor were more compact and tense ...

Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications.

Science.gov (United States)

Stone, David B; Tamburro, Gabriella; Fiedler, Patrique; Haueisen, Jens; Comani, Silvia

2018-01-01

Data contamination due to physiological artifacts such as those generated by eyeblinks, eye movements, and muscle activity continues to be a central concern in the acquisition and analysis of electroencephalographic (EEG) data. This issue is further compounded in EEG sports science applications where the presence of artifacts is notoriously difficult to control because behaviors that generate these interferences are often the behaviors under investigation. Therefore, there is a need to develop effective and efficient methods to identify physiological artifacts in EEG recordings during sports applications so that they can be isolated from cerebral activity related to the activities of interest. We have developed an EEG artifact detection model, the Fingerprint Method, which identifies different spatial, temporal, spectral, and statistical features indicative of physiological artifacts and uses these features to automatically classify artifactual independent components in EEG based on a machine leaning approach. Here, we optimized our method using artifact-rich training data and a procedure to determine which features were best suited to identify eyeblinks, eye movements, and muscle artifacts. We then applied our model to an experimental dataset collected during endurance cycling. Results reveal that unique sets of features are suitable for the detection of distinct types of artifacts and that the Optimized Fingerprint Method was able to correctly identify over 90% of the artifactual components with physiological origin present in the experimental data. These results represent a significant advancement in the search for effective means to address artifact contamination in EEG sports science applications.

International Conference on Advances in Applied Mathematics

CERN Document Server

Hammami, Mohamed; Masmoudi, Afif

2015-01-01

This contributed volume presents some recent theoretical advances in mathematics and its applications in various areas of science and technology.   Written by internationally recognized scientists and researchers, the chapters in this book are based on talks given at the International Conference on Advances in Applied Mathematics (ICAAM), which took place December 16-19, 2013, in Hammamet, Tunisia.  Topics discussed at the conference included spectral theory, operator theory, optimization, numerical analysis, ordinary and partial differential equations, dynamical systems, control theory, probability, and statistics.  These proceedings aim to foster and develop further growth in all areas of applied mathematics.

International Conference on Advanced Computing for Innovation

CERN Document Server

Angelova, Galia; Agre, Gennady

2016-01-01

This volume is a selected collection of papers presented and discussed at the International Conference “Advanced Computing for Innovation (AComIn 2015)”. The Conference was held at 10th -11th of November, 2015 in Sofia, Bulgaria and was aimed at providing a forum for international scientific exchange between Central/Eastern Europe and the rest of the world on several fundamental topics of computational intelligence. The papers report innovative approaches and solutions in hot topics of computational intelligence – advanced computing, language and semantic technologies, signal and image processing, as well as optimization and intelligent control.

Compound light ion fuel cycles: An approach to optimization

International Nuclear Information System (INIS)

Kernbichler, W.; Heindler, M.

1985-01-01

Together with the relatively high complexity and the low power density anticipated for fusion reactors have produced different attitude towards the long term perspective of fusion as a commercial energy source. The favourite pathway is to trust in optimization aiming at low tritium inventory, the availability of low-activation structure materials, the increase of redundancy, etc. In contrast, a respectable minority suggests turning away from d-t fusion or to envisage fusion as powerful neutron rather than energy source (fusion as fissile fuel or synfuel factory). We here intend to investigate the potentiality of fusion based on alternatives to d-t fuel. Such so called ''advanced fuels'' require higher burn temperatures and advanced reactor concepts (high-beta confinement schemes to compensate for their inherently lower reactivities. The experience that has been gained in fusion oriented plasma research admittedly justifies optimism for advanced fuels to a still lesser extent than for d-t. It can however be argued that it may pay off to choose a developmental direction with higher risk for failure but aiming at a more desirable end product. In order to explore this eventual desirability of advanced fuel fusion, we assume, as has been done in the case of d-t, that the first category of problems can be successfully handled. Our goal is thus to examine the potentiality of advanced fuels with respect to the second category of problems which largely determines the attractivity of utilization in fusion reactors

Optimization and Control of Electric Power Systems

Energy Technology Data Exchange (ETDEWEB)

Lesieutre, Bernard C. [Univ. of Wisconsin, Madison, WI (United States); Molzahn, Daniel K. [Univ. of Wisconsin, Madison, WI (United States)

2014-10-17

The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.

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.

Aerodynamic shape optimization using preconditioned conjugate gradient methods

Science.gov (United States)

Burgreen, Greg W.; Baysal, Oktay

1993-01-01

In an effort to further improve upon the latest advancements made in aerodynamic shape optimization procedures, a systematic study is performed to examine several current solution methodologies as applied to various aspects of the optimization procedure. It is demonstrated that preconditioned conjugate gradient-like methodologies dramatically decrease the computational efforts required for such procedures. The design problem investigated is the shape optimization of the upper and lower surfaces of an initially symmetric (NACA-012) airfoil in inviscid transonic flow and at zero degree angle-of-attack. The complete surface shape is represented using a Bezier-Bernstein polynomial. The present optimization method then automatically obtains supercritical airfoil shapes over a variety of freestream Mach numbers. Furthermore, the best optimization strategy examined resulted in a factor of 8 decrease in computational time as well as a factor of 4 decrease in memory over the most efficient strategies in current use.

