WorldWideScience

Sample records for optimization based reactive

  1. Opposition-Based Improved PSO for Optimal Reactive Power Dispatch and Voltage Control

    Directory of Open Access Journals (Sweden)

    Shengrang Cao

    2015-01-01

    Full Text Available An opposition-based improved particle swarm optimization algorithm (OIPSO is presented for solving multiobjective reactive power optimization problem. OIPSO uses the opposition learning to improve search efficiency, adopts inertia weight factors to balance global and local exploration, and takes crossover and mutation and neighborhood model strategy to enhance population diversity. Then, a new multiobjective model is built, which includes system network loss, voltage dissatisfaction, and switching operation. Based on the market cost prices, objective functions are converted to least-cost model. In modeling process, switching operation cost is described according to the life cycle cost of transformer, and voltage dissatisfaction penalty is developed considering different voltage quality requirements of customers. The experiment is done on the new mathematical model. Through the simulation of IEEE 30-, 118-bus power systems, the results prove that OIPSO is more efficient to solve reactive power optimization problems and the model is more accurate to reflect the real power system operation.

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

    Science.gov (United States)

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

    2018-01-01

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

  3. A Fast Reactive Power Optimization in Distribution Network Based on Large Random Matrix Theory and Data Analysis

    Directory of Open Access Journals (Sweden)

    Wanxing Sheng

    2016-05-01

    Full Text Available In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. Load similarity (LS is defined to measure the degree of similarity between the loads in different days and the calculation method of the load similarity of load random matrix (LRM is presented. By calculating the load similarity between the forecasting random matrix and the random matrix of historical load, the historical reactive power optimization dispatching scheme that most matches the forecasting load can be found for reactive power control usage. The differences of daily load curves between working days and weekends in different seasons are considered in the proposed method. The proposed method is tested on a standard 14 nodes distribution network with three different types of load. The computational result demonstrates that the proposed method for reactive power optimization is fast, feasible and effective in distribution network.

  4. Optimization-based reactive power control in HVDC-connected wind power plants

    OpenAIRE

    Schönleber, Kevin; Collados Rodríguez, Carlos; Teixeira Pinto, Rodrigo; Ratés Palau, Sergi; Gomis Bellmunt, Oriol

    2017-01-01

    One application of high–voltage dc (HVdc) systems is the connection of remotely located offshore wind power plants (WPPs). In these systems, the offshore WPP grid and the synchronous main grid operate in decoupled mode, and the onshore HVdc converter fulfills the grid code requirements of the main grid. Thus, the offshore grid can be operated independently during normal conditions by the offshore HVdc converter and the connected wind turbines. In general, it is well known that optimized react...

  5. Optimization Based Shunt APF Controller to Mitigate Reactive Power, Burden of Neutral Conductor, Current Harmonics and Improve cosɸ

    Directory of Open Access Journals (Sweden)

    P. Anjana

    2017-03-01

    Full Text Available This paper presents a Modified Gravitational Search Algorithm (MGSA to improve the performance of PI controller in varying load condition. The proposed approach is capable of mitigating reactive power, neutral current, source current THD and significant improvement in power factor nearly unity (0.997. The DC link voltage across the capacitor is controlled by PI controller which is deciding the performance of shunt APF. Hence, the robust optimization technique based integral time square error (ITSE with consideration of weight factor (α & β, maximum overshoot ((|(∆_Ve ̅〖(n〗_max | and setling time t_s-t_0, is providing the optimum solution of Kp & Ki. The robustness of proposed objective function and algorithm compared with GSA based three other error criterion techniques. The efficiency of the proposed controller has been tested over nonlinear and unbalance loading condition. The performance of ITSE based MGSA-PI controller is batter then other three error criterion techniques. The values of THD are below the mark of 5% specified in IEEE-519 standard.

  6. Ant colony search algorithm for optimal reactive power optimization

    Directory of Open Access Journals (Sweden)

    Lenin K.

    2006-01-01

    Full Text Available The paper presents an (ACSA Ant colony search Algorithm for Optimal Reactive Power Optimization and voltage control of power systems. ACSA is a new co-operative agents’ approach, which is inspired by the observation of the behavior of real ant colonies on the topic of ant trial formation and foraging methods. Hence, in the ACSA a set of co-operative agents called "Ants" co-operates to find good solution for Reactive Power Optimization problem. The ACSA is applied for optimal reactive power optimization is evaluated on standard IEEE, 30, 57, 191 (practical test bus system. The proposed approach is tested and compared to genetic algorithm (GA, Adaptive Genetic Algorithm (AGA.

  7. An Optimal Reactive Power Control Strategy for a DFIG-Based Wind Farm to Damp the Sub-Synchronous Oscillation of a Power System

    Directory of Open Access Journals (Sweden)

    Bin Zhao

    2014-05-01

    Full Text Available This study presents the auxiliary damping control with the reactive power loop on the rotor-side converter of doubly-fed induction generator (DFIG-based wind farms to depress the sub-synchronous resonance oscillations in nearby turbogenerators. These generators are connected to a series capacitive compensation transmission system. First, the damping effect of the reactive power control of the DFIG-based wind farms was theoretically analyzed, and a transfer function between turbogenerator speed and the output reactive power of the wind farms was introduced to derive the analytical expression of the damping coefficient. The phase range to obtain positive damping was determined. Second, the PID phase compensation parameters of the auxiliary damping controller were optimized by a genetic algorithm to obtain the optimum damping in the entire subsynchronous frequency band. Finally, the validity and effectiveness of the proposed auxiliary damping control were demonstrated on a modified version of the IEEE first benchmark model by time domain simulation analysis with the use of DigSILENT/PowerFactory. Theoretical analysis and simulation results show that this derived damping factor expression and the condition of the positive damping can effectively analyze their impact on the system sub-synchronous oscillations, the proposed wind farms reactive power additional damping control strategy can provide the optimal damping effect over the whole sub-synchronous frequency band, and the control effect is better than the active power additional damping control strategy based on the power system stabilizator.

  8. Statistical Optimization of Reactive Plasma Cladding to Synthesize a WC-Reinforced Fe-Based Alloy Coating

    Science.gov (United States)

    Wang, Miqi; Zhou, Zehua; Wu, Lintao; Ding, Ying; Xu, Feilong; Wang, Zehua

    2018-04-01

    A new compound Fe-W-C powder for reactive plasma cladding was fabricated by precursor carbonization process using sucrose as a precursor. The application of quadratic general rotary unitized design was highlighted to develop a mathematical model to predict and accomplish the desired surface hardness of plasma-cladded coating. The microstructure and microhardness of the coating with optimal parameters were also investigated. According to the developed empirical model, the optimal process parameters were determined as follows: 1.4 for C/W atomic ratio, 20 wt.% for W content, 130 A for scanning current and 100 mm/min (1.67 mm/s) for scanning rate. The confidence level of the model was 99% according to the results of the F-test and lack-of-fit test. Microstructural study showed that the dendritic structure was comprised of a mechanical mixture of α-Fe and carbides, while the interdendritic structure was a eutectic of α-Fe and carbides in the composite coating with optimal parameters. WC phase generation can be confirmed from the XRD pattern. Due to good preparation parameters, the average microhardness of cladded coating can reach 1120 HV0.1, which was four times the substrate microhardness.

  9. Reactive power dispatch considering voltage stability with seeker optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Dai, Chaohua; Chen, Weirong; Zhang, Xuexia [The School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031 (China); Zhu, Yunfang [Department of Computer and Communication Engineering, E' mei Campus, Southwest Jiaotong University, E' mei 614202 (China)

    2009-10-15

    Optimal reactive power dispatch (ORPD) has a growing impact on secure and economical operation of power systems. This issue is well known as a non-linear, multi-modal and multi-objective optimization problem where global optimization techniques are required in order to avoid local minima. In the last decades, computation intelligence-based techniques such as genetic algorithms (GAs), differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA) based method is proposed for ORPD considering static voltage stability and voltage deviation. The SOA is based on the concept of simulating the act of human searching where search direction is based on the empirical gradient by evaluating the response to the position changes and step length is based on uncertainty reasoning by using a simple Fuzzy rule. The algorithm's performance is studied with comparisons of two versions of GAs, three versions of DE algorithms and four versions of PSO algorithms on the IEEE 57 and 118-bus power systems. The simulation results show that the proposed approach performed better than the other listed algorithms and can be efficiently used for the ORPD problem. (author)

  10. Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problem

    Directory of Open Access Journals (Sweden)

    Kanagasabai Lenin

    2015-03-01

    Full Text Available This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality  of wolf is  possessing  both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .

  11. Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

    Directory of Open Access Journals (Sweden)

    Kanagasabai Lenin

    2015-04-01

    Full Text Available In this paper, a novel approach Modified Monkey optimization (MMO algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases.  The proposed (MMO algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.

  12. An optimal reactive power control strategy for a DFIG-based wind farm to damp the sub-synchronous oscillation of a power system

    DEFF Research Database (Denmark)

    Zhao, Bin; Li, Hui; Wang, Mingyu

    2014-01-01

    This study presents the auxiliary damping control with the reactive power loop on the rotor-side converter of doubly-fed induction generator (DFIG)-based wind farms to depress the sub-synchronous resonance oscillations in nearby turbogenerators. These generators are connected to a series capaciti...

  13. Pay-as-bid based reactive power market

    International Nuclear Information System (INIS)

    Amjady, N.; Rabiee, A.; Shayanfar, H.A.

    2010-01-01

    In energy market clearing, the offers are stacked in increasing order and the offer that intersects demand curve, determines the market clearing price (MCP). In reactive power market, the location of reactive power compensator is so important. A low cost reactive producer may not essentially be favorable if it is far from the consumer. Likewise, a high cost local reactive compensator at a heavily loaded demand center of network could be inevitably an alternative required to produce reactive power to maintain the integrity of power system. Given the background, this paper presents a day-ahead reactive power market based on pay-as-bid (PAB) mechanism. Generators expected payment function (EPF) is used to construct a bidding framework. Then, total payment function (TPF) of generators is used as the objective function of optimal power flow (OPF) problem to clear the PAB based market. The CIGRE-32 bus test system is used to examine the effectiveness of the proposed reactive power market.

  14. Pay-as-bid based reactive power market

    Energy Technology Data Exchange (ETDEWEB)

    Amjady, N. [Department of Electrical Engineering, Semnan University, Semnan (Iran, Islamic Republic of); Rabiee, A., E-mail: Rabiee@iust.ac.i [Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

    2010-02-15

    In energy market clearing, the offers are stacked in increasing order and the offer that intersects demand curve, determines the market clearing price (MCP). In reactive power market, the location of reactive power compensator is so important. A low cost reactive producer may not essentially be favorable if it is far from the consumer. Likewise, a high cost local reactive compensator at a heavily loaded demand center of network could be inevitably an alternative required to produce reactive power to maintain the integrity of power system. Given the background, this paper presents a day-ahead reactive power market based on pay-as-bid (PAB) mechanism. Generators expected payment function (EPF) is used to construct a bidding framework. Then, total payment function (TPF) of generators is used as the objective function of optimal power flow (OPF) problem to clear the PAB based market. The CIGRE-32 bus test system is used to examine the effectiveness of the proposed reactive power market.

  15. A Method of Dynamic Extended Reactive Power Optimization in Distribution Network Containing Photovoltaic-Storage System

    Science.gov (United States)

    Wang, Wu; Huang, Wei; Zhang, Yongjun

    2018-03-01

    The grid-integration of Photovoltaic-Storage System brings some undefined factors to the network. In order to make full use of the adjusting ability of Photovoltaic-Storage System (PSS), this paper puts forward a reactive power optimization model, which are used to construct the objective function based on power loss and the device adjusting cost, including energy storage adjusting cost. By using Cataclysmic Genetic Algorithm to solve this optimization problem, and comparing with other optimization method, the result proved that: the method of dynamic extended reactive power optimization this article puts forward, can enhance the effect of reactive power optimization, including reducing power loss and device adjusting cost, meanwhile, it gives consideration to the safety of voltage.

  16. Modified artificial bee colony algorithm for reactive power optimization

    Science.gov (United States)

    Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

    2015-05-01

    Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

  17. Evaluation of reactivity shutdown margin for nuclear fuel reload optimization

    International Nuclear Information System (INIS)

    Wong, Hing-Ip; Maldonado, G.I.

    1995-01-01

    The FORMOSA-P code is a nuclear fuel management optimization package that combines simulated annealing (SA) and nodal generalized perturbation theory (GPT). Recent studies at Electricite de France (EdF-Clamart) have produced good results for power-peaking minimizations under multiple limiting control rod configurations. However, since the reactivity shutdown margin is not explicitly treated as an objective or constraint function, then any optimal loading patterns (LPs) are not guaranteed to yield an adequate shutdown margin (SDM). This study describes the implementation of the SDM calculation within a FORMOSA-P optimization. Maintaining all additional computational requirements to a minimum was a key consideration

  18. Evaluation of reactivity shutdown margin for nuclear fuel reload optimization

    International Nuclear Information System (INIS)

    Engrand, P.; Wong, H. I.; Maldonado, G.I.

    1996-01-01

    The FORMOSA-P code is a nuclear fuel management optimization package which combines simulated annealing (SA) and nodal generalized perturbation theory (GPT). Recent studies at Electricite de France have produced good results for power peaking minimizations under multiple limiting control rod configurations. However, since the reactivity shutdown margin is not explicitly treated as an objective or constraint function, then any optimal loading patterns (LPs) are not guaranteed to yield an adequate shutdown margin (SDM). This study describes the implementation of the SDM calculation within a FORMOSA-P optimization. Maintaining all additional computational requirements to a minimum was a key consideration. (authors). 4 refs., 2 figs

  19. On Variable Reverse Power Flow-Part I: Active-Reactive Optimal Power Flow with Reactive Power of Wind Stations

    Directory of Open Access Journals (Sweden)

    Aouss Gabash

    2016-02-01

    Full Text Available It has recently been shown that using battery storage systems (BSSs to provide reactive power provision in a medium-voltage (MV active distribution network (ADN with embedded wind stations (WSs can lead to a huge amount of reverse power to an upstream transmission network (TN. However, unity power factors (PFs of WSs were assumed in those studies to analyze the potential of BSSs. Therefore, in this paper (Part-I, we aim to further explore the pure reactive power potential of WSs (i.e., without BSSs by investigating the issue of variable reverse power flow under different limits on PFs in an electricity market model. The main contributions of this work are summarized as follows: (1 Introducing the reactive power capability of WSs in the optimization model of the active-reactive optimal power flow (A-R-OPF and highlighting the benefits/impacts under different limits on PFs. (2 Investigating the impacts of different agreements for variable reverse power flow on the operation of an ADN under different demand scenarios. (3 Derivation of the function of reactive energy losses in the grid with an equivalent-π circuit and comparing its value with active energy losses. (4 Balancing the energy curtailment of wind generation, active-reactive energy losses in the grid and active-reactive energy import-export by a meter-based method. In Part-II, the potential of the developed model is studied through analyzing an electricity market model and a 41-bus network with different locations of WSs.

  20. Application of Newton's optimal power flow in voltage/reactive power control

    Energy Technology Data Exchange (ETDEWEB)

    Bjelogrlic, M.; Babic, B.S. (Electric Power Board of Serbia, Belgrade (YU)); Calovic, M.S. (Dept. of Electrical Engineering, University of Belgrade, Belgrade (YU)); Ristanovic, P. (Institute Nikola Tesla, Belgrade (YU))

    1990-11-01

    This paper considers an application of Newton's optimal power flow to the solution of the secondary voltage/reactive power control in transmission networks. An efficient computer program based on the latest achievements in the sparse matrix/vector techniques has been developed for this purpose. It is characterized by good robustness, accuracy and speed. A combined objective function appropriate for various system load levels with suitable constraints, for treatment of the power system security and economy is also proposed. For the real-time voltage/reactive power control, a suboptimal power flow procedure has been derived by using the reduced set of control variables. This procedure is based on the sensitivity theory applied to the determination of zones for the secondary voltage/reactive power control and corresponding reduced set of regulating sources, whose reactive outputs represent control variables in the optimal power flow program. As a result, the optimal power flow program output becomes a schedule to be used by operators in the process of the real-time voltage/reactive power control in both normal and emergency operating states.

  1. Agent-Based Optimization

    CERN Document Server

    Jędrzejowicz, Piotr; Kacprzyk, Janusz

    2013-01-01

    This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve  difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

  2. Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

    Science.gov (United States)

    Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

    2018-05-04

    Particle swarm optimization is a powerful metaheuristic population-based global optimization algorithm. However, when applied to non-separable objective functions its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant particle swarm optimization algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates a superior performance across several nonlinear, multimodal benchmark functions compared to the rotation-invariant Particle Swam Optimization (PSO) algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in ReaxFF-lg reactive force field is carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents a better performance compared to a Genetic Algorithm optimization method in the optimization of a ReaxFF-lg correction model parameters. The computational framework is implemented in a standalone C++ code that allows a straightforward development of ReaxFF reactive force fields.

  3. An Interval Bound Algorithm of optimizing reactor core loading pattern by using reactivity interval schema

    International Nuclear Information System (INIS)

    Gong Zhaohu; Wang Kan; Yao Dong

    2011-01-01

    Highlights: → We present a new Loading Pattern Optimization method - Interval Bound Algorithm (IBA). → IBA directly uses the reactivity of fuel assemblies and burnable poison. → IBA can optimize fuel assembly orientation in a coupled way. → Numerical experiment shows that IBA outperforms genetic algorithm and engineers. → We devise DDWF technique to deal with multiple objectives and constraints. - Abstract: In order to optimize the core loading pattern in Nuclear Power Plants, the paper presents a new optimization method - Interval Bound Algorithm (IBA). Similar to the typical population based algorithms, e.g. genetic algorithm, IBA maintains a population of solutions and evolves them during the optimization process. IBA acquires the solution by statistical learning and sampling the control variable intervals of the population in each iteration. The control variables are the transforms of the reactivity of fuel assemblies or the worth of burnable poisons, which are the crucial heuristic information for loading pattern optimization problems. IBA can deal with the relationship between the dependent variables by defining the control variables. Based on the IBA algorithm, a parallel Loading Pattern Optimization code, named IBALPO, has been developed. To deal with multiple objectives and constraints, the Dynamic Discontinuous Weight Factors (DDWF) for the fitness function have been used in IBALPO. Finally, the code system has been used to solve a realistic reloading problem and a better pattern has been obtained compared with the ones searched by engineers and genetic algorithm, thus the performance of the code is proved.

  4. Reactive Robustness and Integrated Approaches for Railway Optimization Problems

    DEFF Research Database (Denmark)

    Haahr, Jørgen Thorlund

    journeys helps the driver to drive efficiently and enhances robustness in a realistic (dynamic) environment. Four international scientific prizes have been awarded for distinct parts of the research during the course of this PhD project. The first prize was awarded for work during the \\2014 RAS Problem...... to absorb or withstand unexpected events such as delays. Making robust plans is central in order to maintain a safe and timely railway operation. This thesis focuses on reactive robustness, i.e., the ability to react once a plan is rendered infeasible in operation due to disruptions. In such time...... Solving Competition", where a freight yard optimization problem was considered. The second junior (PhD) prize was awared for the work performed in the \\ROADEF/EURO Challenge 2014: Trains don't vanish!", where the planning of rolling stock movements at a large station was considered. An honorable mention...

  5. Optimal Control of Wind Farms for Coordinated TSO-DSO Reactive Power Management

    Directory of Open Access Journals (Sweden)

    David Sebastian Stock

    2018-01-01

    Full Text Available The growing importance of renewable generation connected to distribution grids requires an increased coordination between transmission system operators (TSOs and distribution system operators (DSOs for reactive power management. This work proposes a practical and effective interaction method based on sequential optimizations to evaluate the reactive flexibility potential of distribution networks and to dispatch them along with traditional synchronous generators, keeping to a minimum the information exchange. A modular optimal power flow (OPF tool featuring multi-objective optimization is developed for this purpose. The proposed method is evaluated for a model of a real German 110 kV grid with 1.6 GW of installed wind power capacity and a reduced order model of the surrounding transmission system. Simulations show the benefit of involving wind farms in reactive power support reducing losses both at distribution and transmission level. Different types of setpoints are investigated, showing the feasibility for the DSO to fulfill also individual voltage and reactive power targets over multiple connection points. Finally, some suggestions are presented to achieve a fair coordination, combining both TSO and DSO requirements.

  6. An optimal frequency range for assessing the pressure reactivity index in patients with traumatic brain injury.

    Science.gov (United States)

    Howells, Tim; Johnson, Ulf; McKelvey, Tomas; Enblad, Per

    2015-02-01

    The objective of this study was to identify the optimal frequency range for computing the pressure reactivity index (PRx). PRx is a clinical method for assessing cerebral pressure autoregulation based on the correlation of spontaneous variations of arterial blood pressure (ABP) and intracranial pressure (ICP). Our hypothesis was that optimizing the methodology for computing PRx in this way could produce a more stable, reliable and clinically useful index of autoregulation status. The patients studied were a series of 131 traumatic brain injury patients. Pressure reactivity indices were computed in various frequency bands during the first 4 days following injury using bandpass filtering of the input ABP and ICP signals. Patient outcome was assessed using the extended Glasgow Outcome Scale (GOSe). The optimization criterion was the strength of the correlation with GOSe of the mean index value over the first 4 days following injury. Stability of the indices was measured as the mean absolute deviation of the minute by minute index value from 30-min moving averages. The optimal index frequency range for prediction of outcome was identified as 0.018-0.067 Hz (oscillations with periods from 55 to 15 s). The index based on this frequency range correlated with GOSe with ρ=-0.46 compared to -0.41 for standard PRx, and reduced the 30-min variation by 23%.

  7. Reduced Cost of Reactive Power in Doubly Fed Induction Generator Wind Turbine System with Optimized Grid Filter

    DEFF Research Database (Denmark)

    Zhou, Dao; Blaabjerg, Frede; Franke, Toke

    2014-01-01

    The modern grid requirement has caused that the wind power system behaves more like conventional rotating generators and it is able to support certain amount of the reactive power. For a typical doubly-fed induction generator wind turbine system, the reactive power can be supported either through...... for the generator and the wind power converter in terms of the reactive power done by the rotor-side converter or the grid-side converter with various grid filters. Afterwards, the annual energy loss is also estimated based on yearly wind profile. Finally, experimental results of the loss distribution are performed...... the rotor-side converter or the grid-side converter. This paper firstly compares the current ripples and supportive reactive power ranges between the conventional L and optimized LCL filter, if the reactive power is injected from the grid-side converter. Then, the loss distribution is evaluated both...

  8. Reduced Cost of Reactive Power in Doubly Fed Induction Generator Wind Turbine System With Optimized Grid Filter

    DEFF Research Database (Denmark)

    Zhou, Dao; Blaabjerg, Frede; Franke, Toke

    2015-01-01

    The modern grid requirement has caused that the wind power system behaves more like conventional rotating generators, and it is able to support certain amount of the reactive power. For a typical doubly fed induction generator (DFIG) wind turbine system, the reactive power can be supported either...... for the generator and the wind power converter in terms of the reactive power done by the rotor-side converter or the grid-side converter with various grid filters. Afterward, the annual energy loss is also estimated based on yearly wind profile. Finally, experimental results of the loss distribution are performed...... through the rotor-side converter or the grid-side converter. This paper first compares the current ripples and supportive reactive power ranges between the conventional L and optimized LCL filter, if the reactive power is injected from the grid-side converter. Then, the loss distribution is evaluated both...

  9. Event-Based Modularization of Reactive Systems

    NARCIS (Netherlands)

    Malakuti Khah Olun Abadi, Somayeh; Aksit, Mehmet

    2014-01-01

    There is a large number of complex software systems that have reactive behavior. As for any other software system, reactive systems are subject to evolution demands. This paper defines a set requirements that must be fulfilled so that reuse of reactive software systems can be increased. Detailed

  10. Risk Based Optimal Fatigue Testing

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M.H.; Kroon, I.B.

    1992-01-01

    Optimal fatigue life testing of materials is considered. Based on minimization of the total expected costs of a mechanical component a strategy is suggested to determine the optimal stress range levels for which additional experiments are to be performed together with an optimal value...

  11. A Model-Based Methodology for Integrated Design and Operation of Reactive Distillation Processes

    DEFF Research Database (Denmark)

    Mansouri, Seyed Soheil; Sales-Cruz, Mauricio; Huusom, Jakob Kjøbsted

    2015-01-01

    and resolved. A new approach isto tackle process intensification and controllability issues in an integrated manner, in the early stages of process design. This integrated and simultaneous synthesis approach provides optimal operation and moreefficient control of complex intensified systems that suffice...... calculation of reactive bubble points. For an energy-efficient design, the driving-forc eapproach (to determine the optimal feed location) for a reactive system has been employed. For both thereactive McCabe-Thiele and driving force method, vapor-liquid equilibrium data are based on elements. Thereactive...... system of compounds (methanol, isobutene and MTBE) to a binary system ofelements (elements A and B). For a binary element system, a simple reactive McCabe-Thiele-type method (to determine the number of reactive stages) has been used. The reactive equilibrium curve is constructed through sequential...

  12. Index-based reactive power compensation scheme for voltage regulation

    Science.gov (United States)

    Dike, Damian Obioma

    2008-10-01

    Increasing demand for electrical power arising from deregulation and the restrictions posed to the construction of new transmission lines by environment, socioeconomic, and political issues had led to higher grid loading. Consequently, voltage instability has become a major concern, and reactive power support is vital to enhance transmission grid performance. Improved reactive power support to distressed grid is possible through the application of relatively unfamiliar emerging technologies of "Flexible AC Transmission Systems (FACTS)" devices and "Distributed Energy Resources (DERS)." In addition to these infrastructure issues, a lack of situational awareness by system operators can cause major power outages as evidenced by the August 14, 2003 widespread North American blackout. This and many other recent major outages have highlighted the inadequacies of existing power system indexes. In this work, a novel "Index-based reactive compensation scheme" appropriate for both on-line and off-line computation of grid status has been developed. A new voltage stability index (Ls-index) suitable for long transmission lines was developed, simulated, and compared to the existing two-machine modeled L-index. This showed the effect of long distance power wheeling amongst regional transmission organizations. The dissertation further provided models for index modulated voltage source converters (VSC) and index-based load flow analysis of both FACTS and microgrid interconnected power systems using the Newton-Raphson's load flow model incorporated with multi-FACTS devices. The developed package has been made user-friendly through the embodiment of interactive graphical user interface and implemented on the IEEE 14, 30, and 300 bus systems. The results showed reactive compensation has system wide-effect, provided readily accessible system status indicators, ensured seamless DERs interconnection through new islanding modes and enhanced VSC utilization. These outcomes may contribute

  13. Fuzzy-TLBO optimal reactive power control variables planning for energy loss minimization

    International Nuclear Information System (INIS)

    Moghadam, Ahmad; Seifi, Ali Reza

    2014-01-01

    Highlights: • A new approach to the problem of optimal reactive power control variables planning is proposed. • The energy loss minimization problem has been formulated by modeling the load of system as a Load Duration Curve. • To solving the energy loss problem, the classic methods and the evolutionary methods are used. • A new proposed fuzzy teaching–learning based algorithm is applied to energy loss problem. • Simulations are done to show the effectiveness and superiority of the proposed algorithm compared with other methods. - Abstract: This paper offers a new approach to the problem of optimal reactive power control variables planning (ORPVCP). The basic idea is division of Load Duration Curve (LDC) into several time intervals with constant active power demand in each interval and then solving the energy loss minimization (ELM) problem to obtain an optimal initial set of control variables of the system so that is valid for all time intervals and can be used as an initial operating condition of the system. In this paper, the ELM problem has been solved by the linear programming (LP) and fuzzy linear programming (Fuzzy-LP) and evolutionary algorithms i.e. MHBMO and TLBO and the results are compared with the proposed Fuzzy-TLBO method. In the proposed method both objective function and constraints are evaluated by membership functions. The inequality constraints are embedded into the fitness function by the membership function of the fuzzy decision and the problem is modeled by fuzzy set theory. The proposed Fuzzy-TLBO method is performed on the IEEE 30 bus test system by considering two different LDC; and it is shown that using this method has further minimized objective function than original TLBO and other optimization techniques and confirms its potential to solve the ORPCVP problem with considering ELM as the objective function

  14. Properties and reactivity of reactivated calcium-based sorbents

    Energy Technology Data Exchange (ETDEWEB)

    Davini, P. [Pisa University, Pisa (Italy). Dept. of Chemical Engineering

    2002-04-01

    Calcium-based sorbents used in the process of high temperature desulfurisation of flue gases are partly regenerable by hydration with steam; the best results are obtained for treatment temperatures of approximately 300{degree}C. The regeneration process, and the consequent increase in the sorbent consumption can be correlated to the surface characteristics (BET surface area, porosity and pore size distribution) of the sorbents themselves. In particular, the presence of suitable pore structure, also having pores large enough to let molecules easily penetrate the inner part of the sorbent particles, is very important. 27 refs., 9 figs., 2 tabs.

  15. A Hybrid Optimization Method for Reactive Power and Voltage Control Considering Power Loss Minimization

    DEFF Research Database (Denmark)

    Liu, Chengxi; Qin, Nan; Bak, Claus Leth

    2015-01-01

    This paper proposes a hybrid optimization method to optimally control the voltage and reactive power with minimum power loss in transmission grid. This approach is used for the Danish automatic voltage control (AVC) system which is typically a non-linear non-convex problem mixed with both...

  16. A framework for reactive optimization in mobile ad hoc networks

    DEFF Research Database (Denmark)

    McClary, Dan; Syrotiuk, Violet; Kulahci, Murat

    2008-01-01

    We present a framework to optimize the performance of a mobile ad hoc network over a wide range of operating conditions. It includes screening experiments to quantify the parameters and interactions among parameters influential to throughput. Profile-driven regression is applied to obtain a model....... The predictive accuracy of the model is monitored and used to update the model dynamically. The results indicate the framework may be useful for the optimization of dynamic systems of high dimension....

  17. A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

    DEFF Research Database (Denmark)

    Ding, Tao; Li, Cheng; Huang, Can

    2018-01-01

    –slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

  18. Review of reactive power dispatch strategies for loss minimization in a DFIG-based wind farm

    DEFF Research Database (Denmark)

    Zhang, Baohua; Hu, Weihao; Hou, Peng

    2017-01-01

    power control strategies are investigated. All of the combined strategies are formulated based on the comprehensive loss models of WFs, including the loss models of DFIGs, converters, filters, transformers, and cables of the collection system. Optimization problems are solved by a Modified Particle......This paper reviews and compares the performance of reactive power dispatch strategies for the loss minimization of Doubly Fed Induction Generator (DFIG)-based Wind Farms (WFs). Twelve possible combinations of three WF level reactive power dispatch strategies and fourWind Turbine (WT) level reactive...... Swarm Optimization (MPSO) algorithm. The effectiveness of these strategies is evaluated by simulations on a carefully designed WF under a series of cases with different wind speeds and reactive power requirements of the WF. The wind speed at each WT inside the WF is calculated using the Jensen wake...

  19. CARBON-BASED REACTIVE BARRIER FOR NITRATE ...

    Science.gov (United States)

    Nitrate (NO3-) is a common ground water contaminant related to agricultural activity, waste water disposal, leachate from landfills, septic systems, and industrial processes. This study reports on the performance of a carbon-based permeable reactive barrier (PRB) that was constructed for in-situ bioremediation of a ground water nitrate plume caused by leakage from a swine CAFO (concentrated animal feeding operation) lagoon. The swine CAFO, located in Logan County, Oklahoma, was in operation from 1992-1999. The overall site remediation strategy includes an ammonia recovery trench to intercept ammonia-contaminated ground water and a hay straw PRB which is used to intercept a nitrate plume caused by nitrification of sorbed ammonia. The PRB extends approximately 260 m to intercept the nitrate plume. The depth of the trench averages 6 m and corresponds to the thickness of the surficial saturated zone; the width of the trench is 1.2 m. Detailed quarterly monitoring of the PRB began in March, 2004, about 1 year after construction activities ended. Nitrate concentrations hydraulically upgradient of the PRB have ranged from 23 to 77 mg/L N, from 0 to 3.2 mg/L N in the PRB, and from 0 to 65 mg/L N hydraulically downgradient of the PRB. Nitrate concentrations have generally decreased in downgradient locations with successive monitoring events. Mass balance considerations indicate that nitrate attenuation is dominantly from denitrification but with some component of

  20. Design analysis for optimal calibration of diffusivity in reactive multilayers

    KAUST Repository

    Vohra, Manav

    2017-05-29

    Calibration of the uncertain Arrhenius diffusion parameters for quantifying mixing rates in Zr–Al nanolaminate foils have been previously performed in a Bayesian setting [M. Vohra, J. Winokur, K.R. Overdeep, P. Marcello, T.P. Weihs, and O.M. Knio, Development of a reduced model of formation reactions in Zr–Al nanolaminates, J. Appl. Phys. 116(23) (2014): Article No. 233501]. The parameters were inferred in a low-temperature, homogeneous ignition regime, and a high-temperature self-propagating reaction regime. In this work, we extend the analysis to determine optimal experimental designs that would provide the best data for inference. We employ a rigorous framework that quantifies the expected information gain in an experiment, and find the optimal design conditions using Monte Carlo techniques, sparse quadrature, and polynomial chaos surrogates. For the low-temperature regime, we find the optimal foil heating rate and pulse duration, and confirm through simulation that the optimal design indeed leads to sharp posterior distributions of the diffusion parameters. For the high-temperature regime, we demonstrate the potential for increasing the expected information gain concerning the posteriors by increasing the sample size and reducing the uncertainty in measurements. Moreover, posterior marginals are also obtained to verify favourable experimental scenarios.

  1. Estimation of dynamic reactivity using an H∞ optimal filter with a nonlinear term

    International Nuclear Information System (INIS)

    Suzuki, Katsuo; Watanabe, Koiti

    1996-01-01

    A method of nonlinear filtering is applied to the problem of estimating the dynamic reactivity of a nonlinear reactor system. The nonlinear filtering algorithm developed is a simple modification of a linear H ∞ optimal filter with a nonlinear feedback loop added. The linear filter is designed on the basis of a linearized dynamical system model that consists of linearized point reactor kinetic equations and a reactivity state equation driven by a fictitious signal. The latter is artificially introduced to deal with the reactivity as a state variable. The results of the computer simulation show that the nonlinear filtering algorithm can be applied to estimate the dynamic reactivity of the nonlinear reactor system, even under relatively large reactivity disturbances

  2. Optimization of integrated chemical-biological degradation of a reactive azo dye using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Sudarjanto, Gatut [Advanced Wastewater Management Centre, The University of Queensland, Qld 4072 (Australia); Keller-Lehmann, Beatrice [Advanced Wastewater Management Centre, The University of Queensland, Qld 4072 (Australia); Keller, Jurg [Advanced Wastewater Management Centre, The University of Queensland, Qld 4072 (Australia)]. E-mail: j.keller@awmc.uq.edu.au

    2006-11-02

    The integrated chemical-biological degradation combining advanced oxidation by UV/H{sub 2}O{sub 2} followed by aerobic biodegradation was used to degrade C.I. Reactive Azo Red 195A, commonly used in the textile industry in Australia. An experimental design based on the response surface method was applied to evaluate the interactive effects of influencing factors (UV irradiation time, initial hydrogen peroxide dosage and recirculation ratio of the system) on decolourisation efficiency and optimizing the operating conditions of the treatment process. The effects were determined by the measurement of dye concentration and soluble chemical oxygen demand (S-COD). The results showed that the dye and S-COD removal were affected by all factors individually and interactively. Maximal colour degradation performance was predicted, and experimentally validated, with no recirculation, 30 min UV irradiation and 500 mg H{sub 2}O{sub 2}/L. The model predictions for colour removal, based on a three-factor/five-level Box-Wilson central composite design and the response surface method analysis, were found to be very close to additional experimental results obtained under near optimal conditions. This demonstrates the benefits of this approach in achieving good predictions while minimising the number of experiments required.

  3. Optimization of integrated chemical-biological degradation of a reactive azo dye using response surface methodology

    International Nuclear Information System (INIS)

    Sudarjanto, Gatut; Keller-Lehmann, Beatrice; Keller, Jurg

    2006-01-01

    The integrated chemical-biological degradation combining advanced oxidation by UV/H 2 O 2 followed by aerobic biodegradation was used to degrade C.I. Reactive Azo Red 195A, commonly used in the textile industry in Australia. An experimental design based on the response surface method was applied to evaluate the interactive effects of influencing factors (UV irradiation time, initial hydrogen peroxide dosage and recirculation ratio of the system) on decolourisation efficiency and optimizing the operating conditions of the treatment process. The effects were determined by the measurement of dye concentration and soluble chemical oxygen demand (S-COD). The results showed that the dye and S-COD removal were affected by all factors individually and interactively. Maximal colour degradation performance was predicted, and experimentally validated, with no recirculation, 30 min UV irradiation and 500 mg H 2 O 2 /L. The model predictions for colour removal, based on a three-factor/five-level Box-Wilson central composite design and the response surface method analysis, were found to be very close to additional experimental results obtained under near optimal conditions. This demonstrates the benefits of this approach in achieving good predictions while minimising the number of experiments required

  4. Estimation of time-varying reactivity by the H∞ optimal linear filter

    International Nuclear Information System (INIS)

    Suzuki, Katsuo; Shimazaki, Junya; Watanabe, Koiti

    1995-01-01

    The problem of estimating the time-varying net reactivity from flux measurements is solved for a point reactor kinetics model using a linear filtering technique in an H ∞ settings. In order to sue this technique, an appropriate dynamical model of the reactivity is constructed that can be embedded into the reactor model as one of its variables. A filter, which minimizes the H ∞ norm of the estimation error power spectrum, operates on neutron density measurements corrupted by noise and provides an estimate of the dynamic net reactivity. Computer simulations are performed to reveal the basic characteristics of the H ∞ optimal filter. The results of the simulation indicate that the filter can be used to determine the time-varying reactivity from neutron density measurements that have been corrupted by noise

  5. Digital reactivity meter construction based on PC

    International Nuclear Information System (INIS)

    Yusi-Eko-Yulianto; Kristedjo-Kurnianto

    2003-01-01

    The reactivitymeter is a core reactivity measuring equipment, which inform the reactor operator the neutron flux development in the core. This digital reactivitymeter is needed to replace analog reactivitymeter, whenever it fails in the future. The replacement of thus reactivitymeter can keep the continuation of reactor operation. The digital reactivitymeter is constructed by using the digital signal processing and computer. Thus real time signal processing is displayed on the monitor graphically. This reactivitymeter has been tested in RSG-GAS and perform a good work. This performance is worthy to use this digital reactivitymeter for RSG-GAS operation

  6. Simulation-based optimization parametric optimization techniques and reinforcement learning

    CERN Document Server

    Gosavi, Abhijit

    2003-01-01

    Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work. Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: *An accessible introduction to reinforcement learning and parametric-optimization techniques. *A step-by-step description of several algorithms of simulation-based optimization. *A clear and simple introduction to the methodology of neural networks. *A gentle introduction to converg...

  7. Preparation of high temperature superconductor ceramics using cuban reactives. Optimization of the synthesis method

    International Nuclear Information System (INIS)

    Leyva Fabelo, A.; Cruz, C.; Aragon, B.; Suarez, J.C.; Mora, M.

    1991-01-01

    Results of the crystallographic characterization of a group of Cuban Products, which are evaluated to be employed in HTSC fabrication are presented in this paper. The first results on the synthesis of HTSC (RBa 2 Cu 3 0 7δ , R= Y, La, Nd) using Cuban reactives, are presented. The so called 'solid state reaction method of synthesis' was optimized, obtaining a critical temperature of more than 93 k

  8. Reactivity index based on orbital energies.

    Science.gov (United States)

    Tsuneda, Takao; Singh, Raman K

    2014-05-30

    This study shows that the chemical reactivities depend on the orbital energy gaps contributing to the reactions. In the process where a reaction only makes progress through charge transfer with the minimal structural transformation of the reactant, the orbital energy gap gradient (OEGG) between the electron-donating and electron-accepting orbitals is proven to be very low. Using this relation, a normalized reaction diagram is constructed by plotting the normalized orbital energy gap with respect to the normalized intrinsic reaction coordinate. Application of this reaction diagram to 43 fundamental reactions showed that the majority of the forward reactions provide small OEGGs in the initial stages, and therefore, the initial processes of the forward reactions are supposed to proceed only through charge transfer. Conversely, more than 60% of the backward reactions are found to give large OEGGs implying very slow reactions associated with considerable structural transformations. Focusing on the anti-activation-energy reactions, in which the forward reactions have higher barriers than those of the backward ones, most of these reactions are shown to give large OEGGs for the backward reactions. It is also found that the reactions providing large OEGGs in the forward directions inconsistent with the reaction rate constants are classified into SN 2, symmetric, and methyl radical reactions. Interestingly, several large-OEGG reactions are experimentally established to get around the optimum pathways. This indicates that the reactions can take significantly different pathways from the optimum ones provided no charge transfer proceeds spontaneously without the structural transformations of the reactants. Copyright © 2014 Wiley Periodicals, Inc.

  9. Multi-objective optimal reactive power dispatch to maximize power system social welfare in the presence of generalized unified power flow controller

    Directory of Open Access Journals (Sweden)

    Suresh Chintalapudi Venkata

    2015-09-01

    Full Text Available In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC. This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.

  10. Distributed Reactive Power Control based Conservation Voltage Reduction in Active Distribution Systems

    Directory of Open Access Journals (Sweden)

    EMIROGLU, S.

    2017-11-01

    Full Text Available This paper proposes a distributed reactive power control based approach to deploy Volt/VAr optimization (VVO / Conservation Voltage Reduction (CVR algorithm in a distribution network with distributed generations (DG units and distribution static synchronous compensators (D-STATCOM. A three-phase VVO/CVR problem is formulated and the reactive power references of D-STATCOMs and DGs are determined in a distributed way by decomposing the VVO/CVR problem into voltage and reactive power control. The main purpose is to determine the coordination between voltage regulator (VR and reactive power sources (Capacitors, D-STATCOMs and DGs based on VVO/CVR. The study shows that the reactive power injection capability of DG units may play an important role in VVO/CVR. In addition, it is shown that the coordination of VR and reactive power sources does not only save more energy and power but also reduces the power losses. Moreover, the proposed VVO/CVR algorithm reduces the computational burden and finds fast solutions. To illustrate the effectiveness of the proposed method, the VVO/CVR is performed on the IEEE 13-node test system feeder considering unbalanced loading and line configurations. The tests are performed taking the practical voltage-dependent load modeling and different customer types into consideration to improve accuracy.

  11. OPF-Based Optimal Location of Two Systems Two Terminal HVDC to Power System Optimal Operation

    Directory of Open Access Journals (Sweden)

    Mehdi Abolfazli

    2013-04-01

    Full Text Available In this paper a suitable mathematical model of the two terminal HVDC system is provided for optimal power flow (OPF and optimal location based on OPF such power injection model. The ability of voltage source converter (VSC-based HVDC to independently control active and reactive power is well represented by the model. The model is used to develop an OPF-based optimal location algorithm of two systems two terminal HVDC to minimize the total fuel cost and active power losses as objective function. The optimization framework is modeled as non-linear programming (NLP and solved by Matlab and GAMS softwares. The proposed algorithm is implemented on the IEEE 14- and 30-bus test systems. The simulation results show ability of two systems two terminal HVDC in improving the power system operation. Furthermore, two systems two terminal HVDC is compared by PST and OUPFC in the power system operation from economical and technical aspects.

  12. Lifecycle-Based Swarm Optimization Method for Numerical Optimization

    Directory of Open Access Journals (Sweden)

    Hai Shen

    2014-01-01

    Full Text Available Bioinspired optimization algorithms have been widely used to solve various scientific and engineering problems. Inspired by biological lifecycle, this paper presents a novel optimization algorithm called lifecycle-based swarm optimization (LSO. Biological lifecycle includes four stages: birth, growth, reproduction, and death. With this process, even though individual organism died, the species will not perish. Furthermore, species will have stronger ability of adaptation to the environment and achieve perfect evolution. LSO simulates Biological lifecycle process through six optimization operators: chemotactic, assimilation, transposition, crossover, selection, and mutation. In addition, the spatial distribution of initialization population meets clumped distribution. Experiments were conducted on unconstrained benchmark optimization problems and mechanical design optimization problems. Unconstrained benchmark problems include both unimodal and multimodal cases the demonstration of the optimal performance and stability, and the mechanical design problem was tested for algorithm practicability. The results demonstrate remarkable performance of the LSO algorithm on all chosen benchmark functions when compared to several successful optimization techniques.

  13. Optimal distribution of reactivity excess in a system of reactors operating at a variable loading schedule

    International Nuclear Information System (INIS)

    Bolsunov, A.A.; Zagrebaev, A.M.; Naumov, V.I.

    1979-01-01

    Considered is the task of reactivity excess distribution optimization in the system of reactors for the purpose of minimazing the summary power production losses at the fixed loading schedule. Mathematical formulation of the task is presented. Given are the curves, characterizing the dependence of possible degree of the reactor power drop on reactivity excees for non-stationary Xe poisoning at different nominal density of neutron flux. Analyzing the results, it is concluded that in case, when the reactors differ only in neutron flux density the reactor with lower neutron flux density should be involved in the variable operation schedule first as the poisoning of this reactor will be less, and therefore, the losses of the system power production will be less. It is advisable to reserve the reactivity excess in the reactor with greater power or in the reactor with higher burnup rate. It is stressed that the obtained results of the optimization task solution point out the possibility of obtaining the certain ecomonic effect and permit to correct the requirements on mobility of separate power units at system approach to NPP operation in a variable loading schedule

  14. Photo-Electrochemical Treatment of Reactive Dyes in Wastewater and Reuse of the Effluent: Method Optimization

    Science.gov (United States)

    Sala, Mireia; López-Grimau, Víctor; Gutiérrez-Bouzán, Carmen

    2014-01-01

    In this work, the efficiency of a photo-electrochemical method to remove color in textile dyeing effluents is discussed. The decolorization of a synthetic effluent containing a bi-functional reactive dye was carried out by applying an electrochemical treatment at different intensities (2 A, 5 A and 10 A), followed by ultraviolet irradiation. The combination of both treatments was optimized. The final percentage of effluent decolorization, the reduction of halogenated organic volatile compound and the total organic carbon removal were the determinant factors in the selection of the best treatment conditions. The optimized method was applied to the treatment of nine simulated dyeing effluents prepared with different reactive dyes in order to compare the behavior of mono, bi, and tri-reactive dyes. Finally, the nine treated effluents were reused in new dyeing processes and the color differences (DECMC (2:1)) with respect to a reference were evaluated. The influence of the effluent organic matter removal on the color differences was also studied. The reuse of the treated effluents provides satisfactory dyeing results, and an important reduction in water consumption and salt discharge is achieved. PMID:28788251

  15. Reliability-Based Optimization in Structural Engineering

    DEFF Research Database (Denmark)

    Enevoldsen, I.; Sørensen, John Dalsgaard

    1994-01-01

    In this paper reliability-based optimization problems in structural engineering are formulated on the basis of the classical decision theory. Several formulations are presented: Reliability-based optimal design of structural systems with component or systems reliability constraints, reliability...