TH-AB-BRB-04: Quality Assurance for Advanced Digital Linac Implementations

International Nuclear Information System (INIS)

Yu, V.

2016-01-01

Current state-of-the art digital C-arm medical linear accelerators are capable of delivering radiation treatments with high level of automation, which affords coordinated motions of gantry, couch, and multileaf collimator (MLC) with dose rate modulations. The new machine capacity has shown the potential to bring substantially improved radiation dosimetry and/or delivery efficiency to many challenging diseases. Combining an integrated beam orientation optimization algorithm with automated machine navigation, markedly improved dose conformity has been achieved using 4ρ therapy. Trajectory modulated radiation therapy (TMAT) can be used to deliver highly conformal dose to partial breast or to carve complex dose distribution for therapy involving extended volumes such as total marrow and total lymph node treatment. Dynamic electron arc radiotherapy (DEAR) not only overcomes the deficiencies of conventional electron therapy in dose conformity and homogeneity but also achieves so without patient-specific shields. The combination of MLC and couch tracking provides improved motion management of thoracic and abdominal tumors. A substantial body of work has been done in these technological advances for clinical translation. The proposed symposium will provide a timely review of these exciting opportunities. Learning Objectives: Recognize the potential of using digitally controlled linacs for clinically significant improvements in delivered dose distributions for various treatment sites. Identify existing approaches to treatment planning, optimization and delivery for treatment techniques utilizing the advanced functions of digital linacs and venues for further development and improvement. Understand methods for testing and validating delivery system performance. Identify tools available on current delivery systems for implementation and control for such treatments. Obtain the update in clinical applications, trials and regulatory approval. K. Sheng, NIH U19AI067769, NIH R43

TH-AB-BRB-04: Quality Assurance for Advanced Digital Linac Implementations

Energy Technology Data Exchange (ETDEWEB)

Yu, V. [UCLA School of Medicine (United States)

2016-06-15

Current state-of-the art digital C-arm medical linear accelerators are capable of delivering radiation treatments with high level of automation, which affords coordinated motions of gantry, couch, and multileaf collimator (MLC) with dose rate modulations. The new machine capacity has shown the potential to bring substantially improved radiation dosimetry and/or delivery efficiency to many challenging diseases. Combining an integrated beam orientation optimization algorithm with automated machine navigation, markedly improved dose conformity has been achieved using 4ρ therapy. Trajectory modulated radiation therapy (TMAT) can be used to deliver highly conformal dose to partial breast or to carve complex dose distribution for therapy involving extended volumes such as total marrow and total lymph node treatment. Dynamic electron arc radiotherapy (DEAR) not only overcomes the deficiencies of conventional electron therapy in dose conformity and homogeneity but also achieves so without patient-specific shields. The combination of MLC and couch tracking provides improved motion management of thoracic and abdominal tumors. A substantial body of work has been done in these technological advances for clinical translation. The proposed symposium will provide a timely review of these exciting opportunities. Learning Objectives: Recognize the potential of using digitally controlled linacs for clinically significant improvements in delivered dose distributions for various treatment sites. Identify existing approaches to treatment planning, optimization and delivery for treatment techniques utilizing the advanced functions of digital linacs and venues for further development and improvement. Understand methods for testing and validating delivery system performance. Identify tools available on current delivery systems for implementation and control for such treatments. Obtain the update in clinical applications, trials and regulatory approval. K. Sheng, NIH U19AI067769, NIH R43

Identifying subgroup markers in heterogeneous populations

NARCIS (Netherlands)

de Ronde, Jorma J.; Rigaill, Guillem; Rottenberg, Sven; Rodenhuis, Sjoerd; Wessels, Lodewyk F. A.

2013-01-01

Traditional methods that aim to identify biomarkers that distinguish between two groups, like Significance Analysis of Microarrays or the t-test, perform optimally when such biomarkers show homogeneous behavior within each group and differential behavior between the groups. However, in many

A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems

International Nuclear Information System (INIS)

Huang, Chia-Ling

2015-01-01

This paper proposes a new swarm intelligence method known as the Particle-based Simplified Swarm Optimization (PSSO) algorithm while undertaking a modification of the Updating Mechanism (UM), called N-UM and R-UM, and simultaneously applying an Orthogonal Array Test (OA) to solve reliability–redundancy allocation problems (RRAPs) successfully. One difficulty of RRAP is the need to maximize system reliability in cases where the number of redundant components and the reliability of corresponding components in each subsystem are simultaneously decided with nonlinear constraints. In this paper, four RRAP benchmarks are used to display the applicability of the proposed PSSO that advances the strengths of both PSO and SSO to enable optimizing the RRAP that belongs to mixed-integer nonlinear programming. When the computational results are compared with those of previously developed algorithms in existing literature, the findings indicate that the proposed PSSO is highly competitive and performs well. - Highlights: • This paper proposes a particle-based simplified swarm optimization algorithm (PSSO) to optimize RRAP. • Furthermore, the UM and an OA are adapted to advance in optimizing RRAP. • Four systems are introduced and the results demonstrate the PSSO performs particularly well

Efficacy of Icotinib for Advanced Non-small Cell Lung Cancer Patients with EGFR Status Identified