  16. A DFIG Islanding Detection Scheme Based on Reactive Power Infusion

    Science.gov (United States)

    Wang, M.; Liu, C.; He, G. Q.; Li, G. H.; Feng, K. H.; Sun, W. W.

    2017-07-01

    A lot of research has been done on photovoltaic (the “PV”) power system islanding detection in recent years. As a comparison, much less attention has been paid to islanding in wind turbines. Meanwhile, wind turbines can work in islanding conditions for quite a long period, which can be harmful to equipments and cause safety hazards. This paper presents and examines a double fed introduction generation (the “DFIG”) islanding detection scheme based on feedback of reactive power and frequency and uses a trigger signal of reactive power infusion which can be obtained by dividing the voltage total harmonic distortion (the "THD") by the voltage THD of last cycle to avoid the deterioration of power quality. This DFIG islanding detection scheme uses feedback of reactive power current loop to amplify the frequency differences in islanding and normal conditions. Simulation results show that the DFIG islanding detection scheme is effective.

  17. Optimal separable bases and molecular collisions

    International Nuclear Information System (INIS)

    Poirier, L.W.

    1997-12-01

    A new methodology is proposed for the efficient determination of Green's functions and eigenstates for quantum systems of two or more dimensions. For a given Hamiltonian, the best possible separable approximation is obtained from the set of all Hilbert space operators. It is shown that this determination itself, as well as the solution of the resultant approximation, are problems of reduced dimensionality for most systems of physical interest. Moreover, the approximate eigenstates constitute the optimal separable basis, in the sense of self-consistent field theory. These distorted waves give rise to a Born series with optimized convergence properties. Analytical results are presented for an application of the method to the two-dimensional shifted harmonic oscillator system. The primary interest however, is quantum reactive scattering in molecular systems. For numerical calculations, the use of distorted waves corresponds to numerical preconditioning. The new methodology therefore gives rise to an optimized preconditioning scheme for the efficient calculation of reactive and inelastic scattering amplitudes, especially at intermediate energies. This scheme is particularly suited to discrete variable representations (DVR's) and iterative sparse matrix methods commonly employed in such calculations. State to state and cumulative reactive scattering results obtained via the optimized preconditioner are presented for the two-dimensional collinear H + H 2 → H 2 + H system. Computational time and memory requirements for this system are drastically reduced in comparison with other methods, and results are obtained for previously prohibitive energy regimes

  18. Reliability-based optimization of engineering structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2008-01-01

    The theoretical basis for reliability-based structural optimization within the framework of Bayesian statistical decision theory is briefly described. Reliability-based cost benefit problems are formulated and exemplitied with structural optimization. The basic reliability-based optimization...... problems are generalized to the following extensions: interactive optimization, inspection and repair costs, systematic reconstruction, re-assessment of existing structures. Illustrative examples are presented including a simple introductory example, a decision problem related to bridge re...

  19. Optimization of Reactive Blue 21 removal by Nanoscale Zero-Valent Iron using response surface methodology

    Directory of Open Access Journals (Sweden)

    Mahmood Reza Sohrabi

    2016-07-01

    Full Text Available Since Reactive Blue 21 (RB21 is one of the dye compounds which is harmful to human life, a simple and sensitive method to remove this pollutant from wastewater is using Nano Zero-Valent Iron (NZVI catalyst. In this paper, a Central Composite Rotatable Design (CCRD was employed for response surface modeling to optimize experimental conditions of the RB21 removal from aqueous solution. The significance and adequacy of the model were analyzed using analysis of variance (ANOVA. Four independent variables—including catalyst amount (0.1–0.9 g, pH (3.5–9.5, removal time (30–150 s and dye concentration (10–50 mg/L—were transformed to coded values and consequently second order quadratic model was built to predict the responses. The result showed that under optimized experimental conditions the removal of RB21 was over 95%.

  20. New Enhanced Artificial Bee Colony (JA-ABC5 Algorithm with Application for Reactive Power Optimization

    Directory of Open Access Journals (Sweden)

    Noorazliza Sulaiman

    2015-01-01

    Full Text Available The standard artificial bee colony (ABC algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement.

  1. New enhanced artificial bee colony (JA-ABC5) algorithm with application for reactive power optimization.

    Science.gov (United States)

    Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

    2015-01-01

    The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement.

  2. A New Approach to Optimal Allocation of Reactive Power Ancillary Service in Distribution Systems in the Presence of Distributed Energy Resources

    Directory of Open Access Journals (Sweden)

    Abouzar Samimi

    2015-11-01

    Full Text Available One of the most important Distribution System Operators (DSO schemes addresses the Volt/Var control (VVC problem. Developing a cost-based reactive power dispatch model for distribution systems, in which the reactive powers are appropriately priced, can motivate Distributed Energy Resources (DERs to participate actively in VVC. In this paper, new reactive power cost models for DERs, including synchronous machine-based DGs and wind turbines (WTs, are formulated based on their capability curves. To address VVC in the context of competitive electricity markets in distribution systems, first, in a day-ahead active power market, the initial active power dispatch of generation units is estimated considering environmental and economic aspects. Based on the results of the initial active power dispatch, the proposed VVC model is executed to optimally allocate reactive power support among all providers. Another novelty of this paper lies in the pricing scheme that rewards transformers and capacitors for tap and step changing, respectively, while incorporating the reactive power dispatch model. A Benders decomposition algorithm is employed as a solution method to solve the proposed reactive power dispatch, which is a mixed integer non-linear programming (MINLP problem. Finally, a typical 22-bus distribution network is used to verify the efficiency of the proposed method.

  3. The Ontology of Knowledge Based Optimization

    OpenAIRE

    Nasution, Mahyuddin K. M.

    2012-01-01

    Optimization has been becoming a central of studies in mathematic and has many areas with different applications. However, many themes of optimization came from different area have not ties closing to origin concepts. This paper is to address some variants of optimization problems using ontology in order to building basic of knowledge about optimization, and then using it to enhance strategy to achieve knowledge based optimization.

  4. OPTIMIZATION OF REACTIVE BLUE 19 DECOLORIZATION BY GANODERMA SP. USING RESPONSE SURFACE METHODOLOGY

    Directory of Open Access Journals (Sweden)

    1M. Mohammadian Fazli, *1A. R. Mesdaghinia, 1K. Naddafi, 1S. Nasseri , 1M. Yunesian, 2M. Mazaheri Assadi, 3S. Rezaie, 4H. Hamzehei

    2010-01-01

    Full Text Available Synthetic dyes are extensively used in different industries. Dyes have adverse impacts such as visual effects, chemical oxygen demand, toxicity, mutagenicity and carcinogenicity characteristics. White rot fungi, due to extracellular enzyme system, are capable to degrade dyes and various xenobiotics. The aim of this study was to optimize decolorization of reactive blue 19 (RB19 dye using Ganoderma sp. fungus. Response Surface Methodology (RSM was used to study the effect of independent variables, namely glycerol concentration (15, 20 and 25 g/L, temperature (27, 30 and 33 oC and pH (5.5, 6.0 and 6.5 on color removal efficiency in aqueous solution. From RSM-generated model, the optimum conditions for RB19 decolorization were identified to be at temperature of 27oC, glycerol concentration of 19.14 mg/L and pH=6.3. At the optimum conditions, predicted decolorization was 95.3 percent. The confirmatory experiments were conducted and confirmed the results by 94.89% color removal. Thus, this statistical approach enabled to improve reactive blue 19 decolorization process by Ganoderma sp. up to 1.27 times higher than non-optimized conditions.

  5. Solving multiobjective optimal reactive power dispatch using modified NSGA-II

    Energy Technology Data Exchange (ETDEWEB)

    Jeyadevi, S.; Baskar, S.; Babulal, C.K.; Willjuice Iruthayarajan, M. [Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai, Tamilnadu 625 015 (India)

    2011-02-15

    This paper addresses an application of modified NSGA-II (MNSGA-II) by incorporating controlled elitism and dynamic crowding distance (DCD) strategies in NSGA-II to multiobjective optimal reactive power dispatch (ORPD) problem by minimizing real power loss and maximizing the system voltage stability. To validate the Pareto-front obtained using MNSGA-II, reference Pareto-front is generated using multiple runs of single objective optimization with weighted sum of objectives. For simulation purposes, IEEE 30 and IEEE 118 bus test systems are considered. The performance of MNSGA-II, NSGA-II and multiobjective particle swarm optimization (MOPSO) approaches are compared with respect to multiobjective performance measures. TOPSIS technique is applied on obtained non-dominated solutions to determine best compromise solution (BCS). Karush-Kuhn-Tucker (KKT) conditions are also applied on the obtained non-dominated solutions to substantiate a claim on optimality. Simulation results are quite promising and the MNSGA-II performs better than NSGA-II in maintaining diversity and authenticates its potential to solve multiobjective ORPD effectively. (author)

  6. Coordinated Volt/Var Control in Distribution Systems with Distributed Generations Based on Joint Active and Reactive Powers Dispatch

    Directory of Open Access Journals (Sweden)

    Abouzar Samimi

    2016-01-01

    Full Text Available One of the most significant control schemes in optimal operation of distribution networks is Volt/Var control (VVC. Owing to the radial structure of distribution systems and distribution lines with a small X/R ratio, the active power scheduling affects the VVC issue. A Distribution System Operator (DSO procures its active and reactive power requirements from Distributed Generations (DGs along with the wholesale electricity market. This paper proposes a new operational scheduling method based on a joint day-ahead active/reactive power market at the distribution level. To this end, based on the capability curve, a generic reactive power cost model for DGs is developed. The joint active/reactive power dispatch model presented in this paper motivates DGs to actively participate not only in the energy markets, but also in the VVC scheme through a competitive market. The proposed method which will be performed in an offline manner aims to optimally determine (i the scheduled active and reactive power values of generation units; (ii reactive power values of switched capacitor banks; and (iii tap positions of transformers for the next day. The joint active/reactive power dispatch model for daily VVC is modeled in GAMS and solved with the DICOPT solver. Finally, the plausibility of the proposed scheduling framework is examined on a typical 22-bus distribution test network over a 24-h period.

  7. Reactive Distillation for Esterification of Bio-based Organic Acids

    Energy Technology Data Exchange (ETDEWEB)

    Fields, Nathan; Miller, Dennis J.; Asthana, Navinchandra S.; Kolah, Aspi K.; Vu, Dung; Lira, Carl T.

    2008-09-23

    The following is the final report of the three year research program to convert organic acids to their ethyl esters using reactive distillation. This report details the complete technical activities of research completed at Michigan State University for the period of October 1, 2003 to September 30, 2006, covering both reactive distillation research and development and the underlying thermodynamic and kinetic data required for successful and rigorous design of reactive distillation esterification processes. Specifically, this project has led to the development of economical, technically viable processes for ethyl lactate, triethyl citrate and diethyl succinate production, and on a larger scale has added to the overall body of knowledge on applying fermentation based organic acids as platform chemicals in the emerging biorefinery. Organic acid esters constitute an attractive class of biorenewable chemicals that are made from corn or other renewable biomass carbohydrate feedstocks and replace analogous petroleum-based compounds, thus lessening U.S. dependence on foreign petroleum and enhancing overall biorefinery viability through production of value-added chemicals in parallel with biofuels production. Further, many of these ester products are candidates for fuel (particularly biodiesel) components, and thus will serve dual roles as both industrial chemicals and fuel enhancers in the emerging bioeconomy. The technical report from MSU is organized around the ethyl esters of four important biorenewables-based acids: lactic acid, citric acid, succinic acid, and propionic acid. Literature background on esterification and reactive distillation has been provided in Section One. Work on lactic acid is covered in Sections Two through Five, citric acid esterification in Sections Six and Seven, succinic acid in Section Eight, and propionic acid in Section Nine. Section Ten covers modeling of ester and organic acid vapor pressure properties using the SPEAD (Step Potential

  8. Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method

    DEFF Research Database (Denmark)

    Chen, Shuheng; Hu, Weihao; Su, Chi

    2015-01-01

    A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid PSO (FAHPSO) is proposed. The objective is to minimize comprehensive cost, consisting of power loss and operation cost of transformers...... that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods....... algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33-node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove...

  9. Improvements of the base bleed effect using reactive particles

    Energy Technology Data Exchange (ETDEWEB)

    Bournot, Herve; Daniel, Eric [Polytech' Marseille, IUSTI UMR CNRS 6595, 5, rue E. Fermi, Technopole de Chateau Gombert, 13453 Marseille cedex 13 (France); Cayzac, Roxan [Giat Industries, 7, Route de Guerry, F-18023 Bourges cedex (France)

    2006-11-15

    A numerical study of the base drag reduction of axisymmetric body projectiles in supersonic flight using a base bleed injection is presented in this paper. Unsteady computations of compressible viscous flow have been achieved in order to investigate the coupled effect of the bleed temperature and the bleed mass flow rate on the base pressure. The idea developed in the study, consists in the addition of metallic particles in the propellant composition used to provide the additional mass injected in order to obtain the lowest base drag. Indeed, for a low mass addition, a significant increase of the mixture energy is expected due to the particles combustion. Base flow with reactive two-phase injection is then simulated. Results show the ability of the method to describe such flows and the efficiency of the particles combustion to increase the base bleed reducing drag effect. (author)

  10. An OPF based approach for assessing the minimal reactive power support for generators in deregulated power systems

    International Nuclear Information System (INIS)

    Wu, H.; Yu, C.W.; Xu, N.; Lin, X.J.

    2008-01-01

    Reactive power support is an important ancillary service for secure and reliable operation in power markets. It has recently been recognized that the reactive power support for a generator has two components: one for supporting its own real power transmission and the other for supplying reactive demand, improving system security, and controlling system voltage; and that only the second part should receive financial compensation in competitive power markets. This makes the problem of separating these two components a new focus of current research. An OPF based reactive power optimization model along with a power flow tracing based method is proposed in this paper to tackle this problem. The methodology is tested on four test systems. Detailed analysis of the results of the 39-bus test system is reported. (author)

  11. Optimal stochastic reactive power scheduling in a microgrid considering voltage droop scheme of DGs and uncertainty of wind farms

    International Nuclear Information System (INIS)

    Khorramdel, Benyamin; Raoofat, Mahdi

    2012-01-01

    Distributed Generators (DGs) in a microgrid may operate in three different reactive power control strategies, including PV, PQ and voltage droop schemes. This paper proposes a new stochastic programming approach for reactive power scheduling of a microgrid, considering the uncertainty of wind farms. The proposed algorithm firstly finds the expected optimal operating point of each DG in V-Q plane while the wind speed is a probabilistic variable. A multi-objective function with goals of loss minimization, reactive power reserve maximization and voltage security margin maximization is optimized using a four-stage multi-objective nonlinear programming. Then, using Monte Carlo simulation enhanced by scenario reduction technique, the proposed algorithm simulates actual condition and finds optimal operating strategy of DGs. Also, if any DGs are scheduled to operate in voltage droop scheme, the optimum droop is determined. Also, in the second part of the research, to enhance the optimality of the results, PSO algorithm is used for the multi-objective optimization problem. Numerical examples on IEEE 34-bus test system including two wind turbines are studied. The results show the benefits of voltage droop scheme for mitigating the impacts of the uncertainty of wind. Also, the results show preference of PSO method in the proposed approach. -- Highlights: ► Reactive power scheduling in a microgrid considering loss and voltage security. ► Stochastic nature of wind farms affects reactive power scheduling and is considered. ► Advantages of using the voltage droop characteristics of DGs in voltage security are shown. ► Power loss, voltage security and VAR reserve are three goals of a multi-objective optimization. ► Monte Carlo method with scenario reduction is used to determine optimal control strategy of DGs.

  12. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....

  13. A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

    DEFF Research Database (Denmark)

    Sousa, Tiago; Morais, Hugo; Vale, Zita

    2015-01-01

    In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power...... at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power...... scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present...

  14. Visual Programming of Subsumption-Based Reactive Behaviour

    Directory of Open Access Journals (Sweden)

    Omid Banyasad

    2008-11-01

    Full Text Available General purpose visual programming languages (VPLs promote the construction of programs that are more comprehensible, robust, and maintainable by enabling programmers to directly observe and manipulate algorithms and data. However, they usually do not exploit the visual representation of entities in the problem domain, even if those entities and their interactions have obvious visual representations, as is the case in the robot control domain. We present a formal control model for autonomous robots, based on subsumption, and use it as the basis for a VPL in which reactive behaviour is programmed via interactions with a simulation.

  15. Unifying Model-Based and Reactive Programming within a Model-Based Executive

    Science.gov (United States)

    Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

    1999-01-01

    Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

  16. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha

    2013-11-25

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  17. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  18. A hybrid bird mating optimizer algorithm with teaching-learning-based optimization for global numerical optimization

    Directory of Open Access Journals (Sweden)

    Qingyang Zhang

    2015-02-01

    Full Text Available Bird Mating Optimizer (BMO is a novel meta-heuristic optimization algorithm inspired by intelligent mating behavior of birds. However, it is still insufficient in convergence of speed and quality of solution. To overcome these drawbacks, this paper proposes a hybrid algorithm (TLBMO, which is established by combining the advantages of Teaching-learning-based optimization (TLBO and Bird Mating Optimizer (BMO. The performance of TLBMO is evaluated on 23 benchmark functions, and compared with seven state-of-the-art approaches, namely BMO, TLBO, Artificial Bee Bolony (ABC, Particle Swarm Optimization (PSO, Fast Evolution Programming (FEP, Differential Evolution (DE, Group Search Optimization (GSO. Experimental results indicate that the proposed method performs better than other existing algorithms for global numerical optimization.

  19. Reliability Based Optimization of Structural Systems

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    1987-01-01

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

  20. Operational experience with reactive power control methods optimized for tokamak power supplies

    International Nuclear Information System (INIS)

    Sihler, C.; Huart, M.; Kaesemann, C.-P.; Streibl, B.

    2003-01-01

    The power and energy of the ASDEX Upgrade (AUG) tokamak are provided by two separate 10.5 kV, 110-85 Hz networks based on the flywheel generators EZ3-EZ4 in addition to the generator EZ2 dedicated to the toroidal field coil. The 10.5 kV networks supply the thyristor converters allowing fast control of the DC currents in the AUG poloidal field coils. Two methods for improving the load power factor in the present experimental campaign of AUG have been investigated, namely the control of the phase-to-neutral voltage in thyristor converters fitted with neutral thyristors, such as the new 145 MVA modular thyristor converter system (Group 6), and reactive power control achieved by means of static VAr compensators (SVC). The paper shows that reliable compensation up to 90 MVAr was regularly achieved and that electrical transients in SVC modules can be kept at an acceptable level. The paper will discuss the results from the reactive power reduction by SVC and neutral thyristor control and draw a comparative conclusion

  1. A Data-Driven Stochastic Reactive Power Optimization Considering Uncertainties in Active Distribution Networks and Decomposition Method

    DEFF Research Database (Denmark)

    Ding, Tao; Yang, Qingrun; Yang, Yongheng

    2018-01-01

    To address the uncertain output of distributed generators (DGs) for reactive power optimization in active distribution networks, the stochastic programming model is widely used. The model is employed to find an optimal control strategy with minimum expected network loss while satisfying all......, in this paper, a data-driven modeling approach is introduced to assume that the probability distribution from the historical data is uncertain within a confidence set. Furthermore, a data-driven stochastic programming model is formulated as a two-stage problem, where the first-stage variables find the optimal...... control for discrete reactive power compensation equipment under the worst probability distribution of the second stage recourse. The second-stage variables are adjusted to uncertain probability distribution. In particular, this two-stage problem has a special structure so that the second-stage problem...

  2. Development of polylactic acid-based materials through reactive modification

    Science.gov (United States)

    Fowlks, Alison Camille

    2009-12-01

    Polylactic acid (PLA)-based systems have shown to be of great potential for the development of materials requiring biobased content, biodegradation, and sufficient properties. The efforts in this study are directed toward addressing the current research need to overcome some of the inherent drawbacks of PLA. To meet this need, reactive extrusion was employed to develop new materials based on PLA by grafting, compounding, and polymer blending. In the first part of this work, maleic anhydride (MA) was grafted onto PLA by reactive extrusion. Two structurally different peroxides were used to initiate grafting and results were reported on the basis of grafting, molecular weight, and thermal behavior. An inverse relationship between degree of grafting and molecular weight was established. It was also found that, regardless of peroxide type, there is an optimum peroxid-to-MA ratio of 0.5:2 that promotes maximum grafting, beyond which degradation reactions become predominant. Overall, it was found that the maleated copolymer (MAPLA) could be used as an interfacial modifier in PLA-based composites. Therefore, MAPLA was incorporated into PLA-talc composites in varying concentrations. The influence of the MAPLA addition on the mechanical and thermal behavior was investigated. When added in an optimum concentration, MAPLA improved the tensile strength and crystallization of the composite. Furthermore, microscopic observation confirmed the compatibilization effect of MAPLA in PLA-talc composites. Vinyltrimethoxysilane was free-radically grafted onto the backbone of PLA and subsequently moisture crosslinked. The effects of monomer, initiator, and catalyst concentration on the degree of crosslinking and the mechanical and thermal properties were investigated. The presence of a small amount of catalyst showed to be a major contributor to the crosslinking formation in the time frame investigated, shown by an increase in gel content and decrease in crystallinity. Furthermore

  3. Reliability Based Optimization of Fire Protection

    DEFF Research Database (Denmark)

    Thoft-Christensen, Palle

    fire protection (PFP) of firewalls and structural members. The paper is partly based on research performed within the EU supported research project B/E-4359 "Optimized Fire Safety of Offshore Structures" and partly on research supported by the Danish Technical Research Council (see Thoft-Christensen [1......]). Special emphasis is put on the optimization software developed within the project.......It is well known that fire is one of the major risks of serious damage or total loss of several types of structures such as nuclear installations, buildings, offshore platforms/topsides etc. This paper presents a methodology and software for reliability based optimization of the layout of passive...

  4. Flavours of XChange, a Rule-Based Reactive Language for the (Semantic) Web

    OpenAIRE

    Bailey, James; Bry, François; Eckert, Michael; Patrânjan, Paula Lavinia

    2005-01-01

    This article introduces XChange, a rule-based reactive language for the Web. Stressing application scenarios, it first argues that high-level reactive languages are needed for bothWeb and SemanticWeb applications. Then, it discusses technologies and paradigms relevant to high-level reactive languages for the (Semantic) Web. Finally, it presents the Event-Condition-Action rules of XChange.

  5. Web-based reactive transport modeling using PFLOTRAN

    Science.gov (United States)

    Zhou, H.; Karra, S.; Lichtner, P. C.; Versteeg, R.; Zhang, Y.

    2017-12-01

    Actionable understanding of system behavior in the subsurface is required for a wide spectrum of societal and engineering needs by both commercial firms and government entities and academia. These needs include, for example, water resource management, precision agriculture, contaminant remediation, unconventional energy production, CO2 sequestration monitoring, and climate studies. Such understanding requires the ability to numerically model various coupled processes that occur across different temporal and spatial scales as well as multiple physical domains (reservoirs - overburden, surface-subsurface, groundwater-surface water, saturated-unsaturated zone). Currently, this ability is typically met through an in-house approach where computational resources, model expertise, and data for model parameterization are brought together to meet modeling needs. However, such an approach has multiple drawbacks which limit the application of high-end reactive transport codes such as the Department of Energy funded[?] PFLOTRAN code. In addition, while many end users have a need for the capabilities provided by high-end reactive transport codes, they do not have the expertise - nor the time required to obtain the expertise - to effectively use these codes. We have developed and are actively enhancing a cloud-based software platform through which diverse users are able to easily configure, execute, visualize, share, and interpret PFLOTRAN models. This platform consists of a web application and available on-demand HPC computational infrastructure. The web application consists of (1) a browser-based graphical user interface which allows users to configure models and visualize results interactively, and (2) a central server with back-end relational databases which hold configuration, data, modeling results, and Python scripts for model configuration, and (3) a HPC environment for on-demand model execution. We will discuss lessons learned in the development of this platform, the

  6. Genetic algorithm based separation cascade optimization

    International Nuclear Information System (INIS)

    Mahendra, A.K.; Sanyal, A.; Gouthaman, G.; Bera, T.K.

    2008-01-01

    The conventional separation cascade design procedure does not give an optimum design because of squaring-off, variation of flow rates and separation factor of the element with respect to stage location. Multi-component isotope separation further complicates the design procedure. Cascade design can be stated as a constrained multi-objective optimization. Cascade's expectation from the separating element is multi-objective i.e. overall separation factor, cut, optimum feed and separative power. Decision maker may aspire for more comprehensive multi-objective goals where optimization of cascade is coupled with the exploration of separating element optimization vector space. In real life there are many issues which make it important to understand the decision maker's perception of cost-quality-speed trade-off and consistency of preferences. Genetic algorithm (GA) is one such evolutionary technique that can be used for cascade design optimization. This paper addresses various issues involved in the GA based multi-objective optimization of the separation cascade. Reference point based optimization methodology with GA based Pareto optimality concept for separation cascade was found pragmatic and promising. This method should be explored, tested, examined and further developed for binary as well as multi-component separations. (author)

  7. Entrainer-based reactive distillation versus conventional reactive distillation for the synthesis of fatty acid esters

    NARCIS (Netherlands)

    Jong, de M.C.; Dimian, A.C.; Haan, de A.B.

    2008-01-01

    In this paper different reactive distillation configurations for the synthesis of isopropyl myristate were compared with the use of process models made in Aspen Plus. It can be concluded that the configurations in which an entrainer is added are more capable to reach the required conversion of

  8. Development of a robust model-based reactivity control system

    International Nuclear Information System (INIS)

    Rovere, L.A.; Otaduy, P.J.; Brittain, C.R.

    1990-01-01

    This paper describes the development and implementation of a digital model-based reactivity control system that incorporates a knowledge of the plant physics into the control algorithm to improve system performance. This controller is composed of a model-based module and modified proportional-integral-derivative (PID) module. The model-based module has an estimation component to synthesize unmeasurable process variables that are necessary for the control action computation. These estimated variables, besides being used within the control algorithm, will be used for diagnostic purposes by a supervisory control system under development. The PID module compensates for inaccuracies in model coefficients by supplementing the model-based output with a correction term that eliminates any demand tracking or steady state errors. This control algorithm has been applied to develop controllers for a simulation of liquid metal reactors in a multimodular plant. It has shown its capability to track demands in neutron power much more accurately than conventional controllers, reducing overshoots to almost negligible value while providing a good degree of robustness to unmodeled dynamics. 10 refs., 4 figs

  9. Genetic algorithm based reactive power dispatch for voltage stability improvement

    Energy Technology Data Exchange (ETDEWEB)

    Devaraj, D. [Department of Electrical and Electronics, Kalasalingam University, Krishnankoil 626 190 (India); Roselyn, J. Preetha [Department of Electrical and Electronics, SRM University, Kattankulathur 603 203, Chennai (India)

    2010-12-15

    Voltage stability assessment and control form the core function in a modern energy control centre. This paper presents an improved Genetic algorithm (GA) approach for voltage stability enhancement. The proposed technique is based on the minimization of the maximum of L-indices of load buses. Generator voltages, switchable VAR sources and transformer tap changers are used as optimization variables of this problem. The proposed approach permits the optimization variables to be represented in their natural form in the genetic population. For effective genetic processing, the crossover and mutation operators which can directly deal with the floating point numbers and integers are used. The proposed algorithm has been tested on IEEE 30-bus and IEEE 57-bus test systems and successful results have been obtained. (author)

  10. Ultrafiltration technology with a ceramic membrane for reactive dye removal: optimization of membrane performance.

    Science.gov (United States)

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

    2012-03-30

    An ultrafiltration (UF) ceramic membrane was used to decolorize Reactive Black 5 (RB5) solutions at different dye concentrations (50 and 500 mg/L). Transmembrane pressure (TMP) and cross-flow velocity (CFV) were modified to study their influence on initial and steady-state permeate flux (J(p)) and dye rejection (R). Generally, J(p) increased with higher TMP and CFV and lower feed concentration, up to a maximum steady-state J(p) of 266.81 L/(m(2)h), obtained at 3 bar, 3m/s and 50mg/L. However, there was a TMP value (which changed depending on operating CFV and concentration) beyond which slight or no further increase in steady-state J(p) was observed. Similarly, the higher the CFV was, the more slightly the steady-state J(p) increased. Furthermore, the effectiveness of ultrafiltration treatment was evaluated through dye rejection coefficient. The results showed significant dye removals, regardless of the tested conditions, with steady-state R higher than 79.8% for the 50mg/L runs and around 73.2% for the 500 mg/L runs. Finally response surface methodology (RSM) was used to optimize membrane performance. At 50mg/L, a TMP of 4 bar and a CFV of 2.53 m/s were found to be the conditions giving the highest steady-state J(p), 255.86 L/(m(2)h), and the highest R, 95.2% simultaneously. Copyright © 2012 Elsevier B.V. All rights reserved.

  11. Development of GPT-based optimization algorithm

    International Nuclear Information System (INIS)

    White, J.R.; Chapman, D.M.; Biswas, D.

    1985-01-01

    The University of Lowell and Westinghouse Electric Corporation are involved in a joint effort to evaluate the potential benefits of generalized/depletion perturbation theory (GPT/DTP) methods for a variety of light water reactor (LWR) physics applications. One part of that work has focused on the development of a GPT-based optimization algorithm for the overall design, analysis, and optimization of LWR reload cores. The use of GPT sensitivity data in formulating the fuel management optimization problem is conceptually straightforward; it is the actual execution of the concept that is challenging. Thus, the purpose of this paper is to address some of the major difficulties, to outline our approach to these problems, and to present some illustrative examples of an efficient GTP-based optimization scheme

  12. Interactive Reliability-Based Optimal Design

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Thoft-Christensen, Palle; Siemaszko, A.

    1994-01-01

    Interactive design/optimization of large, complex structural systems is considered. The objective function is assumed to model the expected costs. The constraints are reliability-based and/or related to deterministic code requirements. Solution of this optimization problem is divided in four main...... tasks, namely finite element analyses, sensitivity analyses, reliability analyses and application of an optimization algorithm. In the paper it is shown how these four tasks can be linked effectively and how existing information on design variables, Lagrange multipliers and the Hessian matrix can...

  13. Optimized Reactive Power Flow of DFIG Power Converters for Better Reliability Performance Considering Grid Codes

    DEFF Research Database (Denmark)

    Zhou, Dao; Blaabjerg, Frede; Lau, Mogens

    2015-01-01

    . In order to fulfill the modern grid codes, over-excited reactive power injection will further reduce the lifetime of the rotor-side converter. In this paper, the additional stress of the power semiconductor due to the reactive power injection is firstly evaluated in terms of modulation index...

  14. Economic-environmental active and reactive power scheduling of modern distribution systems in presence of wind generations: A distribution market-based approach

    International Nuclear Information System (INIS)

    Samimi, Abouzar; Kazemi, Ahad; Siano, Pierluigi

    2015-01-01

    Highlights: • A new market-based approach is proposed to schedule active and reactive powers. • Multi-component reactive power bidding structures for DERs is introduced. • A new economical/environmental operational scheduling method is proposed. • At distribution level, a reactive power market is developed in presence of DERs. - Abstract: Distribution System Operator (DSO) is responsible for active and reactive power scheduling in a distribution system. DSO purchases its active and reactive power requirements from Distributed Energy Resources (DERs) as well as the wholesale electricity market. In this paper, a new economical/environmental operational scheduling method based on sequential day-ahead active and reactive power markets at distribution level is proposed to dispatch active and reactive powers in distribution systems with high penetration of DERs. In the proposed model, after day-ahead active power market was cleared the participants submit their reactive power bids and then the reactive power market will be settled. At distribution level, developing a Var market, in which DERs like synchronous machine-based Distributed Generation (DG) units and Wind Turbines (WTs) could offer their reactive power prices, DERs are motivated to actively participate in the Volt/VAr Control (VVC) problem. To achieve this purpose, based on the capability curves of considered DERs, innovative multi-component reactive power bidding structures for DERs are introduced. Moreover, the effect of reactive power market clearing on the active power scheduling is explicitly considered into the proposed model by rescheduling of active power by usage of energy-balance service bids. On the other hand, environmental concerns that arise from the operation of fossil fuel fired electric generators are included in the proposed model by employing CO_2 emission penalty cost. The suggested reactive power market is cleared through a mixed-integer nonlinear optimization program. The

  15. A Learning-Based Approach to Reactive Security

    Science.gov (United States)

    Barth, Adam; Rubinstein, Benjamin I. P.; Sundararajan, Mukund; Mitchell, John C.; Song, Dawn; Bartlett, Peter L.

    Despite the conventional wisdom that proactive security is superior to reactive security, we show that reactive security can be competitive with proactive security as long as the reactive defender learns from past attacks instead of myopically overreacting to the last attack. Our game-theoretic model follows common practice in the security literature by making worst-case assumptions about the attacker: we grant the attacker complete knowledge of the defender's strategy and do not require the attacker to act rationally. In this model, we bound the competitive ratio between a reactive defense algorithm (which is inspired by online learning theory) and the best fixed proactive defense. Additionally, we show that, unlike proactive defenses, this reactive strategy is robust to a lack of information about the attacker's incentives and knowledge.

  16. Nucleophilic stabilization of water-based reactive ink for titania-based thin film inkjet printing

    DEFF Research Database (Denmark)

    Gadea, Christophe; Marani, Debora; Esposito, Vincenzo

    2017-01-01

    Drop on demand deposition (DoD) of titanium oxide thin films (<500 nm) is performed via a novel titanium-alkoxide-based solution that is tailored as a reactive ink for inkjet printing. The ink is developed as water-based solution by a combined use of titanium isopropoxide and n-methyldiethanolami...

  17. Simulation-based optimization of thermal systems

    International Nuclear Information System (INIS)

    Jaluria, Yogesh

    2009-01-01

    This paper considers the design and optimization of thermal systems on the basis of the mathematical and numerical modeling of the system. Many complexities are often encountered in practical thermal processes and systems, making the modeling challenging and involved. These include property variations, complicated regions, combined transport mechanisms, chemical reactions, and intricate boundary conditions. The paper briefly presents approaches that may be used to accurately simulate these systems. Validation of the numerical model is a particularly critical aspect and is discussed. It is important to couple the modeling with the system performance, design, control and optimization. This aspect, which has often been ignored in the literature, is considered in this paper. Design of thermal systems based on concurrent simulation and experimentation is also discussed in terms of dynamic data-driven optimization methods. Optimization of the system and of the operating conditions is needed to minimize costs and improve product quality and system performance. Different optimization strategies that are currently used for thermal systems are outlined, focusing on new and emerging strategies. Of particular interest is multi-objective optimization, since most thermal systems involve several important objective functions, such as heat transfer rate and pressure in electronic cooling systems. A few practical thermal systems are considered in greater detail to illustrate these approaches and to present typical simulation, design and optimization results

  18. Effects of acid-base imbalance on vascular reactivity

    Directory of Open Access Journals (Sweden)

    A.C. Celotto

    2008-06-01

    Full Text Available Acid-base homeostasis maintains systemic arterial pH within a narrow range. Whereas the normal range of pH for clinical laboratories is 7.35-7.45, in vivo pH is maintained within a much narrower range. In clinical and experimental settings, blood pH can vary in response to respiratory or renal impairment. This altered pH promotes changes in vascular smooth muscle tone with impact on circulation and blood pressure control. Changes in pH can be divided into those occurring in the extracellular space (pHo and those occurring within the intracellular space (pHi, although, extracellular and intracellular compartments influence each other. Consistent with the multiple events involved in the changes in tone produced by altered pHo, including type of vascular bed, several factors and mechanisms, in addition to hydrogen ion concentration, have been suggested to be involved. The scientific literature has many reports concerning acid-base balance and endothelium function, but these concepts are not clear about acid-base disorders and their relations with the three known mechanisms of endothelium-dependent vascular reactivity: nitric oxide (NO/cGMP-dependent, prostacyclin (PGI2/cAMP-dependent and hyperpolarization. During the last decades, many studies have been published and have given rise to confronting data on acid-base disorder and endothelial function. Therefore, the main proposal of this review is to provide a critical analysis of the state of art and incentivate researchers to develop more studies about these issues.

  19. Coverage-based constraints for IMRT optimization

    Science.gov (United States)

    Mescher, H.; Ulrich, S.; Bangert, M.

    2017-09-01

    Radiation therapy treatment planning requires an incorporation of uncertainties in order to guarantee an adequate irradiation of the tumor volumes. In current clinical practice, uncertainties are accounted for implicitly with an expansion of the target volume according to generic margin recipes. Alternatively, it is possible to account for uncertainties by explicit minimization of objectives that describe worst-case treatment scenarios, the expectation value of the treatment or the coverage probability of the target volumes during treatment planning. In this note we show that approaches relying on objectives to induce a specific coverage of the clinical target volumes are inevitably sensitive to variation of the relative weighting of the objectives. To address this issue, we introduce coverage-based constraints for intensity-modulated radiation therapy (IMRT) treatment planning. Our implementation follows the concept of coverage-optimized planning that considers explicit error scenarios to calculate and optimize patient-specific probabilities q(\\hat{d}, \\hat{v}) of covering a specific target volume fraction \\hat{v} with a certain dose \\hat{d} . Using a constraint-based reformulation of coverage-based objectives we eliminate the trade-off between coverage and competing objectives during treatment planning. In-depth convergence tests including 324 treatment plan optimizations demonstrate the reliability of coverage-based constraints for varying levels of probability, dose and volume. General clinical applicability of coverage-based constraints is demonstrated for two cases. A sensitivity analysis regarding penalty variations within this planing study based on IMRT treatment planning using (1) coverage-based constraints, (2) coverage-based objectives, (3) probabilistic optimization, (4) robust optimization and (5) conventional margins illustrates the potential benefit of coverage-based constraints that do not require tedious adjustment of target volume objectives.

  20. Implementation of reactive and predictive real-time control strategies to optimize dry stormwater detention ponds

    Science.gov (United States)

    Gaborit, Étienne; Anctil, François; Vanrolleghem, Peter A.; Pelletier, Geneviève

    2013-04-01

    Dry detention ponds have been widely implemented in U.S.A (National Research Council, 1993) and Canada (Shammaa et al. 2002) to mitigate the impacts of urban runoff on receiving water bodies. The aim of such structures is to allow a temporary retention of the water during rainfall events, decreasing runoff velocities and volumes (by infiltration in the pond) as well as providing some water quality improvement from sedimentation. The management of dry detention ponds currently relies on static control through a fixed pre-designed limitation of their maximum outflow (Middleton and Barrett 2008), for example via a proper choice of their outlet pipe diameter. Because these ponds are designed for large storms, typically 1- or 2-hour duration rainfall events with return periods comprised between 5 and 100 years, one of their main drawbacks is that they generally offer almost no retention for smaller rainfall events (Middleton and Barrett 2008), which are by definition much more common. Real-Time Control (RTC) has a high potential for optimizing retention time (Marsalek 2005) because it allows adopting operating strategies that are flexible and hence more suitable to the prevailing fluctuating conditions than static control. For dry ponds, this would basically imply adapting the outlet opening percentage to maximize water retention time, while being able to open it completely for severe storms. This study developed several enhanced RTC scenarios of a dry detention pond located at the outlet of a small urban catchment near Québec City, Canada, following the previous work of Muschalla et al. (2009). The catchment's runoff quantity and TSS concentration were simulated by a SWMM5 model with an improved wash-off formulation. The control procedures rely on rainfall detection and measures of the pond's water height for the reactive schemes, and on rainfall forecasts in addition to these variables for the predictive schemes. The automatic reactive control schemes implemented

  1. 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.

  2. Auto-reactive T cells revised. Overestimation based on methodology?

    DEFF Research Database (Denmark)

    Thorlacius-Ussing, Gorm; Sørensen, Jesper F; Wandall, Hans H

    2015-01-01

    . Thus, T cell antigen reactivities identified with unmodified antigens in vitro may in part represent in vitro T cell activation against neo-epitopes and not true in vivo autoreactivity as postulated. This methodological problem may have implications for the interpretation of the frequent reporting...... methodology applied to document T cell reactivity against unmodified protein or peptide may lead to overinterpretation of the reported frequencies of autoreactive CD4+ and CD8+ T cells....

  3. Reliability-Based Optimization of Wind Turbines

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Tarp-Johansen, N.J.

    2004-01-01

    Reliability-based optimization of the main tower and monopile foundation of an offshore wind turbine is considered. Different formulations are considered of the objective function including benefits and building and failure costs of the wind turbine. Also different reconstruction policies in case...

  4. Performance-based Pareto optimal design

    NARCIS (Netherlands)

    Sariyildiz, I.S.; Bittermann, M.S.; Ciftcioglu, O.

    2008-01-01

    A novel approach for performance-based design is presented, where Pareto optimality is pursued. Design requirements may contain linguistic information, which is difficult to bring into computation or make consistent their impartial estimations from case to case. Fuzzy logic and soft computing are

  5. Demand response strategy management with active and reactive power incentive in the smart grid: a two-level optimization approach

    Directory of Open Access Journals (Sweden)

    Ryuto Shigenobu

    2017-05-01

    Full Text Available High penetration of distributed generators (DGs using renewable energy sources (RESs is raising some important issues in the operation of modern po­wer system. The output power of RESs fluctuates very steeply, and that include uncertainty with weather conditions. This situation causes voltage deviation and reverse power flow. Several methods have been proposed for solving these problems. Fundamentally, these methods involve reactive power control for voltage deviation and/or the installation of large battery energy storage system (BESS at the interconnection point for reverse power flow. In order to reduce the installation cost of static var compensator (SVC, Distribution Company (DisCo gives reactive power incentive to the cooperating customers. On the other hand, photovoltaic (PV generator, energy storage and electric vehicle (EV are introduced in customer side with the aim of achieving zero net energy homes (ZEHs. This paper proposes not only reactive power control but also active power flow control using house BESS and EV. Moreover, incentive method is proposed to promote participation of customers in the control operation. Demand response (DR system is verified with several DR menu. To create profit for both side of DisCo and customer, two level optimization approach is executed in this research. Mathematical modeling of price elasticity and detailed simulations are executed by case study. The effectiveness of the proposed incentive menu is demonstrated by using heuristic optimization method.

  6. Optimal Design for Reactivity Ratio Estimation: A Comparison of Techniques for AMPS/Acrylamide and AMPS/Acrylic Acid Copolymerizations

    Directory of Open Access Journals (Sweden)

    Alison J. Scott

    2015-11-01

    Full Text Available Water-soluble polymers of acrylamide (AAm and acrylic acid (AAc have significant potential in enhanced oil recovery, as well as in other specialty applications. To improve the shear strength of the polymer, a third comonomer, 2-acrylamido-2-methylpropane sulfonic acid (AMPS, can be added to the pre-polymerization mixture. Copolymerization kinetics of AAm/AAc are well studied, but little is known about the other comonomer pairs (AMPS/AAm and AMPS/AAc. Hence, reactivity ratios for AMPS/AAm and AMPS/AAc copolymerization must be established first. A key aspect in the estimation of reliable reactivity ratios is design of experiments, which minimizes the number of experiments and provides increased information content (resulting in more precise parameter estimates. However, design of experiments is hardly ever used during copolymerization parameter estimation schemes. In the current work, copolymerization experiments for both AMPS/AAm and AMPS/AAc are designed using two optimal techniques (Tidwell-Mortimer and the error-in-variables-model (EVM. From these optimally designed experiments, accurate reactivity ratio estimates are determined for AMPS/AAm (rAMPS = 0.18, rAAm = 0.85 and AMPS/AAc (rAMPS = 0.19, rAAc = 0.86.

  7. Parameter optimization toward optimal microneedle-based dermal vaccination.

    Science.gov (United States)

    van der Maaden, Koen; Varypataki, Eleni Maria; Yu, Huixin; Romeijn, Stefan; Jiskoot, Wim; Bouwstra, Joke

    2014-11-20

    Microneedle-based vaccination has several advantages over vaccination by using conventional hypodermic needles. Microneedles are used to deliver a drug into the skin in a minimally-invasive and potentially pain free manner. Besides, the skin is a potent immune organ that is highly suitable for vaccination. However, there are several factors that influence the penetration ability of the skin by microneedles and the immune responses upon microneedle-based immunization. In this study we assessed several different microneedle arrays for their ability to penetrate ex vivo human skin by using trypan blue and (fluorescently or radioactively labeled) ovalbumin. Next, these different microneedles and several factors, including the dose of ovalbumin, the effect of using an impact-insertion applicator, skin location of microneedle application, and the area of microneedle application, were tested in vivo in mice. The penetration ability and the dose of ovalbumin that is delivered into the skin were shown to be dependent on the use of an applicator and on the microneedle geometry and size of the array. Besides microneedle penetration, the above described factors influenced the immune responses upon microneedle-based vaccination in vivo. It was shown that the ovalbumin-specific antibody responses upon microneedle-based vaccination could be increased up to 12-fold when an impact-insertion applicator was used, up to 8-fold when microneedles were applied over a larger surface area, and up to 36-fold dependent on the location of microneedle application. Therefore, these influencing factors should be considered to optimize microneedle-based dermal immunization technologies. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Stability-index based method for optimal Var planning in distribution feeders

    International Nuclear Information System (INIS)

    Hamouda, Abdellatif; Zehar, Khaled

    2011-01-01

    Research highlights: → Optimal Var planning is modelled using heuristic methods. → Capacitor sizes and location are determined by a two stage method. → Capacitor locations are determined using nodes stability-indices. → Their sizes are calculated subject to a new constraint on the branches reactive currents. → The solution is fast and leads to better results without over compensation. -- Abstract: The problem of the reactive energy optimal planning can be solved in a fast and efficient way using heuristic techniques. The latter reduce the number of the control variables to be determined and lead to a near global optimal solution. The capacitor appropriate locations are firstly determined by decisive indices then, their optimal sizes are calculated. In this paper a stability-index based method is presented. The nodes stability-indices are calculated for identifying the most sensitive nodes to be candidate for receiving near optimal standard capacitors that, reduce the feeder power losses, improve the voltage profile and maximise the economic saving (objective function). In this multi-objective optimisation problem, the commonly used voltage constraint is substituted by a new constraint on the branch reactive currents. This new constraint, allows overcoming the over compensation phenomenon by setting positive branch reactive currents. The solution is further improved by regulating the source node voltage. The proposed approach has been tested on several feeder examples and its effectiveness has been demonstrated through comparative studies. The obtained results have shown that the proposed approach leads to a promising and feasible solution.

  9. Stability-index based method for optimal Var planning in distribution feeders

    Energy Technology Data Exchange (ETDEWEB)

    Hamouda, Abdellatif, E-mail: a_hamouda1@yahoo.f [QUERE Laboratory, Optics and Mechanics Institut, University Ferhat Abbas, Setif 19000 (Algeria); Zehar, Khaled [QUERE Laboratory, Department of Electrical and Electronics Engineering, University of Bahrain, Isa Town (Bahrain)

    2011-05-15

    Research highlights: {yields} Optimal Var planning is modelled using heuristic methods. {yields} Capacitor sizes and location are determined by a two stage method. {yields} Capacitor locations are determined using nodes stability-indices. {yields} Their sizes are calculated subject to a new constraint on the branches reactive currents. {yields} The solution is fast and leads to better results without over compensation. -- Abstract: The problem of the reactive energy optimal planning can be solved in a fast and efficient way using heuristic techniques. The latter reduce the number of the control variables to be determined and lead to a near global optimal solution. The capacitor appropriate locations are firstly determined by decisive indices then, their optimal sizes are calculated. In this paper a stability-index based method is presented. The nodes stability-indices are calculated for identifying the most sensitive nodes to be candidate for receiving near optimal standard capacitors that, reduce the feeder power losses, improve the voltage profile and maximise the economic saving (objective function). In this multi-objective optimisation problem, the commonly used voltage constraint is substituted by a new constraint on the branch reactive currents. This new constraint, allows overcoming the over compensation phenomenon by setting positive branch reactive currents. The solution is further improved by regulating the source node voltage. The proposed approach has been tested on several feeder examples and its effectiveness has been demonstrated through comparative studies. The obtained results have shown that the proposed approach leads to a promising and feasible solution.

  10. Priority Queue Based Reactive Buffer Management Policy for Delay Tolerant Network under City Based Environments.

    Directory of Open Access Journals (Sweden)

    Qaisar Ayub

    Full Text Available Delay Tolerant Network (DTN multi-copy routing protocols are privileged to create and transmit multiple copies of each message that causes congestion and some messages are dropped. This process is known as reactive drop because messages were dropped re-actively to overcome buffer overflows. The existing reactive buffer management policies apply a single metric to drop source, relay and destine messages. Hereby, selection to drop a message is dubious because each message as source, relay or destine may have consumed dissimilar magnitude of network resources. Similarly, DTN has included time to live (ttl parameter which defines lifetime of message. Hence, when ttl expires then message is automatically destroyed from relay nodes. However, time-to-live (ttl is not applicable on messages reached at their destinations. Moreover, nodes keep replicating messages till ttl expires even-though large number of messages has already been dispersed. In this paper, we have proposed Priority Queue Based Reactive Buffer Management Policy (PQB-R for DTN under City Based Environments. The PQB-R classifies buffered messages into source, relay and destine queues. Moreover, separate drop metric has been applied on individual queue. The experiment results prove that proposed PQB-R has reduced number of messages transmissions, message drop and increases delivery ratio.

  11. Priority Queue Based Reactive Buffer Management Policy for Delay Tolerant Network under City Based Environments.

    Science.gov (United States)

    Ayub, Qaisar; Ngadi, Asri; Rashid, Sulma; Habib, Hafiz Adnan

    2018-01-01

    Delay Tolerant Network (DTN) multi-copy routing protocols are privileged to create and transmit multiple copies of each message that causes congestion and some messages are dropped. This process is known as reactive drop because messages were dropped re-actively to overcome buffer overflows. The existing reactive buffer management policies apply a single metric to drop source, relay and destine messages. Hereby, selection to drop a message is dubious because each message as source, relay or destine may have consumed dissimilar magnitude of network resources. Similarly, DTN has included time to live (ttl) parameter which defines lifetime of message. Hence, when ttl expires then message is automatically destroyed from relay nodes. However, time-to-live (ttl) is not applicable on messages reached at their destinations. Moreover, nodes keep replicating messages till ttl expires even-though large number of messages has already been dispersed. In this paper, we have proposed Priority Queue Based Reactive Buffer Management Policy (PQB-R) for DTN under City Based Environments. The PQB-R classifies buffered messages into source, relay and destine queues. Moreover, separate drop metric has been applied on individual queue. The experiment results prove that proposed PQB-R has reduced number of messages transmissions, message drop and increases delivery ratio.

  12. Biogeography-Based Optimization with Orthogonal Crossover

    Directory of Open Access Journals (Sweden)

    Quanxi Feng

    2013-01-01

    Full Text Available Biogeography-based optimization (BBO is a new biogeography inspired, population-based algorithm, which mainly uses migration operator to share information among solutions. Similar to crossover operator in genetic algorithm, migration operator is a probabilistic operator and only generates the vertex of a hyperrectangle defined by the emigration and immigration vectors. Therefore, the exploration ability of BBO may be limited. Orthogonal crossover operator with quantization technique (QOX is based on orthogonal design and can generate representative solution in solution space. In this paper, a BBO variant is presented through embedding the QOX operator in BBO algorithm. Additionally, a modified migration equation is used to improve the population diversity. Several experiments are conducted on 23 benchmark functions. Experimental results show that the proposed algorithm is capable of locating the optimal or closed-to-optimal solution. Comparisons with other variants of BBO algorithms and state-of-the-art orthogonal-based evolutionary algorithms demonstrate that our proposed algorithm possesses faster global convergence rate, high-precision solution, and stronger robustness. Finally, the analysis result of the performance of QOX indicates that QOX plays a key role in the proposed algorithm.

  13. Optimization of binary breeder reactor. 1. Sodium void reactivity and Doppler effect in a new model

    International Nuclear Information System (INIS)

    Nascimento, J.A. do; Dias, A.F.; Ishiguro, Y.

    1985-01-01

    A model for the Binary Breeder Reactor (BBR) is examined for the inherent safety characteristics, sodium void reactivity and Doppler effect in the beginning of cycle and a hypothetical end of cycle. In addition to the standard fueling mode of the BBR, two others are considered: U 238 /U 233 -alternate fueling, and U 238 /PU-normal fueling of LMFBRs. (Author) [pt

  14. Optimal depth-based regional frequency analysis

    Directory of Open Access Journals (Sweden)

    H. Wazneh

    2013-06-01

    Full Text Available Classical methods of regional frequency analysis (RFA of hydrological variables face two drawbacks: (1 the restriction to a particular region which can lead to a loss of some information and (2 the definition of a region that generates a border effect. To reduce the impact of these drawbacks on regional modeling performance, an iterative method was proposed recently, based on the statistical notion of the depth function and a weight function φ. This depth-based RFA (DBRFA approach was shown to be superior to traditional approaches in terms of flexibility, generality and performance. The main difficulty of the DBRFA approach is the optimal choice of the weight function ϕ (e.g., φ minimizing estimation errors. In order to avoid a subjective choice and naïve selection procedures of φ, the aim of the present paper is to propose an algorithm-based procedure to optimize the DBRFA and automate the choice of ϕ according to objective performance criteria. This procedure is applied to estimate flood quantiles in three different regions in North America. One of the findings from the application is that the optimal weight function depends on the considered region and can also quantify the region's homogeneity. By comparing the DBRFA to the canonical correlation analysis (CCA method, results show that the DBRFA approach leads to better performances both in terms of relative bias and mean square error.

  15. Optimal depth-based regional frequency analysis

    Science.gov (United States)

    Wazneh, H.; Chebana, F.; Ouarda, T. B. M. J.

    2013-06-01

    Classical methods of regional frequency analysis (RFA) of hydrological variables face two drawbacks: (1) the restriction to a particular region which can lead to a loss of some information and (2) the definition of a region that generates a border effect. To reduce the impact of these drawbacks on regional modeling performance, an iterative method was proposed recently, based on the statistical notion of the depth function and a weight function φ. This depth-based RFA (DBRFA) approach was shown to be superior to traditional approaches in terms of flexibility, generality and performance. The main difficulty of the DBRFA approach is the optimal choice of the weight function ϕ (e.g., φ minimizing estimation errors). In order to avoid a subjective choice and naïve selection procedures of φ, the aim of the present paper is to propose an algorithm-based procedure to optimize the DBRFA and automate the choice of ϕ according to objective performance criteria. This procedure is applied to estimate flood quantiles in three different regions in North America. One of the findings from the application is that the optimal weight function depends on the considered region and can also quantify the region's homogeneity. By comparing the DBRFA to the canonical correlation analysis (CCA) method, results show that the DBRFA approach leads to better performances both in terms of relative bias and mean square error.

  16. Stress reactivity and personality in extreme sport athletes: The psychobiology of BASE jumpers.

    Science.gov (United States)

    Monasterio, Erik; Mei-Dan, Omer; Hackney, Anthony C; Lane, Amy R; Zwir, Igor; Rozsa, Sandor; Cloninger, C Robert

    2016-12-01

    This is the first report of the psychobiology of stress in BASE jumpers, one of the most dangerous forms of extreme sport. We tested the hypotheses that indicators of emotional style (temperament) predict salivary cortisol reactivity, whereas indicators of intentional goal-setting (persistence and character) predict salivary alpha-amylase reactivity during BASE jumping. Ninety-eight subjects completed the Temperament and Character Inventory (TCI) the day before the jump, and 77 also gave salivary samples at baseline, pre-jump on the bridge over the New River Gorge, and post-jump upon landing. Overall BASE jumpers are highly resilient individuals who are highly self-directed, persistent, and risk-taking, but they are heterogeneous in their motives and stress reactivity in the Hypothalamic-Pituitary-Adrenal (HPA) stress system (cortisol reactivity) and the sympathetic arousal system (alpha-amylase reactivity). Three classes of jumpers were identified using latent class analysis based on their personality profiles, prior jumping experience, and levels of cortisol and alpha-amylase at all three time points. "Masterful" jumpers (class 1) had a strong sense of self-directedness and mastery, extensive prior experience, and had little alpha-amylase reactivity and average cortisol reactivity. "Trustful" jumpers (class 2) were highly cooperative and trustful individuals who had little cortisol reactivity coincident with the social support they experienced prior to jumping. "Courageous" jumpers (class 3) were determined despite anxiety and inexperience, and they had high sympathetic reactivity but average cortisol activation. We conclude that trusting social attachment (Reward Dependence) and not jumping experience predicted low cortisol reactivity, whereas persistence (determination) and not jumping experience predicted high alpha-amylase reactivity. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Optimal interference code based on machine learning

    Science.gov (United States)

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

    2016-10-01

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

  18. Model-Based Testing of a Reactive System with Coloured Petri Nets

    DEFF Research Database (Denmark)

    Tjell, Simon

    2006-01-01

    In this paper, a reactive and nondeterministic system is tested. This is doneby applying a generic model that has been specified as a configurable Coloured PetriNet. In this way, model-based testing is possible for a wide class of reactive system atthe level of discrete events. Concurrently...

  19. An Optimized Reactive Power Control of Distributed Solar Inverters in Low Voltage Networks

    DEFF Research Database (Denmark)

    Demirok, Erhan; Sera, Dezso; Teodorescu, Remus

    2011-01-01

    This study examines the reactive power ancillary services of solar inverters which are connected to low voltage (LV) distribution networks by giving attention to the grid voltage support service and grid losses. Two typical reference LV distribution network models as suburban and farm...... are introduced from the literature in order to evaluate contribution of two static droop strategies cosφ(P) and Q(U) on the grid voltage. Photovoltaic (PV) hosting capacities of the suburban and farm networks are estimated and the most predominant limitations of connecting more solar inverters are emphasized...... for each network type. Regarding the overloading of MV/LV distribution transformers, overloading of lines and the grid overvoltage limitations, new local grid voltage support methods (cosφ(P,U) and Q(U,P)) are also proposed. Resulting maximum allowable penetration levels with different reactive power...

  20. Optimal Coordinated EV Charging with Reactive Power Support in Constrained Distribution Grids

    Energy Technology Data Exchange (ETDEWEB)

    Paudyal, Sumit; Ceylan, Oğuzhan; Bhattarai, Bishnu P.; Myers, Kurt S.

    2017-07-01

    Electric vehicle (EV) charging/discharging can take place in any P-Q quadrants, which means EVs could support reactive power to the grid while charging the battery. In controlled charging schemes, distribution system operator (DSO) coordinates with the charging of EV fleets to ensure grid’s operating constraints are not violated. In fact, this refers to DSO setting upper bounds on power limits for EV charging. In this work, we demonstrate that if EVs inject reactive power into the grid while charging, DSO could issue higher upper bounds on the active power limits for the EVs for the same set of grid constraints. We demonstrate the concept in an 33-node test feeder with 1,500 EVs. Case studies show that in constrained distribution grids in coordinated charging, average costs of EV charging could be reduced if the charging takes place in the fourth P-Q quadrant compared to charging with unity power factor.

  1. Two-layer optimization methodology for wind distributed generation planning considering plug-in electric vehicles uncertainty: A flexible active-reactive power approach

    International Nuclear Information System (INIS)

    Ahmadian, Ali; Sedghi, Mahdi; Aliakbar-Golkar, Masoud; Fowler, Michael; Elkamel, Ali

    2016-01-01

    Highlights: • Flexible active-reactive power control of WDGs is proposed for WDGs planning. • The uncertainty of PEVs effect is considered in WDGs planning. • The wind data is classified in four separate seasons to reach more accurate results. • The PSO algorithm is modified to overcome the complexity of problem. - Abstract: With increasing the penetration of wind power, the voltage regulation becomes a more important problem in active distribution networks. In addition, as an uncertain load Plug-in Electric Vehicles (PEVs) will introduce a new concern in voltage adjustment of future distribution networks. Hence, this paper presents a flexible active-reactive power based Wind Distributed Generation (WDG) planning procedure to address the mentioned challenges. The uncertainties related to WDGs, load demand as well as PEVs load have been handled using the Point Estimate Method (PEM). The distribution network under study is equipped to on-load tap-changer and, as a conventional voltage control component, the Capacitor Banks (CBs) will be planned simultaneously with WDGs. The planning procedure has been considered as a two-loop optimization problem that is solved using Particle Swarm Optimization (PSO) and Tabu Search (TS) algorithms. The tap position and power factor of WDGs are taken into account as stochastic variables with practical limitations. The proposed methodology is applied to a typical distribution network and several scenarios are considered and analyzed. Simulation results show that the standard deviation of power factor depends on PEVs penetration that highlights the capability curve of WDGs. The optimal penetration of wind power increases nonlinearly versus increasing of PEVs connected to the distribution network, however the fixed CBs are required to increase the optimal penetration of WDGs. The proposed Modified PSO (MPSO) is compared with the conventional PSO in numerical studies that show MPSO is more efficient than the conventional

  2. Risk-based optimization of land reclamation

    International Nuclear Information System (INIS)

    Lendering, K.T.; Jonkman, S.N.; Gelder, P.H.A.J.M. van; Peters, D.J.

    2015-01-01

    Large-scale land reclamations are generally constructed by means of a landfill well above mean sea level. This can be costly in areas where good quality fill material is scarce. An alternative to save materials and costs is a ‘polder terminal’. The quay wall acts as a flood defense and the terminal level is well below the level of the quay wall. Compared with a conventional terminal, the costs are lower, but an additional flood risk is introduced. In this paper, a risk-based optimization is developed for a conventional and a polder terminal. It considers the investment and residual flood risk. The method takes into account both the quay wall and terminal level, which determine the probability and damage of flooding. The optimal quay wall level is found by solving a Lambert function numerically. The terminal level is bounded by engineering boundary conditions, i.e. piping and uplift of the cover layer of the terminal yard. It is found that, for a representative case study, the saving of reclamation costs for a polder terminal is larger than the increase of flood risk. The model is applicable to other cases of land reclamation and to similar optimization problems in flood risk management. - Highlights: • A polder terminal can be an attractive alternative for a conventional terminal. • A polder terminal is feasible at locations with high reclamation cost. • A risk-based approach is required to determine the optimal protection levels. • The depth of the polder terminal yard is bounded by uplifting of the cover layer. • This paper can support decisions regarding alternatives for port expansions.

  3. Pixel-based OPC optimization based on conjugate gradients.

    Science.gov (United States)

    Ma, Xu; Arce, Gonzalo R

    2011-01-31

    Optical proximity correction (OPC) methods are resolution enhancement techniques (RET) used extensively in the semiconductor industry to improve the resolution and pattern fidelity of optical lithography. In pixel-based OPC (PBOPC), the mask is divided into small pixels, each of which is modified during the optimization process. Two critical issues in PBOPC are the required computational complexity of the optimization process, and the manufacturability of the optimized mask. Most current OPC optimization methods apply the steepest descent (SD) algorithm to improve image fidelity augmented by regularization penalties to reduce the complexity of the mask. Although simple to implement, the SD algorithm converges slowly. The existing regularization penalties, however, fall short in meeting the mask rule check (MRC) requirements often used in semiconductor manufacturing. This paper focuses on developing OPC optimization algorithms based on the conjugate gradient (CG) method which exhibits much faster convergence than the SD algorithm. The imaging formation process is represented by the Fourier series expansion model which approximates the partially coherent system as a sum of coherent systems. In order to obtain more desirable manufacturability properties of the mask pattern, a MRC penalty is proposed to enlarge the linear size of the sub-resolution assistant features (SRAFs), as well as the distances between the SRAFs and the main body of the mask. Finally, a projection method is developed to further reduce the complexity of the optimized mask pattern.

  4. Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

    2016-10-01

    The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

  5. PRODUCT OPTIMIZATION METHOD BASED ON ANALYSIS OF OPTIMAL VALUES OF THEIR CHARACTERISTICS

    Directory of Open Access Journals (Sweden)

    Constantin D. STANESCU

    2016-05-01

    Full Text Available The paper presents an original method of optimizing products based on the analysis of optimal values of their characteristics . Optimization method comprises statistical model and analytical model . With this original method can easily and quickly obtain optimal product or material .

  6. Robust optimization based upon statistical theory.

    Science.gov (United States)

    Sobotta, B; Söhn, M; Alber, M

    2010-08-01

    Organ movement is still the biggest challenge in cancer treatment despite advances in online imaging. Due to the resulting geometric uncertainties, the delivered dose cannot be predicted precisely at treatment planning time. Consequently, all associated dose metrics (e.g., EUD and maxDose) are random variables with a patient-specific probability distribution. The method that the authors propose makes these distributions the basis of the optimization and evaluation process. The authors start from a model of motion derived from patient-specific imaging. On a multitude of geometry instances sampled from this model, a dose metric is evaluated. The resulting pdf of this dose metric is termed outcome distribution. The approach optimizes the shape of the outcome distribution based on its mean and variance. This is in contrast to the conventional optimization of a nominal value (e.g., PTV EUD) computed on a single geometry instance. The mean and variance allow for an estimate of the expected treatment outcome along with the residual uncertainty. Besides being applicable to the target, the proposed method also seamlessly includes the organs at risk (OARs). The likelihood that a given value of a metric is reached in the treatment is predicted quantitatively. This information reveals potential hazards that may occur during the course of the treatment, thus helping the expert to find the right balance between the risk of insufficient normal tissue sparing and the risk of insufficient tumor control. By feeding this information to the optimizer, outcome distributions can be obtained where the probability of exceeding a given OAR maximum and that of falling short of a given target goal can be minimized simultaneously. The method is applicable to any source of residual motion uncertainty in treatment delivery. Any model that quantifies organ movement and deformation in terms of probability distributions can be used as basis for the algorithm. Thus, it can generate dose

  7. Optimal reactive power planning for distribution systems considering intermittent wind power using Markov model and genetic algorithm

    Science.gov (United States)

    Li, Cheng

    Wind farms, photovoltaic arrays, fuel cells, and micro-turbines are all considered to be Distributed Generation (DG). DG is defined as the generation of power which is dispersed throughout a utility's service territory and either connected to the utility's distribution system or isolated in a small grid. This thesis addresses modeling and economic issues pertaining to the optimal reactive power planning for distribution system with wind power generation (WPG) units. Wind farms are inclined to cause reverse power flows and voltage variations due to the random-like outputs of wind turbines. To deal with this kind of problem caused by wide spread usage of wind power generation, this thesis investigates voltage and reactive power controls in such a distribution system. Consequently static capacitors (SC) and transformer taps are introduced into the system and treated as controllers. For the purpose of getting optimum voltage and realizing reactive power control, the research proposes a proper coordination among the controllers like on-load tap changer (OLTC), feeder-switched capacitors. What's more, in order to simulate its uncertainty, the wind power generation is modeled by the Markov model. In that way, calculating the probabilities for all the scenarios is possible. Some outputs with consecutive and discrete values have been used for transition between successive time states and within state wind speeds. The thesis will describe the method to generate the wind speed time series from the transition probability matrix. After that, utilizing genetic algorithm, the optimal locations of SCs, the sizes of SCs and transformer taps are determined so as to minimize the cost or minimize the power loss, and more importantly improve voltage profiles. The applicability of the proposed method is verified through simulation on a 9-bus system and a 30-bus system respectively. At last, the simulation results indicate that as long as the available capacitors are able to sufficiently

  8. Location based Network Optimizations for Mobile Wireless Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen

    selection in Wi-Fi networks and predictive handover optimization in heterogeneous wireless networks. The investigations in this work have indicated that location based network optimizations are beneficial compared to typical link measurement based approaches. Especially the knowledge of geographical...

  9. Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

    Energy Technology Data Exchange (ETDEWEB)

    Tuvshinjargal, Doopalam; Lee, Deok Jin [Kunsan National University, Gunsan (Korea, Republic of)

    2015-06-15

    In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

  10. Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

    International Nuclear Information System (INIS)

    Tuvshinjargal, Doopalam; Lee, Deok Jin

    2015-01-01

    In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments

  11. Optimization of the Case Based Reasoning Systems

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2014-01-01

    Intrusion Detection System (IDS) have a great importance in saving the authority of the information widely spread all over the world through the networks. Many Case Based Systems concerned on the different methods of the unauthorized users/hackers that face the developers of the IDS. The proposed system introduces a new hybrid system that uses the genetic algorithm to optimize an IDS - case based system. It can detect the new anomalies appeared through the network and use the cases in the case library to determine the suitable solution for their behavior. The suggested system can solve the problem either by using an old identical solution or adapt the optimum one till have the targeted solution. The proposed system has been applied to block unauthorized users / hackers from attach the medical images for radiotherapy of the cancer diseases during their transmission through web. The proposed system can prove its accepted performance in this manner

  12. Supervisory Control for Real Time Reactive Power Flow Optimization in Islanded Microgrids

    DEFF Research Database (Denmark)

    Milczarek, Adam; Vasquez, Juan Carlos; Malinowski, Mariusz

    2013-01-01

    -line measurements. Similarly to any process system, MG hierarchical control is divided into three levels. However, an additional control algorithm is required to manage power transmission between sources and loads, maximizing efficiency and minimizing transmission losses. This real-time optimization problem......A microgrid (MG) is a local energy system consisting of a number of energy sources, energy storage units and loads that operate connected to the main electrical grid or autonomously. MGs include wind, solar or other renewable energy sources. MGs provide flexibility, reduce the main electricity grid...... dependence and contribute to change the large centralized production paradigm to local and distributed generation. However, such energy systems require complex management, advanced control and optimization. Interest on MGs hierarchical control has increased due to the availability of cheap on...

  13. Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids

    DEFF Research Database (Denmark)

    Chen, Feixiong; Chen, Minyou; Li, Qiang

    2016-01-01

    of the control model, in which the uncertainty of intermittent DGs, variations in load demands, as well as impacts of time delays are considered. The simulation results demonstrate the eectiveness of the control model in proportional reactive power sharing, and the plug and play capability of the control model......In islanded microgrids (MGs), the reactive power cannot be shared proportionally among distributed generators (DGs) with conventional droop control, due to the mismatch in feeder impedances. For the purpose of proportional reactive power sharing, a multiagent system (MAS) based distributed control...

  14. Entropy-based critical reaction time for mixing-controlled reactive transport

    DEFF Research Database (Denmark)

    Chiogna, Gabriele; Rolle, Massimo

    2017-01-01

    Entropy-based metrics, such as the dilution index, have been proposed to quantify dilution and reactive mixing in solute transport problems. In this work, we derive the transient advection dispersion equation for the entropy density of a reactive plume. We restrict our analysis to the case where...... the concentration distribution of the transported species is Gaussian and we observe that, even in case of an instantaneous complete bimolecular reaction, dilution caused by dispersive processes dominates the entropy balance at early times and results in the net increase of the entropy density of a reactive species...

  15. Performance-based shape optimization of continuum structures

    International Nuclear Information System (INIS)

    Liang Qingquan

    2010-01-01

    This paper presents a performance-based optimization (PBO) method for optimal shape design of continuum structures with stiffness constraints. Performance-based design concepts are incorporated in the shape optimization theory to achieve optimal designs. In the PBO method, the traditional shape optimization problem of minimizing the weight of a continuum structure with displacement or mean compliance constraints is transformed to the problem of maximizing the performance of the structure. The optimal shape of a continuum structure is obtained by gradually eliminating inefficient finite elements from the structure until its performance is maximized. Performance indices are employed to monitor the performance of optimized shapes in an optimization process. Performance-based optimality criteria are incorporated in the PBO method to identify the optimum from the optimization process. The PBO method is used to produce optimal shapes of plane stress continuum structures and plates in bending. Benchmark numerical results are provided to demonstrate the effectiveness of the PBO method for generating the maximum stiffness shape design of continuum structures. It is shown that the PBO method developed overcomes the limitations of traditional shape optimization methods in optimal design of continuum structures. Performance-based optimality criteria presented can be incorporated in any shape and topology optimization methods to obtain optimal designs of continuum structures.

  16. Photo-reactive charge trapping memory based on lanthanide complex

    Science.gov (United States)

    Zhuang, Jiaqing; Lo, Wai-Sum; Zhou, Li; Sun, Qi-Jun; Chan, Chi-Fai; Zhou, Ye; Han, Su-Ting; Yan, Yan; Wong, Wing-Tak; Wong, Ka-Leung; Roy, V. A. L.

    2015-10-01

    Traditional utilization of photo-induced excitons is popularly but restricted in the fields of photovoltaic devices as well as photodetectors, and efforts on broadening its function have always been attempted. However, rare reports are available on organic field effect transistor (OFET) memory employing photo-induced charges. Here, we demonstrate an OFET memory containing a novel organic lanthanide complex Eu(tta)3ppta (Eu(tta)3 = Europium(III) thenoyltrifluoroacetonate, ppta = 2-phenyl-4,6-bis(pyrazol-1-yl)-1,3,5-triazine), in which the photo-induced charges can be successfully trapped and detrapped. The luminescent complex emits intense red emission upon ultraviolet (UV) light excitation and serves as a trapping element of holes injected from the pentacene semiconductor layer. Memory window can be significantly enlarged by light-assisted programming and erasing procedures, during which the photo-induced excitons in the semiconductor layer are separated by voltage bias. The enhancement of memory window is attributed to the increasing number of photo-induced excitons by the UV light. The charges are stored in this luminescent complex for at least 104 s after withdrawing voltage bias. The present study on photo-assisted novel memory may motivate the research on a new type of light tunable charge trapping photo-reactive memory devices.

  17. Reliability-Based Optimization of Structural Elements

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    In this paper structural elements from an optimization point of view are considered, i.e. only the geometry of a structural element is optimized. Reliability modelling of the structural element is discussed both from an element point of view and from a system point of view. The optimization...

  18. Optimal truss and frame design from projected homogenization-based topology optimization

    DEFF Research Database (Denmark)

    Larsen, S. D.; Sigmund, O.; Groen, J. P.

    2018-01-01

    In this article, we propose a novel method to obtain a near-optimal frame structure, based on the solution of a homogenization-based topology optimization model. The presented approach exploits the equivalence between Michell’s problem of least-weight trusses and a compliance minimization problem...... using optimal rank-2 laminates in the low volume fraction limit. In a fully automated procedure, a discrete structure is extracted from the homogenization-based continuum model. This near-optimal structure is post-optimized as a frame, where the bending stiffness is continuously decreased, to allow...

  19. GA based CNC turning center exploitation process parameters optimization

    Directory of Open Access Journals (Sweden)

    Z. Car

    2009-01-01

    Full Text Available This paper presents machining parameters (turning process optimization based on the use of artificial intelligence. To obtain greater efficiency and productivity of the machine tool, optimal cutting parameters have to be obtained. In order to find optimal cutting parameters, the genetic algorithm (GA has been used as an optimal solution finder. Optimization has to yield minimum machining time and minimum production cost, while considering technological and material constrains.

  20. CFD based draft tube hydraulic design optimization

    International Nuclear Information System (INIS)

    McNabb, J; Murry, N; Mullins, B F; Devals, C; Kyriacou, S A

    2014-01-01

    The draft tube design of a hydraulic turbine, particularly in low to medium head applications, plays an important role in determining the efficiency and power characteristics of the overall machine, since an important proportion of the available energy, being in kinetic form leaving the runner, needs to be recovered by the draft tube into static head. For large units, these efficiency and power characteristics can equate to large sums of money when considering the anticipated selling price of the energy produced over the machine's life-cycle. This same draft tube design is also a key factor in determining the overall civil costs of the powerhouse, primarily in excavation and concreting, which can amount to similar orders of magnitude as the price of the energy produced. Therefore, there is a need to find the optimum compromise between these two conflicting requirements. In this paper, an elaborate approach is described for dealing with this optimization problem. First, the draft tube's detailed geometry is defined as a function of a comprehensive set of design parameters (about 20 of which a subset is allowed to vary during the optimization process) and are then used in a non-uniform rational B-spline based geometric modeller to fully define the wetted surfaces geometry. Since the performance of the draft tube is largely governed by 3D viscous effects, such as boundary layer separation from the walls and swirling flow characteristics, which in turn governs the portion of the available kinetic energy which will be converted into pressure, a full 3D meshing and Navier-Stokes analysis is performed for each design. What makes this even more challenging is the fact that the inlet velocity distribution to the draft tube is governed by the runner at each of the various operating conditions that are of interest for the exploitation of the powerhouse. In order to determine these inlet conditions, a combined steady-state runner and an initial draft tube analysis

  1. CFD based draft tube hydraulic design optimization

    Science.gov (United States)

    McNabb, J.; Devals, C.; Kyriacou, S. A.; Murry, N.; Mullins, B. F.

    2014-03-01

    The draft tube design of a hydraulic turbine, particularly in low to medium head applications, plays an important role in determining the efficiency and power characteristics of the overall machine, since an important proportion of the available energy, being in kinetic form leaving the runner, needs to be recovered by the draft tube into static head. For large units, these efficiency and power characteristics can equate to large sums of money when considering the anticipated selling price of the energy produced over the machine's life-cycle. This same draft tube design is also a key factor in determining the overall civil costs of the powerhouse, primarily in excavation and concreting, which can amount to similar orders of magnitude as the price of the energy produced. Therefore, there is a need to find the optimum compromise between these two conflicting requirements. In this paper, an elaborate approach is described for dealing with this optimization problem. First, the draft tube's detailed geometry is defined as a function of a comprehensive set of design parameters (about 20 of which a subset is allowed to vary during the optimization process) and are then used in a non-uniform rational B-spline based geometric modeller to fully define the wetted surfaces geometry. Since the performance of the draft tube is largely governed by 3D viscous effects, such as boundary layer separation from the walls and swirling flow characteristics, which in turn governs the portion of the available kinetic energy which will be converted into pressure, a full 3D meshing and Navier-Stokes analysis is performed for each design. What makes this even more challenging is the fact that the inlet velocity distribution to the draft tube is governed by the runner at each of the various operating conditions that are of interest for the exploitation of the powerhouse. In order to determine these inlet conditions, a combined steady-state runner and an initial draft tube analysis, using a

  2. Logic-based methods for optimization combining optimization and constraint satisfaction

    CERN Document Server

    Hooker, John

    2011-01-01

    A pioneering look at the fundamental role of logic in optimization and constraint satisfaction While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible

  3. NHS-Esters As Versatile Reactivity-Based Probes for Mapping Proteome-Wide Ligandable Hotspots.

    Science.gov (United States)

    Ward, Carl C; Kleinman, Jordan I; Nomura, Daniel K

    2017-06-16

    Most of the proteome is considered undruggable, oftentimes hindering translational efforts for drug discovery. Identifying previously unknown druggable hotspots in proteins would enable strategies for pharmacologically interrogating these sites with small molecules. Activity-based protein profiling (ABPP) has arisen as a powerful chemoproteomic strategy that uses reactivity-based chemical probes to map reactive, functional, and ligandable hotspots in complex proteomes, which has enabled inhibitor discovery against various therapeutic protein targets. Here, we report an alkyne-functionalized N-hydroxysuccinimide-ester (NHS-ester) as a versatile reactivity-based probe for mapping the reactivity of a wide range of nucleophilic ligandable hotspots, including lysines, serines, threonines, and tyrosines, encompassing active sites, allosteric sites, post-translational modification sites, protein interaction sites, and previously uncharacterized potential binding sites. Surprisingly, we also show that fragment-based NHS-ester ligands can be made to confer selectivity for specific lysine hotspots on specific targets including Dpyd, Aldh2, and Gstt1. We thus put forth NHS-esters as promising reactivity-based probes and chemical scaffolds for covalent ligand discovery.

  4. Optimizing a Water Simulation based on Wavefront Parameter Optimization

    OpenAIRE

    Lundgren, Martin

    2017-01-01

    DICE, a Swedish game company, wanted a more realistic water simulation. Currently, most large scale water simulations used in games are based upon ocean simulation technology. These techniques falter when used in other scenarios, such as coastlines. In order to produce a more realistic simulation, a new one was created based upon the water simulation technique "Wavefront Parameter Interpolation". This technique involves a rather extensive preprocess that enables ocean simulations to have inte...

  5. Optimization Strategies for Hardware-Based Cofactorization

    Science.gov (United States)

    Loebenberger, Daniel; Putzka, Jens

    We use the specific structure of the inputs to the cofactorization step in the general number field sieve (GNFS) in order to optimize the runtime for the cofactorization step on a hardware cluster. An optimal distribution of bitlength-specific ECM modules is proposed and compared to existing ones. With our optimizations we obtain a speedup between 17% and 33% of the cofactorization step of the GNFS when compared to the runtime of an unoptimized cluster.

  6. Self-healing anticorrosive organic coating based on an encapsulated water reactive silyl ester: synthesis and proof of concept

    NARCIS (Netherlands)

    García, S.J.; Fischer, H.R.; White, P.A.; Mardel, J.; González-García, Y.; Mol, J.M.C.; Hughes, A.E.

    2011-01-01

    In this paper a self-healing anticorrosive organic coating based on an encapsulated water reactive organic agent is presented. A reactive silyl ester is proposed as a new organic reactive healing agent and its synthesis, performance, incorporation into an organic coating and evaluation of

  7. Voltage stability index based optimal placement of static VAR compensator and sizing using Cuckoo search algorithm

    Science.gov (United States)

    Venkateswara Rao, B.; Kumar, G. V. Nagesh; Chowdary, D. Deepak; Bharathi, M. Aruna; Patra, Stutee

    2017-07-01

    This paper furnish the new Metaheuristic algorithm called Cuckoo Search Algorithm (CSA) for solving optimal power flow (OPF) problem with minimization of real power generation cost. The CSA is found to be the most efficient algorithm for solving single objective optimal power flow problems. The CSA performance is tested on IEEE 57 bus test system with real power generation cost minimization as objective function. Static VAR Compensator (SVC) is one of the best shunt connected device in the Flexible Alternating Current Transmission System (FACTS) family. It has capable of controlling the voltage magnitudes of buses by injecting the reactive power to system. In this paper SVC is integrated in CSA based Optimal Power Flow to optimize the real power generation cost. SVC is used to improve the voltage profile of the system. CSA gives better results as compared to genetic algorithm (GA) in both without and with SVC conditions.

  8. Transmission tariffs based on optimal power flow

    International Nuclear Information System (INIS)

    Wangensteen, Ivar; Gjelsvik, Anders

    1998-01-01

    This report discusses transmission pricing as a means of obtaining optimal scheduling and dispatch in a power system. This optimality includes consumption as well as generation. The report concentrates on how prices can be used as signals towards operational decisions of market participants (generators, consumers). The main focus is on deregulated systems with open access to the network. The optimal power flow theory, with demand side modelling included, is briefly reviewed. It turns out that the marginal costs obtained from the optimal power flow gives the optimal transmission tariff for the particular load flow in case. There is also a correspondence between losses and optimal prices. Emphasis is on simple examples that demonstrate the connection between optimal power flow results and tariffs. Various cases, such as open access and single owner are discussed. A key result is that the location of the ''marketplace'' in the open access case does not influence the net economical result for any of the parties involved (generators, network owner, consumer). The optimal power flow is instantaneous, and in its standard form cannot deal with energy constrained systems that are coupled in time, such as hydropower systems with reservoirs. A simplified example of how the theory can be extended to such a system is discussed. An example of the influence of security constraints on prices is also given. 4 refs., 24 figs., 7 tabs

  9. Reactive power and voltage control strategy based on dynamic and adaptive segment for DG inverter

    Science.gov (United States)

    Zhai, Jianwei; Lin, Xiaoming; Zhang, Yongjun

    2018-03-01

    The inverter of distributed generation (DG) can support reactive power to help solve the problem of out-of-limit voltage in active distribution network (ADN). Therefore, a reactive voltage control strategy based on dynamic and adaptive segment for DG inverter is put forward to actively control voltage in this paper. The proposed strategy adjusts the segmented voltage threshold of Q(U) droop curve dynamically and adaptively according to the voltage of grid-connected point and the power direction of adjacent downstream line. And then the reactive power reference of DG inverter can be got through modified Q(U) control strategy. The reactive power of inverter is controlled to trace the reference value. The proposed control strategy can not only control the local voltage of grid-connected point but also help to maintain voltage within qualified range considering the terminal voltage of distribution feeder and the reactive support for adjacent downstream DG. The scheme using the proposed strategy is compared with the scheme without the reactive support of DG inverter and the scheme using the Q(U) control strategy with constant segmented voltage threshold. The simulation results suggest that the proposed method has a significant improvement on solving the problem of out-of-limit voltage, restraining voltage variation and improving voltage quality.

  10. Optimizing reactive responses to outbreaks of immunizing infections: balancing case management and vaccination.

    Directory of Open Access Journals (Sweden)

    Petra Klepac

    Full Text Available For vaccine-preventable infections, immunization generally needs to be supplemented by palliative care of individuals missed by the vaccination. Costs and availability of vaccine doses and palliative care vary by disease and by region. In many situations, resources for delivery of palliative care are independent of resources required for vaccination; however we also need to consider the conservative scenario where there is some trade-off between efforts, which is of potential relevance for resource-poor settings. We formulate an SEIR model that includes those two control strategies--vaccination and palliative care. We consider their relative merit and optimal allocation in the context of a highly efficacious vaccine, and under the assumption that palliative care may reduce transmission. We investigate the utility of a range of mixed or pure strategies that can be implemented after an epidemic has started, and look for rule-of-thumb principles of how best to reduce the burden of disease during an acute outbreak over a spectrum of vaccine-preventable infections. Intuitively, we expect the best strategy to initially focus on vaccination, and enhanced palliative care after the infection has peaked, but a number of plausible realistic constraints for control result in important qualifications on the intervention strategy. The time in the epidemic when one should switch strategy depends sensitively on the relative cost of vaccine to palliative care, the available budget, and R0. Crucially, outbreak response vaccination may be more effective in managing low-R0 diseases, while high R0 scenarios enhance the importance of routine vaccination and case management.

  11. Theoretical comparison of performance using transfer functions for reactivity meters based on inverse kinetic method and simple feedback method

    International Nuclear Information System (INIS)

    Shimazu, Yoichiro; Tashiro, Shoichi; Tojo, Masayuki

    2017-01-01

    The performance of two digital reactivity meters, one based on the conventional inverse kinetic method and the other one based on simple feedback theory, are compared analytically using their respective transfer functions. The latter one is proposed by one of the authors. It has been shown that the performance of the two reactivity meters become almost identical when proper system parameters are selected for each reactivity meter. A new correlation between the system parameters of the two reactivity meters is found. With this correlation, filter designers can easily determine the system parameters for the respective reactivity meters to obtain identical performance. (author)

  12. Global stability-based design optimization of truss structures using ...

    Indian Academy of Sciences (India)

    Furthermore, a pure pareto-ranking based multi-objective optimization model is employed for the design optimization of the truss structure with multiple objectives. The computational performance of the optimization model is increased by implementing an island model into its evolutionary search mechanism. The proposed ...

  13. Process optimization of friction stir welding based on thermal models

    DEFF Research Database (Denmark)

    Larsen, Anders Astrup

    2010-01-01

    This thesis investigates how to apply optimization methods to numerical models of a friction stir welding process. The work is intended as a proof-of-concept using different methods that are applicable to models of high complexity, possibly with high computational cost, and without the possibility...... information of the high-fidelity model. The optimization schemes are applied to stationary thermal models of differing complexity of the friction stir welding process. The optimization problems considered are based on optimizing the temperature field in the workpiece by finding optimal translational speed....... Also an optimization problem based on a microstructure model is solved, allowing the hardness distribution in the plate to be optimized. The use of purely thermal models represents a simplification of the real process; nonetheless, it shows the applicability of the optimization methods considered...

  14. PARTICLE SWARM OPTIMIZATION BASED OF THE MAXIMUM ...

    African Journals Online (AJOL)

    2010-06-30

    Jun 30, 2010 ... Keywords: Particle Swarm Optimization (PSO), photovoltaic system, MPOP, ... systems from one hand and because of the instantaneous change of ..... Because of the P-V characteristics this heuristic method is used to seek ...

  15. Development of the Calibrator of Reactivity Meter Using PC-Based DAQ System

    International Nuclear Information System (INIS)

    Edison; Mariatmo, A.; Sujarwono

    2007-01-01

    The reactivity meter calibrator has been developed by applying the PC-Based DAQ System programmed using LabVIEW. The Output of the calibrator is voltage proportional to neutron density n(t) corresponding to the step reactivity change ρ 0 . The “Kalibrator meter reactivitas.vi” program calculates seven roots and coefficients of solution n(t) of Reactor Kinetic equation using the in-hour equation. Based on data of dt = t k+1 - t k and t 0 = 0 input by user, the program approximates n(t) for each time interval t k ≤ t k+1 , where k = 0, 1, 2, 3, .... by a step function n(t) = n 0 ∑ j=1 7 A j e ω j t k . Then the program commands the DAQ device to output voltage V(t) = n(t) Volt at time t. The measurement of standard reactivity with the meter reactivity showed that the maximum deviation of measured reactivity from its standard were less than 1 %. (author)

  16. Product portfolio optimization based on substitution

    DEFF Research Database (Denmark)

    Myrodia, Anna; Moseley, A.; Hvam, Lars

    2017-01-01

    The development of production capabilities has led to proliferation of the product variety offered to the customer. Yet this fact does not directly imply increase of manufacturers' profitability, nor customers' satisfaction. Consequently, recent research focuses on portfolio optimization through...... substitution and standardization techniques. However when re-defining the strategic market decisions are characterized by uncertainty due to several parameters. In this study, by using a GAMS optimization model we present a method for supporting strategic decisions on substitution, by quantifying the impact...

  17. Optimized and Automated Radiosynthesis of [18F]DHMT for Translational Imaging of Reactive Oxygen Species with Positron Emission Tomography

    Directory of Open Access Journals (Sweden)

    Wenjie Zhang

    2016-12-01

    Full Text Available Reactive oxygen species (ROS play important roles in cell signaling and homeostasis. However, an abnormally high level of ROS is toxic, and is implicated in a number of diseases. Positron emission tomography (PET imaging of ROS can assist in the detection of these diseases. For the purpose of clinical translation of [18F]6-(4-((1-(2-fluoroethyl-1H-1,2,3-triazol-4-ylmethoxyphenyl-5-methyl-5,6-dihydrophenanthridine-3,8-diamine ([18F]DHMT, a promising ROS PET radiotracer, we first manually optimized the large-scale radiosynthesis conditions and then implemented them in an automated synthesis module. Our manual synthesis procedure afforded [18F]DHMT in 120 min with overall radiochemical yield (RCY of 31.6% ± 9.3% (n = 2, decay-uncorrected and specific activity of 426 ± 272 GBq/µmol (n = 2. Fully automated radiosynthesis of [18F]DHMT was achieved within 77 min with overall isolated RCY of 6.9% ± 2.8% (n = 7, decay-uncorrected and specific activity of 155 ± 153 GBq/µmol (n = 7 at the end of synthesis. This study is the first demonstration of producing 2-[18F]fluoroethyl azide by an automated module, which can be used for a variety of PET tracers through click chemistry. It is also the first time that [18F]DHMT was successfully tested for PET imaging in a healthy beagle dog.

  18. Optimization of a space based radiator

    International Nuclear Information System (INIS)

    Sam, Kien Fan Cesar Hung; Deng Zhongmin

    2011-01-01

    Nowadays there is an increased demand in satellite weight reduction for the reduction of costs. Thermal control system designers have to face the challenge of reducing both the weight of the system and required heater power while maintaining the components temperature within their design ranges. The main purpose of this paper is to present an optimization of a heat pipe radiator applied to a practical engineering design application. For this study, a communications satellite payload panel was considered. Four radiator areas were defined instead of a centralized one in order to improve the heat rejection into space; the radiator's dimensions were determined considering worst hot scenario, solar fluxes, heat dissipation and the component's design temperature upper limit. Dimensions, thermal properties of the structural panel, optical properties and degradation/contamination on thermal control coatings were also considered. A thermal model was constructed for thermal analysis and two heat pipe network designs were evaluated and compared. The model that allowed better radiator efficiency was selected for parametric thermal analysis and optimization. This pursues finding the minimum size of the heat pipe network while keeping complying with thermal control requirements without increasing power consumption. - Highlights: →Heat pipe radiator optimization applied to a practical engineering design application. →The heat pipe radiator of a communications satellite panel is optimized. →A thermal model was built for parametric thermal analysis and optimization. →Optimal heat pipe network size is determined for the optimal weight solution. →The thermal compliance was verified by transient thermal analysis.

  19. Synthesis and Reactivity of Tripodal Complexes Containing Pendant Bases

    Energy Technology Data Exchange (ETDEWEB)

    Blacquiere, Johanna M.; Pegis, Michael L.; Raugei, Simone; Kaminsky, Werner; Forget, Amelie; Cook, Sarah; Taguchi, Taketo; Borovik, Andrew S.; Mayer, James M.

    2014-09-02

    The synthesis of a new tripodal ligand family is reported, with tertiary-amine groups in the second-coordination sphere. The ligands are tris(amido)amine derivatives, with the pendant amines attached via a peptide coupling strategy. They were designed to be used in new catalysts for the oxygen reduction reaction (ORR), in which the pendant acid/base group could improve catalyst performance. Two members of the new ligand family were each metallated with Co(II) and Zn(II) to afford trigonal monopyramidal complexes. Reaction of the cobalt complexes, [Co(L)]-, with dioxygen reversibly generates a small amount of a Co(III)-superoxo species, which was characterized by EPR. Protonation of the zinc complex Zn[N{CH2CH2NC(O)CH2N(CH2Ph)2}3)-– ([Zn(TNBn)]-) with one equivalent of acid occurs with displacement and dissociation of an amide ligand. Addition of excess acid to the any of the complexes [M(L)]- results in complete proteolysis and formation of the ligands H3L. This decomposition limits the use of these complexes as catalysts for the ORR. An alternative ligand with two pyridyl arms was also prepared but could not be metallated. These studies highlight the importance of stability of the primary-coordination sphere of ORR electrocatalysts to both oxidative and acidic conditions. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences.

  20. Loss Minimizing Operation of Doubly Fed Induction Generator Based Wind Generation Systems Considering Reactive Power Provision

    DEFF Research Database (Denmark)

    Baohua, Zhang; Hu, Weihao; Chen, Zhe

    2014-01-01

    The paper deals with control techniques for minimizing the operating loss of doubly fed induction generator based wind generation systems when providing reactive power. The proposed method achieves its goal through controlling the rotor side q-axis current in the synchronous reference frame...

  1. Agent-based Simulation of Reactive, Pro-active, and Social Animal Behaviour

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.; Mira, J.

    1998-01-01

    In this paper it is shown how animal behaviour can be simulated in an agent-based manner. Different models are shown for different types of behaviour, varying from purely reactive behaviour to pro-active and social behaviour. The compositional development method for multi-agent systems DESIRE and

  2. Entrainer selection for the synthesis of fatty acid esters by entrainer-based reactive distillation

    NARCIS (Netherlands)

    Jong, de M.C.; Zondervan, E.; Dimian, A.C.; Haan, de A.B.