Directory of Open Access Journals (Sweden)

Yiping ZHANG

2013-03-01

Full Text Available Background and objective As the first epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI in China, icotinib shows promising anticancer activity in vitro and vivo. The phase III clinical study (ICOGEN showed that icotinib has a good efficacy and tolerability in Chinese patients with advanced non-small cell lung cancer (NSCLC compared with gefitinib. This retrospective study aims to evaluate the efficacy and tolerability of icotinib monotherapy for advanced NSCLC patients with EGFR mutation and wild-type patients in our hospital. Methods Patients with advanced NSCLC who were treated with icotinib in Zhejiang Cancer Hospital were retrospectively analyzed from August, 2011 to August, 2012. Survival was estimated using Kaplan-Meier analysis and Log-rank tests. Results The clinical data of 49 patients (13 with wild-type and 36 with EGFR mutation with NSCLC were enrolled in the current study. The patients’ overall objective response rate (ORR was 58.3% and the disease control rate (DCR in 36 EGFR mutation patients was 88.9%. The ORR was 7.7% and DCR was 53.8% in the wild-type patients. Median progression-free survival (PFS with icotinib treatment in EGFR mutation patients was 9.5 months and 2.2 months in wild-type patients (P<0.001. Nineteen patients with EGFR mutation received icotinib as first-line and 17 in further-line treatment. The PFS was 9.5 months in the first-line and 8.5 months for second-line or further-line patients (P=0.41. Median overall survival (OS in EGFR mutation patients was not reached, but was 12.6 months in wild-type patients. Most of the drug-related adverse events were mild (grade I or II and reversible with no grade IV toxicity. Conclusion Icotinib monotherapy showed significant antitumor activity in advanced NSCLC EGFR mutation patients. The toxicity was well tolerated and acceptable.

[Efficacy of icotinib for advanced non-small cell lung cancer patients with EGFR status identified].

Science.gov (United States)

Song, Zhengbo; Yu, Xinmin; Cai, Jufen; Shao, Lan; Lin, Baochai; He, Chunxiao; Zhang, Beibei; Zhang, Yiping

2013-03-01

As the first epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) in China, icotinib shows promising anticancer activity in vitro and vivo. The phase III clinical study (ICOGEN) showed that icotinib has a good efficacy and tolerability in Chinese patients with advanced non-small cell lung cancer (NSCLC) compared with gefitinib. This retrospective study aims to evaluate the efficacy and tolerability of icotinib monotherapy for advanced NSCLC patients with EGFR mutation and wild-type patients in our hospital. Patients with advanced NSCLC who were treated with icotinib in Zhejiang Cancer Hospital were retrospectively analyzed from August, 2011 to August, 2012. Survival was estimated using Kaplan-Meier analysis and Log-rank tests. The clinical data of 49 patients (13 with wild-type and 36 with EGFR mutation) with NSCLC were enrolled in the current study. The patients' overall objective response rate (ORR) was 58.3% and the disease control rate (DCR) in 36 EGFR mutation patients was 88.9%. The ORR was 7.7% and DCR was 53.8% in the wild-type patients. Median progression-free survival (PFS) with icotinib treatment in EGFR mutation patients was 9.5 months and 2.2 months in wild-type patients (Picotinib as first-line and 17 in further-line treatment. The PFS was 9.5 months in the first-line and 8.5 months for second-line or further-line patients (P=0.41). Median overall survival (OS) in EGFR mutation patients was not reached, but was 12.6 months in wild-type patients. Most of the drug-related adverse events were mild (grade I or II) and reversible with no grade IV toxicity. Icotinib monotherapy showed significant antitumor activity in advanced NSCLC EGFR mutation patients. The toxicity was well tolerated and acceptable.

Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO

Directory of Open Access Journals (Sweden)

Adel Taieb

2017-01-01

Full Text Available This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO Fuzzy Optimal Model Predictive Control (FOMPC using the Adaptive Particle Swarm Optimization (APSO algorithm. The aim of this proposed control, called FOMPC-APSO, is to develop an efficient algorithm that is able to have good performance by guaranteeing a minimal control. This is done by determining the optimal weights of the objective function. Our method is considered an optimization problem based on the APSO algorithm. The MIMO system to be controlled is modeled by a Takagi-Sugeno (TS fuzzy system whose parameters are identified using weighted recursive least squares method. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, Continuous Stirred Tank Reactor (CSTR and Tank system, where the proposed approach provides better performances compared with other methods.

Delineating advanced practice nursing in New Zealand: a national survey.

Science.gov (United States)

Carryer, J; Wilkinson, J; Towers, A; Gardner, G

2018-03-01

A variety of advanced practice nursing roles and titles have proliferated in response to the changing demands of a population characterized by increasing age and chronic illness. Whilst similarly identified as advanced practice roles, they do not share a common practice profile, educational requirements or legislative direction. The lack of clarity limits comparative research that can inform policy and health service planning. To identify advanced practice roles within nursing titles employed in New Zealand and practice differences between advanced practice and other roles. Replicating recent Australian research, 3255 registered nurses/nurse practitioners in New Zealand completed the amended Advanced Practice Delineation survey tool. The mean domain scores of the predominant advanced practice position were compared with those of other positions. Differences between groups were explored using one-way ANOVA and post hoc between group comparisons. Four nursing position bands were identified: nurse practitioner, clinical nurse specialist, domain-specific and registered nurse. Significant differences between the bands were found on many domain scores. The nurse practitioner and clinical nurse specialist bands had the most similar practice profiles, nurse practitioners being more involved in direct care and professional leadership. Similar to the position of clinical nurse consultant in Australia, those practicing as clinical nurse specialists were deemed to reflect the threshold for advanced practice nursing. The results identified different practice patterns for the identified bands and distinguish the advanced practice nursing roles. By replicating the Australian study of Gardener et al. (2016), this NZ paper extends the international data available to support more evidence-based nursing workforce planning and policy development. © 2017 International Council of Nurses.

Microbial engineering for the production of advanced biofuels.

Science.gov (United States)

Peralta-Yahya, Pamela P; Zhang, Fuzhong; del Cardayre, Stephen B; Keasling, Jay D

2012-08-16

Advanced biofuels produced by microorganisms have similar properties to petroleum-based fuels, and can 'drop in' to the existing transportation infrastructure. However, producing these biofuels in yields high enough to be useful requires the engineering of the microorganism's metabolism. Such engineering is not based on just one specific feedstock or host organism. Data-driven and synthetic-biology approaches can be used to optimize both the host and pathways to maximize fuel production. Despite some success, challenges still need to be met to move advanced biofuels towards commercialization, and to compete with more conventional fuels.

Advances in independent component analysis and learning machines

CERN Document Server

Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

2015-01-01

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t

Optimizing Cardiac Out-Put to Increase Cerebral Penumbral Perfusion in Large Middle Cerebral Artery Ischemic Lesion—OPTIMAL Study

Directory of Open Access Journals (Sweden)

Hannah Fuhrer

2017-08-01

Full Text Available IntroductionIn unsuccessful vessel recanalization, clinical outcome of acute stroke patients depends on early improvement of penumbral perfusion. So far, mean arterial blood pressure (MAP is the target hemodynamic parameter. However, the correlations of MAP to cardiac output (CO and cerebral perfusion are volume state dependent. In severe subarachnoid hemorrhage, optimizing CO leads to a reduction of delayed ischemic neurological deficits and improvement of clinical outcome. This study aims to investigate the effect of standard versus advanced cardiac monitoring with optimization of CO on the clinical outcome in patients with large ischemic stroke.Methods and analysisThe OPTIMAL study is a prospective, multicenter, open, into two arms (1:1 randomized, controlled trial. Sample size estimate: sample sizes of 150 for each treatment group (300 in total ensure an 80% power to detect a difference of 16% of a dichotomized level of functional clinical outcome at 3 months at a significance level of 0.05. Study outcomes: the primary endpoint is the functional outcome at 3 months. The secondary endpoints include functional outcome at 6 months follow-up, and complications related to hemodynamic monitoring and therapies.DiscussionThe results of this trial will provide data on the safety and efficacy of advanced hemodynamic monitoring on clinical outcome.Ethics and disseminationThe trial was approved by the leading ethics committee of Freiburg University, Germany (438/14, 2015 and the local ethics committees of the participating centers. The study is performed in accordance with the Declaration of Helsinki and the guidelines of Good Clinical Practice. It is registered in the German Clinical Trial register (DRKS; DRKS00007805. Dissemination will include submission to peer-reviewed professional journals and presentation at congresses. Hemodynamic monitoring may be altered in a specific stroke patient cohort if the study shows that advanced monitoring is

INTEGRATED PLASMA CONTROL FOR ADVANCED TOKAMAKS

International Nuclear Information System (INIS)

HUMPHREYS, D.A.; FERRON, J.R.; JOHNSON, R.D; LEUER, J.A.; PENAFLOR, B.G.; WALKER, M.L.; WELANDER, A.S.; KHAYRUTDINOV, R.R; DOKOUKA, V.; EDGELL, D.H.; FRANSSON, C.M.

2004-03-01

OAK-B135 Advanced tokamaks (AT) are distinguished from conventional tokamaks by their high degree of shaping, achievement of profiles optimized for high confinement and stability characteristics, and active stabilization of MHD instabilities to attain high values of normalized beta and confinement. These high performance fusion devices thus require accurate regulation of the plasma boundary, internal profiles, pumping, fueling, and heating, as well as simultaneous and well-coordinated MHD control action to stabilize such instabilities as tearing modes and resistive wall modes. Satisfying the simultaneous demands on control accuracy, reliability, and performance for all of these subsystems requires a high degree of integration in both design and operation of the plasma control system in an advanced tokamak. The present work describes the approach, benefits, and progress made in integrated plasma control with application examples drawn from the DIII-D tokamak. The approach includes construction of plasma and system response models, validation of models against operating experiments, design of integrated controllers which operate in concert with one another as well as with supervisory modules, simulation of control action against off-line and actual machine control platforms, and iteration of the design-test loop to optimize performance

Identifying Knowledge and Communication

Directory of Open Access Journals (Sweden)