    2010-01-01

    In this research it is demonstrated that, due to the similarities between Entrainer-based Reactive Distillation and azeotropic distillation, the same selection rules can be applied to select a suitable entrainer. From a list of suitable entrainers for the azeotropic distillation of isopropanol and

  3. Lattice Boltzmann based multicomponent reactive transport model coupled with geochemical solver for scale simulations

    NARCIS (Netherlands)

    Patel, R.A.; Perko, J.; Jaques, D.; De Schutter, G.; Ye, G.; Van Breugel, K.

    2013-01-01

    A Lattice Boltzmann (LB) based reactive transport model intended to capture reactions and solid phase changes occurring at the pore scale is presented. The proposed approach uses LB method to compute multi component mass transport. The LB multi-component transport model is then coupled with the

  4. Optical acetone vapor sensors based on chiral nematic liquid crystals and reactive chiral dopants

    NARCIS (Netherlands)

    Cachelin, P.; Green, J.P.; Peijs, T.; Heeney, M.; Bastiaansen, C.W.M.

    2016-01-01

    Accurate monitoring of exposure to organic vapors, such as acetone, is an important part of maintaining a safe working environment and adhering to long- and short-term exposure limits. Here, a novel acetone vapor detection system is described based on the use of a reactive chiral dopant in a nematic

  5. Consequences of the electronic tuning of latent ruthenium-based olefin metathesis catalysts on their reactivity

    KAUST Repository

    Żukowska, Karolina

    2015-08-20

    Two ruthenium olefin metathesis initiators featuring electronically modified quinoline-based chelating carbene ligands are introduced. Their reactivity in RCM and ROMP reactions was tested and the results were compared to those obtained with the parent unsubstituted compound. The studied complexes are very stable at high temperatures up to 140 °C. The placement of an electron-withdrawing functionality translates into an enhanced activity in RCM. While electronically modified precatalysts, which exist predominantly in the trans-dichloro configuration, gave mostly the RCM and a minor amount of the cycloisomerization product, the unmodified congener, which preferentially exists as its cis-dichloro isomer, shows a switched reactivity. The position of the equilibrium between the cis- and the trans-dichloro species was found to be the crucial factor governing the reactivity of the complexes.

  6. Consequences of the electronic tuning of latent ruthenium-based olefin metathesis catalysts on their reactivity

    KAUST Repository

    Żukowska, Karolina; Pump, Eva; Pazio, Aleksandra E; Woźniak, Krzysztof; Cavallo, Luigi; Slugovc, Christian

    2015-01-01

    Two ruthenium olefin metathesis initiators featuring electronically modified quinoline-based chelating carbene ligands are introduced. Their reactivity in RCM and ROMP reactions was tested and the results were compared to those obtained with the parent unsubstituted compound. The studied complexes are very stable at high temperatures up to 140 °C. The placement of an electron-withdrawing functionality translates into an enhanced activity in RCM. While electronically modified precatalysts, which exist predominantly in the trans-dichloro configuration, gave mostly the RCM and a minor amount of the cycloisomerization product, the unmodified congener, which preferentially exists as its cis-dichloro isomer, shows a switched reactivity. The position of the equilibrium between the cis- and the trans-dichloro species was found to be the crucial factor governing the reactivity of the complexes.

  7. 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...

  8. Topology optimization based on the harmony search method

    International Nuclear Information System (INIS)

    Lee, Seung-Min; Han, Seog-Young

    2017-01-01

    A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

  9. Topology optimization based on the harmony search method

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung-Min; Han, Seog-Young [Hanyang University, Seoul (Korea, Republic of)

    2017-06-15

    A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

  10. Reliability-Based Optimization of Series Systems of Parallel Systems

    DEFF Research Database (Denmark)

    Enevoldsen, I.; Sørensen, John Dalsgaard

    1993-01-01

    Reliability-based design of structural systems is considered. In particular, systems where the reliability model is a series system of parallel systems are treated. A sensitivity analysis for this class of problems is presented. Optimization problems with series systems of parallel systems...... optimization of series systems of parallel systems, but it is also efficient in reliability-based optimization of series systems in general....

  11. Geometrically based optimization for extracranial radiosurgery

    International Nuclear Information System (INIS)

    Liu Ruiguo; Wagner, Thomas H; Buatti, John M; Modrick, Joseph; Dill, John; Meeks, Sanford L

    2004-01-01

    For static beam conformal intracranial radiosurgery, geometry of the beam arrangement dominates overall dose distribution. Maximizing beam separation in three dimensions decreases beam overlap, thus maximizing dose conformality and gradient outside of the target volume. Webb proposed arrangements of isotropically convergent beams that could be used as the starting point for a radiotherapy optimization process. We have developed an extracranial radiosurgery optimization method by extending Webb's isotropic beam arrangements to deliverable beam arrangements. This method uses an arrangement of N maximally separated converging vectors within the space available for beam delivery. Each bouquet of isotropic beam vectors is generated by a random sampling process that iteratively maximizes beam separation. Next, beam arrangement is optimized for critical structure avoidance while maintaining minimal overlap between beam entrance and exit pathways. This geometrically optimized beam set can then be used as a template for either conformal beam or intensity modulated extracranial radiosurgery. Preliminary results suggest that using this technique with conformal beam planning provides high plan conformality, a steep dose gradient outside of the tumour volume and acceptable critical structure avoidance in the majority of clinical cases

  12. Optimal control of transverse mode coupling instability based on the two particle model

    International Nuclear Information System (INIS)

    Ogata, Atsushi

    1985-01-01

    The optimal regulator design technique is applied to asymptotically stabilize the transverse mode coupling instability of a storage ring. The state equations are based on the two particle model. These are a pair of equation sets, one for the first and one for the second half of the synchrotron phase. Each set consists of first-order difference equations in vector-matrix form, with time step equal to the revolution time of the ring. Solution of the discrete Riccati equation gives the optimal gain matrix of the transverse feedback. Computer simulations are carried out to verify its effectiveness. Some modifications necessary to apply it to the real accelerator operation are made. The old methods, the classical output feedback and the reactive feedback, are interpreted from the viewpoint of the optimal control. (orig.)

  13. The Optimal Wavelengths for Light Absorption Spectroscopy Measurements Based on Genetic Algorithm-Particle Swarm Optimization

    Science.gov (United States)

    Tang, Ge; Wei, Biao; Wu, Decao; Feng, Peng; Liu, Juan; Tang, Yuan; Xiong, Shuangfei; Zhang, Zheng

    2018-03-01

    To select the optimal wavelengths in the light extinction spectroscopy measurement, genetic algorithm-particle swarm optimization (GAPSO) based on genetic algorithm (GA) and particle swarm optimization (PSO) is adopted. The change of the optimal wavelength positions in different feature size parameters and distribution parameters is evaluated. Moreover, the Monte Carlo method based on random probability is used to identify the number of optimal wavelengths, and good inversion effects of the particle size distribution are obtained. The method proved to have the advantage of resisting noise. In order to verify the feasibility of the algorithm, spectra with bands ranging from 200 to 1000 nm are computed. Based on this, the measured data of standard particles are used to verify the algorithm.

  14. Physical bases for diffusion welding processes optimization

    International Nuclear Information System (INIS)

    Bulygina, S.M.; Berber, N.N.; Mukhambetov, D.G.

    1999-01-01

    One of wide-spread method of different materials joint is diffusion welding. It has being brought off at the expense of mutual diffusion of atoms of contacting surfaces under long-duration curing at its heating and compression. Welding regime in dependence from properties of welding details is defining of three parameters: temperature, pressure, time. Problem of diffusion welding optimization concludes in determination less values of these parameters, complying with requirements for quality of welded joint. In the work experiments on diffusion welding for calculated temperature and for given surface's roughness were carried out. Tests conduct on samples of iron and iron-nickel alloy with size 1·1·1 cm 3 . Optimal regime of diffusion welding of examined samples in vacuum is defined. It includes compression of welding samples, heating, isothermal holding at temperature 650 deg C during 0.5 h and affords the required homogeneity of joint

  15. A chromate-contaminated site in southern Switzerland – Part 2: Reactive transport modeling to optimize remediation options

    International Nuclear Information System (INIS)

    Wanner, Christoph; Eggenberger, Urs; Mäder, Urs

    2012-01-01

    A 2D horizontal reactive transport model of a chromate-contaminated site near Rivera, Switzerland, was developed using the computer code CrunchFlow to evaluate site remediation strategies. Transport processes were defined according to the results of an existing hydrological model, and the definition of geochemical (reactive) processes is based on the results of a detailed mineralogical and geochemical site characterization leading to a comprehensive conceptual site model. Kinetics of naturally occurring Cr(VI) reduction by Fe(II) and natural solid organic matter is quantified by fitting measured Cr isotope ratios to a modeled 1D section along the best constrained flow line. The simulation of Cr isotope fractionation was also incorporated into the 2D model. Simulation of the measured present day Cr(VI) plume and δ 53 Cr value distribution was used for the 2D model calibration and corresponds to a situation where only monitored natural attenuation (MNA) is occurring. Other 2D model runs simulate alternate excavation scenarios. The simulations show that with an excavation of the top 2–4 m the groundwater Cr(VI) plume can be minimized, and that a deeper excavation depth only diminishes the plume if all the contaminants can be removed. A combination of an excavation of the top 2–4 m and monitoring of the ongoing natural Cr(VI) reduction is suggested as the most ecological and economical remediation strategy, even though a remaining time period with ongoing subsoil Cr(VI) contamination in the order of 1 ka is predicted.

  16. Interleaver Optimization using Population-Based Metaheuristics

    Czech Academy of Sciences Publication Activity Database

    Snášel, V.; Platoš, J.; Krömer, P.; Abraham, A.; Ouddane, N.; Húsek, Dušan

    2010-01-01

    Roč. 20, č. 5 (2010), s. 591-608 ISSN 1210-0552 R&D Projects: GA ČR GA205/09/1079 Grant - others:GA ČR(CZ) GA102/09/1494 Institutional research plan: CEZ:AV0Z10300504 Keywords : turbo codes * global optimization * genetic algorithms * differential evolution * noisy communication channel Subject RIV: IN - Informatics, Computer Science Impact factor: 0.511, year: 2010

  17. Defining a region of optimization based on engine usage data

    Science.gov (United States)

    Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

    2015-08-04

    Methods and systems for engine control optimization are provided. One or more operating conditions of a vehicle engine are detected. A value for each of a plurality of engine control parameters is determined based on the detected one or more operating conditions of the vehicle engine. A range of the most commonly detected operating conditions of the vehicle engine is identified and a region of optimization is defined based on the range of the most commonly detected operating conditions of the vehicle engine. The engine control optimization routine is initiated when the one or more operating conditions of the vehicle engine are within the defined region of optimization.

  18. 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

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

    Directory of Open Access Journals (Sweden)

    Ruisheng Sun

    2016-01-01

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

  20. Empty tracks optimization based on Z-Map model

    Science.gov (United States)

    Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao

    2017-12-01

    For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.

  1. Urea impedimetric biosensor based on reactive RF magnetron sputtered zinc oxide nanoporous transducer

    International Nuclear Information System (INIS)

    Mozaffari, Sayed Ahmad; Rahmanian, Reza; Abedi, Mohammad; Amoli, Hossein Salar

    2014-01-01

    Graphical abstract: - Highlights: • Application and optimization of reactive RF magnetron sputtering for homogeneous nanoporous ZnO thin film formation. • Exploiting nanoporous ZnO thin film as a good porous framework with large surface area/volume for having stable immobilized enzyme with minimum loss of activity. • Application of impedimetric assessment for urea biosensing due to its rapidity, sensitivity, and repeatability. - Abstract: Uniform sputtered nanoporous zinc oxide (Nano-ZnO) thin film on the conductive fluorinated-tin oxide (FTO) layer was applied to immobilize urease enzyme (Urs) for urea detection. Highly uniform nanoporous ZnO thin film were obtained by reactive radio frequency (RF) magnetron sputtering system at the optimized instrumental deposition conditions. Characterization of the surface morphology and roughness of ZnO thin film by field emission-scanning electron microscopy (FE-SEM) exhibits cavities of nanoporous film as an effective biosensing area for enzyme immobilization. Step by step monitoring of FTO/Nano-ZnO/Urs biosensor fabrication were performed using electrochemical methods such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. Fabricated FTO/Nano-ZnO/Urs biosensor was used for urea determination using EIS experiments. The impedimetric results show high sensitivity for urea detection within 0.83–23.24 mM and limit of detection as 0.40 mM

  2. Reactive power and voltage control based on general quantum genetic algorithms

    DEFF Research Database (Denmark)

    Vlachogiannis, Ioannis (John); Østergaard, Jacob

    2009-01-01

    This paper presents an improved evolutionary algorithm based on quantum computing for optima l steady-state performance of power systems. However, the proposed general quantum genetic algorithm (GQ-GA) can be applied in various combinatorial optimization problems. In this study the GQ-GA determines...... techniques such as enhanced GA, multi-objective evolutionary algorithm and particle swarm optimization algorithms, as well as the classical primal-dual interior-point optimal power flow algorithm. The comparison demonstrates the ability of the GQ-GA in reaching more optimal solutions....

  3. Elitism set based particle swarm optimization and its application

    Directory of Open Access Journals (Sweden)

    Yanxia Sun

    2017-01-01

    Full Text Available Topology plays an important role for Particle Swarm Optimization (PSO to achieve good optimization performance. It is difficult to find one topology structure for the particles to achieve better optimization performance than the others since the optimization performance not only depends on the searching abilities of the particles, also depends on the type of the optimization problems. Three elitist set based PSO algorithm without using explicit topology structure is proposed in this paper. An elitist set, which is based on the individual best experience, is used to communicate among the particles. Moreover, to avoid the premature of the particles, different statistical methods have been used in these three proposed methods. The performance of the proposed PSOs is compared with the results of the standard PSO 2011 and several PSO with different topologies, and the simulation results and comparisons demonstrate that the proposed PSO with adaptive probabilistic preference can achieve good optimization performance.

  4. Shape signature based on Ricci flow and optimal mass transportation

    Science.gov (United States)

    Luo, Wei; Su, Zengyu; Zhang, Min; Zeng, Wei; Dai, Junfei; Gu, Xianfeng

    2014-11-01

    A shape signature based on surface Ricci flow and optimal mass transportation is introduced for the purpose of surface comparison. First, the surface is conformally mapped onto plane by Ricci flow, which induces a measure on the planar domain. Second, the unique optimal mass transport map is computed that transports the new measure to the canonical measure on the plane. The map is obtained by a convex optimization process. This optimal transport map encodes all the information of the Riemannian metric on the surface. The shape signature consists of the optimal transport map, together with the mean curvature, which can fully recover the original surface. The discrete theories of surface Ricci flow and optimal mass transportation are explained thoroughly. The algorithms are given in detail. The signature is tested on human facial surfaces with different expressions accquired by structured light 3-D scanner based on phase-shifting method. The experimental results demonstrate the efficiency and efficacy of the method.

  5. Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems.

    Science.gov (United States)

    Yu, Xue; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Yuan, Huaqiang; Kwong, Sam; Zhang, Jun

    2017-08-07

    This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.

  6. Agreement and repeatability of vascular reactivity estimates based on a breath-hold task and a resting state scan.

    Science.gov (United States)

    Lipp, Ilona; Murphy, Kevin; Caseras, Xavier; Wise, Richard G

    2015-06-01

    FMRI BOLD responses to changes in neural activity are influenced by the reactivity of the vasculature. By complementing a task-related BOLD acquisition with a vascular reactivity measure obtained through breath-holding or hypercapnia, this unwanted variance can be statistically reduced in the BOLD responses of interest. Recently, it has been suggested that vascular reactivity can also be estimated using a resting state scan. This study aimed to compare three breath-hold based analysis approaches (block design, sine-cosine regressor and CO2 regressor) and a resting state approach (CO2 regressor) to measure vascular reactivity. We tested BOLD variance explained by the model and repeatability of the measures. Fifteen healthy participants underwent a breath-hold task and a resting state scan with end-tidal CO2 being recorded during both. Vascular reactivity was defined as CO2-related BOLD percent signal change/mmHg change in CO2. Maps and regional vascular reactivity estimates showed high repeatability when the breath-hold task was used. Repeatability and variance explained by the CO2 trace regressor were lower for the resting state data based approach, which resulted in highly variable measures of vascular reactivity. We conclude that breath-hold based vascular reactivity estimations are more repeatable than resting-based estimates, and that there are limitations with replacing breath-hold scans by resting state scans for vascular reactivity assessment. Copyright © 2015. Published by Elsevier Inc.

  7. Optimal, Reliability-Based Code Calibration

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2002-01-01

    Reliability based code calibration is considered in this paper. It is described how the results of FORM based reliability analysis may be related to the partial safety factors and characteristic values. The code calibration problem is presented in a decision theoretical form and it is discussed how...... of reliability based code calibration of LRFD based design codes....

  8. Support vector machines optimization based theory, algorithms, and extensions

    CERN Document Server

    Deng, Naiyang; Zhang, Chunhua

    2013-01-01

    Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized twi

  9. Optimal design of RTCs in digital circuit fault self-repair based on global signal optimization

    Institute of Scientific and Technical Information of China (English)

    Zhang Junbin; Cai Jinyan; Meng Yafeng

    2016-01-01

    Since digital circuits have been widely and thoroughly applied in various fields, electronic systems are increasingly more complicated and require greater reliability. Faults may occur in elec-tronic systems in complicated environments. If immediate field repairs are not made on the faults, elec-tronic systems will not run normally, and this will lead to serious losses. The traditional method for improving system reliability based on redundant fault-tolerant technique has been unable to meet the requirements. Therefore, on the basis of (evolvable hardware)-based and (reparation balance technology)-based electronic circuit fault self-repair strategy proposed in our preliminary work, the optimal design of rectification circuits (RTCs) in electronic circuit fault self-repair based on global sig-nal optimization is deeply researched in this paper. First of all, the basic theory of RTC optimal design based on global signal optimization is proposed. Secondly, relevant considerations and suitable ranges are analyzed. Then, the basic flow of RTC optimal design is researched. Eventually, a typical circuit is selected for simulation verification, and detailed simulated analysis is made on five circumstances that occur during RTC evolution. The simulation results prove that compared with the conventional design method based RTC, the global signal optimization design method based RTC is lower in hardware cost, faster in circuit evolution, higher in convergent precision, and higher in circuit evolution success rate. Therefore, the global signal optimization based RTC optimal design method applied in the elec-tronic circuit fault self-repair technology is proven to be feasible, effective, and advantageous.

  10. Agent-based reactive power management of power distribution networks with distributed energy generation

    International Nuclear Information System (INIS)

    Rahman, M.S.; Mahmud, M.A.; Oo, A.M.T.; Pota, H.R.; Hossain, M.J.

    2016-01-01

    Highlights: • A coordinated multi-agent system is proposed for reactive power management. • A linear quadratic regulator with a proportional integral controller is designed. • Proposed multi-agent scheme provides accurate estimation and control of the system. • Voltage stability is improved with proper power management for different scenarios. • Results obtained from the proposed scheme is compared to the traditional approach. - Abstract: In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

  11. Reactivation of Reward-Related Patterns from Single Past Episodes Supports Memory-Based Decision Making.

    Science.gov (United States)

    Wimmer, G Elliott; Büchel, Christian

    2016-03-09

    Rewarding experiences exert a strong influence on later decision making. While decades of neuroscience research have shown how reinforcement gradually shapes preferences, decisions are often influenced by single past experiences. Surprisingly, relatively little is known about the influence of single learning episodes. Although recent work has proposed a role for episodes in decision making, it is largely unknown whether and how episodic experiences contribute to value-based decision making and how the values of single episodes are represented in the brain. In multiple behavioral experiments and an fMRI experiment, we tested whether and how rewarding episodes could support later decision making. Participants experienced episodes of high reward or low reward in conjunction with incidental, trial-unique neutral pictures. In a surprise test phase, we found that participants could indeed remember the associated level of reward, as evidenced by accurate source memory for value and preferences to re-engage with rewarded objects. Further, in a separate experiment, we found that high-reward objects shown as primes before a gambling task increased financial risk taking. Neurally, re-exposure to objects in the test phase led to significant reactivation of reward-related patterns. Importantly, individual variability in the strength of reactivation predicted value memory performance. Our results provide a novel demonstration that affect-related neural patterns are reactivated during later experience. Reactivation of value information represents a mechanism by which memory can guide decision making. Copyright © 2016 the authors 0270-6474/16/362868-13$15.00/0.

  12. portfolio optimization based on nonparametric estimation methods

    Directory of Open Access Journals (Sweden)

    mahsa ghandehari

    2017-03-01

    Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.

  13. Optimal separable bases and series expansions

    International Nuclear Information System (INIS)

    Poirier, B.

    1997-01-01

    A method is proposed for the efficient calculation of the Green close-quote s functions and eigenstates for quantum systems of two or more dimensions. For a given Hamiltonian, the best possible separable approximation is obtained from the set of all Hilbert-space operators. It is shown that this determination itself, as well as the solution of the resultant approximation, is a problem of reduced dimensionality. Moreover, the approximate eigenstates constitute the optimal separable basis, in the sense of self-consistent field theory. The full solution is obtained from the approximation via iterative expansion. In the time-independent perturbation expansion for instance, all of the first-order energy corrections are zero. In the Green close-quote s function case, we have a distorted-wave Born series with optimized convergence properties. This series may converge even when the usual Born series diverges. Analytical results are presented for an application of the method to the two-dimensional shifted harmonic-oscillator system, in the course of which the quantum tanh 2 potential problem is solved exactly. The universal presence of bound states in the latter is shown to imply long-lived resonances in the former. In a comparison with other theoretical methods, we find that the reaction path Hamiltonian fails to predict such resonances. copyright 1997 The American Physical Society

  14. An integrated reliability-based design optimization of offshore towers

    International Nuclear Information System (INIS)

    Karadeniz, Halil; Togan, Vedat; Vrouwenvelder, Ton

    2009-01-01

    After recognizing the uncertainty in the parameters such as material, loading, geometry and so on in contrast with the conventional optimization, the reliability-based design optimization (RBDO) concept has become more meaningful to perform an economical design implementation, which includes a reliability analysis and an optimization algorithm. RBDO procedures include structural analysis, reliability analysis and sensitivity analysis both for optimization and for reliability. The efficiency of the RBDO system depends on the mentioned numerical algorithms. In this work, an integrated algorithms system is proposed to implement the RBDO of the offshore towers, which are subjected to the extreme wave loading. The numerical strategies interacting with each other to fulfill the RBDO of towers are as follows: (a) a structural analysis program, SAPOS, (b) an optimization program, SQP and (c) a reliability analysis program based on FORM. A demonstration of an example tripod tower under the reliability constraints based on limit states of the critical stress, buckling and the natural frequency is presented.

  15. An integrated reliability-based design optimization of offshore towers

    Energy Technology Data Exchange (ETDEWEB)

    Karadeniz, Halil [Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft (Netherlands)], E-mail: h.karadeniz@tudelft.nl; Togan, Vedat [Department of Civil Engineering, Karadeniz Technical University, Trabzon (Turkey); Vrouwenvelder, Ton [Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft (Netherlands)

    2009-10-15

    After recognizing the uncertainty in the parameters such as material, loading, geometry and so on in contrast with the conventional optimization, the reliability-based design optimization (RBDO) concept has become more meaningful to perform an economical design implementation, which includes a reliability analysis and an optimization algorithm. RBDO procedures include structural analysis, reliability analysis and sensitivity analysis both for optimization and for reliability. The efficiency of the RBDO system depends on the mentioned numerical algorithms. In this work, an integrated algorithms system is proposed to implement the RBDO of the offshore towers, which are subjected to the extreme wave loading. The numerical strategies interacting with each other to fulfill the RBDO of towers are as follows: (a) a structural analysis program, SAPOS, (b) an optimization program, SQP and (c) a reliability analysis program based on FORM. A demonstration of an example tripod tower under the reliability constraints based on limit states of the critical stress, buckling and the natural frequency is presented.

  16. Electron Transfer Reactivity Patterns at Chemically Modified Electrodes: Fundamentals and Application to the Optimization of Redox Recycling Amplification Systems

    Energy Technology Data Exchange (ETDEWEB)

    Bergren, Adam Johan [Iowa State Univ., Ames, IA (United States)

    2006-01-01

    Electroanalytical chemistry is often utilized in chemical analysis and Fundamental studies. Important advances have been made in these areas since the advent of chemically modified electrodes: the coating of an electrode with a chemical film in order to impart desirable, and ideally, predictable properties. These procedures enable the exploitation of unique reactivity patterns. This dissertation presents studies that investigate novel reaction mechanisms at self-assembled monolayers on gold. In particular, a unique electrochemical current amplification scheme is detailed that relies on a selective electrode to enable a reactivity pattern that results in regeneration of the analyte (redox recycling). This regenerating reaction can occur up to 250 times for each analyte molecule, leading to a notable enhancement in the observed current. The requirements of electrode selectivity and the resulting amplification and detection limit improvements are described with respect to the heterogeneous and homogeneous electron transfer rates that characterize the system. These studies revealed that the heterogeneous electrolysis of the analyte should ideally be electrochemically reversible, while that for the regenerating agent should be held to a low level. Moreover, the homogeneous reaction that recycles the analyte should occur at a rapid rate. The physical selectivity mechanism is also detailed with respect to the properties of the electrode and redox probes utilized. It is shown that partitioning of the analyte into/onto the adlayer leads to the extraordinary selectivity of the alkanethiolate monolayer modified electrode. Collectively, these studies enable a thorough understanding of the complex electrode mechanism required for successful redox recycling amplification systems, Finally, in a separate (but related) study, the effect of the akyl chain length on the heterogeneous electron transfer behavior of solution-based redox probes is reported, where an odd-even oscillation

  17. Optimizing block-based maintenance under random machine usage

    NARCIS (Netherlands)

    de Jonge, Bram; Jakobsons, Edgars

    Existing studies on maintenance optimization generally assume that machines are either used continuously, or that times until failure do not depend on the actual usage. In practice, however, these assumptions are often not realistic. In this paper, we consider block-based maintenance optimization

  18. Reliability-Based Optimization of Series Systems of Parallel Systems

    DEFF Research Database (Denmark)

    Enevoldsen, I.; Sørensen, John Dalsgaard

    Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...

  19. Optimization of microgrids based on controller designing for ...

    African Journals Online (AJOL)

    The power quality of microgrid during islanded operation is strongly related with the controller performance of DGs. Therefore a new optimal control strategy for distributed generation based inverter to connect to the generalized microgrid is proposed. This work shows developing optimal control algorithms for the DG ...

  20. Theoretical study of the structure and reactivity of lanthanide and actinide based organometallic complexes

    International Nuclear Information System (INIS)

    Barros, N.

    2007-06-01

    In this PhD thesis, lanthanide and actinide based organometallic complexes are studied using quantum chemistry methods. In a first part, the catalytic properties of organo-lanthanide compounds are evaluated by studying two types of reactions: the catalytic hydro-functionalization of olefins and the polymerisation of polar monomers. The reaction mechanisms are theoretically determined and validated, and the influence of possible secondary non productive reactions is envisaged. A second part focuses on uranium-based complexes. Firstly, the electronic structure of uranium metallocenes is analysed. An analogy with the uranyl compounds is proposed. In a second chapter, two isoelectronic complexes of uranium IV are studied. After validating the use of DFT methods for describing the electronic structure and the reactivity of these compounds, it is shown that their reactivity difference can be related to a different nature of chemical bonding in these complexes. (author)

  1. Optimization algorithm based on densification and dynamic canonical descent

    Science.gov (United States)

    Bousson, K.; Correia, S. D.

    2006-07-01

    Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable. They have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper proposes an optimization method, which reduces the search space by means of densification curves, coupled with the dynamic canonical descent algorithm. The performances of the new method are shown on several known problems classically used for testing optimization algorithms, and proved to outperform competitive algorithms such as simulated annealing and genetic algorithms.

  2. 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.

  3. Novel Verification Method for Timing Optimization Based on DPSO

    Directory of Open Access Journals (Sweden)

    Chuandong Chen

    2018-01-01

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

  4. A comparison of physically and radiobiologically based optimization for IMRT

    International Nuclear Information System (INIS)

    Jones, Lois; Hoban, Peter

    2002-01-01

    Many optimization techniques for intensity modulated radiotherapy have now been developed. The majority of these techniques including all the commercial systems that are available are based on physical dose methods of assessment. Some techniques have also been based on radiobiological models. None of the radiobiological optimization techniques however have assessed the clinically realistic situation of considering both tumor and normal cells within the target volume. This study considers a ratio-based fluence optimizing technique to compare a dose-based optimization method described previously and two biologically based models. The biologically based methods use the values of equivalent uniform dose calculated for the tumor cells and integral biological effective dose for normal cells. The first biologically based method includes only tumor cells in the target volume while the second considers both tumor and normal cells in the target volume. All three methods achieve good conformation to the target volume. The biologically based optimization without the normal tissue in the target volume shows a high dose region in the center of the target volume while this is reduced when the normal tissues are also considered in the target volume. This effect occurs because the normal tissues in the target volume require the optimization to reduce the dose and therefore limit the maximum dose to that volume

  5. Pyridoxylamine reactivity kinetics as an amine based nucleophile for screening electrophilic dermal sensitizers

    Science.gov (United States)

    Chipinda, Itai; Mbiya, Wilbes; Adigun, Risikat Ajibola; Morakinyo, Moshood K.; Law, Brandon F.; Simoyi, Reuben H.; Siegel, Paul D.

    2015-01-01

    Chemical allergens bind directly, or after metabolic or abiotic activation, to endogenous proteins to become allergenic. Assessment of this initial binding has been suggested as a target for development of assays to screen chemicals for their allergenic potential. Recently we reported a nitrobenzenethiol (NBT) based method for screening thiol reactive skin sensitizers, however, amine selective sensitizers are not detected by this assay. In the present study we describe an amine (pyridoxylamine (PDA)) based kinetic assay to complement the NBT assay for identification of amine-selective and non-selective skin sensitizers. UV-Vis spectrophotometry and fluorescence were used to measure PDA reactivity for 57 chemicals including anhydrides, aldehydes, and quinones where reaction rates ranged from 116 to 6.2 × 10−6 M−1 s−1 for extreme to weak sensitizers, respectively. No reactivity towards PDA was observed with the thiol-selective sensitizers, non-sensitizers and prohaptens. The PDA rate constants correlated significantly with their respective murine local lymph node assay (LLNA) threshold EC3 values (R2 = 0.76). The use of PDA serves as a simple, inexpensive amine based method that shows promise as a preliminary screening tool for electrophilic, amine-selective skin sensitizers. PMID:24333919

  6. Long-Term Groundwater Monitoring Optimization, Clare Water Supply Superfund Site, Permeable Reactive Barrier and Soil Remedy Areas, Clare, Michigan

    Science.gov (United States)

    This report contains a review of the long-term groundwater monitoring network for the Permeable Reactive Barrier (PRB) and Soil Remedy Areas at the Clare Water Supply Superfund Site in Clare, Michigan.

  7. Intelligent fault recognition strategy based on adaptive optimized multiple centers

    Science.gov (United States)

    Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

    2018-06-01

    For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

  8. Integrated Reliability-Based Optimal Design of Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Thoft-Christensen, Palle

    1987-01-01

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

  9. Topology Optimization of Passive Micromixers Based on Lagrangian Mapping Method

    Directory of Open Access Journals (Sweden)

    Yuchen Guo

    2018-03-01

    Full Text Available This paper presents an optimization-based design method of passive micromixers for immiscible fluids, which means that the Peclet number infinitely large. Based on topology optimization method, an optimization model is constructed to find the optimal layout of the passive micromixers. Being different from the topology optimization methods with Eulerian description of the convection-diffusion dynamics, this proposed method considers the extreme case, where the mixing is dominated completely by the convection with negligible diffusion. In this method, the mixing dynamics is modeled by the mapping method, a Lagrangian description that can deal with the case with convection-dominance. Several numerical examples have been presented to demonstrate the validity of the proposed method.

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

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2015-09-01

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

  11. Reactivity to unpredictable threat as a treatment target for fear-based anxiety disorders.

    Science.gov (United States)

    Gorka, S M; Lieberman, L; Klumpp, H; Kinney, K L; Kennedy, A E; Ajilore, O; Francis, J; Duffecy, J; Craske, M G; Nathan, J; Langenecker, S; Shankman, S A; Phan, K L

    2017-10-01

    Heightened reactivity to unpredictable threat (U-threat) is a core individual difference factor underlying fear-based psychopathology. Little is known, however, about whether reactivity to U-threat is a stable marker of fear-based psychopathology or if it is malleable to treatment. The aim of the current study was to address this question by examining differences in reactivity to U-threat within patients before and after 12-weeks of selective serotonin reuptake inhibitors (SSRIs) or cognitive-behavioral therapy (CBT). Participants included patients with principal fear (n = 22) and distress/misery disorders (n = 29), and a group of healthy controls (n = 21) assessed 12-weeks apart. A well-validated threat-of-shock task was used to probe reactivity to predictable (P-) and U-threat and startle eyeblink magnitude was recorded as an index of defensive responding. Across both assessments, individuals with fear-based disorders displayed greater startle magnitude to U-threat relative to healthy controls and distress/misery patients (who did not differ). From pre- to post-treatment, startle magnitude during U-threat decreased only within the fear patients who received CBT. Moreover, within fear patients, the magnitude of decline in startle to U-threat correlated with the magnitude of decline in fear symptoms. For the healthy controls, startle to U-threat across the two time points was highly reliable and stable. Together, these results indicate that startle to U-threat characterizes fear disorder patients and is malleable to treatment with CBT but not SSRIs within fear patients. Startle to U-threat may therefore reflect an objective, psychophysiological indicator of fear disorder status and CBT treatment response.

  12. optimization of object tracking based on enhanced imperialist ...

    African Journals Online (AJOL)

    Damuut and Dogara

    A typical example is the Roman Empire which had influence or control over ... the Enhance Imperialist Competitive Algorithm (EICA) in optimizing the generated ... segment the video frame into a number of regions based on visual features like ...

  13. Optimizing ring-based CSR sources

    International Nuclear Information System (INIS)

    Byrd, J.M.; De Santis, S.; Hao, Z.; Martin, M.C.; Munson, D.V.; Li, D.; Nishimura, H.; Robin, D.S.; Sannibale, F.; Schlueter, R.D.; Schoenlein, R.; Jung, J.Y.; Venturini, M.; Wan, W.; Zholents, A.A.; Zolotorev, M.

    2004-01-01

    Coherent synchrotron radiation (CSR) is a fascinating phenomenon recently observed in electron storage rings and shows tremendous promise as a high power source of radiation at terahertz frequencies. However, because of the properties of the radiation and the electron beams needed to produce it, there are a number of interesting features of the storage ring that can be optimized for CSR. Furthermore, CSR has been observed in three distinct forms: as steady pulses from short bunches, bursts from growth of spontaneous modulations in high current bunches, and from micro modulations imposed on a bunch from laser slicing. These processes have their relative merits as sources and can be improved via the ring design. The terahertz (THz) and sub-THz region of the electromagnetic spectrum lies between the infrared and the microwave . This boundary region is beyond the normal reach of optical and electronic measurement techniques and sources associated with these better-known neighbors. Recent research has demonstrated a relatively high power source of THz radiation from electron storage rings: coherent synchrotron radiation (CSR). Besides offering high power, CSR enables broadband optical techniques to be extended to nearly the microwave region, and has inherently sub-picosecond pulses. As a result, new opportunities for scientific research and applications are enabled across a diverse array of disciplines: condensed matter physics, medicine, manufacturing, and space and defense industries. CSR will have a strong impact on THz imaging, spectroscopy, femtosecond dynamics, and driving novel non-linear processes. CSR is emitted by bunches of accelerated charged particles when the bunch length is shorter than the wavelength being emitted. When this criterion is met, all the particles emit in phase, and a single-cycle electromagnetic pulse results with an intensity proportional to the square of the number of particles in the bunch. It is this quadratic dependence that can

  14. Optimal portfolio model based on WVAR

    OpenAIRE

    Hao, Tianyu

    2012-01-01

    This article is focused on using a new measurement of risk-- Weighted Value at Risk to develop a new method of constructing initiate from the TVAR solving problem, based on MATLAB software, using the historical simulation method (avoiding income distribution will be assumed to be normal), the results of previous studies also based on, study the U.S. Nasdaq composite index, combining the Simpson formula for the solution of TVAR and its deeply study; then, through the representation of WVAR for...

  15. Phospholipase A1-based cross-reactivity among venoms of clinically relevant Hymenoptera from Neotropical and temperate regions.

    Science.gov (United States)

    Perez-Riverol, Amilcar; Fernandes, Luís Gustavo Romani; Musacchio Lasa, Alexis; Dos Santos-Pinto, José Roberto Aparecido; Moitinho Abram, Débora; Izuka Moraes, Gabriel Hideki; Jabs, Frederic; Miehe, Michaela; Seismman, Henning; Palma, Mario Sergio; de Lima Zollner, Ricardo; Spillner, Edzard; Brochetto-Braga, Márcia Regina

    2018-01-01

    Molecular cross-reactivity caused by allergen homology or cross-reactive carbohydrate determinants (CCDs) is a major challenge for diagnosis and immunotherapy of insect venom allergy. Venom phospholipases A1 (PLA1s) are classical, mostly non-glycosylated wasp and ant allergens that provide diagnostic benefit for differentiation of genuine sensitizations from cross-reactivity. As CCD-free molecules, venom PLA1s are not causative for CCD-based cross-reactivity. Little is known however about the protein-based cross-reactivity of PLA1 within vespid species. Here, we address PLA1-based cross-reactivity among ten clinically relevant Hymenoptera venoms from Neotropical and temperate regions including Polybia paulista (paulistinha) venom and Vespula vulgaris (yellow jacket) venom. In order to evaluate cross-reactivity, sera of mice sensitized with recombinant PLA1 (rPoly p 1) from P. paulista wasp venom were used. Pronounced IgE and IgG based cross-reactivity was detected for wasp venoms regardless the geographical region of origin. The cross-reactivity correlated well with the identity of the primary sequence and 3-D models of PLA1 proteins. In contrast, these mice sera showed no reaction with honeybee (HBV) and fire ant venom. Furthermore, sera from patients monosensitized to HBV and fire ants did not recognize the rPoly p 1 in immunoblotting. Our findings reveal the presence of conserved epitopes in the PLA1s from several clinically relevant wasps as major cause of PLA1-based in vitro cross-reactivity. These findings emphasize the limitations but also the potential of PLA1-based HVA diagnostics. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Reliability-Based Structural Optimization of Wave Energy Converters

    DEFF Research Database (Denmark)

    Ambühl, Simon; Kramer, Morten; Sørensen, John Dalsgaard

    2014-01-01

    More and more wave energy converter (WEC) concepts are reaching prototype level. Once the prototype level is reached, the next step in order to further decrease the levelized cost of energy (LCOE) is optimizing the overall system with a focus on structural and maintenance (inspection) costs......, as well as on the harvested power from the waves. The target of a fully-developed WEC technology is not maximizing its power output, but minimizing the resulting LCOE. This paper presents a methodology to optimize the structural design of WECs based on a reliability-based optimization problem...

  17. Analyses of criticality and reactivity for TRACY experiments based on JENDL-3.3 data library

    International Nuclear Information System (INIS)

    Sono, Hiroki; Miyoshi, Yoshinori; Nakajima, Ken

    2003-01-01

    The parameters on criticality and reactivity employed for computational simulations of the TRACY supercritical experiments were analyzed using a recently revised nuclear data library, JENDL-3.3. The parameters based on the JENDL-3.3 library were compared to those based on two former-used libraries, JENDL-3.2 and ENDF/B-VI. In the analyses computational codes, MVP, MCNP version 4C and TWOTRAN, were used. The following conclusions were obtained from the analyses: (1) The computational biases of the effective neutron multiplication factor attributable to the nuclear data libraries and to the computational codes do not depend the TRACY experimental conditions such as fuel conditions. (2) The fractional discrepancies in the kinetic parameters and coefficients of reactivity are within ∼5% between the three libraries. By comparison between calculations and measurements of the parameters, the JENDL-3.3 library is expected to give closer values to the measurements than the JENDL-3.2 and ENDF/B-VI libraries. (3) While the reactivity worth of transient rods expressed in the $ unit shows ∼5% discrepancy between the three libraries according to their respective β eff values, there is little discrepancy in that expressed in the Δk/k unit. (author)

  18. A new concept for spatially divided Deep Reactive Ion Etching with ALD-based passivation

    International Nuclear Information System (INIS)

    Roozeboom, F; Kniknie, B; Lankhorst, A M; Winands, G; Knaapen, R; Smets, M; Poodt, P; Dingemans, G; Keuning, W; Kessels, W M M

    2012-01-01

    Conventional Deep Reactive Ion Etching (DRIE) is a plasma etch process with alternating half-cycles of 1) Si-etching with SF 6 to form gaseous SiF x etch products, and 2) passivation with C 4 F 8 that polymerizes as a protecting fluorocarbon deposit on the sidewalls and bottom of the etched features. In this work we report on a novel alternative and disruptive technology concept of Spatially-divided Deep Reactive Ion Etching, S-DRIE, where the process is converted from the time-divided into the spatially divided regime. The spatial division can be accomplished by inert gas bearing 'curtains' of heights down to ∼20 μm. These curtains confine the reactive gases to individual (often linear) injection slots constructed in a gas injector head. By horizontally moving the substrate back and forth under the head one can realize the alternate exposures to the overall cycle. A second improvement in the spatially divided approach is the replacement of the CVD-based C 4 F 8 passivation steps by ALD-based oxide (e.g. SiO 2 ) deposition cycles. The method can have industrial potential in cost-effective creation of advanced 3D interconnects (TSVs), MEMS manufacturing and advanced patterning, e.g., in nanoscale transistor line edge roughness using Atomic Layer Etching.

  19. Kinetics of biological decolorisation of anthraquinone based Reactive Blue 19 using an isolated strain of Enterobacter sp.F NCIM 5545.

    Science.gov (United States)

    Holkar, Chandrakant R; Pandit, Aniruddha B; Pinjari, Dipak V

    2014-12-01

    In the present study, an attempt was made to evaluate the bacterial decolorisation of Reactive Blue 19 by an Enterobacter sp.F which was isolated from a mixed culture from anaerobic digester for biogas production. Phenotypic characterization and phylogenetic analysis based on DNA sequencing comparisons indicate that Enterobacter sp.F was 99.7% similar to Enterobacter cloacae ATCC13047. The kinetics of Reactive Blue 19 dye decolorisation by bacterium had been estimated. Effects of substrate concentration, oxygen, temperature, pH, glucose and glucose to microbe weight ratio on the rate of decolorisation were investigated to understand key factor that determines the performance of dye decolorisation. The maximum decolorisation efficiency of Reactive Blue 19 was 90% over period of 24 h for optimized parameter. To the best of our knowledge, this research study is the report where Enterobacter sp.F has been reported with about 90% decolorizing ability against anthraquinone based Reactive Blue 19 dye. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. An Improved Real-Coded Population-Based Extremal Optimization Method for Continuous Unconstrained Optimization Problems

    Directory of Open Access Journals (Sweden)

    Guo-Qiang Zeng

    2014-01-01

    Full Text Available As a novel evolutionary optimization method, extremal optimization (EO has been successfully applied to a variety of combinatorial optimization problems. However, the applications of EO in continuous optimization problems are relatively rare. This paper proposes an improved real-coded population-based EO method (IRPEO for continuous unconstrained optimization problems. The key operations of IRPEO include generation of real-coded random initial population, evaluation of individual and population fitness, selection of bad elements according to power-law probability distribution, generation of new population based on uniform random mutation, and updating the population by accepting the new population unconditionally. The experimental results on 10 benchmark test functions with the dimension N=30 have shown that IRPEO is competitive or even better than the recently reported various genetic algorithm (GA versions with different mutation operations in terms of simplicity, effectiveness, and efficiency. Furthermore, the superiority of IRPEO to other evolutionary algorithms such as original population-based EO, particle swarm optimization (PSO, and the hybrid PSO-EO is also demonstrated by the experimental results on some benchmark functions.

  1. Optimal perturbations for nonlinear systems using graph-based optimal transport

    Science.gov (United States)

    Grover, Piyush; Elamvazhuthi, Karthik

    2018-06-01

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

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

    Science.gov (United States)

    Paasche, H.; Tronicke, J.

    2012-04-01

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

  3. Optimal policy for value-based decision-making.

    Science.gov (United States)

    Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

    2016-08-18

    For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

  4. A new optimization method based on cellular automata for VVER-1000 nuclear reactor loading pattern

    International Nuclear Information System (INIS)

    Fadaei, Amir Hosein; Setayeshi, Saeed

    2009-01-01

    This paper presents a new and innovative optimization technique, which uses cellular automata for solving multi-objective optimization problems. Due to its ability in simulating the local information while taking neighboring effects into account, the cellular automata technique is a powerful tool for optimization. The fuel-loading pattern in nuclear reactor cores is a major optimization problem. Due to the immensity of the search space in fuel management optimization problems, finding the optimum solution requires a huge amount of calculations in the classical method. The cellular automata models, based on local information, can reduce the computations significantly. In this study, reducing the power peaking factor, while increasing the initial excess reactivity inside the reactor core of VVER-1000, which are two apparently contradictory objectives, are considered as the objective functions. The result is an optimum configuration, which is in agreement with the pattern proposed by the designer. In order to gain confidence in the reliability of this method, the aforementioned problem was also solved using neural network and simulated annealing, and the results and procedures were compared.

  5. Segment-based dose optimization using a genetic algorithm

    International Nuclear Information System (INIS)

    Cotrutz, Cristian; Xing Lei

    2003-01-01

    Intensity modulated radiation therapy (IMRT) inverse planning is conventionally done in two steps. Firstly, the intensity maps of the treatment beams are optimized using a dose optimization algorithm. Each of them is then decomposed into a number of segments using a leaf-sequencing algorithm for delivery. An alternative approach is to pre-assign a fixed number of field apertures and optimize directly the shapes and weights of the apertures. While the latter approach has the advantage of eliminating the leaf-sequencing step, the optimization of aperture shapes is less straightforward than that of beamlet-based optimization because of the complex dependence of the dose on the field shapes, and their weights. In this work we report a genetic algorithm for segment-based optimization. Different from a gradient iterative approach or simulated annealing, the algorithm finds the optimum solution from a population of candidate plans. In this technique, each solution is encoded using three chromosomes: one for the position of the left-bank leaves of each segment, the second for the position of the right-bank and the third for the weights of the segments defined by the first two chromosomes. The convergence towards the optimum is realized by crossover and mutation operators that ensure proper exchange of information between the three chromosomes of all the solutions in the population. The algorithm is applied to a phantom and a prostate case and the results are compared with those obtained using beamlet-based optimization. The main conclusion drawn from this study is that the genetic optimization of segment shapes and weights can produce highly conformal dose distribution. In addition, our study also confirms previous findings that fewer segments are generally needed to generate plans that are comparable with the plans obtained using beamlet-based optimization. Thus the technique may have useful applications in facilitating IMRT treatment planning

  6. Modified Chaos Particle Swarm Optimization-Based Optimized Operation Model for Stand-Alone CCHP Microgrid

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2017-07-01

    Full Text Available The optimized dispatch of different distributed generations (DGs in stand-alone microgrid (MG is of great significance to the operation’s reliability and economy, especially for energy crisis and environmental pollution. Based on controllable load (CL and combined cooling-heating-power (CCHP model of micro-gas turbine (MT, a multi-objective optimization model with relevant constraints to optimize the generation cost, load cut compensation and environmental benefit is proposed in this paper. The MG studied in this paper consists of photovoltaic (PV, wind turbine (WT, fuel cell (FC, diesel engine (DE, MT and energy storage (ES. Four typical scenarios were designed according to different day types (work day or weekend and weather conditions (sunny or rainy in view of the uncertainty of renewable energy in variable situations and load fluctuation. A modified dispatch strategy for CCHP is presented to further improve the operation economy without reducing the consumers’ comfort feeling. Chaotic optimization and elite retention strategy are introduced into basic particle swarm optimization (PSO to propose modified chaos particle swarm optimization (MCPSO whose search capability and convergence speed are improved greatly. Simulation results validate the correctness of the proposed model and the effectiveness of MCPSO algorithm in the optimized operation application of stand-alone MG.