Eduardo Coutinho Lourenço de Lima

2006-12-01

Full Text Available In this paper, I discuss how the principle of identifying knowledge which Strawson advances in ‘Singular Terms and Predication’ (1961, and in ‘Identifying Reference and Truth-Values’ (1964 turns out to constrain communication. The principle states that a speaker’s use of a referring expression should invoke identifying knowledge on the part of the hearer, if the hearer is to understand what the speaker is saying, and also that, in so referring, speakers are attentive to hearers’ epistemic states. In contrasting it with Russell’s Principle (Evans 1982, as well as with the principle of identifying descriptions (Donnellan 1970, I try to show that the principle of identifying knowledge, ultimately a condition for understanding, makes sense only in a situation of conversation. This allows me to conclude that the cooperative feature of communication (Grice 1975 and reference (Clark andWilkes-Gibbs 1986 holds also at the understanding level. Finally, I discuss where Strawson’s views seem to be unsatisfactory, and suggest how they might be improved.

Low-Level Space Optimization of an AES Implementation for a Bit-Serial Fully Pipelined Architecture

Science.gov (United States)

Weber, Raphael; Rettberg, Achim

A previously developed AES (Advanced Encryption Standard) implementation is optimized and described in this paper. The special architecture for which this implementation is targeted comprises synchronous and systematic bit-serial processing without a central controlling instance. In order to shrink the design in terms of logic utilization we deeply analyzed the architecture and the AES implementation to identify the most costly logic elements. We propose to merge certain parts of the logic to achieve better area efficiency. The approach was integrated into an existing synthesis tool which we used to produce synthesizable VHDL code. For testing purposes, we simulated the generated VHDL code and ran tests on an FPGA board.

Dynamic statistical optimization of GNSS radio occultation bending angles: advanced algorithm and performance analysis

Science.gov (United States)

Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.

2015-08-01

We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.

Teaching learning based optimization algorithm and its engineering applications

CERN Document Server

Rao, R Venkata

2016-01-01

Describing a new optimization algorithm, the “Teaching-Learning-Based Optimization (TLBO),” in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners’ results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.

OpenMDAO: Framework for Flexible Multidisciplinary Design, Analysis and Optimization Methods

Science.gov (United States)

Heath, Christopher M.; Gray, Justin S.

2012-01-01

The OpenMDAO project is underway at NASA to develop a framework which simplifies the implementation of state-of-the-art tools and methods for multidisciplinary design, analysis and optimization. Foremost, OpenMDAO has been designed to handle variable problem formulations, encourage reconfigurability, and promote model reuse. This work demonstrates the concept of iteration hierarchies in OpenMDAO to achieve a flexible environment for supporting advanced optimization methods which include adaptive sampling and surrogate modeling techniques. In this effort, two efficient global optimization methods were applied to solve a constrained, single-objective and constrained, multiobjective version of a joint aircraft/engine sizing problem. The aircraft model, NASA's nextgeneration advanced single-aisle civil transport, is being studied as part of the Subsonic Fixed Wing project to help meet simultaneous program goals for reduced fuel burn, emissions, and noise. This analysis serves as a realistic test problem to demonstrate the flexibility and reconfigurability offered by OpenMDAO.

Optimization of Antivirus Software

OpenAIRE

Catalin BOJA; Adrian VISOIU

2007-01-01

The paper describes the main techniques used in development of computer antivirus software applications. For this particular category of software, are identified and defined optimum criteria that helps determine which solution is better and what are the objectives of the optimization process. From the general viewpoint of software optimization are presented methods and techniques that are applied at code development level. Regarding the particularities of antivirus software, the paper analyze...

Advanced Education and Technology Business Plan, 2008-11

Science.gov (United States)

Alberta Advanced Education and Technology, 2008

2008-01-01

The Ministry of Advanced Education and Technology's 2008-11 business plan identifies how it plans to work over the next three years to enhance advanced learning opportunities and innovation for all Albertans. Alberta's advanced learning system is composed of public board-governed institutions, the apprenticeship and industry training system,…

Improving source discrimination performance by using an optimized acoustic array and adaptive high-resolution CLEAN-SC beamforming

NARCIS (Netherlands)

Luesutthiviboon, S.; Malgoezar, A.M.N.; Snellen, M.; Sijtsma, P.; Simons, D.G.

2018-01-01

Beamforming performance can be improved in two ways: optimizing the location of microphones on the acoustic array and applying advanced beamforming algorithms. In this study, the effects of the two approaches are studied. An optimization method is developed to optimize the location of microphones

Safe Exploration for Identifying Linear Systems via Robust Optimization

OpenAIRE

Lu, Tyler; Zinkevich, Martin; Boutilier, Craig; Roy, Binz; Schuurmans, Dale

2017-01-01

Safely exploring an unknown dynamical system is critical to the deployment of reinforcement learning (RL) in physical systems where failures may have catastrophic consequences. In scenarios where one knows little about the dynamics, diverse transition data covering relevant regions of state-action space is needed to apply either model-based or model-free RL. Motivated by the cooling of Google's data centers, we study how one can safely identify the parameters of a system model with a desired ...

Economic benefits of advanced materials in nuclear power systems

International Nuclear Information System (INIS)

Busby, J.T.