  7. GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

    Directory of Open Access Journals (Sweden)

    Ashish Jain

    2012-07-01

    Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.

  8. Interactive Reliability-Based Optimization of Structural Systems

    DEFF Research Database (Denmark)

    Pedersen, Claus

    In order to introduce the basic concepts within the field of reliability-based structural optimization problems, this chapter is devoted to a brief outline of the basic theories. Therefore, this chapter is of a more formal nature and used as a basis for the remaining parts of the thesis. In section...... 2.2 a general non-linear optimization problem and corresponding terminology are presented whereupon optimality conditions and the standard form of an iterative optimization algorithm are outlined. Subsequently, the special properties and characteristics concerning structural optimization problems...... are treated in section 2.3. With respect to the reliability evalutation, the basic theory behind a reliability analysis and estimation of probability of failure by the First-Order Reliability Method (FORM) and the iterative Rackwitz-Fiessler (RF) algorithm are considered in section 2.5 in which...

  9. Robust optimization-based DC optimal power flow for managing wind generation uncertainty

    Science.gov (United States)

    Boonchuay, Chanwit; Tomsovic, Kevin; Li, Fangxing; Ongsakul, Weerakorn

    2012-11-01

    Integrating wind generation into the wider grid causes a number of challenges to traditional power system operation. Given the relatively large wind forecast errors, congestion management tools based on optimal power flow (OPF) need to be improved. In this paper, a robust optimization (RO)-based DCOPF is proposed to determine the optimal generation dispatch and locational marginal prices (LMPs) for a day-ahead competitive electricity market considering the risk of dispatch cost variation. The basic concept is to use the dispatch to hedge against the possibility of reduced or increased wind generation. The proposed RO-based DCOPF is compared with a stochastic non-linear programming (SNP) approach on a modified PJM 5-bus system. Primary test results show that the proposed DCOPF model can provide lower dispatch cost than the SNP approach.

  10. An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems

    Directory of Open Access Journals (Sweden)

    Vivek Patel

    2012-08-01

    Full Text Available Nature inspired population based algorithms is a research field which simulates different natural phenomena to solve a wide range of problems. Researchers have proposed several algorithms considering different natural phenomena. Teaching-Learning-based optimization (TLBO is one of the recently proposed population based algorithm which simulates the teaching-learning process of the class room. This algorithm does not require any algorithm-specific control parameters. In this paper, elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated. The effects of common controlling parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 35 constrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. The proposed algorithm can be applied to various optimization problems of the industrial environment.

  11. Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm

    International Nuclear Information System (INIS)

    Chaudhary, Kailash; Chaudhary, Himanshu

    2015-01-01

    In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).

  12. Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Chaudhary, Kailash; Chaudhary, Himanshu [Malaviya National Institute of Technology, Jaipur (Malaysia)

    2015-11-15

    In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).

  13. Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique

    Directory of Open Access Journals (Sweden)

    Po-Chen Cheng

    2015-06-01

    Full Text Available In this paper, an asymmetrical fuzzy-logic-control (FLC-based maximum power point tracking (MPPT algorithm for photovoltaic (PV systems is presented. Two membership function (MF design methodologies that can improve the effectiveness of the proposed asymmetrical FLC-based MPPT methods are then proposed. The first method can quickly determine the input MF setting values via the power–voltage (P–V curve of solar cells under standard test conditions (STC. The second method uses the particle swarm optimization (PSO technique to optimize the input MF setting values. Because the PSO approach must target and optimize a cost function, a cost function design methodology that meets the performance requirements of practical photovoltaic generation systems (PGSs is also proposed. According to the simulated and experimental results, the proposed asymmetrical FLC-based MPPT method has the highest fitness value, therefore, it can successfully address the tracking speed/tracking accuracy dilemma compared with the traditional perturb and observe (P&O and symmetrical FLC-based MPPT algorithms. Compared to the conventional FLC-based MPPT method, the obtained optimal asymmetrical FLC-based MPPT can improve the transient time and the MPPT tracking accuracy by 25.8% and 0.98% under STC, respectively.

  14. Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium

    Directory of Open Access Journals (Sweden)

    Xiao Han

    2017-12-01

    Full Text Available This paper focuses on the optimal intraday scheduling of a distribution system that includes renewable energy (RE generation, energy storage systems (ESSs, and thermostatically controlled loads (TCLs. This system also provides time-of-use pricing to customers. Unlike previous studies, this study attempts to examine how to optimize the allocation of electric energy and to improve the equilibrium of the load curve. Accordingly, we propose a concept of load equilibrium entropy to quantify the overall equilibrium of the load curve and reflect the allocation optimization of electric energy. Based on this entropy, we built a novel multi-objective optimal dispatching model to minimize the operational cost and maximize the load curve equilibrium. To aggregate TCLs into the optimization objective, we introduced the concept of a virtual power plant (VPP and proposed a calculation method for VPP operating characteristics based on the equivalent thermal parameter model and the state-queue control method. The Particle Swarm Optimization algorithm was employed to solve the optimization problems. The simulation results illustrated that the proposed dispatching model can achieve cost reductions of system operations, peak load curtailment, and efficiency improvements, and also verified that the load equilibrium entropy can be used as a novel index of load characteristics.

  15. Enhanced GSA-Based Optimization for Minimization of Power Losses in Power System

    Directory of Open Access Journals (Sweden)

    Gonggui Chen

    2015-01-01

    Full Text Available Gravitational Search Algorithm (GSA is a heuristic method based on Newton’s law of gravitational attraction and law of motion. In this paper, to further improve the optimization performance of GSA, the memory characteristic of Particle Swarm Optimization (PSO is employed in GSAPSO for searching a better solution. Besides, to testify the prominent strength of GSAPSO, GSA, PSO, and GSAPSO are applied for the solution of optimal reactive power dispatch (ORPD of power system. Conventionally, ORPD is defined as a problem of minimizing the total active power transmission losses by setting control variables while satisfying numerous constraints. Therefore ORPD is a complicated mixed integer nonlinear optimization problem including many constraints. IEEE14-bus, IEEE30-bus, and IEEE57-bus test power systems are used to implement this study, respectively. The obtained results of simulation experiments using GSAPSO method, especially the power loss reduction rates, are compared to those yielded by the other modern artificial intelligence-based techniques including the conventional GSA and PSO methods. The results presented in this paper reveal the potential and effectiveness of the proposed method for solving ORPD problem of power system.

  16. Orthogonal Analysis Based Performance Optimization for Vertical Axis Wind Turbine

    Directory of Open Access Journals (Sweden)

    Lei Song

    2016-01-01

    Full Text Available Geometrical shape of a vertical axis wind turbine (VAWT is composed of multiple structural parameters. Since there are interactions among the structural parameters, traditional research approaches, which usually focus on one parameter at a time, cannot obtain performance of the wind turbine accurately. In order to exploit overall effect of a novel VAWT, we firstly use a single parameter optimization method to obtain optimal values of the structural parameters, respectively, by Computational Fluid Dynamics (CFD method; based on the results, we then use an orthogonal analysis method to investigate the influence of interactions of the structural parameters on performance of the wind turbine and to obtain optimization combination of the structural parameters considering the interactions. Results of analysis of variance indicate that interactions among the structural parameters have influence on performance of the wind turbine, and optimization results based on orthogonal analysis have higher wind energy utilization than that of traditional research approaches.

  17. 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)

  18. Theoretical study of some aspects of the nucleo-bases reactivity: definition of new theoretical tools for the study of chemical reactivity

    International Nuclear Information System (INIS)

    Labet, V.

    2009-09-01

    In this work, three kinds of nucleo-base damages were studied from a theoretical point of view with quantum chemistry methods based on the density-functional theory: the spontaneous deamination of cytosine and its derivatives, the formation of tandem lesion induced by hydroxyl radicals in anaerobic medium and the formation of pyrimidic dimers under exposition to an UV radiation. The complementary use of quantitative static methods allowing the exploration of the potential energy surface of a chemical reaction, and of 'conceptual DFT' principles, leads to information concerning the mechanisms involved and to the rationalization of the differences in the nucleo-bases reactivity towards the formation of a same kind of damage. At the same time, a reflexion was undertaken on the asynchronous concerted mechanism concept, in terms of physical meaning of the transition state, respect of the Maximum Hardness Principle, and determination of the number of primitive processes involved. Finally, a new local reactivity index was developed, relevant to understand the reactivity of a molecular system in an excited state. (author)

  19. Length scale and manufacturability in density-based topology optimization

    DEFF Research Database (Denmark)

    Lazarov, Boyan Stefanov; Wang, Fengwen; Sigmund, Ole

    2016-01-01

    Since its original introduction in structural design, density-based topology optimization has been applied to a number of other fields such as microelectromechanical systems, photonics, acoustics and fluid mechanics. The methodology has been well accepted in industrial design processes where it can...... provide competitive designs in terms of cost, materials and functionality under a wide set of constraints. However, the optimized topologies are often considered as conceptual due to loosely defined topologies and the need of postprocessing. Subsequent amendments can affect the optimized design...

  20. Cooperative Game Study of Airlines Based on Flight Frequency Optimization

    Directory of Open Access Journals (Sweden)

    Wanming Liu

    2014-01-01

    Full Text Available By applying the game theory, the relationship between airline ticket price and optimal flight frequency is analyzed. The paper establishes the payoff matrix of the flight frequency in noncooperation scenario and flight frequency optimization model in cooperation scenario. The airline alliance profit distribution is converted into profit distribution game based on the cooperation game theory. The profit distribution game is proved to be convex, and there exists an optimal distribution strategy. The results show that joining the airline alliance can increase airline whole profit, the change of negotiated prices and cost is beneficial to profit distribution of large airlines, and the distribution result is in accordance with aviation development.

  1. Genetic-evolution-based optimization methods for engineering design

    Science.gov (United States)

    Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

    1990-01-01

    This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

  2. Maximum length scale in density based topology optimization

    DEFF Research Database (Denmark)

    Lazarov, Boyan Stefanov; Wang, Fengwen

    2017-01-01

    The focus of this work is on two new techniques for imposing maximum length scale in topology optimization. Restrictions on the maximum length scale provide designers with full control over the optimized structure and open possibilities to tailor the optimized design for broader range...... of manufacturing processes by fulfilling the associated technological constraints. One of the proposed methods is based on combination of several filters and builds on top of the classical density filtering which can be viewed as a low pass filter applied to the design parametrization. The main idea...

  3. An opinion formation based binary optimization approach for feature selection

    Science.gov (United States)

    Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

    2018-02-01

    This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

  4. Reactivity-based industrial volatile organic compounds emission inventory and its implications for ozone control strategies in China

    Science.gov (United States)

    Liang, Xiaoming; Chen, Xiaofang; Zhang, Jiani; Shi, Tianli; Sun, Xibo; Fan, Liya; Wang, Liming; Ye, Daiqi

    2017-08-01

    Increasingly serious ozone (O3) pollution, along with decreasing NOx emission, is creating a big challenge in the control of volatile organic compounds (VOCs) in China. More efficient and effective measures are assuredly needed for controlling VOCs. In this study, a reactivity-based industrial VOCs emission inventory was established in China based on the concept of ozone formation potential (OFP). Key VOCs species, major VOCs sources, and dominant regions with high reactivity were identified. Our results show that the top 15 OFP-based species, including m/p-xylene, toluene, propene, o-xylene, and ethyl benzene, contribute 69% of the total OFP but only 30% of the total emission. The architectural decoration industry, oil refinery industry, storage and transport, and seven other sources constituted the top 10 OFP subsectors, together contributing a total of 85%. The provincial and spatial characteristics of OFP are generally consistent with those of mass-based inventory. The implications for O3 control strategies in China are discussed. We propose a reactivity-based national definition of VOCs and low-reactive substitution strategies, combined with evaluations of health risks. Priority should be given to the top 15 or more species with high reactivity through their major emission sources. Reactivity-based policies should be flexibly applied for O3 mitigation based on the sensitivity of O3 formation conditions.

  5. Discounted cost model for condition-based maintenance optimization

    International Nuclear Information System (INIS)

    Weide, J.A.M. van der; Pandey, M.D.; Noortwijk, J.M. van

    2010-01-01

    This paper presents methods to evaluate the reliability and optimize the maintenance of engineering systems that are damaged by shocks or transients arriving randomly in time and overall degradation is modeled as a cumulative stochastic point process. The paper presents a conceptually clear and comprehensive derivation of formulas for computing the discounted cost associated with a maintenance policy combining both condition-based and age-based criteria for preventive maintenance. The proposed discounted cost model provides a more realistic basis for optimizing the maintenance policies than those based on the asymptotic, non-discounted cost rate criterion.

  6. Cancer Classification Based on Support Vector Machine Optimized by Particle Swarm Optimization and Artificial Bee Colony.

    Science.gov (United States)

    Gao, Lingyun; Ye, Mingquan; Wu, Changrong

    2017-11-29

    Intelligent optimization algorithms have advantages in dealing with complex nonlinear problems accompanied by good flexibility and adaptability. In this paper, the FCBF (Fast Correlation-Based Feature selection) method is used to filter irrelevant and redundant features in order to improve the quality of cancer classification. Then, we perform classification based on SVM (Support Vector Machine) optimized by PSO (Particle Swarm Optimization) combined with ABC (Artificial Bee Colony) approaches, which is represented as PA-SVM. The proposed PA-SVM method is applied to nine cancer datasets, including five datasets of outcome prediction and a protein dataset of ovarian cancer. By comparison with other classification methods, the results demonstrate the effectiveness and the robustness of the proposed PA-SVM method in handling various types of data for cancer classification.

  7. Gradient-based methods for production optimization of oil reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Suwartadi, Eka

    2012-07-01

    Production optimization for water flooding in the secondary phase of oil recovery is the main topic in this thesis. The emphasis has been on numerical optimization algorithms, tested on case examples using simple hypothetical oil reservoirs. Gradientbased optimization, which utilizes adjoint-based gradient computation, is used to solve the optimization problems. The first contribution of this thesis is to address output constraint problems. These kinds of constraints are natural in production optimization. Limiting total water production and water cut at producer wells are examples of such constraints. To maintain the feasibility of an optimization solution, a Lagrangian barrier method is proposed to handle the output constraints. This method incorporates the output constraints into the objective function, thus avoiding additional computations for the constraints gradient (Jacobian) which may be detrimental to the efficiency of the adjoint method. The second contribution is the study of the use of second-order adjoint-gradient information for production optimization. In order to speedup convergence rate in the optimization, one usually uses quasi-Newton approaches such as BFGS and SR1 methods. These methods compute an approximation of the inverse of the Hessian matrix given the first-order gradient from the adjoint method. The methods may not give significant speedup if the Hessian is ill-conditioned. We have developed and implemented the Hessian matrix computation using the adjoint method. Due to high computational cost of the Newton method itself, we instead compute the Hessian-timesvector product which is used in a conjugate gradient algorithm. Finally, the last contribution of this thesis is on surrogate optimization for water flooding in the presence of the output constraints. Two kinds of model order reduction techniques are applied to build surrogate models. These are proper orthogonal decomposition (POD) and the discrete empirical interpolation method (DEIM

  8. Feasibility Study for the Use of Green, Bio-Based, Efficient Reactive Sorbent Material to Neutralize Chemical Warfare Agents

    Science.gov (United States)

    2012-08-02

    REPORT Feasibility study for the use of green, bio-based, efficient reactive sorbent material to neutralize chemical warfare agents 14. ABSTRACT 16...way cellulose, lignin and hemicelluloses interact as well as whole wood dissolution occurs in ILs. The present project was conducted to 1. REPORT...Feasibility study for the use of green, bio-based, efficient reactive sorbent material to neutralize chemical warfare agents Report Title ABSTRACT Over the

  9. Global Optimization Based on the Hybridization of Harmony Search and Particle Swarm Optimization Methods

    Directory of Open Access Journals (Sweden)

    A. P. Karpenko

    2014-01-01

    Full Text Available We consider a class of stochastic search algorithms of global optimization which in various publications are called behavioural, intellectual, metaheuristic, inspired by the nature, swarm, multi-agent, population, etc. We use the last term.Experience in using the population algorithms to solve challenges of global optimization shows that application of one such algorithm may not always effective. Therefore now great attention is paid to hybridization of population algorithms of global optimization. Hybrid algorithms unite various algorithms or identical algorithms, but with various values of free parameters. Thus efficiency of one algorithm can compensate weakness of another.The purposes of the work are development of hybrid algorithm of global optimization based on known algorithms of harmony search (HS and swarm of particles (PSO, software implementation of algorithm, study of its efficiency using a number of known benchmark problems, and a problem of dimensional optimization of truss structure.We set a problem of global optimization, consider basic algorithms of HS and PSO, give a flow chart of the offered hybrid algorithm called PSO HS , present results of computing experiments with developed algorithm and software, formulate main results of work and prospects of its development.

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

    Directory of Open Access Journals (Sweden)

    Jiajun Liu

    2017-10-01

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

  11. Cover crop-based ecological weed management: exploration and optimization

    NARCIS (Netherlands)

    Kruidhof, H.M.

    2008-01-01

    Keywords: organic farming, ecologically-based weed management, cover crops, green manure, allelopathy, Secale cereale, Brassica napus, Medicago sativa

    Cover crop-based ecological weed management: exploration and optimization. In organic farming systems, weed control is recognized as one

  12. GPU-Monte Carlo based fast IMRT plan optimization

    Directory of Open Access Journals (Sweden)

    Yongbao Li

    2014-03-01

    Full Text Available Purpose: Intensity-modulated radiation treatment (IMRT plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow.Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, a rough dose calculation is conducted with only a few number of particle per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final result.Results: For a lung case with 5317 beamlets, 105 particles per beamlet in the first round, and 108 particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec.Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.--------------------------------Cite this article as: Li Y, Tian Z

  13. Integrated Design and Control of Reactive and Non-Reactive Distillation Processes

    DEFF Research Database (Denmark)

    Mansouri, Seyed Soheil; Sales-Cruz, Mauricio; Huusom, Jakob Kjøbsted

    , an alternative approach is to tackle process design and controllability issues simultaneously, in the early stages of process design. This simultaneous synthesis approach provides optimal/near optimal operation and more efficient control of conventional (non-reactive binary distillation columns) (Hamid et al...... of methodologies have been proposed and applied on various problems to address the interactions between process design and control, and they range from optimization-based approaches to model-based methods (Sharifzadeh, 2013). In this work, integrated design and control of non-reactive distillation, ternary...... reactive distillation processes. The element concept (Pérez Cisneros et al., 1997) is used to translate a ternary system of compounds (A + B ↔ C) to a binary system of element (WA and WB). In the case of multicomponent reactive distillation processes the equivalent element concept is used to translate...

  14. Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.

    Science.gov (United States)

    Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao

    2015-04-01

    Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Trust regions in Kriging-based optimization with expected improvement

    Science.gov (United States)

    Regis, Rommel G.

    2016-06-01

    The Kriging-based Efficient Global Optimization (EGO) method works well on many expensive black-box optimization problems. However, it does not seem to perform well on problems with steep and narrow global minimum basins and on high-dimensional problems. This article develops a new Kriging-based optimization method called TRIKE (Trust Region Implementation in Kriging-based optimization with Expected improvement) that implements a trust-region-like approach where each iterate is obtained by maximizing an Expected Improvement (EI) function within some trust region. This trust region is adjusted depending on the ratio of the actual improvement to the EI. This article also develops the Kriging-based CYCLONE (CYClic Local search in OptimizatioN using Expected improvement) method that uses a cyclic pattern to determine the search regions where the EI is maximized. TRIKE and CYCLONE are compared with EGO on 28 test problems with up to 32 dimensions and on a 36-dimensional groundwater bioremediation application in appendices supplied as an online supplement available at http://dx.doi.org/10.1080/0305215X.2015.1082350. The results show that both algorithms yield substantial improvements over EGO and they are competitive with a radial basis function method.

  16. APPROACH ON INTELLIGENT OPTIMIZATION DESIGN BASED ON COMPOUND KNOWLEDGE

    Institute of Scientific and Technical Information of China (English)

    Yao Jianchu; Zhou Ji; Yu Jun

    2003-01-01

    A concept of an intelligent optimal design approach is proposed, which is organized by a kind of compound knowledge model. The compound knowledge consists of modularized quantitative knowledge, inclusive experience knowledge and case-based sample knowledge. By using this compound knowledge model, the abundant quantity information of mathematical programming and the symbolic knowledge of artificial intelligence can be united together in this model. The intelligent optimal design model based on such a compound knowledge and the automatically generated decomposition principles based on it are also presented. Practically, it is applied to the production planning, process schedule and optimization of production process of a refining & chemical work and a great profit is achieved. Specially, the methods and principles are adaptable not only to continuous process industry, but also to discrete manufacturing one.

  17. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    Science.gov (United States)

    Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

  18. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Mohammed Hasan Abdulameer

    2014-01-01

    Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  19. A systematic optimization for graphene-based supercapacitors

    Science.gov (United States)

    Deuk Lee, Sung; Lee, Han Sung; Kim, Jin Young; Jeong, Jaesik; Kahng, Yung Ho

    2017-08-01

    Increasing the energy-storage density for supercapacitors is critical for their applications. Many researchers have attempted to identify optimal candidate component materials to achieve this goal, but investigations into systematically optimizing their mixing rate for maximizing the performance of each candidate material have been insufficient, which hinders the progress in their technology. In this study, we employ a statistically systematic method to determine the optimum mixing ratio of three components that constitute graphene-based supercapacitor electrodes: reduced graphene oxide (rGO), acetylene black (AB), and polyvinylidene fluoride (PVDF). By using the extreme-vertices design, the optimized proportion is determined to be (rGO: AB: PVDF  =  0.95: 0.00: 0.05). The corresponding energy-storage density increases by a factor of 2 compared with that of non-optimized electrodes. Electrochemical and microscopic analyses are performed to determine the reason for the performance improvements.

  20. 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.

  1. EUD-based biological optimization for carbon ion therapy

    International Nuclear Information System (INIS)

    Brüningk, Sarah C.; Kamp, Florian; Wilkens, Jan J.

    2015-01-01

    Purpose: Treatment planning for carbon ion therapy requires an accurate modeling of the biological response of each tissue to estimate the clinical outcome of a treatment. The relative biological effectiveness (RBE) accounts for this biological response on a cellular level but does not refer to the actual impact on the organ as a whole. For photon therapy, the concept of equivalent uniform dose (EUD) represents a simple model to take the organ response into account, yet so far no formulation of EUD has been reported that is suitable to carbon ion therapy. The authors introduce the concept of an equivalent uniform effect (EUE) that is directly applicable to both ion and photon therapies and exemplarily implemented it as a basis for biological treatment plan optimization for carbon ion therapy. Methods: In addition to a classical EUD concept, which calculates a generalized mean over the RBE-weighted dose distribution, the authors propose the EUE to simplify the optimization process of carbon ion therapy plans. The EUE is defined as the biologically equivalent uniform effect that yields the same probability of injury as the inhomogeneous effect distribution in an organ. Its mathematical formulation is based on the generalized mean effect using an effect-volume parameter to account for different organ architectures and is thus independent of a reference radiation. For both EUD concepts, quadratic and logistic objective functions are implemented into a research treatment planning system. A flexible implementation allows choosing for each structure between biological effect constraints per voxel and EUD constraints per structure. Exemplary treatment plans are calculated for a head-and-neck patient for multiple combinations of objective functions and optimization parameters. Results: Treatment plans optimized using an EUE-based objective function were comparable to those optimized with an RBE-weighted EUD-based approach. In agreement with previous results from photon

  2. A Novel Consensus-Based Particle Swarm Optimization-Assisted Trust-Tech Methodology for Large-Scale Global Optimization.

    Science.gov (United States)

    Zhang, Yong-Feng; Chiang, Hsiao-Dong

    2017-09-01

    A novel three-stage methodology, termed the "consensus-based particle swarm optimization (PSO)-assisted Trust-Tech methodology," to find global optimal solutions for nonlinear optimization problems is presented. It is composed of Trust-Tech methods, consensus-based PSO, and local optimization methods that are integrated to compute a set of high-quality local optimal solutions that can contain the global optimal solution. The proposed methodology compares very favorably with several recently developed PSO algorithms based on a set of small-dimension benchmark optimization problems and 20 large-dimension test functions from the CEC 2010 competition. The analytical basis for the proposed methodology is also provided. Experimental results demonstrate that the proposed methodology can rapidly obtain high-quality optimal solutions that can contain the global optimal solution. The scalability of the proposed methodology is promising.

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

    Directory of Open Access Journals (Sweden)

    Na Tian

    2015-01-01

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

  4. Optimization of reactive simulated moving bed systems with modulation of feed concentration for production of glycol ether ester.

    Science.gov (United States)

    Agrawal, Gaurav; Oh, Jungmin; Sreedhar, Balamurali; Tie, Shan; Donaldson, Megan E; Frank, Timothy C; Schultz, Alfred K; Bommarius, Andreas S; Kawajiri, Yoshiaki

    2014-09-19

    In this article, we extend the simulated moving bed reactor (SMBR) mode of operation to the production of propylene glycol methyl ether acetate (DOWANOL™ PMA glycol ether) through the esterification of 1-methoxy-2-propanol (DOWANOL™ PM glycol ether) and acetic acid using AMBERLYST™ 15 as a catalyst and adsorbent. In addition, for the first time, we integrate the concept of modulation of the feed concentration (ModiCon) to SMBR operation. The performance of the conventional (constant feed) and ModiCon operation modes of SMBR are analyzed and compared. The SMBR processes are designed using a model based on a multi-objective optimization approach, where a transport dispersive model with a linear driving force for the adsorption rate has been used for modeling the SMBR system. The adsorption equilibrium and kinetics parameters are estimated from the batch and single column injection experiments by the inverse method. The multiple objectives are to maximize the production rate of DOWANOL™ PMA glycol ether, maximize the conversion of the esterification reaction and minimize the consumption of DOWANOL™ PM glycol ether which also acts as the desorbent in the chromatographic separation. It is shown that ModiCon achieves a higher productivity by 12-36% over the conventional operation with higher product purity and recovery. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Simulation-based optimization of sustainable national energy systems

    International Nuclear Information System (INIS)

    Batas Bjelić, Ilija; Rajaković, Nikola

    2015-01-01

    The goals of the EU2030 energy policy should be achieved cost-effectively by employing the optimal mix of supply and demand side technical measures, including energy efficiency, renewable energy and structural measures. In this paper, the achievement of these goals is modeled by introducing an innovative method of soft-linking of EnergyPLAN with the generic optimization program (GenOpt). This soft-link enables simulation-based optimization, guided with the chosen optimization algorithm, rather than manual adjustments of the decision vectors. In order to obtain EnergyPLAN simulations within the optimization loop of GenOpt, the decision vectors should be chosen and explained in GenOpt for scenarios created in EnergyPLAN. The result of the optimization loop is an optimal national energy master plan (as a case study, energy policy in Serbia was taken), followed with sensitivity analysis of the exogenous assumptions and with focus on the contribution of the smart electricity grid to the achievement of EU2030 goals. It is shown that the increase in the policy-induced total costs of less than 3% is not significant. This general method could be further improved and used worldwide in the optimal planning of sustainable national energy systems. - Highlights: • Innovative method of soft-linking of EnergyPLAN with GenOpt has been introduced. • Optimal national energy master plan has been developed (the case study for Serbia). • Sensitivity analysis on the exogenous world energy and emission price development outlook. • Focus on the contribution of smart energy systems to the EU2030 goals. • Innovative soft-linking methodology could be further improved and used worldwide.

  6. Void reactivity feedback analysis for U-based and Th-based LWR incineration cycles

    Energy Technology Data Exchange (ETDEWEB)

    Lindley, B.A.; Parks, G.T. [Cambridge University Engineering Department, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom); Franceschini, F. [Westinghouse Electric Company LLC, Cranberry Township, PA (United States)

    2013-07-01

    In reduced-moderation LWRs, an external supply of transuranic (TRU) can be incinerated by mixing it with a fertile isotope ({sup 238}U or {sup 232}Th) and recycling all the actinides after each cycle. Performance is limited by coolant reactivity feedback - the moderator density coefficient (MDC) must be kept negative. The MDC is worse when more TRU is loaded, but TRU feed is also needed to maintain criticality. To assess the performance of this fuel cycle in different neutron spectra, three LWRs are considered: 'reference' PWRs and reduced-moderation PWRs and BWRs. The MDC of the equilibrium cycle is analysed by reactivity decomposition with perturbed coolant density by isotope and neutron energy. The results show that using {sup 232}Th as a fertile isotope yields superior performance to {sup 238}U. This is due essentially to the high resonance η of U bred from Th (U3), which increases the fissility of the U3-TRU isotope vector in the Th-fueled system relative to the U-fueled system, and also improves the MDC in a sufficiently hard spectrum. Spatial separation of TRU and U3 in the Th-fueled system renders further improvement by hardening the neutron spectrum in the TRU and softening it in the U3. This improves the TRU η and increases the negative MDC contribution from reduced thermal fission in U3. (authors)

  7. An Image Morphing Technique Based on Optimal Mass Preserving Mapping

    Science.gov (United States)

    Zhu, Lei; Yang, Yan; Haker, Steven; Tannenbaum, Allen

    2013-01-01

    Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The L2 mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods. PMID:17547128

  8. The reactivity meter and core reactivity

    International Nuclear Information System (INIS)

    Siltanen, P.

    1999-01-01

    This paper discussed in depth the point kinetic equations and the characteristics of the point kinetic reactivity meter, particularly for large negative reactivities. From a given input signal representing the neutron flux seen by a detector, the meter computes a value of reactivity in dollars (ρ/β), based on inverse point kinetics. The prompt jump point of view is emphasised. (Author)

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

    Directory of Open Access Journals (Sweden)

    Biwei Tang

    2016-01-01

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

  10. Optimization of DNA Sensor Model Based Nanostructured Graphene Using Particle Swarm Optimization Technique

    Directory of Open Access Journals (Sweden)

    Hediyeh Karimi

    2013-01-01

    Full Text Available It has been predicted that the nanomaterials of graphene will be among the candidate materials for postsilicon electronics due to their astonishing properties such as high carrier mobility, thermal conductivity, and biocompatibility. Graphene is a semimetal zero gap nanomaterial with demonstrated ability to be employed as an excellent candidate for DNA sensing. Graphene-based DNA sensors have been used to detect the DNA adsorption to examine a DNA concentration in an analyte solution. In particular, there is an essential need for developing the cost-effective DNA sensors holding the fact that it is suitable for the diagnosis of genetic or pathogenic diseases. In this paper, particle swarm optimization technique is employed to optimize the analytical model of a graphene-based DNA sensor which is used for electrical detection of DNA molecules. The results are reported for 5 different concentrations, covering a range from 0.01 nM to 500 nM. The comparison of the optimized model with the experimental data shows an accuracy of more than 95% which verifies that the optimized model is reliable for being used in any application of the graphene-based DNA sensor.

  11. Soft sensor based composition estimation and controller design for an ideal reactive distillation column.

    Science.gov (United States)

    Vijaya Raghavan, S R; Radhakrishnan, T K; Srinivasan, K

    2011-01-01

    In this research work, the authors have presented the design and implementation of a recurrent neural network (RNN) based inferential state estimation scheme for an ideal reactive distillation column. Decentralized PI controllers are designed and implemented. The reactive distillation process is controlled by controlling the composition which has been estimated from the available temperature measurements using a type of RNN called Time Delayed Neural Network (TDNN). The performance of the RNN based state estimation scheme under both open loop and closed loop have been compared with a standard Extended Kalman filter (EKF) and a Feed forward Neural Network (FNN). The online training/correction has been done for both RNN and FNN schemes for every ten minutes whenever new un-trained measurements are available from a conventional composition analyzer. The performance of RNN shows better state estimation capability as compared to other state estimation schemes in terms of qualitative and quantitative performance indices. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Single-Phase Boost Inverter-Based Electric Vehicle Charger With Integrated Vehicle to Grid Reactive Power Compensation

    DEFF Research Database (Denmark)

    Wickramasinghe Abeywardana, Damith Buddika; Acuna, Pablo; Hredzak, Branislav

    2018-01-01

    Vehicle to grid (V2G) reactive power compensation using electric vehicle (EV) onboard chargers helps to ensure grid power quality by achieving unity power factor operation. However, the use of EVs for V2G reactive power compensation increases the second-order harmonic ripple current component...... from the grid, exposes the EV battery to these undesirable ripple current components for a longer period and discharges the battery due to power conversion losses. This paper presents a way to provide V2G reactive power compensation through a boost inverter-based single stage EV charger and a DC...

  13. Rapid Optimal Generation Algorithm for Terrain Following Trajectory Based on Optimal Control

    Institute of Scientific and Technical Information of China (English)

    杨剑影; 张海; 谢邦荣; 尹健

    2004-01-01

    Based on the optimal control theory, a 3-dimensionnal direct generation algorithm is proposed for anti-ground low altitude penetration tasks under complex terrain. By optimizing the terrain following(TF) objective function,terrain coordinate system, missile dynamic model and control vector, the TF issue is turning into the improved optimal control problem whose mathmatical model is simple and need not solve the second order terrain derivative. Simulation results prove that this method is reasonable and feasible. The TF precision is in the scope from 0.3 m to 3.0 m,and the planning time is less than 30 min. This method have the strongpionts such as rapidness, precision and has great application value.

  14. Trafficability Analysis at Traffic Crossing and Parameters Optimization Based on Particle Swarm Optimization Method

    Directory of Open Access Journals (Sweden)

    Bin He

    2014-01-01

    Full Text Available In city traffic, it is important to improve transportation efficiency and the spacing of platoon should be shortened when crossing the street. The best method to deal with this problem is automatic control of vehicles. In this paper, a mathematical model is established for the platoon’s longitudinal movement. A systematic analysis of longitudinal control law is presented for the platoon of vehicles. However, the parameter calibration for the platoon model is relatively difficult because the platoon model is complex and the parameters are coupled with each other. In this paper, the particle swarm optimization method is introduced to effectively optimize the parameters of platoon. The proposed method effectively finds the optimal parameters based on simulations and makes the spacing of platoon shorter.

  15. Sizing optimization of skeletal structures using teaching-learning based optimization

    Directory of Open Access Journals (Sweden)

    Vedat Toğan

    2017-03-01

    Full Text Available Teaching Learning Based Optimization (TLBO is one of the non-traditional techniques to simulate natural phenomena into a numerical algorithm. TLBO mimics teaching learning process occurring between a teacher and students in a classroom. A parameter named as teaching factor, TF, seems to be the only tuning parameter in TLBO. Although the value of the teaching factor, TF, is determined by an equation, the value of 1 or 2 has been used by the researchers for TF. This study intends to explore the effect of the variation of teaching factor TF on the performances of TLBO. This effect is demonstrated in solving structural optimization problems including truss and frame structures under the stress and displacement constraints. The results indicate that the variation of TF in the TLBO process does not change the results obtained at the end of the optimization procedure when the computational cost of TLBO is ignored.

  16. Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Sen Zhang

    2015-01-01

    Full Text Available One heuristic evolutionary algorithm recently proposed is the grey wolf optimizer (GWO, inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature. This paper presents an extended GWO algorithm based on Powell local optimization method, and we call it PGWO. PGWO algorithm significantly improves the original GWO in solving complex optimization problems. Clustering is a popular data analysis and data mining technique. Hence, the PGWO could be applied in solving clustering problems. In this study, first the PGWO algorithm is tested on seven benchmark functions. Second, the PGWO algorithm is used for data clustering on nine data sets. Compared to other state-of-the-art evolutionary algorithms, the results of benchmark and data clustering demonstrate the superior performance of PGWO algorithm.

  17. Effect of Relative Humidity and CO2 Concentration on the Properties of Carbonated Reactive MgO Cement Based Materials

    Science.gov (United States)

    Bilan, Yaroslav

    Sustainability of modern concrete industry recently has become an important topic of scientific discussion, and consequently there is an effort to study the potential of the emerging new supplementary cementitious materials. This study has a purpose to investigate the effect of reactive magnesia (reactive MgO) as a replacement for general use (GU) Portland Cements and the effect of environmental factors (CO2 concentrations and relative humidity) on accelerated carbonation curing results. The findings of this study revealed that improvement of physical properties is related directly to the increase in CO2 concentrations and inversely to the increase in relative humidity and also depends much on %MgO in the mixture. The conclusions of this study helped to clarify the effect of variable environmental factors and the material replacement range on carbonation of reactive magnesia concrete materials, as well as providing an assessment of the optimal conditions for the effective usage of the material.

  18. Reliability-based performance simulation for optimized pavement maintenance

    International Nuclear Information System (INIS)

    Chou, Jui-Sheng; Le, Thanh-Son

    2011-01-01

    Roadway pavement maintenance is essential for driver safety and highway infrastructure efficiency. However, regular preventive maintenance and rehabilitation (M and R) activities are extremely costly. Unfortunately, the funds available for the M and R of highway pavement are often given lower priority compared to other national development policies, therefore, available funds must be allocated wisely. Maintenance strategies are typically implemented by optimizing only the cost whilst the reliability of facility performance is neglected. This study proposes a novel algorithm using multi-objective particle swarm optimization (MOPSO) technique to evaluate the cost-reliability tradeoff in a flexible maintenance strategy based on non-dominant solutions. Moreover, a probabilistic model for regression parameters is employed to assess reliability-based performance. A numerical example of a highway pavement project is illustrated to demonstrate the efficacy of the proposed MOPSO algorithms. The analytical results show that the proposed approach can help decision makers to optimize roadway maintenance plans. - Highlights: →A novel algorithm using multi-objective particle swarm optimization technique. → Evaluation of the cost-reliability tradeoff in a flexible maintenance strategy. → A probabilistic model for regression parameters is employed to assess reliability-based performance. → The proposed approach can help decision makers to optimize roadway maintenance plans.

  19. Reliability-based performance simulation for optimized pavement maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Chou, Jui-Sheng, E-mail: jschou@mail.ntust.edu.tw [Department of Construction Engineering, National Taiwan University of Science and Technology (Taiwan Tech), 43 Sec. 4, Keelung Rd., Taipei 106, Taiwan (China); Le, Thanh-Son [Department of Construction Engineering, National Taiwan University of Science and Technology (Taiwan Tech), 43 Sec. 4, Keelung Rd., Taipei 106, Taiwan (China)

    2011-10-15

    Roadway pavement maintenance is essential for driver safety and highway infrastructure efficiency. However, regular preventive maintenance and rehabilitation (M and R) activities are extremely costly. Unfortunately, the funds available for the M and R of highway pavement are often given lower priority compared to other national development policies, therefore, available funds must be allocated wisely. Maintenance strategies are typically implemented by optimizing only the cost whilst the reliability of facility performance is neglected. This study proposes a novel algorithm using multi-objective particle swarm optimization (MOPSO) technique to evaluate the cost-reliability tradeoff in a flexible maintenance strategy based on non-dominant solutions. Moreover, a probabilistic model for regression parameters is employed to assess reliability-based performance. A numerical example of a highway pavement project is illustrated to demonstrate the efficacy of the proposed MOPSO algorithms. The analytical results show that the proposed approach can help decision makers to optimize roadway maintenance plans. - Highlights: > A novel algorithm using multi-objective particle swarm optimization technique. > Evaluation of the cost-reliability tradeoff in a flexible maintenance strategy. > A probabilistic model for regression parameters is employed to assess reliability-based performance. > The proposed approach can help decision makers to optimize roadway maintenance plans.

  20. A class-based search for the in-core fuel management optimization of a pressurized water reactor

    International Nuclear Information System (INIS)

    Alvarenga de Moura Meneses, Anderson; Rancoita, Paola; Schirru, Roberto; Gambardella, Luca Maria

    2010-01-01

    The In-Core Fuel Management Optimization (ICFMO) is a prominent problem in nuclear engineering, with high complexity and studied for more than 40 years. Besides manual optimization and knowledge-based methods, optimization metaheuristics such as Genetic Algorithms, Ant Colony Optimization and Particle Swarm Optimization have yielded outstanding results for the ICFMO. In the present article, the Class-Based Search (CBS) is presented for application to the ICFMO. It is a novel metaheuristic approach that performs the search based on the main nuclear characteristics of the fuel assemblies, such as reactivity. The CBS is then compared to the one of the state-of-art algorithms applied to the ICFMO, the Particle Swarm Optimization. Experiments were performed for the optimization of Angra 1 Nuclear Power Plant, located at the Southeast of Brazil. The CBS presented noticeable performance, providing Loading Patterns that yield a higher average of Effective Full Power Days in the simulation of Angra 1 NPP operation, according to our methodology.

  1. A class-based search for the in-core fuel management optimization of a pressurized water reactor

    Energy Technology Data Exchange (ETDEWEB)

    Alvarenga de Moura Meneses, Anderson, E-mail: ameneses@lmp.ufrj.b [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); Rancoita, Paola [IDSIA (Dalle Molle Institute for Artificial Intelligence), Galleria 2, 6982 Manno-Lugano, TI (Switzerland); Mathematics Department, Universita degli Studi di Milano (Italy); Schirru, Roberto [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); Gambardella, Luca Maria [IDSIA (Dalle Molle Institute for Artificial Intelligence), Galleria 2, 6982 Manno-Lugano, TI (Switzerland)

    2010-11-15

    The In-Core Fuel Management Optimization (ICFMO) is a prominent problem in nuclear engineering, with high complexity and studied for more than 40 years. Besides manual optimization and knowledge-based methods, optimization metaheuristics such as Genetic Algorithms, Ant Colony Optimization and Particle Swarm Optimization have yielded outstanding results for the ICFMO. In the present article, the Class-Based Search (CBS) is presented for application to the ICFMO. It is a novel metaheuristic approach that performs the search based on the main nuclear characteristics of the fuel assemblies, such as reactivity. The CBS is then compared to the one of the state-of-art algorithms applied to the ICFMO, the Particle Swarm Optimization. Experiments were performed for the optimization of Angra 1 Nuclear Power Plant, located at the Southeast of Brazil. The CBS presented noticeable performance, providing Loading Patterns that yield a higher average of Effective Full Power Days in the simulation of Angra 1 NPP operation, according to our methodology.

  2. Optimization for PET imaging based on phantom study and NECdensity

    International Nuclear Information System (INIS)

    Daisaki, Hiromitsu; Shimada, Naoki; Shinohara, Hiroyuki

    2012-01-01

    In consideration of the requirement for global standardization and quality control of PET imaging, the present studies gave an outline of phantom study to decide both scan and reconstruction parameters based on FDG-PET/CT procedure guideline in Japan, and optimization of scan duration based on NEC density was performed continuously. In the phantom study, scan and reconstruction parameters were decided by visual assessment and physical indexes (N 10mm , NEC phantom , Q H,10mm /N 10mm ) to visualize hot spot of 10 mm diameter with standardized uptake value (SUV)=4 explicitly. Simultaneously, Recovery Coefficient (RC) was evaluated to recognize that PET images had enough quantifiably. Scan durations were optimized by Body Mass Index (BMI) based on retrospective analysis of NEC density . Correlation between visual score in clinical FDG-PET images and NEC density fell after the optimization of scan duration. Both Inter-institution and inter-patient variability were decreased by performing the phantom study based on the procedure guideline and the optimization of scan duration based on NEC density which seem finally useful to practice highly precise examination and promote high-quality controlled study. (author)

  3. Group search optimiser-based optimal bidding strategies with no Karush-Kuhn-Tucker optimality conditions

    Science.gov (United States)

    Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.

    2017-03-01

    General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.

  4. Radiation protection optimization using a knowledge based methodology

    International Nuclear Information System (INIS)

    Reyes-Jimenez, J.; Tsoukalas, L.H.

    1991-01-01

    This paper presents a knowledge based methodology for radiological planning and radiation protection optimization. The cost-benefit methodology described on International Commission of Radiation Protection Report No. 37 is employed within a knowledge based framework for the purpose of optimizing radiation protection and plan maintenance activities while optimizing radiation protection. 1, 2 The methodology is demonstrated through an application to a heating ventilation and air conditioning (HVAC) system. HVAC is used to reduce radioactivity concentration levels in selected contaminated multi-compartment models at nuclear power plants when higher than normal radiation levels are detected. The overall objective is to reduce personnel exposure resulting from airborne radioactivity, when routine or maintenance access is required in contaminated areas. 2 figs, 15 refs

  5. Techno-economical optimization of Reactive Blue 19 removal by combined electrocoagulation/coagulation process through MOPSO using RSM and ANFIS models.

    Science.gov (United States)

    Taheri, M; Alavi Moghaddam, M R; Arami, M

    2013-10-15

    In this research, Response Surface Methodology (RSM) and Adaptive Neuro Fuzzy Inference System (ANFIS) models were applied for optimization of Reactive Blue 19 removal using combined electrocoagulation/coagulation process through Multi-Objective Particle Swarm Optimization (MOPSO). By applying RSM, the effects of five independent parameters including applied current, reaction time, initial dye concentration, initial pH and dosage of Poly Aluminum Chloride were studied. According to the RSM results, all the independent parameters are equally important in dye removal efficiency. In addition, ANFIS was applied for dye removal efficiency and operating costs modeling. High R(2) values (≥85%) indicate that the predictions of RSM and ANFIS models are acceptable for both responses. ANFIS was also used in MOPSO for finding the best techno-economical Reactive Blue 19 elimination conditions according to RSM design. Through MOPSO and the selected ANFIS model, Minimum and maximum values of 58.27% and 99.67% dye removal efficiencies were obtained, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    T. SHANKAR

    2014-04-01

    Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.

  7. Enhancing product robustness in reliability-based design optimization

    International Nuclear Information System (INIS)

    Zhuang, Xiaotian; Pan, Rong; Du, Xiaoping

    2015-01-01

    Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example. - Highlights: • A unifying framework for integrating RBDO and RPD is proposed. • Implicit product performance function is considered. • The design problem is solved by sequential optimization and reliability assessment. • A sequential sampling technique is developed for improving design optimization. • The comparison with traditional RBDO is provided

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

    Directory of Open Access Journals (Sweden)

    B. Thamaraikannan

    2014-01-01

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

  9. A modified teaching–learning based optimization for multi-objective optimal power flow problem

    International Nuclear Information System (INIS)

    Shabanpour-Haghighi, Amin; Seifi, Ali Reza; Niknam, Taher

    2014-01-01

    Highlights: • A new modified teaching–learning based algorithm is proposed. • A self-adaptive wavelet mutation strategy is used to enhance the performance. • To avoid reaching a large repository size, a fuzzy clustering technique is used. • An efficiently smart population selection is utilized. • Simulations show the superiority of this algorithm compared with other ones. - Abstract: In this paper, a modified teaching–learning based optimization algorithm is analyzed to solve the multi-objective optimal power flow problem considering the total fuel cost and total emission of the units. The modified phase of the optimization algorithm utilizes a self-adapting wavelet mutation strategy. Moreover, a fuzzy clustering technique is proposed to avoid extremely large repository size besides a smart population selection for the next iteration. These techniques make the algorithm searching a larger space to find the optimal solutions while speed of the convergence remains good. The IEEE 30-Bus and 57-Bus systems are used to illustrate performance of the proposed algorithm and results are compared with those in literatures. It is verified that the proposed approach has better performance over other techniques

  10. Rapid and quantitative detection of C-reactive protein based on quantum dots and immunofiltration assay

    Directory of Open Access Journals (Sweden)

    Zhang PF

    2015-09-01

    Full Text Available Pengfei Zhang,1,* Yan Bao,1,* Mohamed Shehata Draz,2,3,* Huiqi Lu,1 Chang Liu,1 Huanxing Han11Center for Translational Medicine, Changzheng Hospital, Second Military Medical University, Shanghai, People’s Republic of China; 2Zhejiang-California International Nanosystems Institute, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 3Faculty of Science, Tanta University, Tanta, Egypt*These authors contributed equally to this workAbstract: Convenient and rapid immunofiltration assays (IFAs enable on-site “yes” or “no” determination of disease markers. However, traditional IFAs are commonly qualitative or semi-quantitative and are very limited for the efficient testing of samples in field diagnostics. Here, we overcome these limitations by developing a quantum dots (QDs-based fluorescent IFA for the quantitative detection of C-reactive proteins (CRP. CRP, the well-known diagnostic marker for acute viral and bacterial infections, was used as a model analyte to demonstrate performance and sensitivity of our developed QDs-based IFA. QDs capped with both polyethylene glycol (PEG and glutathione were used as fluorescent labels for our IFAs. The presence of the surface PEG layer, which reduced the non-specific protein interactions, in conjunction with the inherent optical properties of QDs, resulted in lower background signal, increased sensitivity, and ability to detect CRP down to 0.79 mg/L with only 5 µL serum sample. In addition, the developed assay is simple, fast and can quantitatively detect CRP with a detection limit up to 200 mg/L. Clinical test results of our QD-based IFA are well correlated with the traditional latex enhance immune-agglutination aggregation. The proposed QD-based fluorescent IFA is very promising, and potentially will be adopted for multiplexed immunoassay and in field point-of-care test.Keywords: C-reactive proteins, point-of-care test, Glutathione capped QDs, PEGylation

  11. MVMO-based approach for optimal placement and tuning of ...

    African Journals Online (AJOL)

    DR OKE

    differential evolution DE algorithm with adaptive crossover operator, .... x are assigned by using a sequential scheme which accounts for mean and ... the representative scenarios from probabilistic model based Monte Carlo ... Comparison of average convergence of MVMO-S with other metaheuristic optimization methods.

  12. Runtime Optimizations for Tree-Based Machine Learning Models

    NARCIS (Netherlands)

    N. Asadi; J.J.P. Lin (Jimmy); A.P. de Vries (Arjen)

    2014-01-01

    htmlabstractTree-based models have proven to be an effective solution for web ranking as well as other machine learning problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, specifically using gradient-boosted regression

  13. Optimal energy management for a flywheel-based hybrid vehicle

    NARCIS (Netherlands)

    Berkel, van K.; Hofman, T.; Vroemen, B.G.; Steinbuch, M.

    2011-01-01

    This paper presents the modeling and design of an optimal Energy Management Strategy (EMS) for a flywheel-based hybrid vehicle, that does not use any electrical motor/generator, or a battery, for its hybrid functionalities. The hybrid drive train consists of only low-cost components, such as a

  14. Reality based optimization of steel monopod offshore-towers

    NARCIS (Netherlands)

    Vrouwenvelder, A.C.W.M.

    2008-01-01

    In this work, the implementation of reliability-based optimization (RBO) of a circular steel monopod-offshore-tower with constant and variable diameters (represented by segmentations) and thicknesses is presented. The tower is subjected to the extreme wave loading. For this purpose, the

  15. Economics-based optimal control of greenhouse tomato crop production

    NARCIS (Netherlands)

    Tap, F.

    2000-01-01

    The design and testing of an optimal control algorithm, based on scientific models of greenhouse and tomato crop and an economic criterion (goal function), to control greenhouse climate, is described. An important characteristic of this control is that it aims at maximising an economic

  16. Optimization-based Method for Automated Road Network Extraction

    International Nuclear Information System (INIS)

    Xiong, D

    2001-01-01

    Automated road information extraction has significant applicability in transportation. It provides a means for creating, maintaining, and updating transportation network databases that are needed for purposes ranging from traffic management to automated vehicle navigation and guidance. This paper is to review literature on the subject of road extraction and to describe a study of an optimization-based method for automated road network extraction

  17. Optimal Sequential Rules for Computer-Based Instruction.

    Science.gov (United States)

    Vos, Hans J.

    1998-01-01

    Formulates sequential rules for adapting the appropriate amount of instruction to learning needs in the context of computer-based instruction. Topics include Bayesian decision theory, threshold and linear-utility structure, psychometric model, optimal sequential number of test questions, and an empirical example of sequential instructional…

  18. Degradation of reactive orange 4 dye using hydrodynamic cavitation based hybrid techniques.

    Science.gov (United States)

    Gore, Mohan M; Saharan, Virendra Kumar; Pinjari, Dipak V; Chavan, Prakash V; Pandit, Aniruddha B

    2014-05-01

    In the present work, degradation of reactive orange 4 dye (RO4) has been investigated using hydrodynamic cavitation (HC) and in combination with other AOP's. In the hybrid techniques, combination of hydrodynamic cavitation and other oxidizing agents such as H2O2 and ozone have been used to get the enhanced degradation efficiency through HC device. The hydrodynamic cavitation was first optimized in terms of different operating parameters such as operating inlet pressure, cavitation number and pH of the operating medium to get the maximum degradation of RO4. Following the optimization of HC parameters, the degradation of RO4 was carried out using the combination of HC with H2O2 and ozone. It has been found that the efficiency of the HC can be improved significantly by combining it with H2O2 and ozone. The mineralization rate of RO4 increases considerably with 14.67% mineralization taking place using HC alone increases to 31.90% by combining it with H2O2 and further increases to 76.25% through the combination of HC and ozone. The synergetic coefficient of greater than one for the hybrid processes of HC+H2O2 and HC+Ozone has suggested that the combination of HC with other oxidizing agents is better than the individual processes for the degradation of dye effluent containing RO4. The combination of HC with ozone proves to be the most energy efficient method for the degradation of RO4 as compared to HC alone and the hybrid process of HC and H2O2. Copyright © 2013 Elsevier B.V. All rights reserved.

  19. Development of a faulty reactivity detection system applying a digital H∞ estimator

    International Nuclear Information System (INIS)

    Suzuki, Katsuo; Suzudo, Tomoaki; Nabeshima, Kunihiko

    2004-01-01

    This paper concerns an application of digital optimal H ∞ estimator to the detection of faulty reactivity in real-time. The detection system, fundamentally based on the reactivity balance method, is composed of three modules, i.e. the net reactivity estimator, the feedback reactivity estimator and the reactivity balance circuit. H ∞ optimal filters are used for these two reactivity estimators, and the nonlinear neutronics are taken into consideration especially for the design of the net reactivity estimator. A series of performance test of the detection system are conducted by using numerical simulations of reactor dynamics with the insertion of a faulty reactivity for an experimental fast breeder reactor JOYO. The system detects the typical artificial reactivity insertions during a few seconds with no stationary offset and the accuracy of 0.1 cent, and is satisfactory for its practical use. (author)

  20. Comparative performance of an elitist teaching-learning-based optimization algorithm for solving unconstrained optimization problems

    Directory of Open Access Journals (Sweden)

    R. Venkata Rao

    2013-01-01

    Full Text Available Teaching-Learning-based optimization (TLBO is a recently proposed population based algorithm, which simulates the teaching-learning process of the class room. This algorithm requires only the common control parameters and does not require any algorithm-specific control parameters. In this paper, the effect of elitism on the performance of the TLBO algorithm is investigated while solving unconstrained benchmark problems. The effects of common control parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 76 unconstrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. A statistical test is also performed to investigate the results obtained using different algorithms. The results have proved the effectiveness of the proposed elitist TLBO algorithm.

  1. Attitude Optimal Backstepping Controller Based Quaternion for a UAV

    OpenAIRE

    Djamel, Kaddouri; Abdellah, Mokhtari; Benallegue, Abdelaziz

    2016-01-01

    A hierarchical controller design based on nonlinear H∞ theory and backstepping technique is developed for a nonlinear and coupled dynamic attitude system using conventional quaternion based method. The derived controller combines the attractive features of H∞ optimal controller and the advantages of the backstepping technique leading to a control law which avoids winding phenomena. Performance issues of the controller are illustrated in a simulation study made for a four-rotor vertical take-o...

  2. Mesh Denoising based on Normal Voting Tensor and Binary Optimization

    OpenAIRE

    Yadav, S. K.; Reitebuch, U.; Polthier, K.

    2016-01-01

    This paper presents a tensor multiplication based smoothing algorithm that follows a two step denoising method. Unlike other traditional averaging approaches, our approach uses an element based normal voting tensor to compute smooth surfaces. By introducing a binary optimization on the proposed tensor together with a local binary neighborhood concept, our algorithm better retains sharp features and produces smoother umbilical regions than previous approaches. On top of that, we provide a stoc...

  3. Optimize Etching Based Single Mode Fiber Optic Temperature Sensor

    OpenAIRE

    Ajay Kumar; Dr. Pramod Kumar

    2014-01-01

    This paper presents a description of etching process for fabrication single mode optical fiber sensors. The process of fabrication demonstrates an optimized etching based method to fabricate single mode fiber (SMF) optic sensors in specified constant time and temperature. We propose a single mode optical fiber based temperature sensor, where the temperature sensing region is obtained by etching its cladding diameter over small length to a critical value. It is observed that th...

  4. A Rapid Aeroelasticity Optimization Method Based on the Stiffness characteristics

    OpenAIRE

    Yuan, Zhe; Huo, Shihui; Ren, Jianting

    2018-01-01

    A rapid aeroelasticity optimization method based on the stiffness characteristics was proposed in the present study. Large time expense in static aeroelasticity analysis based on traditional time domain aeroelasticity method is solved. Elastic axis location and torsional stiffness are discussed firstly. Both torsional stiffness and the distance between stiffness center and aerodynamic center have a direct impact on divergent velocity. The divergent velocity can be adjusted by changing the cor...

  5. Parallel Harmony Search Based Distributed Energy Resource Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Ceylan, Oguzhan [ORNL; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

    2015-01-01

    This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.

  6. Resource-based optimization of electric power production (in Iran)

    International Nuclear Information System (INIS)

    Sadeghzadeh, Mohammad

    1999-01-01

    This paper is about electric power production optimization and chiefly discusses on the types of resources available in Iran. The modeling has been based on the marginal cost of different energy resources and types of technologies used. the computed costs are the basic standards for optimization of the production system of energy. the costs associated with environmental pollution and also pollution control are considered. the present paper also studied gas fossil fuel, hydro, nuclear, renewable and co-generation of heat and power. The results are discussed and reported at the last of the paper

  7. Proposal optimization in nuclear accident emergency decision based on IAHP

    International Nuclear Information System (INIS)

    Xin Jing

    2007-01-01

    On the basis of establishing the multi-layer structure of nuclear accident emergency decision, several decision objectives are synthetically analyzed, and an optimization model of decision proposals for nuclear accident emergency based on interval analytic hierarchy process is proposed in the paper. The model makes comparisons among several emergency decision proposals quantified, and the optimum proposal is selected out, which solved the uncertain and fuzzy decision problem of judgments by experts' experiences in nuclear accidents emergency decision. Case study shows that the optimization result is much more reasonable, objective and reliable than subjective judgments, and it could be decision references for nuclear accident emergency. (authors)

  8. Optimization of morphing flaps based on fluid structure interaction modeling

    DEFF Research Database (Denmark)

    Barlas, Athanasios; Akay, Busra

    2018-01-01

    This article describes the design optimization of morphing trailing edge flaps for wind turbines with ‘smart blades’. A high fidelity Fluid Structure Interaction (FSI) simulation framework is utilized, comprised of 2D Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) models....... A coupled aero-structural simulation of a 10% chordwise length morphing trailing edge flap for a 4 MW wind turbine rotor is carried out and response surfaces are produced with respect to the flap internal geometry design parameters for the design conditions. Surrogate model based optimization is applied...

  9. Investment Strategies Optimization based on a SAX-GA Methodology

    CERN Document Server

    Canelas, António M L; Horta, Nuno C G

    2013-01-01

    This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.

  10. Removal of Selenium and Nitrate in Groundwater Using Organic Carbon-Based Reactive Mixtures

    Science.gov (United States)

    An, Hyeonsil; Jeen, Sung-Wook

    2016-04-01

    Treatment of selenium and nitrate in groundwater was evaluated through column experiments. Four columns consisting of reactive mixtures, either organic carbon-limestone (OC-LS) or organic carbon-zero valent iron (OC-ZVI), were used to determine the removal efficiency of selenium with different concentrations of nitrate. The source waters were collected from a mine site in Korea or were prepared artificially based on the mine drainage water or deionized water, followed by spiking of elevated concentrations of Se (40 mg/L) and nitrate (100 or 10 mg/L as NO3-N). The results for the aqueous chemistry showed that selenium and nitrate were effectively removed both in the mine drainage water and deionized water-based artificial input solution. However, the removal of selenium was delayed when selenium and nitrate coexisted in the OC-LS columns. The removal of selenium was not significant when the influent nitrate concentration was 100 mg/L as NO3-N, while most of nitrate was gradually removed within the columns. In contrast, 94% of selenium was removed when the influent nitrate concentration was reduced to 10 mg/L as NO3-N. In the OC-ZVI column, selenium and nitrate was removed almost simultaneously and completely even with the high nitrate concentration; however, a high concentration of ammonia was produced as a by-product of abiotic reaction between ZVI and nitrate. The elemental analysis for the solid samples after the termination of the experiments showed that selenium was accumulated in the reactive materials where removal of aqueous-phase selenium mostly occurred. The X-ray absorption near-edge structure (XANES) study indicated that selenium existed in the forms of SeS2 and Se(0) in the OC-LS column, while selenium was present in the forms of FeSe, SeS2 and absorbed Se(IV) in the OC-ZVI column. This study shows that OC-based reactive mixtures have an ability to remove selenium and nitrate in groundwater. However, the removal of selenium was influenced by the high

  11. Reliability-Based Structural Optimization of Wave Energy Converters

    Directory of Open Access Journals (Sweden)

    Simon Ambühl

    2014-12-01

    Full Text Available More and more wave energy converter (WEC concepts are reaching prototypelevel. Once the prototype level is reached, the next step in order to further decrease thelevelized cost of energy (LCOE is optimizing the overall system with a focus on structuraland maintenance (inspection costs, as well as on the harvested power from the waves.The target of a fully-developed WEC technology is not maximizing its power output,but minimizing the resulting LCOE. This paper presents a methodology to optimize thestructural design of WECs based on a reliability-based optimization problem and the intentto maximize the investor’s benefits by maximizing the difference between income (e.g., fromselling electricity and the expected expenses (e.g., structural building costs or failure costs.Furthermore, different development levels, like prototype or commercial devices, may havedifferent main objectives and will be located at different locations, as well as receive varioussubsidies. These points should be accounted for when performing structural optimizationsof WECs. An illustrative example on the gravity-based foundation of the Wavestar deviceis performed showing how structural design can be optimized taking target reliability levelsand different structural failure modes due to extreme loads into account.

  12. Bare-Bones Teaching-Learning-Based Optimization

    Directory of Open Access Journals (Sweden)

    Feng Zou

    2014-01-01

    Full Text Available Teaching-learning-based optimization (TLBO algorithm which simulates the teaching-learning process of the class room is one of the recently proposed swarm intelligent (SI algorithms. In this paper, a new TLBO variant called bare-bones teaching-learning-based optimization (BBTLBO is presented to solve the global optimization problems. In this method, each learner of teacher phase employs an interactive learning strategy, which is the hybridization of the learning strategy of teacher phase in the standard TLBO and Gaussian sampling learning based on neighborhood search, and each learner of learner phase employs the learning strategy of learner phase in the standard TLBO or the new neighborhood search strategy. To verify the performance of our approaches, 20 benchmark functions and two real-world problems are utilized. Conducted experiments can been observed that the BBTLBO performs significantly better than, or at least comparable to, TLBO and some existing bare-bones algorithms. The results indicate that the proposed algorithm is competitive to some other optimization algorithms.

  13. Optimal diabatic dynamics of Majorana-based quantum gates

    Science.gov (United States)

    Rahmani, Armin; Seradjeh, Babak; Franz, Marcel

    2017-08-01

    In topological quantum computing, unitary operations on qubits are performed by adiabatic braiding of non-Abelian quasiparticles, such as Majorana zero modes, and are protected from local environmental perturbations. In the adiabatic regime, with timescales set by the inverse gap of the system, the errors can be made arbitrarily small by performing the process more slowly. To enhance the performance of quantum information processing with Majorana zero modes, we apply the theory of optimal control to the diabatic dynamics of Majorana-based qubits. While we sacrifice complete topological protection, we impose constraints on the optimal protocol to take advantage of the nonlocal nature of topological information and increase the robustness of our gates. By using the Pontryagin's maximum principle, we show that robust equivalent gates to perfect adiabatic braiding can be implemented in finite times through optimal pulses. In our implementation, modifications to the device Hamiltonian are avoided. Focusing on thermally isolated systems, we study the effects of calibration errors and external white and 1 /f (pink) noise on Majorana-based gates. While a noise-induced antiadiabatic behavior, where a slower process creates more diabatic excitations, prohibits indefinite enhancement of the robustness of the adiabatic scheme, our fast optimal protocols exhibit remarkable stability to noise and have the potential to significantly enhance the practical performance of Majorana-based information processing.

  14. Optimization of degradation of Reactive Black 5 (RB5) and electricity generation in solar photocatalytic fuel cell system.

    Science.gov (United States)

    Khalik, Wan Fadhilah; Ho, Li-Ngee; Ong, Soon-An; Voon, Chun-Hong; Wong, Yee-Shian; Yusoff, NikAthirah; Lee, Sin-Li; Yusuf, Sara Yasina

    2017-10-01

    The photocatalytic fuel cell (PFC) system was developed in order to study the effect of several operating parameters in degradation of Reactive Black 5 (RB5) and its electricity generation. Light irradiation, initial dye concentration, aeration, pH and cathode electrode are the operating parameters that might give contribution in the efficiency of PFC system. The degradation of RB5 depends on the presence of light irradiation and solar light gives better performance to degrade the azo dye. The azo dye with low initial concentration decolorizes faster compared to higher initial concentration and presence of aeration in PFC system would enhance its performance. Reactive Black 5 rapidly decreased at higher pH due to the higher amount of OH generated at higher pH and Pt-loaded carbon (Pt/C) was more suitable to be used as cathode in PFC system compared to Cu foil and Fe foil. The rapid decolorization of RB5 would increase their voltage output and in addition, it would also increase their V oc , J sc and P max . The breakage of azo bond and aromatic rings was confirmed through UV-Vis spectrum and COD analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Reactivity perturbation formulation for a discontinuous Galerkin-based transport solver and its use with adaptive mesh refinement

    International Nuclear Information System (INIS)

    Le Tellier, R.; Fournier, D.; Suteau, C.

    2011-01-01

    Within the framework of a Discontinuous Galerkin spatial approximation of the multigroup discrete ordinates transport equation, we present a generalization of the exact standard perturbation formula that takes into account spatial discretization-induced reactivity changes. It encompasses in two separate contributions the nuclear data-induced reactivity change and the reactivity modification induced by two different spatial discretizations. The two potential uses of such a formulation when considering adaptive mesh refinement are discussed, and numerical results on a simple two-group Cartesian two-dimensional benchmark are provided. In particular, such a formulation is shown to be useful to filter out a more accurate estimate of nuclear data-related reactivity effects from initial and perturbed calculations based on independent adaptation processes. (authors)

  16. Adaptive surrogate model based multiobjective optimization for coastal aquifer management

    Science.gov (United States)

    Song, Jian; Yang, Yun; Wu, Jianfeng; Wu, Jichun; Sun, Xiaomin; Lin, Jin

    2018-06-01

    In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is developed for optimal pumping strategies of large-scale coastal groundwater problems. The proposed SMOMA integrates an efficient data-driven surrogate model with an improved non-dominated sorted genetic algorithm-II (NSGAII) that employs a local search operator to accelerate its convergence in optimization. The surrogate model based on Kernel Extreme Learning Machine (KELM) is developed and evaluated as an approximate simulator to generate the patterns of regional groundwater flow and salinity levels in coastal aquifers for reducing huge computational burden. The KELM model is adaptively trained during evolutionary search to satisfy desired fidelity level of surrogate so that it inhibits error accumulation of forecasting and results in correctly converging to true Pareto-optimal front. The proposed methodology is then applied to a large-scale coastal aquifer management in Baldwin County, Alabama. Objectives of minimizing the saltwater mass increase and maximizing the total pumping rate in the coastal aquifers are considered. The optimal solutions achieved by the proposed adaptive surrogate model are compared against those solutions obtained from one-shot surrogate model and original simulation model. The adaptive surrogate model does not only improve the prediction accuracy of Pareto-optimal solutions compared with those by the one-shot surrogate model, but also maintains the equivalent quality of Pareto-optimal solutions compared with those by NSGAII coupled with original simulation model, while retaining the advantage of surrogate models in reducing computational burden up to 94% of time-saving. This study shows that the proposed methodology is a computationally efficient and promising tool for multiobjective optimizations of coastal aquifer managements.

  17. An opposition-based harmony search algorithm for engineering optimization problems

    Directory of Open Access Journals (Sweden)

    Abhik Banerjee

    2014-03-01

    Full Text Available Harmony search (HS is a derivative-free real parameter optimization algorithm. It draws inspiration from the musical improvisation process of searching for a perfect state of harmony. The proposed opposition-based HS (OHS of the present work employs opposition-based learning for harmony memory initialization and also for generation jumping. The concept of opposite number is utilized in OHS to improve the convergence rate of the HS algorithm. The potential of the proposed algorithm is assessed by means of an extensive comparative study of the numerical results on sixteen benchmark test functions. Additionally, the effectiveness of the proposed algorithm is tested for reactive power compensation of an autonomous power system. For real-time reactive power compensation of the studied model, Takagi Sugeno fuzzy logic (TSFL is employed. Time-domain simulation reveals that the proposed OHS-TSFL yields on-line, off-nominal model parameters, resulting in real-time incremental change in terminal voltage response profile.

  18. Optimal Model-Based Control in HVAC Systems

    DEFF Research Database (Denmark)

    Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

    2008-01-01

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

  19. Visibility-based optimal path and motion planning

    CERN Document Server

    Wang, Paul Keng-Chieh

    2015-01-01

    This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...

  20. Optimization of Classical Hydraulic Engine Mounts Based on RMS Method

    Directory of Open Access Journals (Sweden)

    J. Christopherson

    2005-01-01

    Full Text Available Based on RMS averaging of the frequency response functions of the absolute acceleration and relative displacement transmissibility, optimal parameters describing the hydraulic engine mount are determined to explain the internal mount geometry. More specifically, it is shown that a line of minima exists to define a relationship between the absolute acceleration and relative displacement transmissibility of a sprung mass using a hydraulic mount as a means of suspension. This line of minima is used to determine several optimal systems developed on the basis of different clearance requirements, hence different relative displacement requirements, and compare them by means of their respective acceleration and displacement transmissibility functions. In addition, the transient response of the mount to a step input is also investigated to show the effects of the optimization upon the time domain response of the hydraulic mount.

  1. Analog Circuit Design Optimization Based on Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Mansour Barari

    2014-01-01

    Full Text Available This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs. Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met. Comparisons with available methods like genetic algorithms show that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.

  2. Joint Optimization in UMTS-Based Video Transmission

    Directory of Open Access Journals (Sweden)

    Attila Zsiros

    2007-01-01

    Full Text Available A software platform is exposed, which was developed to enable demonstration and capacity testing. The platform simulates a joint optimized wireless video transmission. The development succeeded within the frame of the IST-PHOENIX project and is based on the system optimization model of the project. One of the constitutive parts of the model, the wireless network segment, is changed to a detailed, standard UTRA network simulation module. This paper consists of (1 a brief description of the projects simulation chain, (2 brief description of the UTRAN system, and (3 the integration of the two segments. The role of the UTRAN part in the joint optimization is described, with the configuration and control of this element. Finally, some simulation results are shown. In the conclusion, we show how our simulation results translate into real-world performance gains.

  3. Nozzle Mounting Method Optimization Based on Robot Kinematic Analysis

    Science.gov (United States)

    Chen, Chaoyue; Liao, Hanlin; Montavon, Ghislain; Deng, Sihao

    2016-08-01

    Nowadays, the application of industrial robots in thermal spray is gaining more and more importance. A desired coating quality depends on factors such as a balanced robot performance, a uniform scanning trajectory and stable parameters (e.g. nozzle speed, scanning step, spray angle, standoff distance). These factors also affect the mass and heat transfer as well as the coating formation. Thus, the kinematic optimization of all these aspects plays a key role in order to obtain an optimal coating quality. In this study, the robot performance was optimized from the aspect of nozzle mounting on the robot. An optimized nozzle mounting for a type F4 nozzle was designed, based on the conventional mounting method from the point of view of robot kinematics validated on a virtual robot. Robot kinematic parameters were obtained from the simulation by offline programming software and analyzed by statistical methods. The energy consumptions of different nozzle mounting methods were also compared. The results showed that it was possible to reasonably assign the amount of robot motion to each axis during the process, so achieving a constant nozzle speed. Thus, it is possible optimize robot performance and to economize robot energy.

  4. Optimization Model for Web Based Multimodal Interactive Simulations.

    Science.gov (United States)

    Halic, Tansel; Ahn, Woojin; De, Suvranu

    2015-07-15

    This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update . In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach.

  5. Optimal difference-based estimation for partially linear models

    KAUST Repository

    Zhou, Yuejin; Cheng, Yebin; Dai, Wenlin; Tong, Tiejun

    2017-01-01

    Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.

  6. Modification of species-based differential evolution for multimodal optimization

    Science.gov (United States)

    Idrus, Said Iskandar Al; Syahputra, Hermawan; Firdaus, Muliawan

    2015-12-01

    At this time optimization has an important role in various fields as well as between other operational research, industry, finance and management. Optimization problem is the problem of maximizing or minimizing a function of one variable or many variables, which include unimodal and multimodal functions. Differential Evolution (DE), is a random search technique using vectors as an alternative solution in the search for the optimum. To localize all local maximum and minimum on multimodal function, this function can be divided into several domain of fitness using niching method. Species-based niching method is one of method that build sub-populations or species in the domain functions. This paper describes the modification of species-based previously to reduce the computational complexity and run more efficiently. The results of the test functions show species-based modifications able to locate all the local optima in once run the program.

  7. Optimal difference-based estimation for partially linear models

    KAUST Repository

    Zhou, Yuejin

    2017-12-16

    Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.

  8. An EEGLAB plugin to analyze individual EEG alpha rhythms using the "channel reactivity-based method".

    Science.gov (United States)

    Goljahani, A; Bisiacchi, P; Sparacino, G

    2014-03-01

    A recent paper [1] proposed a new technique, termed the channel reactivity-based method (CRB), for characterizing EEG alpha rhythms using individual (IAFs) and channel (CAFs) alpha frequencies. These frequencies were obtained by identifying the frequencies at which the power of the alpha rhythms decreases. In the present study, we present a graphical interactive toolbox that can be plugged into the popular open source environment EEGLAB, making it easy to use CRB. In particular, we illustrate the major functionalities of the software and discuss the advantages of this toolbox for common EEG investigations. The CRB analysis plugin, along with extended documentation and the sample dataset utilized in this study, is freely available on the web at http://bio.dei.unipd.it/crb/. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  9. Cytochromes c': Structure, Reactivity and Relevance to Haem-Based Gas Sensing.

    Science.gov (United States)

    Hough, Michael A; Andrew, Colin R

    2015-01-01

    Cytochromes c' are a group of class IIa cytochromes with pentacoordinate haem centres and are found in photosynthetic, denitrifying and methanotrophic bacteria. Their function remains unclear, although roles in nitric oxide (NO) trafficking during denitrification or in cellular defence against nitrosoative stress have been proposed. Cytochromes c' are typically dimeric with each c-type haem-containing monomer folding as a four-α-helix bundle. Their hydrophobic and crowded distal sites impose severe restrictions on the binding of distal ligands, including diatomic gases. By contrast, NO binds to the proximal haem face in a similar manner to that of the eukaryotic NO sensor, soluble guanylate cyclase and bacterial analogues. In this review, we focus on how structural features of cytochromes c' influence haem spectroscopy and reactivity with NO, CO and O2. We also discuss the relevance of cytochrome c' to understanding the mechanisms of gas binding to haem-based sensor proteins. © 2015 Elsevier Ltd. All rights reserved.

  10. Adjoint current-based approaches to prostate brachytherapy optimization

    International Nuclear Information System (INIS)

    Roberts, J. A.; Henderson, D. L.

    2009-01-01

    This paper builds on previous work done at the Univ. of Wisconsin - Madison to employ the adjoint concept of nuclear reactor physics in the so-called greedy heuristic of brachytherapy optimization. Whereas that previous work focused on the adjoint flux, i.e. the importance, this work has included use of the adjoint current to increase the amount of information available in optimizing. Two current-based approaches were developed for 2-D problems, and each was compared to the most recent form of the flux-based methodology. The first method aimed to take a treatment plan from the flux-based greedy heuristic and adjust via application of the current-displacement, or a vector displacement based on a combination of tissue (adjoint) and seed (forward) currents acting as forces on a seed. This method showed promise in improving key urethral and rectal dosimetric quantities. The second method uses the normed current-displacement as the greedy criterion such that seeds are placed in regions of least force. This method, coupled with the dose-update scheme, generated treatment plans with better target irradiation and sparing of the urethra and normal tissues than the flux-based approach. Tables of these parameters are given for both approaches. In summary, these preliminary results indicate adjoint current methods are useful in optimization and further work in 3-D should be performed. (authors)

  11. Development and reactivity tests of Ce-Zr-based Claus catalysts for coal gas cleanup

    Energy Technology Data Exchange (ETDEWEB)

    No-Kuk Park; Dong Cheul Han; Gi Bo Han; Si Ok Ryu; Tae Jin Lee; Ki Jun Yoon [Yeungnam University, Gyeongbuk (Republic of Korea). National Research Laboratory, School of Chemical Engineering and Technology

    2007-09-15

    Claus reaction (2H{sub 2}S + SO{sub 2} {leftrightarrow} 3/nS{sub n} + 2H{sub 2}O) was used to clean the gasified coal gas and the reactivity of several metal oxide-based catalysts on Claus reaction was investigated at various operating conditions. In order to convert H{sub 2}S contained in the gasified coal gas to elemental sulfur during Claus reaction, the catalysts having the high activity under the highly reducing condition with the moisture should be developed. CeO{sub 2}, ZrO{sub 2}, and Ce{sub 1-x}Zr{sub x}O{sub 2} catalysts were prepared for Claus reaction and their reactivity changes due to the existence of the reducing gases and H{sub 2}O in the fuel gas was investigated in this study. The Ce-based catalysts shows that their activity was deteriorated by the reduction of the catalyst due to the reducing gases at higher than 220{sup o}C. Meanwhile, the effect of the reducing gases on the catalytic activity was not considerable at low temperature. The activities of all three catalysts were degraded on the condition that the moisture existed in the test gas. Specifically, the Ce-based catalysts were remarkably deactivated by their sulfation. The Ce-Zr-based catalyst had a high catalytic activity when the reducing gases and the moisture co-existed in the simulated fuel gas. The deactivation of the Ce-Zr-based catalyst was not observed in this study. The lattice oxygen of the Ce-based catalyst was used for the oxidation of H{sub 2}S and the lattice oxygen vacancy on the catalyst was contributed to the reduction of SO{sub 2}. ZrO{sub 2} added to the Ce-Zr-based catalyst improved the redox properties of the catalyst in Claus reaction by increasing the mobility of the lattice oxygen of CeO{sub 2}. 21 refs., 14 figs.

  12. Group Elevator Peak Scheduling Based on Robust Optimization Model

    Directory of Open Access Journals (Sweden)

    ZHANG, J.

    2013-08-01

    Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.

  13. Computer Based Porosity Design by Multi Phase Topology Optimization

    Science.gov (United States)

    Burblies, Andreas; Busse, Matthias

    2008-02-01

    A numerical simulation technique called Multi Phase Topology Optimization (MPTO) based on finite element method has been developed and refined by Fraunhofer IFAM during the last five years. MPTO is able to determine the optimum distribution of two or more different materials in components under thermal and mechanical loads. The objective of optimization is to minimize the component's elastic energy. Conventional topology optimization methods which simulate adaptive bone mineralization have got the disadvantage that there is a continuous change of mass by growth processes. MPTO keeps all initial material concentrations and uses methods adapted from molecular dynamics to find energy minimum. Applying MPTO to mechanically loaded components with a high number of different material densities, the optimization results show graded and sometimes anisotropic porosity distributions which are very similar to natural bone structures. Now it is possible to design the macro- and microstructure of a mechanical component in one step. Computer based porosity design structures can be manufactured by new Rapid Prototyping technologies. Fraunhofer IFAM has applied successfully 3D-Printing and Selective Laser Sintering methods in order to produce very stiff light weight components with graded porosities calculated by MPTO.

  14. Surrogate-Based Optimization of Biogeochemical Transport Models

    Science.gov (United States)

    Prieß, Malte; Slawig, Thomas

    2010-09-01

    First approaches towards a surrogate-based optimization method for a one-dimensional marine biogeochemical model of NPZD type are presented. The model, developed by Oschlies and Garcon [1], simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. A key issue is to minimize the misfit between the model output and given observational data. Our aim is to reduce the overall optimization cost avoiding expensive function and derivative evaluations by using a surrogate model replacing the high-fidelity model in focus. This in particular becomes important for more complex three-dimensional models. We analyse a coarsening in the discretization of the model equations as one way to create such a surrogate. Here the numerical stability crucially depends upon the discrete stepsize in time and space and the biochemical terms. We show that for given model parameters the level of grid coarsening can be choosen accordingly yielding a stable and satisfactory surrogate. As one example of a surrogate-based optimization method we present results of the Aggressive Space Mapping technique (developed by John W. Bandler [2, 3]) applied to the optimization of this one-dimensional biogeochemical transport model.

  15. Chaos Time Series Prediction Based on Membrane Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Meng Li

    2015-01-01

    Full Text Available This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m and least squares support vector machine (LS-SVM (γ,σ by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE, root mean square error (RMSE, and mean absolute percentage error (MAPE.

  16. Simultaneous allocation of distributed resources using improved teaching learning based optimization

    International Nuclear Information System (INIS)

    Kanwar, Neeraj; Gupta, Nikhil; Niazi, K.R.; Swarnkar, Anil

    2015-01-01

    Highlights: • Simultaneous allocation of distributed energy resources in distribution networks. • Annual energy loss reduction is optimized using a multi-level load profile. • A new penalty factor approach is suggested to check node voltage deviations. • An improved TLBO is proposed by suggesting several modifications in standard TLBO. • An intelligent search is proposed to enhance the performance of solution technique. - Abstract: Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results

  17. Optimization of furfural production from D-xylose with formic acid as catalyst in a reactive extraction system.

    Science.gov (United States)

    Yang, Wandian; Li, Pingli; Bo, Dechen; Chang, Heying; Wang, Xiaowei; Zhu, Tao

    2013-04-01

    Furfural is one of the most promising platform chemicals derived from biomass. In this study, response surface methodology (RSM) was utilized to determine four important parameters including reaction temperature (170-210°C), formic acid concentration (5-25 g/L), o-nitrotoluene volume percentage (20-80 vt.%), and residence time (40-200 min). The maximum furfural yield of 74% and selectivity of 86% were achieved at 190°C for 20 g/L formic acid concentration and 75 vt.% o-nitrotoluene by 75 min. The high boiling solvent, o-nitrotoluene, was recommended as extraction solvent in a reactive extraction system to obtain high furfural yield and reduce furfural-solvent separation costs. Although the addition of halides to the xylose solutions enhanced the furfural yield and selectivity, the concentration of halides was not an important factor on the furfural yield and selectivity. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Optimizing shape uniformity and increasing structure heights of deep reactive ion etched silicon x-ray lenses

    DEFF Research Database (Denmark)

    Stöhr, Frederik; Wright, Jonathan; Simons, Hugh

    2015-01-01

    Line-focusing compound silicon x-ray lenses with structure heights exceeding 300 μm were fabricated using deep reactive ion etching. To ensure profile uniformity over the full height, a new strategy was developed in which the perimeter of the structures was defined by trenches of constant width....... The remaining sacrificial material inside the lens cavities was removed by etching through the silicon wafer. Since the wafers become fragile after through-etching, they were then adhesively bonded to a carrier wafer. Individual chips were separated using laser micro machining and the 3D shape of fabricated...... analysis, where a slight bowing of the lens sidewalls and an insufficiently uniform apex region are identified as resolution-limiting factors. Despite these, the proposed fabrication route proved a viable approach for producing x-ray lenses with large structure heights and provides the means to improve...

  19. Effects of reactive filters based on modified zeolite in dairy industry wastewater treatment process

    Directory of Open Access Journals (Sweden)

    Kolaković Srđan

    2013-01-01

    Full Text Available Application of adsorbents based on organo-zeolites has certain advantages over conventional methods applied in food industry wastewater treatment process. The case study presented in this paper examines the possibilities and effects of treatment of dairy industry wastewater by using adsorbents based on organo-zeolites. The obtained results indicate favorable filtration properties of organo-zeolite, their high level of adsorption of organic matter and nitrate nitrogen in the analyzed wastewater. This paper concludes with recommendations of optimal technical and technological parameters for the application of these filters in practice.

  20. An optimal photochemical energy conversion and environmental effects in the reactive molecular dynamics; Optimale Photochemische Energiekonversion und Umgebungseffekte in Reaktiver Molekueldynamik

    Energy Technology Data Exchange (ETDEWEB)

    Fingerhut, Benjamin Philipp

    2011-02-08

    One of the main challenges in photochemical energy conversion is the design of charge separating units which are able to generate a long lived charge separated state, and to couple efficiently to an energy storage state. In part I of this work the energy conversion efficiency of a photochemical unit inspired by bacterial photosynthesis is investigated. The developed model is based on non-adiabatic multi step electron transfer to generate a trans-membrane potential gradient. Upon optimization with multi objective genetic algorithms, the biological strategies for high quantum efficiency in photosynthetic reaction centers are derived, which have to suppress loss channels such as charge recombination. The concepts of bacterial photosynthesis are extended to the design of artificial photochemical devices. The unified model consists of a charge separation unit and an energy storing system whereby the coupling between both units is assured by thermal repopulation according to the principle of detailed balance. The complete photosynthetic unit is characterized by the respective current-voltage relation and an upper limit for the overall energy efficiency is derived under AM1.5 global conditions. Such a realistic chemical solar energy conversion system can reach efficiencies, which are comparable to the limits of an ideal single-junction solar cell. In Part II of this work the reactive dynamics of two surrounding controlled photoreactions is investigated on a microscopic scale. In general the effect of the surrounding can be classified into intramolecular contributions, like steric or electronic effects, and intermolecular contributions like the solvent or the embedding in an enzyme. Both limiting cases are examined on the basis of two generic photoreactions. The Dewar DNA lesion follows quantitatively from the 6-4 lesion by UV-A/B irradiation and constitutes the stable end product of continuous solar irradiation. Here the detailed mechanism of the formally 4{pi

  1. Processes of change in a school-based mindfulness programme: cognitive reactivity and self-coldness as mediators.

    Science.gov (United States)

    Van der Gucht, Katleen; Takano, Keisuke; Raes, Filip; Kuppens, Peter

    2018-05-01

    The underlying mechanisms of the effectiveness of mindfulness-based interventions for emotional well-being remain poorly understood. Here, we examined the potential mediating effects of cognitive reactivity and self-compassion on symptoms of depression, anxiety and stress using data from an earlier randomised controlled school trial. A moderated time-lagged mediation model based on multilevel modelling was used to analyse the data. The findings showed that post-treatment changes in cognitive reactivity and self-coldness, an aspect of self-compassion, mediated subsequent changes in symptoms of depression, anxiety and stress. These results suggest that cognitive reactivity and self-coldness may be considered as transdiagnostic mechanisms of change of a mindfulness-based intervention programme for youth.

  2. Image-based modeling of flow and reactive transport in porous media

    Science.gov (United States)

    Qin, Chao-Zhong; Hoang, Tuong; Verhoosel, Clemens V.; Harald van Brummelen, E.; Wijshoff, Herman M. A.

    2017-04-01

    Due to the availability of powerful computational resources and high-resolution acquisition of material structures, image-based modeling has become an important tool in studying pore-scale flow and transport processes in porous media [Scheibe et al., 2015]. It is also playing an important role in the upscaling study for developing macroscale porous media models. Usually, the pore structure of a porous medium is directly discretized by the voxels obtained from visualization techniques (e.g. micro CT scanning), which can avoid the complex generation of computational mesh. However, this discretization may considerably overestimate the interfacial areas between solid walls and pore spaces. As a result, it could impact the numerical predictions of reactive transport and immiscible two-phase flow. In this work, two types of image-based models are used to study single-phase flow and reactive transport in a porous medium of sintered glass beads. One model is from a well-established voxel-based simulation tool. The other is based on the mixed isogeometric finite cell method [Hoang et al., 2016], which has been implemented in the open source Nutils (http://www.nutils.org). The finite cell method can be used in combination with isogeometric analysis to enable the higher-order discretization of problems on complex volumetric domains. A particularly interesting application of this immersed simulation technique is image-based analysis, where the geometry is smoothly approximated by segmentation of a B-spline level set approximation of scan data [Verhoosel et al., 2015]. Through a number of case studies by the two models, we will show the advantages and disadvantages of each model in modeling single-phase flow and reactive transport in porous media. Particularly, we will highlight the importance of preserving high-resolution interfaces between solid walls and pore spaces in image-based modeling of porous media. References Hoang, T., C. V. Verhoosel, F. Auricchio, E. H. van

  3. Corrosion resistance and electrochemical potentiokinetic reactivation testing of some iron-base hardfacing alloys

    International Nuclear Information System (INIS)

    Cockeram, B.V.

    1999-01-01

    Hardfacing alloys are weld deposited on a base material to provide a wear resistant surface. Commercially available iron-base hardfacing alloys are being evaluated for replacement of cobalt-base alloys to reduce nuclear plant activation levels. Corrosion testing was used to evaluate the corrosion resistance of several iron-base hardfacing alloys in highly oxygenated environments. The corrosion test results indicate that iron-base hardfacing alloys in the as-deposited condition have acceptable corrosion resistance when the chromium to carbon ratio is greater than 4. Tristelle 5183, with a high niobium (stabilizer) content, did not follow this trend due to precipitation of niobium-rich carbides instead of chromium-rich carbides. This result indicates that iron-base hardfacing alloys containing high stabilizer contents may possess good corrosion resistance with Cr:C < 4. NOREM 02, NOREM 01, and NoCo-M2 hardfacing alloys had acceptable corrosion resistance in the as-deposited and 885 C/4 hour heat treated condition, but rusting from sensitization was observed in the 621 C/6 hour heat treated condition. The feasibility of using an Electrochemical Potentiokinetic Reactivation (EPR) test method, such as used for stainless steel, to detect sensitization in iron-base hardfacing alloys was evaluated. A single loop-EPR method was found to provide a more consistent measurement of sensitization than a double loop-EPR method. The high carbon content that is needed for a wear resistant hardfacing alloy produces a high volume fraction of chromium-rich carbides that are attacked during EPR testing. This results in inherently lower sensitivity for detection of a sensitized iron-base hardfacing alloy than stainless steel using conventional EPR test methods

  4. Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm

    Directory of Open Access Journals (Sweden)

    N. Sri Madhava Raja

    2014-01-01

    Full Text Available Histogram based multilevel thresholding approach is proposed using Brownian distribution (BD guided firefly algorithm (FA. A bounded search technique is also presented to improve the optimization accuracy with lesser search iterations. Otsu’s between-class variance function is maximized to obtain optimal threshold level for gray scale images. The performances of the proposed algorithm are demonstrated by considering twelve benchmark images and are compared with the existing FA algorithms such as Lévy flight (LF guided FA and random operator guided FA. The performance assessment comparison between the proposed and existing firefly algorithms is carried using prevailing parameters such as objective function, standard deviation, peak-to-signal ratio (PSNR, structural similarity (SSIM index, and search time of CPU. The results show that BD guided FA provides better objective function, PSNR, and SSIM, whereas LF based FA provides faster convergence with relatively lower CPU time.

  5. Optimization based tuning approach for offset free MPC

    DEFF Research Database (Denmark)

    Olesen, Daniel Haugård; Huusom, Jakob Kjøbsted; Jørgensen, John Bagterp

    2012-01-01

    We present an optimization based tuning procedure with certain robustness properties for an offset free Model Predictive Controller (MPC). The MPC is designed for multivariate processes that can be represented by an ARX model. The advantage of ARX model representations is that standard system...... identifiation techniques using convex optimization can be used for identification of such models from input-output data. The stochastic model of the ARX model identified from input-output data is modified with an ARMA model designed as part of the MPC-design procedure to ensure offset-free control. The ARMAX...... model description resulting from the extension can be realized as a state space model in innovation form. The MPC is designed and implemented based on this state space model in innovation form. Expressions for the closed-loop dynamics of the unconstrained system is used to derive the sensitivity...

  6. A surrogate based multistage-multilevel optimization procedure for multidisciplinary design optimization

    NARCIS (Netherlands)

    Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.

    2011-01-01

    Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with

  7. Optimal placement of capacito

    Directory of Open Access Journals (Sweden)

    N. Gnanasekaran

    2016-06-01

    Full Text Available Optimal size and location of shunt capacitors in the distribution system plays a significant role in minimizing the energy loss and the cost of reactive power compensation. This paper presents a new efficient technique to find optimal size and location of shunt capacitors with the objective of minimizing cost due to energy loss and reactive power compensation of distribution system. A new Shark Smell Optimization (SSO algorithm is proposed to solve the optimal capacitor placement problem satisfying the operating constraints. The SSO algorithm is a recently developed metaheuristic optimization algorithm conceptualized using the shark’s hunting ability. It uses a momentum incorporated gradient search and a rotational movement based local search for optimization. To demonstrate the applicability of proposed method, it is tested on IEEE 34-bus and 118-bus radial distribution systems. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

  8. Optimized data evaluation for k0-based NAA

    International Nuclear Information System (INIS)

    Van Sluijs, R.; Bossus, D.A.W.