2009-01-01

A key obstacle to the commercial deployment of advanced fast reactors is the capital cost. There is a perception of higher capital cost for fast reactor systems than advanced light water reactors. However, cost estimates come with a large uncertainty since far fewer fast reactors have been built than light water reactor facilities. Furthermore, the large variability of industrial cost estimates complicates accurate comparisons. Reductions in capital cost can result from design simplifications, new technologies that allow reduced capital costs, and simulation techniques that help optimize system design. It is plausible that improved materials will provide opportunities for both simplified design and reduced capital cost. Advanced materials may also allow improved safety and longer component lifetimes. This work examines the potential impact of advanced materials on the capital investment cost of fast nuclear reactors.

Optimization of advanced liquid natural gas-fuelled machineries for a high-speed ferry

DEFF Research Database (Denmark)

Tveitaskog, Kari Anne; Haglind, Fredrik

-based optimization routine are used. The top cycle is modeled as the aero-derivative gas turbine LM2500, while the following five options for bottoming cycles are modeled: ∙ Single pressure steam cycle ∙ Dual-pressure steam cycle ∙ ORC using Toluene as the working fluid with an intermediate oil loop ∙ ABC with inter......This report is aimed at designing and optimizing combined cycles in order to define the most suitable machinery system for the future high-speed Incat ferry operated by Mols-Linien. For this purpose, an in-house numerical simulation tool called DNA (Dynamic Network Analysis) and a genetic algorithm...

Research on loading pattern optimization for VVER reactor

International Nuclear Information System (INIS)

Tran Viet Phu; Nguyen Thi Mai Huong; Nguyen Huu Tiep; Ta Duy Long; Tran Vinh Thanh; Tran Hoai Nam

2017-01-01

A study on fuel loading pattern optimization of a VVER reactor was performed. In this study, a core physics simulator was developed based on a multi-group diffusion theory for the use in the problem of fuel loading optimization of VVER reactors. The core simulator could handle the triangular meshes of the core and the computational speed is fast. Verification of the core simulator was confirmed against a benchmark problem of a VVER-1000 reactor. Several optimization methods such as DS, SA, TS and a combination of them were investigated and implemented in coupling with the core simulator. Calculations was performed for optimizing the fuel loading pattern of the core using these methods based on a benchmark core model in comparison with the reference core. Comparison among these methods have shown that a combination of SA+TS is the most effective for the problem of fuel loading pattern optimization. Advanced methods are being researched continuously. (author)

Management of patients with advanced prostate cancer: recommendations of the St Gallen Advanced Prostate Cancer Consensus Conference (APCCC) 2015

NARCIS (Netherlands)

Gillessen, S.; Omlin, A.; Attard, G.; Bono, J.S. de; Efstathiou, E.; Fizazi, K.; Halabi, S.; Nelson, P.S.; Sartor, O.; Smith, M.R.; Soule, H.R.; Akaza, H.; Beer, T.M.; Beltran, H.; Chinnaiyan, A.M.; Daugaard, G.; Davis, I.D.; Santis, M. de; Drake, C.G.; Eeles, R.A.; Fanti, S.; Gleave, M.E.; Heidenreich, A.; Hussain, M.; James, N.D.; Lecouvet, F.E.; Logothetis, C.J.; Mastris, K.; Nilsson, S.; Oh, W.K.; Olmos, D.; Padhani, A.R.; Parker, C.; Rubin, M.A.; Schalken, J.A.; Scher, H.I.; Sella, A.; Shore, N.D.; Small, E.J.; Sternberg, C.N.; Suzuki, H; Sweeney, C.J.; Tannock, I.F.; Tombal, B.

2015-01-01

The first St Gallen Advanced Prostate Cancer Consensus Conference (APCCC) Expert Panel identified and reviewed the available evidence for the ten most important areas of controversy in advanced prostate cancer (APC) management. The successful registration of several drugs for castration-resistant

Optimized conditions for chelation of yttrium-90-DOTA immunoconjugates.

Science.gov (United States)

Kukis, D L; DeNardo, S J; DeNardo, G L; O'Donnell, R T; Meares, C F

1998-12-01

Radioimmunotherapy (RIT) with 90Y-labeled immunoconjugates has shown promise in clinical trials. The macrocyclic chelating agent 1,4,7,10-tetraazacyclododecane-N,N',N",N"'-tetraacetic acid (DOTA) binds 90Y with extraordinary stability, minimizing the toxicity of 90Y-DOTA immunoconjugates arising from loss of 90Y to bone. However, reported 90Y-DOTA immunoconjugate product yields have been typically only BAD) was conjugated to the monoclonal antibody Lym-1 via 2-iminothiolane (2IT). The immunoconjugate product, 2IT-BAD-Lym-1, was labeled in excess yttrium in various buffers over a range of concentrations and pH. Kinetic studies were performed in selected buffers to estimate radiolabeling reaction times under prospective radiopharmacy labeling conditions. The effect of temperature on reaction kinetics was examined. Optimal radiolabeling conditions were identified and used in eight radiolabeling experiments with 2IT-BAD-Lym-1 and a second immunoconjugate, DOTA-peptide-chimeric L6, with 248-492 MBq (6.7-13.3 mCi) of 90Y. Ammonium acetate buffer (0.5 M) was associated with the highest uptake of yttrium. On the basis of kinetic data, the time required to chelate 94% of 90Y (four half-times) under prospective radiopharmacy labeling conditions in 0.5 M ammonium acetate was 17-148 min at pH 6.5, but it was only 1-10 min at pH 7.5. Raising the reaction temperature from 25 degrees C to 37 degrees C markedly increased the chelation rate. Optimal radiolabeling conditions were identified as: 30-min reaction time, 0.5 M ammonium acetate buffer, pH 7-7.5 and 37 degrees C. In eight labeling experiments under optimal conditions, a mean product yield (+/- s.d.) of 91%+/-8% was achieved, comparable to iodination yields. The specific activity of final products was 74-130 MBq (2.0-3.5 mCi) of 90Y per mg of monoclonal antibody. The immunoreactivity of 90Y-labeled immunoconjugates was 100%+/-11%. The optimization of 90Y-DOTA chelation conditions represents an important advance in 90Y RIT