    1999-01-01

    k 0 -NAA allows the simultaneous analysis of up-to 67 elements. The k 0 method is based on calculations using a special library instead of measuring standards. For an efficient use of the method, the calculations and resulting raw data require optimized evaluation procedures. In this paper two efficient procedures for nuclide identification and gamma interference correction are outlined. For a fast computation of the source-detector efficiency and coincidence correction factors the matrix interpolation technique is introduced. (author)

  9. Simulation based optimization on automated fibre placement process

    Science.gov (United States)

    Lei, Shi

    2018-02-01

    In this paper, a software simulation (Autodesk TruPlan & TruFiber) based method is proposed to optimize the automate fibre placement (AFP) process. Different types of manufacturability analysis are introduced to predict potential defects. Advanced fibre path generation algorithms are compared with respect to geometrically different parts. Major manufacturing data have been taken into consideration prior to the tool paths generation to achieve high success rate of manufacturing.

  10. Environmentally Optimal, Nutritionally Aware Beef Replacement Plant-Based Diets.

    Science.gov (United States)

    Eshel, Gidon; Shepon, Alon; Noor, Elad; Milo, Ron

    2016-08-02

    Livestock farming incurs large and varied environmental burdens, dominated by beef. Replacing beef with resource efficient alternatives is thus potentially beneficial, but may conflict with nutritional considerations. Here we show that protein-equivalent plant based alternatives to the beef portion of the mean American diet are readily devisible, and offer mostly improved nutritional profile considering the full lipid profile, key vitamins, minerals, and micronutrients. We then show that replacement diets require on average only 10% of land, 4% of greenhouse gas (GHG) emissions, and 6% of reactive nitrogen (Nr) compared to what the replaced beef diet requires. Applied to 320 million Americans, the beef-to-plant shift can save 91 million cropland acres (and 770 million rangeland acres), 278 million metric ton CO2e, and 3.7 million metric ton Nr annually. These nationwide savings are 27%, 4%, and 32% of the respective national environmental burdens.

  11. Optimal control and optimal trajectories of regional macroeconomic dynamics based on the Pontryagin maximum principle

    Science.gov (United States)

    Bulgakov, V. K.; Strigunov, V. V.

    2009-05-01

    The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.

  12. Tour Route Multiobjective Optimization Design Based on the Tourist Satisfaction

    Directory of Open Access Journals (Sweden)

    Yan Han

    2014-01-01

    Full Text Available The question prompted is how to design the tour route to make the tourists get the maximum satisfactions considering the tourists’ demand. The influence factors of the tour route choices of tourists were analyzed and tourists’ behavior characteristics and psychological preferences were regarded as the important influence factors based on the tourist behavioral theories. A questionnaire of tourists’ tour route information and satisfaction degree was carried out. Some information about the scene spot and tourists demand and tour behaviors characteristic such as visit frequency, number of attractions visited was obtained and analyzed. Based on the convey datum, tour routes multiobjective optimization functions were prompted for the tour route design regarding the maximum satisfaction and the minimum tour distance as the optimal objective. The available routes are listed and categorized. Based on the particle swarm optimization model, the priorities of the tour route are calculated and finally the suggestion depth tour route and quick route tour routes are given considering the different tour demands of tourists. The results can offer constructive suggestions on how to design tour routes on the part of tourism enterprises and how to choose a proper tour route on the part of tourists.

  13. Genetic Algorithm (GA)-Based Inclinometer Layout Optimization.

    Science.gov (United States)

    Liang, Weijie; Zhang, Ping; Chen, Xianping; Cai, Miao; Yang, Daoguo

    2015-04-17

    This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors.

  14. Simulated Annealing-Based Krill Herd Algorithm for Global Optimization

    Directory of Open Access Journals (Sweden)

    Gai-Ge Wang

    2013-01-01

    Full Text Available Recently, Gandomi and Alavi proposed a novel swarm intelligent method, called krill herd (KH, for global optimization. To enhance the performance of the KH method, in this paper, a new improved meta-heuristic simulated annealing-based krill herd (SKH method is proposed for optimization tasks. A new krill selecting (KS operator is used to refine krill behavior when updating krill’s position so as to enhance its reliability and robustness dealing with optimization problems. The introduced KS operator involves greedy strategy and accepting few not-so-good solutions with a low probability originally used in simulated annealing (SA. In addition, a kind of elitism scheme is used to save the best individuals in the population in the process of the krill updating. The merits of these improvements are verified by fourteen standard benchmarking functions and experimental results show that, in most cases, the performance of this improved meta-heuristic SKH method is superior to, or at least highly competitive with, the standard KH and other optimization methods.

  15. Fog computing job scheduling optimization based on bees swarm

    Science.gov (United States)

    Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid

    2018-04-01

    Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

  16. Kriging-based algorithm for nuclear reactor neutronic design optimization

    International Nuclear Information System (INIS)

    Kempf, Stephanie; Forget, Benoit; Hu, Lin-Wen

    2012-01-01

    Highlights: ► A Kriging-based algorithm was selected to guide research reactor optimization. ► We examined impacts of parameter values upon the algorithm. ► The best parameter values were incorporated into a set of best practices. ► Algorithm with best practices used to optimize thermal flux of concept. ► Final design produces thermal flux 30% higher than other 5 MW reactors. - Abstract: Kriging, a geospatial interpolation technique, has been used in the present work to drive a search-and-optimization algorithm which produces the optimum geometric parameters for a 5 MW research reactor design. The technique has been demonstrated to produce an optimal neutronic solution after a relatively small number of core calculations. It has additionally been successful in producing a design which significantly improves thermal neutron fluxes by 30% over existing reactors of the same power rating. Best practices for use of this algorithm in reactor design were identified and indicated the importance of selecting proper correlation functions.

  17. An optimization-based framework for anisotropic simplex mesh adaptation

    Science.gov (United States)

    Yano, Masayuki; Darmofal, David L.

    2012-09-01

    We present a general framework for anisotropic h-adaptation of simplex meshes. Given a discretization and any element-wise, localizable error estimate, our adaptive method iterates toward a mesh that minimizes error for a given degrees of freedom. Utilizing mesh-metric duality, we consider a continuous optimization problem of the Riemannian metric tensor field that provides an anisotropic description of element sizes. First, our method performs a series of local solves to survey the behavior of the local error function. This information is then synthesized using an affine-invariant tensor manipulation framework to reconstruct an approximate gradient of the error function with respect to the metric tensor field. Finally, we perform gradient descent in the metric space to drive the mesh toward optimality. The method is first demonstrated to produce optimal anisotropic meshes minimizing the L2 projection error for a pair of canonical problems containing a singularity and a singular perturbation. The effectiveness of the framework is then demonstrated in the context of output-based adaptation for the advection-diffusion equation using a high-order discontinuous Galerkin discretization and the dual-weighted residual (DWR) error estimate. The method presented provides a unified framework for optimizing both the element size and anisotropy distribution using an a posteriori error estimate and enables efficient adaptation of anisotropic simplex meshes for high-order discretizations.

  18. Optimal configuration of power grid sources based on optimal particle swarm algorithm

    Science.gov (United States)

    Wen, Yuanhua

    2018-04-01

    In order to optimize the distribution problem of power grid sources, an optimized particle swarm optimization algorithm is proposed. First, the concept of multi-objective optimization and the Pareto solution set are enumerated. Then, the performance of the classical genetic algorithm, the classical particle swarm optimization algorithm and the improved particle swarm optimization algorithm are analyzed. The three algorithms are simulated respectively. Compared with the test results of each algorithm, the superiority of the algorithm in convergence and optimization performance is proved, which lays the foundation for subsequent micro-grid power optimization configuration solution.

  19. Prognostic value of the C-reactive protein to albumin ratio: a novel inflammation-based prognostic indicator in osteosarcoma

    Directory of Open Access Journals (Sweden)

    Li YJ

    2017-11-01

    Full Text Available Yong-Jiang Li,1,* Kai Yao,2,* Min-Xun Lu,2 Wen-Biao Zhang,1 Cong Xiao,2 Chong-Qi Tu2 1Department of Oncology, 2Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, People’s Republic of China *These authors contributed equally to this work Abstract: The prognostic role of the C-reactive protein to albumin ratio (CRP/Alb ratio in patients with osteosarcoma has not been investigated. A total of 216 osteosarcoma patients were enrolled in the study. Univariate and multivariate survival analyses between the groups were performed and Kaplan–Meier analysis was conducted to plot the survival curves. Receiver operating characteristic curves were generated and areas under the curve (AUCs were compared to assess the discriminatory ability of the inflammation-based indicators, including CRP/Alb ratio, Glasgow prognostic score (GPS, neutrophil–lymphocyte ratio (NLR, and platelet–lymphocyte ratio (PLR. The optimal cutoff value was 0.210 for CRP/Alb ratio with a Youden index of 0.319. Higher values of CRP/Alb ratio were significantly associated with poorer overall survival in univariate (HR =2.62, 95% CI =1.70–4.03; P<0.001 and multivariate (HR =2.21, 95% CI =1.40–3.49; P=0.001 analyses. In addition, the CRP/Alb ratio had significantly higher AUC values compared with GPS (P=0.003, NLR (P<0.001, and PLR (P<0.001. The study demonstrated that the CRP/Alb ratio is an effective inflammation-based prognostic indicator in osteosarcoma, which potentially has a discriminatory ability superior to that of other inflammatory indicators including GPS, NLR, and PLR. Keywords: osteosarcoma, CRP to albumin ratio, prognosis

  20. A KDE-Based Random Walk Method for Modeling Reactive Transport With Complex Kinetics in Porous Media

    Science.gov (United States)

    Sole-Mari, Guillem; Fernà ndez-Garcia, Daniel; Rodríguez-Escales, Paula; Sanchez-Vila, Xavier

    2017-11-01

    In recent years, a large body of the literature has been devoted to study reactive transport of solutes in porous media based on pure Lagrangian formulations. Such approaches have also been extended to accommodate second-order bimolecular reactions, in which the reaction rate is proportional to the concentrations of the reactants. Rather, in some cases, chemical reactions involving two reactants follow more complicated rate laws. Some examples are (1) reaction rate laws written in terms of powers of concentrations, (2) redox reactions incorporating a limiting term (e.g., Michaelis-Menten), or (3) any reaction where the activity coefficients vary with the concentration of the reactants, just to name a few. We provide a methodology to account for complex kinetic bimolecular reactions in a fully Lagrangian framework where each particle represents a fraction of the total mass of a specific solute. The method, built as an extension to the second-order case, is based on the concept of optimal Kernel Density Estimator, which allows the concentrations to be written in terms of particle locations, hence transferring the concept of reaction rate to that of particle location distribution. By doing so, we can update the probability of particles reacting without the need to fully reconstruct the concentration maps. The performance and convergence of the method is tested for several illustrative examples that simulate the Advection-Dispersion-Reaction Equation in a 1-D homogeneous column. Finally, a 2-D application example is presented evaluating the need of fully describing non-bilinear chemical kinetics in a randomly heterogeneous porous medium.

  1. Reactively loaded arrays based on overlapping sub-arrays with flat-top radiation pattern

    NARCIS (Netherlands)

    Maximidis, R. T.; Smolders, A. B.; Toso, G.; Caratelli, D.

    2017-01-01

    The design of reactively-loaded antenna arrays featuring a pulse-shaped radiation pattern for limited scan-angle applications is presented. The use of the reactive loading allows reducing the complexity of the feeding structure, eliminating the need for complex overlapping beam-forming networks and

  2. Cat swarm optimization based evolutionary framework for multi document summarization

    Science.gov (United States)

    Rautray, Rasmita; Balabantaray, Rakesh Chandra

    2017-07-01

    Today, World Wide Web has brought us enormous quantity of on-line information. As a result, extracting relevant information from massive data has become a challenging issue. In recent past text summarization is recognized as one of the solution to extract useful information from vast amount documents. Based on number of documents considered for summarization, it is categorized as single document or multi document summarization. Rather than single document, multi document summarization is more challenging for the researchers to find accurate summary from multiple documents. Hence in this study, a novel Cat Swarm Optimization (CSO) based multi document summarizer is proposed to address the problem of multi document summarization. The proposed CSO based model is also compared with two other nature inspired based summarizer such as Harmony Search (HS) based summarizer and Particle Swarm Optimization (PSO) based summarizer. With respect to the benchmark Document Understanding Conference (DUC) datasets, the performance of all algorithms are compared in terms of different evaluation metrics such as ROUGE score, F score, sensitivity, positive predicate value, summary accuracy, inter sentence similarity and readability metric to validate non-redundancy, cohesiveness and readability of the summary respectively. The experimental analysis clearly reveals that the proposed approach outperforms the other summarizers included in the study.

  3. Reactive power planning with FACTS devices using gravitational search algorithm

    Directory of Open Access Journals (Sweden)

    Biplab Bhattacharyya

    2015-09-01

    Full Text Available In this paper, Gravitational Search Algorithm (GSA is used as optimization method in reactive power planning using FACTS (Flexible AC transmission system devices. The planning problem is formulated as a single objective optimization problem where the real power loss and bus voltage deviations are minimized under different loading conditions. GSA based optimization algorithm and particle swarm optimization techniques (PSO are applied on IEEE 30 bus system. Results show that GSA can also be a very effective tool for reactive power planning.

  4. Analyze the optimal solutions of optimization problems by means of fractional gradient based system using VIM

    Directory of Open Access Journals (Sweden)

    Firat Evirgen

    2016-04-01

    Full Text Available In this paper, a class of Nonlinear Programming problem is modeled with gradient based system of fractional order differential equations in Caputo's sense. To see the overlap between the equilibrium point of the fractional order dynamic system and theoptimal solution of the NLP problem in a longer timespan the Multistage Variational İteration Method isapplied. The comparisons among the multistage variational iteration method, the variationaliteration method and the fourth order Runge-Kutta method in fractional and integer order showthat fractional order model and techniques can be seen as an effective and reliable tool for finding optimal solutions of Nonlinear Programming problems.

  5. Mesh Denoising based on Normal Voting Tensor and Binary Optimization.

    Science.gov (United States)

    Yadav, Sunil Kumar; Reitebuch, Ulrich; Polthier, Konrad

    2017-08-17

    This paper presents a two-stage mesh denoising algorithm. Unlike other traditional averaging approaches, our approach uses an element-based normal voting tensor to compute smooth surfaces. By introducing a binary optimization on the proposed tensor together with a local binary neighborhood concept, our algorithm better retains sharp features and produces smoother umbilical regions than previous approaches. On top of that, we provide a stochastic analysis on the different kinds of noise based on the average edge length. The quantitative results demonstrate that the performance of our method is better compared to state-of-the-art smoothing approaches.

  6. Attitude Optimal Backstepping Controller Based Quaternion for a UAV

    Directory of Open Access Journals (Sweden)

    Kaddouri Djamel

    2016-01-01

    Full Text Available A hierarchical controller design based on nonlinear H∞ theory and backstepping technique is developed for a nonlinear and coupled dynamic attitude system using conventional quaternion based method. The derived controller combines the attractive features of H∞ optimal controller and the advantages of the backstepping technique leading to a control law which avoids winding phenomena. Performance issues of the controller are illustrated in a simulation study made for a four-rotor vertical take-off and landing (VTOL aerial robot prototype known as the quadrotor aircraft.

  7. The first proton sponge-based amino acids: synthesis, acid-base properties and some reactivity.

    Science.gov (United States)

    Ozeryanskii, Valery A; Gorbacheva, Anastasia Yu; Pozharskii, Alexander F; Vlasenko, Marina P; Tereznikov, Alexander Yu; Chernov'yants, Margarita S

    2015-08-21

    The first hybrid base constructed from 1,8-bis(dimethylamino)naphthalene (proton sponge or DMAN) and glycine, N-methyl-N-(8-dimethylamino-1-naphthyl)aminoacetic acid, was synthesised in high yield and its hydrobromide was structurally characterised and used to determine the acid-base properties via potentiometric titration. It was found that the basic strength of the DMAN-glycine base (pKa = 11.57, H2O) is on the level of amidine amino acids like arginine and creatine and its structure, zwitterionic vs. neutral, based on the spectroscopic (IR, NMR, mass) and theoretical (DFT) approaches has a strong preference to the zwitterionic form. Unlike glycine, the DMAN-glycine zwitterion is N-chiral and is hydrolytically cleaved with the loss of glycolic acid on heating in DMSO. This reaction together with the mild decarboxylative conversion of proton sponge-based amino acids into 2,3-dihydroperimidinium salts under air-oxygen was monitored with the help of the DMAN-alanine amino acid. The newly devised amino acids are unique as they combine fluorescence, strongly basic and redox-active properties.

  8. Reactive Systems

    DEFF Research Database (Denmark)

    Aceto, Luca; Ingolfsdottir, Anna; Larsen, Kim Guldstrand

    A reactive system comprises networks of computing components, achieving their goals through interaction among themselves and their environment. Thus even relatively small systems may exhibit unexpectedly complex behaviours. As moreover reactive systems are often used in safety critical systems......, the need for mathematically based formal methodology is increasingly important. There are many books that look at particular methodologies for such systems. This book offers a more balanced introduction for graduate students and describes the various approaches, their strengths and weaknesses, and when...... they are best used. Milner's CCS and its operational semantics are introduced, together with the notions of behavioural equivalences based on bisimulation techniques and with recursive extensions of Hennessy-Milner logic. In the second part of the book, the presented theories are extended to take timing issues...

  9. GPU based Monte Carlo for PET image reconstruction: parameter optimization

    International Nuclear Information System (INIS)

    Cserkaszky, Á; Légrády, D.; Wirth, A.; Bükki, T.; Patay, G.

    2011-01-01

    This paper presents the optimization of a fully Monte Carlo (MC) based iterative image reconstruction of Positron Emission Tomography (PET) measurements. With our MC re- construction method all the physical effects in a PET system are taken into account thus superior image quality is achieved in exchange for increased computational effort. The method is feasible because we utilize the enormous processing power of Graphical Processing Units (GPUs) to solve the inherently parallel problem of photon transport. The MC approach regards the simulated positron decays as samples in mathematical sums required in the iterative reconstruction algorithm, so to complement the fast architecture, our work of optimization focuses on the number of simulated positron decays required to obtain sufficient image quality. We have achieved significant results in determining the optimal number of samples for arbitrary measurement data, this allows to achieve the best image quality with the least possible computational effort. Based on this research recommendations can be given for effective partitioning of computational effort into the iterations in limited time reconstructions. (author)

  10. RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE

    Directory of Open Access Journals (Sweden)

    Ming-Chang LEE

    2015-07-01

    Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets.  The risk analysis and asset allocation are the key technology of banking and risk management.  The aim of this paper, build a loan portfolio optimization model based on risk analysis.  Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank.  In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm.  This paper solves the highly difficult problem by matrix operation method.  Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space.  It is easy calculation in proposed method.

  11. Optimal alignment of mirror based pentaprisms for scanning deflectometric devices

    Energy Technology Data Exchange (ETDEWEB)

    Barber, Samuel K.; Geckeler, Ralf D.; Yashchuk, Valeriy V.; Gubarev, Mikhail V.; Buchheim, Jana; Siewert, Frank; Zeschke, Thomas

    2011-03-04

    In the recent work [Proc. of SPIE 7801, 7801-2/1-12 (2010), Opt. Eng. 50(5) (2011), in press], we have reported on improvement of the Developmental Long Trace Profiler (DLTP), a slope measuring profiler available at the Advanced Light Source Optical Metrology Laboratory, achieved by replacing the bulk pentaprism with a mirror based pentaprism (MBPP). An original experimental procedure for optimal mutual alignment of the MBPP mirrors has been suggested and verified with numerical ray tracing simulations. It has been experimentally shown that the optimally aligned MBPP allows the elimination of systematic errors introduced by inhomogeneity of the optical material and fabrication imperfections of the bulk pentaprism. In the present article, we provide the analytical derivation and verification of easily executed optimal alignment algorithms for two different designs of mirror based pentaprisms. We also provide an analytical description for the mechanism for reduction of the systematic errors introduced by a typical high quality bulk pentaprism. It is also shown that residual misalignments of an MBPP introduce entirely negligible systematic errors in surface slope measurements with scanning deflectometric devices.

  12. Monadic Functional Reactive Programming

    NARCIS (Netherlands)

    A.J. van der Ploeg (Atze); C Shan

    2013-01-01

    htmlabstractFunctional Reactive Programming (FRP) is a way to program reactive systems in functional style, eliminating many of the problems that arise from imperative techniques. In this paper, we present an alternative FRP formulation that is based on the notion of a reactive computation: a

  13. Accounting for the Decreasing Denitrification Potential of Aquifers in Travel-Time Based Reactive-Transport Models of Nitrate

    Science.gov (United States)

    Cirpka, O. A.; Loschko, M.; Wöhling, T.; Rudolph, D. L.

    2017-12-01

    Excess nitrate concentrations pose a threat to drinking-water production from groundwater in all regions of intensive agriculture worldwide. Natural organic matter, pyrite, and other reduced constituents of the aquifer matrix can be oxidized by aerobic and denitrifying bacteria, leading to self-cleaning of groundwater. Various studies have shown that the heterogeneity of both hydraulic and chemical aquifer properties influence the reactive behavior. Since the exact spatial distributions of these properties are not known, predictions on the temporal evolution of nitrate should be probabilistic. However, the computational effort of pde-based, spatially explicit multi-component reactive-transport simulations are so high that multiple model runs become impossible. Conversely, simplistic models that treat denitrification as first-order decay process miss important controls on denitrification. We have proposed a Lagrangian framework of nonlinear reactive transport, in which the electron-donor supply by the aquifer matrix is parameterized by a relative reactivity, that is the reaction rate relative to a standard reaction rate for identical solute concentrations (Loschko et al., 2016). We could show that reactive transport simplifies to solving a single ordinary dfferential equation in terms of the cumulative relative reactivity for a given combination of inflow concentrations. Simulating 3-D flow and reactive transport are computationally so inexpensive that Monte Carlo simulation become feasible. The original scheme did not consider a change of the relative reactivity over time, implying that the electron-donor pool in the matrix is infinite. We have modified the scheme to address the consumption of the reducing aquifer constituents upon the reactions. We also analyzed how a minimally complex model of aerobic respiration and denitrification could look like. With the revised scheme, we performed Monte Carlo simulations in 3-D domains, confirming that the uncertainty in

  14. Optimization on Trajectory of Stanford Manipulator based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Han Xi

    2017-01-01

    Full Text Available The optimization of robot manipulator’s trajectory has become a hot topic in academic and industrial fields. In this paper, a method for minimizing the moving distance of robot manipulators is presented. The Stanford Manipulator is used as the research object and the inverse kinematics model is established with Denavit-Hartenberg method. Base on the initial posture matrix, the inverse kinematics model is used to find the initial state of each joint. In accordance with the given beginning moment, cubic polynomial interpolation is applied to each joint variable and the positive kinematic model is used to calculate the moving distance of end effector. Genetic algorithm is used to optimize the sequential order of each joint and the time difference between different starting time of joints. Numerical applications involving a Stanford manipulator are presented.

  15. Gradient-based optimization in nonlinear structural dynamics

    DEFF Research Database (Denmark)

    Dou, Suguang

    The intrinsic nonlinearity of mechanical structures can give rise to rich nonlinear dynamics. Recently, nonlinear dynamics of micro-mechanical structures have contributed to developing new Micro-Electro-Mechanical Systems (MEMS), for example, atomic force microscope, passive frequency divider......, frequency stabilization, and disk resonator gyroscope. For advanced design of these structures, it is of considerable value to extend current optimization in linear structural dynamics into nonlinear structural dynamics. In this thesis, we present a framework for modelling, analysis, characterization......, and optimization of nonlinear structural dynamics. In the modelling, nonlinear finite elements are used. In the analysis, nonlinear frequency response and nonlinear normal modes are calculated based on a harmonic balance method with higher-order harmonics. In the characterization, nonlinear modal coupling...

  16. Structural Optimization based on the Concept of First Order Analysis

    International Nuclear Information System (INIS)

    Shinji, Nishiwaki; Hidekazu, Nishigaki; Yasuaki, Tsurumi; Yoshio, Kojima; Noboru, Kikuchi

    2002-01-01

    Computer Aided Engineering (CAE) has been successfully utilized in mechanical industries such as the automotive industry. It is, however, difficult for most mechanical design engineers to directly use CAE due to the sophisticated nature of the operations involved. In order to mitigate this problem, a new type of CAE, First Order Analysis (FOA) has been proposed. This paper presents the outcome of research concerning the development of a structural topology optimization methodology within FOA. This optimization method is constructed based on discrete and function-oriented elements such as beam and panel elements, and sequential convex programming. In addition, examples are provided to show the utility of the methodology presented here for mechanical design engineers

  17. Celestial Navigation Fix Based on Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Tsou Ming-Cheng

    2015-09-01

    Full Text Available A technique for solving celestial fix problems is proposed in this study. This method is based on Particle Swarm Optimization from the field of swarm intelligence, utilizing its superior optimization and searching abilities to obtain the most probable astronomical vessel position. In addition to being applicable to two-body fix, multi-body fix, and high-altitude observation problems, it is also less reliant on the initial dead reckoning position. Moreover, by introducing spatial data processing and display functions in a Geographical Information System, calculation results and chart work used in Circle of Position graphical positioning can both be integrated. As a result, in addition to avoiding tedious and complicated computational and graphical procedures, this work has more flexibility and is more robust when compared to other analytical approaches.

  18. Reactivity on the Web

    OpenAIRE

    Bailey, James; Bry, François; Eckert, Michael; Patrânjan, Paula Lavinia

    2005-01-01

    Reactivity, the ability to detect simple and composite events and respond in a timely manner, is an essential requirement in many present-day information systems. With the emergence of new, dynamic Web applications, reactivity on the Web is receiving increasing attention. Reactive Web-based systems need to detect and react not only to simple events but also to complex, real-life situations. This paper introduces XChange, a language for programming reactive behaviour on the Web,...

  19. Chaotic improved PSO-based multi-objective optimization for minimization of power losses and L index in power systems

    International Nuclear Information System (INIS)

    Chen, Gonggui; Liu, Lilan; Song, Peizhu; Du, Yangwei

    2014-01-01

    Highlights: • New method for MOORPD problem using MOCIPSO and MOIPSO approaches. • Constrain-prior Pareto-dominance method is proposed to meet the constraints. • The limits of the apparent power flow of transmission line are considered. • MOORPD model is built up for MOORPD problem. • The achieved results by MOCIPSO and MOIPSO approaches are better than MOPSO method. - Abstract: Multi-objective optimal reactive power dispatch (MOORPD) seeks to not only minimize power losses, but also improve the stability of power system simultaneously. In this paper, the static voltage stability enhancement is achieved through incorporating L index in MOORPD problem. Chaotic improved PSO-based multi-objective optimization (MOCIPSO) and improved PSO-based multi-objective optimization (MOIPSO) approaches are proposed for solving complex multi-objective, mixed integer nonlinear problems such as minimization of power losses and L index in power systems simultaneously. In MOCIPSO and MOIPSO based optimization approaches, crossover operator is proposed to enhance PSO diversity and improve their global searching capability, and for MOCIPSO based optimization approach, chaotic sequences based on logistic map instead of random sequences is introduced to PSO for enhancing exploitation capability. In the two approaches, constrain-prior Pareto-dominance method (CPM) is proposed to meet the inequality constraints on state variables, the sorting and crowding distance methods are considered to maintain a well distributed Pareto optimal solutions, and moreover, fuzzy set theory is employed to extract the best compromise solution over the Pareto optimal curve. The proposed approaches have been examined and tested in the IEEE 30 bus and the IEEE 57 bus power systems. The performances of MOCIPSO, MOIPSO, and multi-objective PSO (MOPSO) approaches are compared with respect to multi-objective performance measures. The simulation results are promising and confirm the ability of MOCIPSO and

  20. Real-time detection of intracellular reactive oxygen species and mitochondrial membrane potential in THP-1 macrophages during ultrasonic irradiation for optimal sonodynamic therapy.

    Science.gov (United States)

    Sun, Xin; Xu, Haobo; Shen, Jing; Guo, Shuyuan; Shi, Sa; Dan, Juhua; Tian, Fang; Tian, Yanfeng; Tian, Ye

    2015-01-01

    Reactive oxygen species (ROS) elevation and mitochondrial membrane potential (MMP) loss have been proven recently to be involved in sonodynamic therapy (SDT)-induced macrophage apoptosis and necrosis. This study aims to develop an experimental system to monitor intracellular ROS and MMP in real-time during ultrasonic irradiation in order to achieve optimal effect in SDT. Cultured THP-1 derived macrophages were incubated with 5-aminolevulinic acid (ALA), and then sonicated at different intensities. Intracellular ROS elevation and MMP loss were detected in real-time by fluorospectrophotometer using fluorescence probe DCFH-DA and jc-1, respectively. Ultrasound at low intensities (less than 0.48W/cm(2)) had no influence on ROS and MMP in macrophages, whereas at an intensity of 0.48W/cm(2), ROS elevation and MMP loss were observed during ultrasonic irradiation. These effects were strongly enhanced in the presence of ALA. Quantitative analysis showed that ROS elevation and MMP loss monotonically increased with the rise of ultrasonic intensity between 0.48 and 1.16W/cm(2). SDT at 0.48 and 0.84W/cm(2) induced mainly apoptosis in THP-1 macrophages while SDT at 1.16W/cm(2) mainly cell necrosis. This study supports the validity and potential utility of real-time ROS and MMP detection as a dosimetric tool for the determination of optimal SDT. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Assessment on the decolourization of textile dye (Reactive Yellow) using Pseudomonas sp. immobilized on fly ash: Response surface methodology optimization and toxicity evaluation.

    Science.gov (United States)

    Roy, Uttariya; Sengupta, Shubhalakshmi; Banerjee, Priya; Das, Papita; Bhowal, Avijit; Datta, Siddhartha

    2018-06-18

    This study focuses on the investigation of removal of textile dye (Reactive Yellow) by a combined approach of sorption integrated with biodegradation using low cost adsorbent fly ash immobilized with Pseudomonas sp. To ensure immobilization of bacterial species on treated fly ash, fly ash with immobilized bacterial cells was characterized using Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and fluorescence microscopy. Comparative batch studies were carried out using Pseudomonas sp, fly ash and immobilized Pseudomonas sp on flyash and were observed that immobilized Pseudomonas sp on flyash acted as better decolourizing agent. The optimized pH, temperature, and immobilized adsorbent dosage for highest percentage of dye removal were observed to be pH 6, 303 K, 1.2 g/L in all the cases. At optimum condition, the highest percentage of dye removal was found to be 88.51%, 92.62% and 98.72% for sorption (flyash), biodegradation (Pseudomonas sp) and integral approach (Pseudomonas sp on flyash) respectively. Optimization of operating parameters of textile dye decolourization was done by response surface methodology (RSM) using Design Expert 7 software. Phytotoxicity evaluation with Cicer arietinum revealed that seeds exposed to untreated dye effluents showed considerably lower growth, inhibited biochemical, and enzyme parameters with compared to those exposed to treated textile effluents. Thus this immobilized inexpensive technique could be used for removal of synthetic dyes present in textile wastewater. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Titanium dioxide-based DGT technique for in situ measurement of dissolved reactive phosphorus in fresh and marine waters

    DEFF Research Database (Denmark)

    Panther, Jared G.; Teasdale, Peter R.; Bennett, William W.

    2010-01-01

    A new diffusive gradients in a thin film (DGT) technique for measuring dissolved reactive phosphorus (DRP) in fresh and marine waters is reported. The new method, which uses a commercially available titanium dioxide based adsorbent (Metsorb), was evaluated and compared to the well-established fer...

  3. Measurement based analysis of active and reactive power losses in a distribution network with wind farms and CHPs

    DEFF Research Database (Denmark)

    Lund, Torsten

    2007-01-01

    The paper presents an investigation of the active and reactive power losses in a distribution network with wind turbines and combined heat and power plants. The investigation is based on 15 min average power measurements and load flow calculations in the power system simulation tool PowerFactory...

  4. The mediating effect of mindful non-reactivity in exposure-based cognitive behavior therapy for severe health anxiety.

    Science.gov (United States)

    Hedman, Erik; Hesser, Hugo; Andersson, Erik; Axelsson, Erland; Ljótsson, Brjánn

    2017-08-01

    Exposure-based cognitive behavior therapy (CBT) has been shown to be effective in the treatment of severe health anxiety, but little is known about mediators of treatment effect. The aim of the present study was to investigate mindful non-reactivity as a putative mediator of health anxiety outcome using data from a large scale randomized controlled trial. We assessed mindful non-reactivity using the Five Facets Mindfulness Questionnaire-Non-Reactivity scale (FFMQ-NR) and health anxiety with the Short Health Anxiety Inventory (SHAI). Participants with severe health anxiety (N=158) were randomized to internet-delivered exposure-based CBT or behavioral stress management (BSM) and throughout the treatment, both the mediator and outcome were measured weekly. As previously reported, exposure-based CBT was more effective than BSM in reducing health anxiety. In the present study, latent process growth modeling showed that treatment condition had a significant effect on the FFMQ-NR growth trajectory (α-path), estimate=0.18, 95% CI [0.04, 0.32], p=.015, indicating a larger increase in mindful non-reactivity among participants receiving exposure-based CBT compared to the BSM group. The FFMQ-NR growth trajectory was significantly correlated with the SHAI trajectory (β-path estimate=-1.82, 95% CI [-2.15, -1.48], panxiety. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions

    International Nuclear Information System (INIS)

    Zhang, Fan; Yeh, Gour-Tsyh; Parker, Jack C.; Brooks, Scott C; Pace, Molly; Kim, Young Jin; Jardine, Philip M.; Watson, David B.

    2007-01-01

    This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M. partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M. species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing NE equilibrium reactions and a set of reactive transport equations of M-NE kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions

  6. Transient voltage control of a DFIG-based wind power plant for suppressing overvoltage using a reactive current reduction loop

    Directory of Open Access Journals (Sweden)

    Geon Park

    2016-01-01

    Full Text Available This paper proposes a transient voltage control scheme of a doubly fed induction generator (DFIG-based wind power plant (WPP using a reactive current reduction loop to suppress the overvoltage at a point of interconnection (POI and DFIG terminal after a fault clearance. The change of terminal voltage of a DFIG is monitored at every predefined time period to detect the fault clearance. If the voltage change exceeds a set value, then the reactive current reduction loop reduces the reactive current reference in the DFIG controller using the step function. The reactive current injection of DFIGs in a WPP is rapidly reduced, and a WPP can rapidly suppress the overvoltage at a fault clearance because the reactive current reference is reduced. Using an electromagnetic transients program–released version (EMTP–RV simulator, the performance of the proposed scheme was validated for a model system comprising 20 units of a 5-MW DFIG considering various scenarios, such as fault and wind conditions. Test results show that the proposed scheme enables a WPP to suppress the overvoltage at the POI and DFIG terminal within a short time under grid fault conditions.

  7. A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions.

    Science.gov (United States)

    Zhang, Fan; Yeh, Gour-Tsyh; Parker, Jack C; Brooks, Scott C; Pace, Molly N; Kim, Young-Jin; Jardine, Philip M; Watson, David B

    2007-06-16

    This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing N(E) equilibrium reactions and a set of reactive transport equations of M-N(E) kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.

  8. Optimizing the dual elemental thermal reactive deposition time in carbide layer formation on SUJ2 tool steel

    Science.gov (United States)

    Mochtar, Myrna Ariati; Putra, Wahyuaji Narottama; Mahardika, Bayu

    2018-05-01

    This paper presents developments contributing to the improvement of thermo-reactive deposition (TRD) process in producing hard carbide layers, on automotive components application. The problem in using FeV powder as a coating material that has been applied in the industries is it is high cost. In this study, FeCr powder coating material was mixed into FeV powder with a ratio of 35:65 weight percent. The SUJ2 steel pins components are processed at 980° C, with varying TRD time was 4,6,8 and 10 hours. Scanning Electron microscope (SEM), Electron Probe Micro Analyzer (EPMA) and X-ray diffraction (XRD) were applied to analyze the coating layers. The thickness of the carbide layer formed will increase with the longer processing time, which thickness at 4-10 hours is increase from 22.7 to 29.7 micron. The gained thickness tends to be homogeneous. Increasing the TRD process holding time results in a higher hardness of the carbide layerwith hardness at 4, 6, 8 and 10 hours is 2049, 2184, 2175 and 2343 HV. The wear rate at TRD holding time of 4-10 hours with the Ogoshi method was reduced from 5.1 × 10-4 mm3/m to 2.5 × 10-4 mm3/m. Optical microscope observations shows that substrate phases consisting of pearlite and cementite and grains that tend to enlarge with the addition of time. Carbide compounds that are formed are vanadium carbide (V8C7, V6C5, V2C) and chromium carbide (Cr3C2, Cr23C7, Cr3C7). While EDS-Linescan results show complex phase (Fe, V, Cr) xC formed. The research shows that addition of FeCr into FeV powder in TRD process in 980°C with optimum time of 10 hours processing meet the mechanical properties requirement of automotive components.

  9. Digital reactivity meter

    International Nuclear Information System (INIS)

    Akkus, B.; Anac, H.; Alsan, S.; Erk, S.

    1991-01-01

    Nowadays, various digital methods making use of microcomputers for neutron detector signals and determining the reactivity by numerical calculations are used in reactor control systems in place of classical reactivity meters. In this work, a calculation based on the ''The Time Dependent Transport Equation'' has been developed for determining the reactivity numerically. The reactivity values have been obtained utilizing a computer-based data acquisition and control system and compared with the analog reactivity meter values as well as the values calculated from the ''Inhour Equation''

  10. Optimal Output of Distributed Generation Based On Complex Power Increment

    Science.gov (United States)

    Wu, D.; Bao, H.

    2017-12-01

    In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

  11. Simulation-based optimal Bayesian experimental design for nonlinear systems

    KAUST Repository

    Huan, Xun

    2013-01-01

    The optimal selection of experimental conditions is essential to maximizing the value of data for inference and prediction, particularly in situations where experiments are time-consuming and expensive to conduct. We propose a general mathematical framework and an algorithmic approach for optimal experimental design with nonlinear simulation-based models; in particular, we focus on finding sets of experiments that provide the most information about targeted sets of parameters.Our framework employs a Bayesian statistical setting, which provides a foundation for inference from noisy, indirect, and incomplete data, and a natural mechanism for incorporating heterogeneous sources of information. An objective function is constructed from information theoretic measures, reflecting expected information gain from proposed combinations of experiments. Polynomial chaos approximations and a two-stage Monte Carlo sampling method are used to evaluate the expected information gain. Stochastic approximation algorithms are then used to make optimization feasible in computationally intensive and high-dimensional settings. These algorithms are demonstrated on model problems and on nonlinear parameter inference problems arising in detailed combustion kinetics. © 2012 Elsevier Inc.

  12. Reliability-Based Optimal Design for Very Large Floating Structure

    Institute of Scientific and Technical Information of China (English)

    ZHANG Shu-hua(张淑华); FUJIKUBO Masahiko

    2003-01-01

    Costs and losses induced by possible future extreme environmental conditions and difficulties in repairing post-yielding damage strongly suggest the need for proper consideration in design rather than just life loss prevention. This can be addressed through the development of design methodology that balances the initial cost of the very large floating structure (VLFS) against the expected potential losses resulting from future extreme wave-induced structural damage. Here, the development of a methodology for determining optimal, cost-effective design will be presented and applied to a VLFS located in the Tokyo bay. Optimal design criteria are determined based on the total expected life-cycle cost and acceptable damage probability and curvature of the structure, and a set of sizes of the structure are obtained. The methodology and applications require expressions of the initial cost and the expected life-cycle damage cost as functions of the optimal design variables. This study includes the methodology, total life-cycle cost function, structural damage modeling, and reliability analysis.

  13. Optimization of heat transfer utilizing graph based evolutionary algorithms

    International Nuclear Information System (INIS)

    Bryden, Kenneth M.; Ashlock, Daniel A.; McCorkle, Douglas S.; Urban, Gregory L.

    2003-01-01

    This paper examines the use of graph based evolutionary algorithms (GBEAs) for optimization of heat transfer in a complex system. The specific case examined in this paper is the optimization of heat transfer in a biomass cookstove utilizing three-dimensional computational fluid dynamics to generate the fitness function. In this stove hot combustion gases are used to heat a cooking surface. The goal is to provide an even spatial temperature distribution on the cooking surface by redirecting the flow of combustion gases with baffles. The variables in the optimization are the position and size of the baffles, which are described by integer values. GBEAs are a novel type of EA in which a topology or geography is imposed on an evolving population of solutions. The choice of graph controls the rate at which solutions can spread within the population, impacting the diversity of solutions and convergence rate of the EAs. In this study, the choice of graph in the GBEAs changes the number of mating events required for convergence by a factor of approximately 2.25 and the diversity of the population by a factor of 2. These results confirm that by tuning the graph and parameters in GBEAs, computational time can be significantly reduced

  14. Energy Optimal Control Strategy of PHEV Based on PMP Algorithm

    Directory of Open Access Journals (Sweden)

    Tiezhou Wu

    2017-01-01

    Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.

  15. A seismic fault recognition method based on ant colony optimization

    Science.gov (United States)

    Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong

    2018-05-01

    Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.

  16. Nanoporous Hybrid Electrolytes for High-Energy Batteries Based on Reactive Metal Anodes

    Energy Technology Data Exchange (ETDEWEB)

    Tu, Zhengyuan [Department of Materials Science and Engineering, Cornell University, Ithaca NY 14850 USA; Zachman, Michael J. [School of Applied and Engineering Physics, Cornell University, Ithaca NY 14850 USA; Choudhury, Snehashis [School of Chemical Engineering and Biomolecular Engineering, Cornell University, Ithaca NY 14850 USA; Wei, Shuya [School of Chemical Engineering and Biomolecular Engineering, Cornell University, Ithaca NY 14850 USA; Ma, Lin [Department of Materials Science and Engineering, Cornell University, Ithaca NY 14850 USA; Yang, Yuan [Department of Chemistry and Geochemistry, Colorado School of Mines, Golden CO 80401 USA; Kourkoutis, Lena F. [School of Applied and Engineering Physics, Cornell University, Ithaca NY 14850 USA; Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca NY 14853 USA; Archer, Lynden A. [Department of Materials Science and Engineering, Cornell University, Ithaca NY 14850 USA; School of Chemical Engineering and Biomolecular Engineering, Cornell University, Ithaca NY 14850 USA

    2017-01-06

    Successful strategies for stabilizing electrodeposition of reactive metals, including lithium, sodium, and aluminum are a requirement for safe, high-energy electrochemical storage technologies that utilize these metals as anodes. Unstable deposition produces high-surface area dendritic structures at the anode/electrolyte interface, which causes premature cell failure by complex physical and chemical processes that have presented formidable barriers to progress. Here, it is reported that hybrid electrolytes created by infusing conventional liquid electrolytes into nanoporous membranes provide exceptional ability to stabilize Li. Electrochemical cells based on γ-Al2O3 ceramics with pore diameters below a cut-off value above 200 nm exhibit long-term stability even at a current density of 3 mA cm-2. The effect is not limited to ceramics; similar large enhancements in stability are observed for polypropylene membranes with less monodisperse pores below 450 nm. These findings are critically assessed using theories for ion rectification and electrodeposition reactions in porous solids and show that the source of stable electrodeposition in nanoporous electrolytes is fundamental.

  17. The Effect of Reactives Diluents to the Physical Properties of Acrylated Palm Oil Based Polyurethane Coatings

    Directory of Open Access Journals (Sweden)

    Onn Munirah

    2016-01-01

    Full Text Available The development of polyurethane with hydroxyl access in a molecule leads to a new alternative of low toxicity green product. Palm oil is one of the major commodities in Malaysia. The potential of palm oil to be used as coatings raw material such as alkyd is limited due to low unsaturated side on fatty acid chains. To overcome this limitation, palm oil was modified through transesterification process to produce polyol. Acrylated isocyanate (urethane oligomer was then grafted onto polyol to produce polyurethane with vinylic ends. The polyurethane was formulated with different cross-linkers (reactive diluents and cured under UV radiation. The effect of three different diluents; monoacrylate, diacrylate and triacrylate on the properties of cured polymer were studied in this research. Fourier Transform Infrared (FTIR, Hydroxyl Value Titration, Gel Content, and Volatile Organic Compound (VOC were used for characterization. Physical testing performed were Pencil Hardness and Pull-Off Adhesion test. Novel palm oil-based polyurethane coatings have been found to have good properties with mono acrylate functionality.

  18. Nanoporous Hybrid Electrolytes for High-Energy Batteries Based on Reactive Metal Anodes

    KAUST Repository

    Tu, Zhengyuan

    2017-01-06

    Successful strategies for stabilizing electrodeposition of reactive metals, including lithium, sodium, and aluminum are a requirement for safe, high-energy electrochemical storage technologies that utilize these metals as anodes. Unstable deposition produces high-surface area dendritic structures at the anode/electrolyte interface, which causes premature cell failure by complex physical and chemical processes that have presented formidable barriers to progress. Here, it is reported that hybrid electrolytes created by infusing conventional liquid electrolytes into nanoporous membranes provide exceptional ability to stabilize Li. Electrochemical cells based on γ-Al2O3 ceramics with pore diameters below a cut-off value above 200 nm exhibit long-term stability even at a current density of 3 mA cm−2. The effect is not limited to ceramics; similar large enhancements in stability are observed for polypropylene membranes with less monodisperse pores below 450 nm. These findings are critically assessed using theories for ion rectification and electrodeposition reactions in porous solids and show that the source of stable electrodeposition in nanoporous electrolytes is fundamental.

  19. Development of a reactive burn model based upon an explicit visco-plastic pore collapse model

    Science.gov (United States)

    Bouton, Eric; Lefrançois, Alexandre; Belmas, Robert

    2015-06-01

    Our aim in this study is to develop a reactive burn model based upon a microscopic hot spot model to compute the initiation and shock to detonation of pressed TATB explosives. For the sake of simplicity, the hot spots are supposed to result from the viscoplastic collapse of spherical micro-voids inside the composition. Such a model has been incorporated in a lagrangian hydrodynamic code. In our calculations, 8 different pore diameters, ranging from 100 nm to 1.2 μm, have been taken into account and the porosity associated to each pore size has been deduced from the PBX-9502 void distribution derived from the SAXS. The last ingredient of our model is the burn rate that depends on two main variables. The first one is the shock pressure as proposed by the developers of the CREST model. The second one is the number of effective chemical reaction sites calculated by the microscopic model. Furthermore, the function of the reaction progress variable of the burn rate is similar to that in the SURF model proposed by Menikoff. Our burn rate has been calibrated by using pressure profile, material velocities wave forms obtained with embedded particle velocity gauges and run distance to detonation. The comparison between the numerical and experimental results is really good and sufficient to perform a wide variety of simulations including single, double shock waves and the desensitization phenomenon. In conclusion, future works are described.