Auto-Clustering using Particle Swarm Optimization and Bacterial Foraging

DEFF Research Database (Denmark)

Rutkowski Olesen, Jakob; Cordero, Jorge; Zeng, Yifeng

2009-01-01

by using simplistic collaboration. Inspired by the advances in clustering using particle swarm optimization, we suggest further improvements. Moreover, we gathered standard benchmark datasets and compared our new approach against the standard K-means algorithm, obtaining promising results. Our hybrid...

A demonstration of magnetic field optimization in LHD

Energy Technology Data Exchange (ETDEWEB)

Murakami, S.; Yamada, H. [National Inst. for Fusion Science, Toki, Gifu (Japan); Wakasa, A. [Hokkaido Univ., Graduate School of Engineering, Sapporo, Hokkaido (JP)] [and others

2002-11-01

An optimized configuration of the neoclassical transport and the energetic particle confinement to a level typical of so-called 'advanced stellarators' is found by shifting the magnetic axis position in LHD. Electron heat transport and NBI beam ion distribution are investigated in low-collisionality LHD plasma in order to study the magnetic field optimization effect on the thermal plasma transport and the energetic particle confinement. A higher electron temperature is obtained in the optimized configuration, and the transport analysis suggests a considerable effect of neoclassical transport on the electron heat transport assuming the ion-root level of radial electric field. Also a higher energetic ion distribution of NBI beam ions is observed showing the improvement of the energetic particle confinement. These obtained results support a future reactor design by magnetic field optimization in a non-axisymmetric configuration. (author)

A demonstration of magnetic field optimization in LHD

Energy Technology Data Exchange (ETDEWEB)

Murakami, S.; Yamada, H. [National Inst. for Fusion Science, Toki, Gifu (Japan); Wakasa, A. [Hokkaido Univ., Graduate School of Engineering, Sapporo, Hokkaido (JP)] [and others

2002-10-01

An optimized configuration of the neoclassical transport and the energetic particle confinement to a level typical of so-called 'advanced stellarators' is found by shifting the magnetic axis position in LHD. Electron heat transport and NBI beam ion distribution are investigated in low-collisionality LHD plasma in order to study the magnetic field optimization effect on the thermal plasma transport and the energetic particle confinement. A higher electron temperature is obtained in the optimized configuration, and the transport analysis suggests a considerable effect of neoclassical transport on the electron heat transport assuming the ion-root level of radial electric field. Also a higher energetic ion distribution of NBI beam ions is observed showing the improvement of the energetic particle confinement. These obtained results support a future reactor design by magnetic field optimization in a non-axisymmetric configuration. (author)

Cooperative research for human factors review of advanced control rooms

Energy Technology Data Exchange (ETDEWEB)

Lee, Jung Woon; Park, Jae Chang; Lee, Yong Hee; Oh, In Seok; Lee, Hyun Chul

2000-12-01

This project has been performed as cooperative research between KAERI and USNRC. Human factors issues related to soft controls, which is one of key features of advanced HSI, are identified in this project. The issues are analyzed for the evaluation approaches in either experimental or analytical ways. Also, issues requiring additional researches for the evaluation of advanced HSI are identified in the areas of advanced information systems design, computer-based procedure systems, soft controls, human systems interface and plant modernization process, and maintainability of digital systems. The issues are analyzed to discriminate the urgency of researches on it to high, medium, and low levels in consideration of advanced HSI development status in Korea, and some of the issues that can be handled by experimental researches are identified. Additionally, an experimental study is performed to compare operator's performance on human error detection in advanced control rooms vs. in conventional control rooms. It is found that advanced control rooms have several design characteristics hindering operator's error detection performance compared to conventional control rooms.

Cooperative research for human factors review of advanced control rooms

International Nuclear Information System (INIS)

Lee, Jung Woon; Park, Jae Chang; Lee, Yong Hee; Oh, In Seok; Lee, Hyun Chul

2000-12-01

This project has been performed as cooperative research between KAERI and USNRC. Human factors issues related to soft controls, which is one of key features of advanced HSI, are identified in this project. The issues are analyzed for the evaluation approaches in either experimental or analytical ways. Also, issues requiring additional researches for the evaluation of advanced HSI are identified in the areas of advanced information systems design, computer-based procedure systems, soft controls, human systems interface and plant modernization process, and maintainability of digital systems. The issues are analyzed to discriminate the urgency of researches on it to high, medium, and low levels in consideration of advanced HSI development status in Korea, and some of the issues that can be handled by experimental researches are identified. Additionally, an experimental study is performed to compare operator's performance on human error detection in advanced control rooms vs. in conventional control rooms. It is found that advanced control rooms have several design characteristics hindering operator's error detection performance compared to conventional control rooms

Advanced hybrid and electric vehicles system optimization and vehicle integration

CERN Document Server

2016-01-01

This contributed volume contains the results of the research program “Agreement for Hybrid and Electric Vehicles”, funded by the International Energy Agency. The topical focus lies on technology options for the system optimization of hybrid and electric vehicle components and drive train configurations which enhance the energy efficiency of the vehicle. The approach to the topic is genuinely interdisciplinary, covering insights from fields. The target audience primarily comprises researchers and industry experts in the field of automotive engineering, but the book may also be beneficial for graduate students.

Development of optimized nanogap plasmonic substrate for improved SERS enhancement

Directory of Open Access Journals (Sweden)

Jayakumar Perumal

2017-05-01

Full Text Available SERS enhancement factor (EF of planar substrates depends on the size and shape of the fine nanostructure forming a defect free, well-arranged matrix. Nano-lithographic process is considered to be the most advanced methods employed for the fabrication SERS substrates. Nanostructured plasmonic substrates with nanogap (NG pattern often results in stable, efficient and reproducible SERS enhancement. For such substrates, NG and their diagonal length (DL need to be optimized. Theoretically smaller NGs (∼30-40 nm or smaller results in higher SERS enhancement. However, fabrication of NG substrates below such limit is a challenge even for the most advanced lithography process. In this context, herein, we report the optimization of fabrication process, where higher SERS enhancement can be realized from larger NGs substrates by optimizing their DL of nanostructures between the NGs. Based on simulation we could demonstrate that, by optimizing the DL, SERS enhancement from larger NG substrate such as 60 and 80 nm could be comparable to that of smaller (40nm NG substrates. We envision that this concept will open up new regime in the nanofabrication of practically feasible NG based plasmonic substrates with higher SERS enhancement. Initial results of our experiments are in close agreement with our simulated study.

Introducing a Novel Hybrid Artificial Intelligence Algorithm to Optimize Network of Industrial Applications in Modern Manufacturing

Directory of Open Access Journals (Sweden)

Aydin Azizi

2017-01-01

Full Text Available Recent advances in modern manufacturing industries have created a great need to track and identify objects and parts by obtaining real-time information. One of the main technologies which has been utilized for this need is the Radio Frequency Identification (RFID system. As a result of adopting this technology to the manufacturing industry environment, RFID Network Planning (RNP has become a challenge. Mainly RNP deals with calculating the number and position of antennas which should be deployed in the RFID network to achieve full coverage of the tags that need to be read. The ultimate goal of this paper is to present and evaluate a way of modelling and optimizing nonlinear RNP problems utilizing artificial intelligence (AI techniques. This effort has led the author to propose a novel AI algorithm, which has been named “hybrid AI optimization technique,” to perform optimization of RNP as a hard learning problem. The proposed algorithm is composed of two different optimization algorithms: Redundant Antenna Elimination (RAE and Ring Probabilistic Logic Neural Networks (RPLNN. The proposed hybrid paradigm has been explored using a flexible manufacturing system (FMS, and results have been compared with Genetic Algorithm (GA that demonstrates the feasibility of the proposed architecture successfully.

Consideration of a design optimization method for advanced nuclear power plant thermal-hydraulic components

International Nuclear Information System (INIS)

Ridluan, Artit; Tokuhiro, Akira; Manic, Milos; Patterson, Michael; Danchus, William

2009-01-01

In order to meet the global energy demand and also mitigate climate change, we anticipate a significant resurgence of nuclear power in the next 50 years. Globally, Generation III plants (ABWR) have been built; Gen' III+ plants (EPR, AP1000 others) are anticipated in the near term. The U.S. DOE and Japan are respectively pursuing the NGNP and MSFR. There is renewed interest in closing the fuel cycle and gradually introducing the fast reactor into the LWR-dominated global fleet. In order to meet Generation IV criteria, i.e. thermal efficiency, inherent safety, proliferation resistance and economic competitiveness, plant and energy conversion system engineering design have to increasingly meet strict design criteria with reduced margin for reliable safety and uncertainties. Here, we considered a design optimization approach using an anticipated NGNP thermal system component as a Case Study. A systematic, efficient methodology is needed to reduce time consuming trial-and-error and computationally-intensive analyses. We thus developed a design optimization method linking three elements; that is, benchmarked CFD used as a 'design tool', artificial neural networks (ANN) to accommodate non-linear system behavior and enhancement of the 'design space', and finally, response surface methodology (RSM) to optimize the design solution with targeted constraints. The paper presents the methodology including guiding principles, an integration of CFD into design theory and practice, consideration of system non-linearities (such as fluctuating operating conditions) and systematic enhancement of the design space via application of ANN, and a stochastic optimization approach (RSM) with targeted constraints. Results from a Case Study optimizing the printed circuit heat exchanger for the NGNP energy conversion system will be presented. (author)