  20. Optimization of Microemulsion Based Transdermal Gel of Triamcinolone.

    Science.gov (United States)

    Jagdale, Swati; Chaudhari, Bhagyashree

    2017-01-01

    Triamcinolone is a long acting corticosteroid used in the treatment of arthritis, eczema, psoriasis and similar conditions which cause inflammation. Triamcinolone has half-life of 88min. Prolonged oral use is associated with gastrointestinal adverse effects as peptic ulcer, abdominal distention and ulcerative esophagitis as described in various patents. Microemulgel offers advantage of better stability, better loading capacity and controlled release especially for drug with short half life. Objective of the present study was to optimize microemulgel based transdermal delivery of triamcinolone. Saturated solubility of triamcinolone in various oils, surfactants and co-surfactants is estimated. Pseudo-ternary phase diagrams were constructed to determine the region of transparent microemulsion. Microemulsion was evaluated for globule size (FE-SEM, zetasizer), % transmittance, pH, viscosity, conductivity etc. Design of experiment was used to optimize microemulsion based gel. Carbopol 971P and HPMC K100M were used as independent variables. Microemulsion based gel was evaluated for in-vitro as well as ex-vivo parameters. Microemulsion was formulated with oleic acid, lauroglycol FCC and propylene glycol. PDI 0.197 indicated microemulsion is mono-disperse. 32 factorial design gave batch F8 as optimized. Design expert suggested drug release; gel viscosity and bio-adhesive strength were three significant dependant factors affecting the transdermal delivery. F8 showed drug release 92.62.16±1.22% through egg membrane, 95.23±1.44% through goat skin after 8hr and Korsmeyer-Peppas release model was followed. It can be concluded that a stable, effective controlled release transdermal microemulgel was optimised for triamcinolone. This would be a promising tool to deliver triamcinolone with enhanced bioavailability and reduced dosing frequency. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  1. Price-based Optimal Control of Electrical Power Systems

    Energy Technology Data Exchange (ETDEWEB)

    Jokic, A.

    2007-09-10

    The research presented in this thesis is motivated by the following issue of concern for the operation of future power systems: Future power systems will be characterized by significantly increased uncertainties at all time scales and, consequently, their behavior in time will be difficult to predict. In Chapter 2 we will present a novel explicit, dynamic, distributed feedback control scheme that utilizes nodal-prices for real-time optimal power balance and network congestion control. The term explicit means that the controller is not based on solving an optimization problem on-line. Instead, the nodal prices updates are based on simple, explicitly defined and easily comprehensible rules. We prove that the developed control scheme, which acts on the measurements from the current state of the system, always provide the correct nodal prices. In Chapter 3 we will develop a novel, robust, hybrid MPC control (model predictive controller) scheme for power balance control with hard constraints on line power flows and network frequency deviations. The developed MPC controller acts in parallel with the explicit controller from Chapter 2, and its task is to enforce the constraints during the transient periods following suddenly occurring power imbalances in the system. In Chapter 4 the concept of autonomous power networks will be presented as a concise formulation to deal with economic, technical and reliability issues in power systems with a large penetration of distributed generating units. With autonomous power networks as new market entities, we propose a novel operational structure of ancillary service markets. In Chapter 5 we will consider the problem of controlling a general linear time-invariant dynamical system to an economically optimal operating point, which is defined by a multiparametric constrained convex optimization problem related with the steady-state operation of the system. The parameters in the optimization problem are values of the exogenous inputs to

  2. Optimal attacks on qubit-based Quantum Key Recycling

    Science.gov (United States)

    Leermakers, Daan; Škorić, Boris

    2018-03-01

    Quantum Key Recycling (QKR) is a quantum cryptographic primitive that allows one to reuse keys in an unconditionally secure way. By removing the need to repeatedly generate new keys, it improves communication efficiency. Škorić and de Vries recently proposed a QKR scheme based on 8-state encoding (four bases). It does not require quantum computers for encryption/decryption but only single-qubit operations. We provide a missing ingredient in the security analysis of this scheme in the case of noisy channels: accurate upper bounds on the required amount of privacy amplification. We determine optimal attacks against the message and against the key, for 8-state encoding as well as 4-state and 6-state conjugate coding. We provide results in terms of min-entropy loss as well as accessible (Shannon) information. We show that the Shannon entropy analysis for 8-state encoding reduces to the analysis of quantum key distribution, whereas 4-state and 6-state suffer from additional leaks that make them less effective. From the optimal attacks we compute the required amount of privacy amplification and hence the achievable communication rate (useful information per qubit) of qubit-based QKR. Overall, 8-state encoding yields the highest communication rates.

  3. An internet graph model based on trade-off optimization

    Science.gov (United States)

    Alvarez-Hamelin, J. I.; Schabanel, N.

    2004-03-01

    This paper presents a new model for the Internet graph (AS graph) based on the concept of heuristic trade-off optimization, introduced by Fabrikant, Koutsoupias and Papadimitriou in[CITE] to grow a random tree with a heavily tailed degree distribution. We propose here a generalization of this approach to generate a general graph, as a candidate for modeling the Internet. We present the results of our simulations and an analysis of the standard parameters measured in our model, compared with measurements from the physical Internet graph.

  4. Simulation Based Optimization for World Line Card Production System

    Directory of Open Access Journals (Sweden)

    Sinan APAK

    2012-07-01

    Full Text Available Simulation based decision support system is one of the commonly used tool to examine complex production systems. The simulation approach provides process modules which can be adjusted with certain parameters by using data relatively easily obtainable in production process. World Line Card production system simulation is developed to evaluate the optimality of existing production line via using discrete event simulation model with variaty of alternative proposals. The current production system is analysed by a simulation model emphasizing the bottlenecks and the poorly utilized production line. Our analysis identified some improvements and efficient solutions for the existing system.

  5. Optimal model-based sensorless adaptive optics for epifluorescence microscopy.

    Science.gov (United States)

    Pozzi, Paolo; Soloviev, Oleg; Wilding, Dean; Vdovin, Gleb; Verhaegen, Michel

    2018-01-01

    We report on a universal sample-independent sensorless adaptive optics method, based on modal optimization of the second moment of the fluorescence emission from a point-like excitation. Our method employs a sample-independent precalibration, performed only once for the particular system, to establish the direct relation between the image quality and the aberration. The method is potentially applicable to any form of microscopy with epifluorescence detection, including the practically important case of incoherent fluorescence emission from a three dimensional object, through minor hardware modifications. We have applied the technique successfully to a widefield epifluorescence microscope and to a multiaperture confocal microscope.

  6. Utilization-Based Modeling and Optimization for Cognitive Radio Networks

    Science.gov (United States)

    Liu, Yanbing; Huang, Jun; Liu, Zhangxiong

    The cognitive radio technique promises to manage and allocate the scarce radio spectrum in the highly varying and disparate modern environments. This paper considers a cognitive radio scenario composed of two queues for the primary (licensed) users and cognitive (unlicensed) users. According to the Markov process, the system state equations are derived and an optimization model for the system is proposed. Next, the system performance is evaluated by calculations which show the rationality of our system model. Furthermore, discussions among different parameters for the system are presented based on the experimental results.

  7. Morphing-Based Shape Optimization in Computational Fluid Dynamics

    Science.gov (United States)

    Rousseau, Yannick; Men'Shov, Igor; Nakamura, Yoshiaki

    In this paper, a Morphing-based Shape Optimization (MbSO) technique is presented for solving Optimum-Shape Design (OSD) problems in Computational Fluid Dynamics (CFD). The proposed method couples Free-Form Deformation (FFD) and Evolutionary Computation, and, as its name suggests, relies on the morphing of shape and computational domain, rather than direct shape parameterization. Advantages of the FFD approach compared to traditional parameterization are first discussed. Then, examples of shape and grid deformations by FFD are presented. Finally, the MbSO approach is illustrated and applied through an example: the design of an airfoil for a future Mars exploration airplane.

  8. An Improved Teaching-Learning-Based Optimization with the Social Character of PSO for Global Optimization

    Directory of Open Access Journals (Sweden)

    Feng Zou

    2016-01-01

    Full Text Available An improved teaching-learning-based optimization with combining of the social character of PSO (TLBO-PSO, which is considering the teacher’s behavior influence on the students and the mean grade of the class, is proposed in the paper to find the global solutions of function optimization problems. In this method, the teacher phase of TLBO is modified; the new position of the individual is determined by the old position, the mean position, and the best position of current generation. The method overcomes disadvantage that the evolution of the original TLBO might stop when the mean position of students equals the position of the teacher. To decrease the computation cost of the algorithm, the process of removing the duplicate individual in original TLBO is not adopted in the improved algorithm. Moreover, the probability of local convergence of the improved method is decreased by the mutation operator. The effectiveness of the proposed method is tested on some benchmark functions, and the results are competitive with respect to some other methods.

  9. Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

    Science.gov (United States)

    Zhang, Jian; Gan, Yang

    2018-04-01

    The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

  10. A surrogate based multistage-multilevel optimization procedure for multidisciplinary design optimization

    OpenAIRE

    Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.

    2011-01-01

    Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with the general process of satellite system design optimization in conceptual design phase, a multistage-multilevel MDO procedure is proposed in this paper by integrating multiple-discipline-feasible (M...

  11. Study of the cross-reactivity of fish allergens based on a questionnaire and blood testing.

    Science.gov (United States)

    Kobayashi, Yukihiro; Huge, Jiletu; Imamura, Shintaro; Hamada-Sato, Naoko

    2016-07-01

    Parvalbumin and collagen have been identified as cross-reactive allergens for fish allergies. Although doctors realize that various fish elicit allergies, the targets of food allergen labeling laws were only mackerels and salmons in Japan and mackerels in South Korea. This study aimed to reveal the causative species for fish allergy via questionnaires and blood tests. Questionnaire research was conducted in Japan via the internet concerning allergies for fish-allergic patients or their family members. Next, IgE reactivities and cross-reactivities of 26 fish species were analyzed using sera obtained from 16 Japanese patients who were allergic to fish parvalbumin or collagen by enzyme-linked immunosorbent assay (ELISA) and inhibition ELISA. Questionnaire research revealed that 88% patients cannot eat mackerel and salmon in addition to other fish. In addition, 85% respondents were not satisfied with the current food allergen labeling law. In ELISA analyses, we clarified that pooled serum obtained from patients with fish parvalbumin-specific allergies exhibited IgE reactivity to the extracts of most fish species, and pooled serum obtained from patients with fish collagen-specific allergies displayed IgE reactivity to the extracts of all types of fish. Inhibition ELISA experiments revealed cross-reactivities of parvalbumin or collagen to extracts from all fish tested. Most patients with fish allergies displayed allergic symptoms following the intake of various fish species. In addition, fish parvalbumin and collagen were causative factors of fish allergy and were highly cross-reactive fish panallergens. Therefore, current laws should be revised in Japan and South Korea. Copyright © 2016 Japanese Society of Allergology. Production and hosting by Elsevier B.V. All rights reserved.

  12. Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization(in English

    Directory of Open Access Journals (Sweden)

    Shi Chen-guang

    2014-08-01

    Full Text Available A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

  13. Optimizing DNA assembly based on statistical language modelling.

    Science.gov (United States)

    Fang, Gang; Zhang, Shemin; Dong, Yafei

    2017-12-15

    By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Design optimization of PVDF-based piezoelectric energy harvesters

    Directory of Open Access Journals (Sweden)

    Jundong Song

    2017-09-01

    Full Text Available Energy harvesting is a promising technology that powers the electronic devices via scavenging the ambient energy. Piezoelectric energy harvesters have attracted considerable interest for their high conversion efficiency and easy fabrication in minimized sensors and transducers. To improve the output capability of energy harvesters, properties of piezoelectric materials is an influential factor, but the potential of the material is less likely to be fully exploited without an optimized configuration. In this paper, an optimization strategy for PVDF-based cantilever-type energy harvesters is proposed to achieve the highest output power density with the given frequency and acceleration of the vibration source. It is shown that the maximum power output density only depends on the maximum allowable stress of the beam and the working frequency of the device, and these two factors can be obtained by adjusting the geometry of piezoelectric layers. The strategy is validated by coupled finite-element-circuit simulation and a practical device. The fabricated device within a volume of 13.1 mm3 shows an output power of 112.8 μW which is comparable to that of the best-performing piezoceramic-based energy harvesters within the similar volume reported so far.

  15. [Study on the land use optimization based on PPI].

    Science.gov (United States)

    Wu, Xiao-Feng; Li, Ting

    2012-03-01

    Land use type and managing method which is greatly influenced by human activities, is one of the most important factors of non-point pollution. Based on the collection and analysis of non-point pollution control methods and the concept of the three ecological fronts, 9 land use optimized scenarios were designed according to rationality analysis of the current land use situation in the 3 typed small watersheds in Miyun reservoir basin. Take Caojialu watershed for example to analyze and compare the influence to environment of different scenarios based on potential pollution index (PPI) and river section potential pollution index (R-PPI) and the best combination scenario was found. Land use scenario designing and comparison on basis of PPI and R-PPI could help to find the best combination scenario of land use type and managing method, to optimize space distribution and managing methods of land use in basin, to reduce soil erosion and to provide powerful support to formulation of land use planning and pollution control project.

  16. Coherent Network Optimizing of Rail-Based Urban Mass Transit

    Directory of Open Access Journals (Sweden)

    Ying Zhang

    2012-01-01

    Full Text Available An efficient public transport is more than ever a crucial factor when it comes to the quality of life and competitiveness of many cities and regions in Asia. In recent years, the rail-based urban mass transit has been regarded as one of the key means to overcoming the great challenges in Chinese megacities. The purpose of this study is going to develop a coherent network optimizing for rail-based urban mass transit to find the best alternatives for the user and to demonstrate how to meet sustainable development needs and to match the enormous capacity requirements simultaneously. This paper presents an introduction to the current situation of the important lines, and transfer points in the metro system Shanghai. The insufficient aspects are analyzed and evaluated; while the optimizing ideas and measurements are developed and concreted. A group of examples are used to illustrate the approach. The whole study could be used for the latest reference for other megacities which have to be confronted with the similar situations and processes with enormous dynamic travel and transport demands.

  17. Market-Based and System-Wide Fuel Cycle Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, Paul Philip Hood [Univ. of Wisconsin, Madison, WI (United States); Scopatz, Anthony [Univ. of South Carolina, Columbia, SC (United States); Gidden, Matthew [Univ. of Wisconsin, Madison, WI (United States); Carlsen, Robert [Univ. of Wisconsin, Madison, WI (United States); Mouginot, Baptiste [Univ. of Wisconsin, Madison, WI (United States); Flanagan, Robert [Univ. of South Carolina, Columbia, SC (United States)

    2017-06-13

    This work introduces automated optimization into fuel cycle simulations in the Cyclus platform. This includes system-level optimizations, seeking a deployment plan that optimizes the performance over the entire transition, and market-level optimization, seeking an optimal set of material trades at each time step. These concepts were introduced in a way that preserves the flexibility of the Cyclus fuel cycle framework, one of its most important design principles.

  18. Market-Based and System-Wide Fuel Cycle Optimization

    International Nuclear Information System (INIS)

    Wilson, Paul Philip Hood; Scopatz, Anthony; Gidden, Matthew; Carlsen, Robert; Mouginot, Baptiste; Flanagan, Robert

    2017-01-01

    This work introduces automated optimization into fuel cycle simulations in the Cyclus platform. This includes system-level optimizations, seeking a deployment plan that optimizes the performance over the entire transition, and market-level optimization, seeking an optimal set of material trades at each time step. These concepts were introduced in a way that preserves the flexibility of the Cyclus fuel cycle framework, one of its most important design principles.

  19. Development of C-reactive protein certified reference material NMIJ CRM 6201-b: optimization of a hydrolysis process to improve the accuracy of amino acid analysis.

    Science.gov (United States)

    Kato, Megumi; Kinumi, Tomoya; Yoshioka, Mariko; Goto, Mari; Fujii, Shin-Ichiro; Takatsu, Akiko

    2015-04-01

    To standardize C-reactive protein (CRP) assays, the National Metrology Institute of Japan (NMIJ) has developed a C-reactive protein solution certified reference material, CRM 6201-b, which is intended for use as a primary reference material to enable the SI-traceable measurement of CRP. This study describes the development process of CRM 6201-b. As a candidate material of the CRM, recombinant human CRP solution was selected because of its higher purity and homogeneity than the purified material from human serum. Gel filtration chromatography was used to examine the homogeneity and stability of the present CRM. The total protein concentration of CRP in the present CRM was determined by amino acid analysis coupled to isotope-dilution mass spectrometry (IDMS-AAA). To improve the accuracy of IDMS-AAA, we optimized the hydrolysis process by examining the effect of parameters such as the volume of protein samples taken for hydrolysis, the procedure of sample preparation prior to the hydrolysis, hydrolysis temperature, and hydrolysis time. Under optimized conditions, we conducted two independent approaches in which the following independent hydrolysis and liquid chromatography-isotope dilution mass spectrometry (LC-IDMS) were combined: one was vapor-phase acid hydrolysis (130 °C, 24 h) and hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) method, and the other was microwave-assisted liquid-phase acid hydrolysis (150 °C, 3 h) and pre-column derivatization liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. The quantitative values of the two different amino acid analyses were in agreement within their uncertainties. The certified value was the weighted mean of the results of the two methods. Uncertainties from the value-assignment method, between-method variance, homogeneity, long-term stability, and short-term stability were taken into account in evaluating the uncertainty for a certified value. The certified value and the

  20. Stochastic Optimized Relevance Feedback Particle Swarm Optimization for Content Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    Muhammad Imran

    2014-01-01

    Full Text Available One of the major challenges for the CBIR is to bridge the gap between low level features and high level semantics according to the need of the user. To overcome this gap, relevance feedback (RF coupled with support vector machine (SVM has been applied successfully. However, when the feedback sample is small, the performance of the SVM based RF is often poor. To improve the performance of RF, this paper has proposed a new technique, namely, PSO-SVM-RF, which combines SVM based RF with particle swarm optimization (PSO. The aims of this proposed technique are to enhance the performance of SVM based RF and also to minimize the user interaction with the system by minimizing the RF number. The PSO-SVM-RF was tested on the coral photo gallery containing 10908 images. The results obtained from the experiments showed that the proposed PSO-SVM-RF achieved 100% accuracy in 8 feedback iterations for top 10 retrievals and 80% accuracy in 6 iterations for 100 top retrievals. This implies that with PSO-SVM-RF technique high accuracy rate is achieved at a small number of iterations.

  1. Vision-based coaching: optimizing resources for leader development

    Science.gov (United States)

    Passarelli, Angela M.

    2015-01-01

    Leaders develop in the direction of their dreams, not in the direction of their deficits. Yet many coaching interactions intended to promote a leader’s development fail to leverage the benefits of the individual’s personal vision. Drawing on intentional change theory, this article postulates that coaching interactions that emphasize a leader’s personal vision (future aspirations and core identity) evoke a psychophysiological state characterized by positive emotions, cognitive openness, and optimal neurobiological functioning for complex goal pursuit. Vision-based coaching, via this psychophysiological state, generates a host of relational and motivational resources critical to the developmental process. These resources include: formation of a positive coaching relationship, expansion of the leader’s identity, increased vitality, activation of learning goals, and a promotion–orientation. Organizational outcomes as well as limitations to vision-based coaching are discussed. PMID:25926803

  2. Optimal Risk-Based Inspection Planning for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Rangel-Ramirez, Jose G.; Sørensen, John Dalsgaard

    2008-01-01

    , inspection and maintenance activities are developed. This paper considers aspects of inspection and maintenance planning of fatigue prone details in jacket and tripod types of wind turbine support structures. Based oil risk-based inspection planning methods used for oil & gas installations, a framework......Wind turbines for electricity production have increased significantly the last years both in production capability and size. This development is expected to continue also in the coining years. The Support structure for offshore wind turbines is typically a steel structure consisting of a tower...... for optimal inspection and maintenance planning of offshore wind turbines is presented. Special aspects for offshore wind turbines are considered: usually the wind loading are dominating the wave loading, wake effects in wind farms are important and the reliability level is typically significantly lower than...

  3. Optimization of an Image-Based Talking Head System

    Directory of Open Access Journals (Sweden)

    Kang Liu

    2009-01-01

    Full Text Available This paper presents an image-based talking head system, which includes two parts: analysis and synthesis. The audiovisual analysis part creates a face model of a recorded human subject, which is composed of a personalized 3D mask as well as a large database of mouth images and their related information. The synthesis part generates natural looking facial animations from phonetic transcripts of text. A critical issue of the synthesis is the unit selection which selects and concatenates these appropriate mouth images from the database such that they match the spoken words of the talking head. Selection is based on lip synchronization and the similarity of consecutive images. The unit selection is refined in this paper, and Pareto optimization is used to train the unit selection. Experimental results of subjective tests show that most people cannot distinguish our facial animations from real videos.

  4. Vision-based coaching: Optimizing resources for leader development

    Directory of Open Access Journals (Sweden)

    Angela M. Passarelli

    2015-04-01

    Full Text Available Leaders develop in the direction of their dreams, not in the direction of their deficits. Yet many coaching interactions intended to promote a leader’s development fail to leverage the developmental benefits of the individual’s personal vision. Drawing on Intentional Change Theory, this article postulates that coaching interactions that emphasize a leader’s personal vision (future aspirations and core identity evoke a psychophysiological state characterized by positive emotions, cognitive openness, and optimal neurobiological functioning for complex goal pursuit. Vision-based coaching, via this psychophysiological state, generates a host of relational and motivational resources critical to the developmental process. These resources include: formation of a positive coaching relationship, expansion of the leader’s identity, increased vitality, activation of learning goals, and a promotion-orientation. Organizational outcomes as well as limitations to vision-based coaching are discussed.

  5. Model-based dynamic control and optimization of gas networks

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    by a structured sequential quadratic programming algorithm of Newton type. Each open loop problem is specified using a nonlinear prediction model. For each iteration of the quadratic programming procedure, a linear time variant prediction model is formulated. The suggested controller also handles time varying source capacity. Potential problems such as infeasibility and the security of the supply when facing a change in the status of the infrastructure of the transmission system under a transient customer load are treated. Comments on the infeasibility due to errors such as load forecast error, model error and state estimation error are also discussed. A simplified nonlinear model called the creep flow model is used to describe the fluid dynamics inside a natural gas transmission line. Different assumptions and reformulations of this model yield the different control, simulation and optimization models used in this thesis. The control of a single gas transmission line is investigated using linear model predictive control based on instant linearization of the nonlinear model. Model predictive control using a bi quadratic optimization model formulated from the creep flow model is also investigated. A distributed parameter control model of the gas dynamics for a transmission line is formulated. An analytic solution of this model is given with both Neuman boundary conditions and distributed supplies and loads. A transfer function model is developed expressing the dynamics between the defined output and the control and disturbance inputs of the transmission line. Based on the qualitative behaviour observed from the step responses of the solutions of the distributed parameter model formulated in this thesis, simplified transfer function models were developed. These control models expresses the dynamics of a natural gas transmission line with Neuman boundary control and load. Further, these models were used to design a control law, which is a combination of a Smith

  6. Multiobjective clearing of reactive power market in deregulated power systems

    International Nuclear Information System (INIS)

    Rabiee, A.; Shayanfar, H.; Amjady, N.

    2009-01-01

    This paper presents a day-ahead reactive power market which is cleared in the form of multiobjective context. Total payment function (TPF) of generators, representing the payment paid to the generators for their reactive power compensation, is considered as the main objective function of reactive power market. Besides that, voltage security margin, overload index, and also voltage drop index are the other objective functions of the optimal power flow (OPF) problem to clear the reactive power market. A Multiobjective Mathematical Programming (MMP) formulation is implemented to solve the problem of reactive power market clearing using a fuzzy approach to choose the best compromise solution according to the specific preference among various non-dominated (pareto optimal) solutions. The effectiveness of the proposed method is examined based on the IEEE 24-bus reliability test system (IEEE 24-bus RTS). (author)

  7. Microcomputer-based equipment-control and data-acquisition system for fission-reactor reactivity-worth measurements

    International Nuclear Information System (INIS)

    McDowell, W.P.; Bucher, R.G.

    1980-01-01

    Material reactivity-worth measurements are one of the major classes of experiments conducted on the Zero Power research reactors (ZPR) at Argonne National Laboratory. These measurements require the monitoring of the position of a servo control element as a sample material is positioned at various locations in a critical reactor configuration. In order to guarantee operational reliability and increase experimental flexibility for these measurements, the obsolete hardware-based control unit has been replaced with a microcomputer based equipment control and data acquisition system. This system is based on an S-100 bus, dual floppy disk computer with custom built cards to interface with the experimental system. To measure reactivity worths, the system accurately positions samples in the reactor core and acquires data on the position of the servo control element. The data are then analyzed to determine statistical adequacy. The paper covers both the hardware and software aspects of the design

  8. Microcomputer-based equipment-control and data-acquisition system for fission-reactor reactivity-worth measurements

    Energy Technology Data Exchange (ETDEWEB)

    McDowell, W.P.; Bucher, R.G.

    1980-01-01

    Material reactivity-worth measurements are one of the major classes of experiments conducted on the Zero Power research reactors (ZPR) at Argonne National Laboratory. These measurements require the monitoring of the position of a servo control element as a sample material is positioned at various locations in a critical reactor configuration. In order to guarantee operational reliability and increase experimental flexibility for these measurements, the obsolete hardware-based control unit has been replaced with a microcomputer based equipment control and data acquisition system. This system is based on an S-100 bus, dual floppy disk computer with custom built cards to interface with the experimental system. To measure reactivity worths, the system accurately positions samples in the reactor core and acquires data on the position of the servo control element. The data are then analyzed to determine statistical adequacy. The paper covers both the hardware and software aspects of the design.

  9. Impact of fluorine based reactive chemistry on structure and properties of high moment magnetic material

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Xiaoyu, E-mail: xiaoyu.yang@wdc.com; Chen, Lifan; Han, Hongmei; Fu, Lianfeng; Sun, Ming; Liu, Feng; Zhang, Jinqiu [Western Digital Corporation, 44100 Osgood Road, Fremont, California 94539 (United States)

    2014-05-07

    The impact of the fluorine-based reactive ion etch (RIE) process on the structural, electrical, and magnetic properties of NiFe and CoNiFe-plated materials was investigated. Several techniques, including X-ray fluorescence, 4-point-probe, BH looper, transmission electron microscopy (TEM), and electron energy loss spectroscopy (EELS), were utilized to characterize both bulk film properties such as thickness, average composition, Rs, ρ, Bs, Ms, and surface magnetic “dead” layers' properties such as thickness and element concentration. Experimental data showed that the majority of Rs and Bs changes of these bulk films were due to thickness reduction during exposure to the RIE process. ρ and Ms change after taking thickness reduction into account were negligible. The composition of the bulk films, which were not sensitive to surface magnetic dead layers with nano-meter scale, showed minimum change as well. It was found by TEM and EELS analysis that although both before and after RIE there were magnetic dead layers on the top surface of these materials, the thickness and element concentration of the layers were quite different. Prior to RIE, dead layer was actually native oxidation layers (about 2 nm thick), while after RIE dead layer consisted of two sub-layers that were about 6 nm thick in total. Sub-layer on the top was native oxidation layer, while the bottom layer was RIE “damaged” layer with very high fluorine concentration. Two in-situ RIE approaches were also proposed and tested to remove such damaged sub-layers.

  10. Optimization of modal filters based on arrays of piezoelectric sensors

    International Nuclear Information System (INIS)

    Pagani, Carlos C Jr; Trindade, Marcelo A

    2009-01-01

    Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25–50%

  11. Quaternion error-based optimal control applied to pinpoint landing

    Science.gov (United States)

    Ghiglino, Pablo

    Accurate control techniques for pinpoint planetary landing - i.e., the goal of achieving landing errors in the order of 100m for unmanned missions - is a complex problem that have been tackled in different ways in the available literature. Among other challenges, this kind of control is also affected by the well known trade-off in UAV control that for complex underlying models the control is sub-optimal, while optimal control is applied to simplifed models. The goal of this research has been the development new control algorithms that would be able to tackle these challenges and the result are two novel optimal control algorithms namely: OQTAL and HEX2OQTAL. These controllers share three key properties that are thoroughly proven and shown in this thesis; stability, accuracy and adaptability. Stability is rigorously demonstrated for both controllers. Accuracy is shown in results of comparing these novel controllers with other industry standard algorithms in several different scenarios: there is a gain in accuracy of at least 15% for each controller, and in many cases much more than that. A new tuning algorithm based on swarm heuristics optimisation was developed as well as part of this research in order to tune in an online manner the standard Proportional-Integral-Derivative (PID) controllers used for benchmarking. Finally, adaptability of these controllers can be seen as a combination of four elements: mathematical model extensibility, cost matrices tuning, reduced computation time required and finally no prior knowledge of the navigation or guidance strategies needed. Further simulations in real planetary landing trajectories has shown that these controllers have the capacity of achieving landing errors in the order of pinpoint landing requirements, making them not only very precise UAV controllers, but also potential candidates for pinpoint landing unmanned missions.

  12. Topological Optimization of Continuum Structure based on ANSYS

    Directory of Open Access Journals (Sweden)

    Li Xue-ping

    2017-01-01

    Full Text Available Topology optimization is at the phase of structural concept design and the result of it is foundation for succeeding design, therefore, structural topology optimization is more important to engineering design. in this thesis, in order to seek the optimal structure shape of the winch’s mounting bracket of ROV simulator, topology optimization design of it by finite element analysis software ANSYS was carried out. the results show that the topology optimization method is an effective optimization method and indicate that the method is correct and effective, it has a certain engineering application prospect.

  13. Warehouse stocking optimization based on dynamic ant colony genetic algorithm

    Science.gov (United States)

    Xiao, Xiaoxu

    2018-04-01

    In view of the various orders of FAW (First Automotive Works) International Logistics Co., Ltd., the SLP method is used to optimize the layout of the warehousing units in the enterprise, thus the warehouse logistics is optimized and the external processing speed of the order is improved. In addition, the relevant intelligent algorithms for optimizing the stocking route problem are analyzed. The ant colony algorithm and genetic algorithm which have good applicability are emphatically studied. The parameters of ant colony algorithm are optimized by genetic algorithm, which improves the performance of ant colony algorithm. A typical path optimization problem model is taken as an example to prove the effectiveness of parameter optimization.

  14. Optimization-Based Approaches to Control of Probabilistic Boolean Networks

    Directory of Open Access Journals (Sweden)

    Koichi Kobayashi

    2017-02-01

    Full Text Available Control of gene regulatory networks is one of the fundamental topics in systems biology. In the last decade, control theory of Boolean networks (BNs, which is well known as a model of gene regulatory networks, has been widely studied. In this review paper, our previously proposed methods on optimal control of probabilistic Boolean networks (PBNs are introduced. First, the outline of PBNs is explained. Next, an optimal control method using polynomial optimization is explained. The finite-time optimal control problem is reduced to a polynomial optimization problem. Furthermore, another finite-time optimal control problem, which can be reduced to an integer programming problem, is also explained.

  15. Consensus-based Distributed Control for Accurate Reactive, Harmonic and Imbalance Power Sharing in Microgrids

    DEFF Research Database (Denmark)

    Zhou, Jianguo; Kim, Sunghyok; Zhang, Huaguang

    2018-01-01

    This paper investigates the issue of accurate reactive, harmonic and imbalance power sharing in a microgrid. Harmonic and imbalance droop controllers are developed to proportionally share the harmonic power and the imbalance power among distributed generation (DG) units and improve the voltage...... voltage. With the proposed methods, the microgrid system reliability and flexibility can be enhanced and the knowledge of the line impedance is not required. And the reactive, harmonic and imbalance power can be proportionally shared among the DG units. Moreover, the quality of the voltage at PCC can...

  16. SO{sub 2} retention by reactivated CaO-based sorbent from multiple CO{sub 2} capture cycles

    Energy Technology Data Exchange (ETDEWEB)

    Vasilije Manovic; Edward J. Anthony [CANMET Energy Technology Centre-Ottawa, Ottawa, ON (Canada). Natural Resources Canada

    2007-06-15

    This paper examines the reactivation of spent sorbent, produced from multiple CO{sub 2} capture cycles, for use in SO{sub 2} capture. CaO-based sorbent samples were obtained from Kelly Rock limestone using three particle size ranges, each containing different impurities levels. Using a thermogravimetric analyzer (TGA), the sulfation behavior of partially sulfated and unsulfated samples obtained after multiple calcination-carbonation cycles in a tube furnace (TF), following steam reactivation in a pressurized reactor, is examined. In addition, samples calcined/sintered under different conditions after hydration are also examined. The results show that suitably treated spent sorbent has better sulfation characteristics than that of the original sorbent. Thus for example, after 2 h sulfation, {gt} 80% of the CaO was sulfated. In addition, the sorbent showed significant activity even after 4 h when {gt} 95% CaO was sulfated. The results were confirmed by X-ray diffraction (XRD) analysis, which showed that, by the end of the sulfation process, samples contained CaSO{sub 4} with only traces of unreacted CaO. The superior behavior of spent reactivated sorbent appears to be due to swelling of the sorbent particles during steam hydration. The surface area morphology of sorbent after reactivation was examined by scanning electron microscopy (SEM). Ca(OH){sub 2} crystals were seen, which displayed their regular shape, and their elemental composition was confirmed by energy-dispersive X-ray (EDX) analysis. These results allow the proposal of a new process for the use of CaO-based sorbent in fluidized bed combustion (FBC) systems, which incorporates CO{sub 2} capture, sorbent reactivation, and SO{sub 2} retention. 26 refs., 4 figs., 2 tabs.

  17. Development of a Theory-Based Intervention to Increase Clinical Measurement of Reactive Balance in Adults at Risk of Falls.

    Science.gov (United States)

    Sibley, Kathryn M; Brooks, Dina; Gardner, Paula; Janaudis-Ferreira, Tania; McGlynn, Mandy; OʼHoski, Sachi; McEwen, Sara; Salbach, Nancy M; Shaffer, Jennifer; Shing, Paula; Straus, Sharon E; Jaglal, Susan B

    2016-04-01

    Effective balance reactions are essential for avoiding falls, but are not regularly measured by physical therapists. Physical therapists report wanting to improve reactive balance assessment, and theory-based approaches are recommended as the foundation for the development of interventions. This article describes how a behavior change theory for health care providers, the theoretical domains framework (TDF), was used to develop an intervention to increase reactive balance measurement among physical therapists who work in rehabilitation settings and treat adults who are at risk of falls. We employed published recommendations for using the TDF-guided intervention development. We identified what health care provider behavior is in need of change, relevant barriers and facilitators, strategies to address them, and how we would measure behavior change. In this case, identifying strategies required selecting both a reactive balance measure and behavior change techniques. Previous research had determined that physical therapists need to increase reactive balance measurement, and identified barriers and facilitators that corresponded to 8 TDF domains. A published review informed the selection of the Balance Evaluation Systems Test (Reactive Postural Responses Section) as addressing the barriers and facilitators, and existing research informed the selection of 9 established behavior change techniques corresponding to each identified TDF domain. The TDF framework were incorporated into a 12-month intervention with interactive group sessions, local champions, and health record modifications. Intervention effect can be evaluated using health record abstraction, questionnaires, and qualitative semistructured interviews. Although future research will evaluate the intervention in a controlled study, the process of theory-based intervention development can be applied to other rehabilitation research contexts, maximizing the impact of this work.Video Abstract is available for more

  18. Robust sawtooth period control based on adaptive online optimization

    International Nuclear Information System (INIS)

    Bolder, J.J.; Witvoet, G.; De Baar, M.R.; Steinbuch, M.; Van de Wouw, N.; Haring, M.A.M.; Westerhof, E.; Doelman, N.J.

    2012-01-01

    The systematic design of a robust adaptive control strategy for the sawtooth period using electron cyclotron current drive (ECCD) is presented. Recent developments in extremum seeking control (ESC) are employed to derive an optimized controller structure and offer practical tuning guidelines for its parameters. In this technique a cost function in terms of the desired sawtooth period is optimized online by changing the ECCD deposition location based on online estimations of the gradient of the cost function. The controller design does not require a detailed model of the sawtooth instability. Therefore, the proposed ESC is widely applicable to any sawtoothing plasma or plasma simulation and is inherently robust against uncertainties or plasma variations. Moreover, it can handle a broad class of disturbances. This is demonstrated by time-domain simulations, which show successful tracking of time-varying sawtooth period references throughout the whole operating space, even in the presence of variations in plasma parameters, disturbances and slow launcher mirror dynamics. Due to its simplicity and robustness the proposed ESC is a valuable sawtooth control candidate for any experimental tokamak plasma, and may even be applicable to other fusion-related control problems. (paper)

  19. Vanpool trip planning based on evolutionary multiple objective optimization

    Science.gov (United States)

    Zhao, Ming; Yang, Disheng; Feng, Shibing; Liu, Hengchang

    2017-08-01

    Carpool and vanpool draw a lot of researchers’ attention, which is the emphasis of this paper. A concrete vanpool operation definition is given, based on the given definition, this paper tackles vanpool operation optimization using user experience decline index(UEDI). This paper is focused on making each user having identical UEDI and the system having minimum sum of all users’ UEDI. Three contributions are made, the first contribution is a vanpool operation scheme diagram, each component of the scheme is explained in detail. The second contribution is getting all customer’s UEDI as a set, standard deviation and sum of all users’ UEDI set are used as objectives in multiple objective optimization to decide trip start address, trip start time and trip destination address. The third contribution is a trip planning algorithm, which tries to minimize the sum of all users’ UEDI. Geographical distribution of the charging stations and utilization rate of the charging stations are considered in the trip planning process.

  20. Bifurcation-based approach reveals synergism and optimal combinatorial perturbation.

    Science.gov (United States)

    Liu, Yanwei; Li, Shanshan; Liu, Zengrong; Wang, Ruiqi

    2016-06-01

    Cells accomplish the process of fate decisions and form terminal lineages through a series of binary choices in which cells switch stable states from one branch to another as the interacting strengths of regulatory factors continuously vary. Various combinatorial effects may occur because almost all regulatory processes are managed in a combinatorial fashion. Combinatorial regulation is crucial for cell fate decisions because it may effectively integrate many different signaling pathways to meet the higher regulation demand during cell development. However, whether the contribution of combinatorial regulation to the state transition is better than that of a single one and if so, what the optimal combination strategy is, seem to be significant issue from the point of view of both biology and mathematics. Using the approaches of combinatorial perturbations and bifurcation analysis, we provide a general framework for the quantitative analysis of synergism in molecular networks. Different from the known methods, the bifurcation-based approach depends only on stable state responses to stimuli because the state transition induced by combinatorial perturbations occurs between stable states. More importantly, an optimal combinatorial perturbation strategy can be determined by investigating the relationship between the bifurcation curve of a synergistic perturbation pair and the level set of a specific objective function. The approach is applied to two models, i.e., a theoretical multistable decision model and a biologically realistic CREB model, to show its validity, although the approach holds for a general class of biological systems.

  1. Optimal Sizing and Placement of Battery Energy Storage in Distribution System Based on Solar Size for Voltage Regulation

    Energy Technology Data Exchange (ETDEWEB)

    Nazaripouya, Hamidreza [Univ. of California, Los Angeles, CA (United States); Wang, Yubo [Univ. of California, Los Angeles, CA (United States); Chu, Peter [Univ. of California, Los Angeles, CA (United States); Pota, Hemanshu R. [Univ. of California, Los Angeles, CA (United States); Gadh, Rajit [Univ. of California, Los Angeles, CA (United States)

    2016-07-26

    This paper proposes a new strategy to achieve voltage regulation in distributed power systems in the presence of solar energy sources and battery storage systems. The goal is to find the minimum size of battery storage and its corresponding location in the network based on the size and place of the integrated solar generation. The proposed method formulates the problem by employing the network impedance matrix to obtain an analytical solution instead of using a recursive algorithm such as power flow. The required modifications for modeling the slack and PV buses (generator buses) are utilized to increase the accuracy of the approach. The use of reactive power control to regulate the voltage regulation is not always an optimal solution as in distribution systems R/X is large. In this paper the minimum size and the best place of battery storage is achieved by optimizing the amount of both active and reactive power exchanged by battery storage and its gridtie inverter (GTI) based on the network topology and R/X ratios in the distribution system. Simulation results for the IEEE 14-bus system verify the effectiveness of the proposed approach.

  2. Winery by-products: extraction optimization, phenolic composition and cytotoxic evaluation to act as a new source of scavenging of reactive oxygen species.

    Science.gov (United States)

    Melo, Priscilla Siqueira; Massarioli, Adna Prado; Denny, Carina; dos Santos, Luciana Ferracini; Franchin, Marcelo; Pereira, Giuliano Elias; Vieira, Thais Maria Ferreira de Souza; Rosalen, Pedro Luiz; de Alencar, Severino Matias

    2015-08-15

    Nearly 20 million tons of winery by-products, with many biological activities, are discarded each year in the world. The extraction of bioactive compounds from Chenin Blanc, Petit Verdot, and Syrah grape by-products, produced in the semi-arid region in Brazil, was optimized by a Central Composite Rotatable Design. The phenolic compounds profile, antioxidant capacity against synthetic free radicals (DPPH and ABTS), reactive oxygen species (ROS; peroxyl radical, superoxide radical, hypochlorous acid), cytotoxicity assay (MTT) and quantification of TNF-α production in RAW 264.7 cells were conducted. Gallic acid, syringic acid, procyanidins B1 and B2, catechin, epicatechin, epicatechin gallate, quercetin 3-β-d-glucoside, delfinidin 3-glucoside, peonidin 3-O-glucoside, and malvidin 3-glucoside were the main phenolic compounds identified. In general, rachis showed higher antioxidant capacity than pomace extract, especially for Chenin Blanc. All extracts showed low cytotoxicity against RAW 264.7 cells and Petit Verdot pomace suppressed TNF-α liberation in vitro. Therefore, these winery by-products can be considered good sources of bioactive compounds, with great potential for application in the food and pharmaceutical industries. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Copper electrowinning in a moving-bed cell based on reactive electrodialysis

    Directory of Open Access Journals (Sweden)

    Cifuentes, L.

    2008-04-01

    Full Text Available A two-compartment lab-scale reactive electrodialysis (RED cell with a moving particulate cathode has been used for copper electrowinning. The cathodic reaction was copper electrodeposition on a bed of copper particles forced to circulate inside a fixed cylindrical enclosure by the action of rotating paddles; the anodic reaction was ferrous to ferric ion oxidation on an anode made of static graphite bars. The anolyte (aqueous FeSO4 + H2SO4 and catholyte (aqueous CuSO4 + H2SO4 are kept separate by an anion membrane which prevents cation transport between the electrolytes. Experiments were carried out in order to characterize cell performance under various conditions. When operating with 40 g/L Cu (II, I = 6 A, T = 50°C, 40 rpm paddle rotation and 990 mL/min electrolyte recirculation flowrate, the specific energy consumption (SEC for copper electrowinning was 2.25 kWh/kg. An optimization of cell dimensions gave an improved SEC of 1.55 kWh/kg whereas a temperature increase from 50 to 56°C (without changing cell dimensions produced a SEC of 1.50 kWh/kg, which is 25% lower than normal values for conventional copper electrowinning cells. A comparison was drawn between the performance of this cell and a squirrel-cage cell previously developed by the authors.

    Una celda a escala laboratorio de electrodiálisis reactiva (EDR, de dos compartimientos con cátodo particulado móvil, se ha utilizado para electroobtener cobre. La reacción catódica fue la electrodeposición de cobre sobre un lecho de partículas de cobre que circulan dentro de un cilindro fijo por la acción de paletas rotatorias; la reacción anódica fue la oxidación de ión ferroso a ión férrico sobre un ánodo hecho de barras de grafito estáticas. El anolito (FeSO4 + H2SO4 acuoso y el catolito (CuSO4 + H2SO4 acuoso se mantienen separados por una

  4. Solution of optimal power flow using evolutionary-based algorithms

    African Journals Online (AJOL)

    It aims to estimate the optimal settings of real generator output power, bus voltage, ...... Lansey, K. E., 2003, Optimization of water distribution network design using ... Pandit, M., 2016, Economic load dispatch of wind-solar-thermal system using ...

  5. Binary cuckoo search based optimal PMU placement scheme for ...

    African Journals Online (AJOL)

    without including zero-injection effect, an Optimal PMU Placement strategy considering ..... in Indian power grid — A case study, Frontiers in Energy, Vol. ... optimization approach, Proceedings: International Conference on Intelligent Systems ...

  6. MVMO-based approach for optimal placement and tuning of ...

    African Journals Online (AJOL)

    bus (New England) test system. Numerical results include performance comparisons with other metaheuristic optimization techniques, namely, comprehensive learning particle swarm optimization (CLPSO), genetic algorithm with multi-parent ...

  7. Power control based on particle swarm optimization of grid-connected inverter for hybrid renewable energy system

    International Nuclear Information System (INIS)

    García-Triviño, Pablo; Gil-Mena, Antonio José; Llorens-Iborra, Francisco; García-Vázquez, Carlos Andrés; Fernández-Ramírez, Luis M.; Jurado, Francisco

    2015-01-01

    Highlights: • Three PSO-based PI controllers for a grid-connected inverter were presented. • Two online PSO-based PI controllers were compared with an offline PSO-tuned PI. • The HRES and the inverter were evaluated under power changes and grid voltage sags. • Online ITAE-based PSO reduced ITAE (current THD) by 15.24% (5.32%) versus offline one. - Abstract: This paper is focused on the study of particle swarm optimization (PSO)-based PI controllers for the power control of a grid-connected inverter supplied from a hybrid renewable energy system. It is composed of two renewable energy sources (wind turbine and photovoltaic – PV – solar panels) and two energy storage systems (battery and hydrogen system, integrated by fuel cell and electrolyzer). Three PSO-based PI controllers are implemented: (1) conventional PI controller with offline tuning by PSO algorithm based on the integral time absolute error (ITAE) index; (2) PI controllers with online self-tuning by PSO algorithm based on the error; and (3) PI controllers with online self-tuning by PSO algorithm based on the ITAE index. To evaluate and compare the three controllers, the hybrid renewable energy system and the grid-connected inverter are simulated under changes in the active and reactive power values, as well as under a grid voltage sag. The results show that the online PSO-based PI controllers that optimize the ITAE index achieves the best response

  8. Dynamic Reactive Power Control in Offshore HVDC Connected Wind Power Plants

    DEFF Research Database (Denmark)

    Sakamuri, Jayachandra N.; Cutululis, Nicolaos Antonio; Rather, Zakir Hussain

    2016-01-01

    This paper presents a coordinated reactive power control for a HVDC connected cluster of offshore wind power plants (WPPs). The reactive power reference for the WPP cluster is estimated by an optimization algorithm aiming at minimum active power losses in the offshore AC Grid. For each optimal......, such as wind turbine (WT) terminal, collector cable, and export cable, on the dynamic voltage profile of the offshore grid is investigated. Furthermore, the dynamic reactive power contribution from WTs from different WPPs of the cluster for such faults has also been studied....... reactive power set point, the OWPP cluster controller generates reactive power references for each WPP which further sends the AC voltage/ reactive power references to the associated WTs based on their available reactive power margin. The impact of faults at different locations in the offshore grid...

  9. Towards a Reactive Power Oscillation Damping Controller for Wind Power Plant Based on Full Converter Wind Turbines

    DEFF Research Database (Denmark)

    Knüppel, Thyge; Kumar, Sathess; Thuring, Patrik

    2012-01-01

    In this paper a power oscillation damping controller (POD) based on modulation of reactive power (Q POD) is analyzed where the modular and distributed characteristics of the wind power plant (WPP) are considered. For a Q POD it is essential that the phase of the modulated output is tightly...... contributes to a collective response. This ability is shown with a 150 wind turbine (WT) WPP with all WTs represented, and it is demonstrated that the WPP contributes to the inter-area damping. The work is based on a nonlinear, dynamic model of the 3.6 MW Siemens Wind Power WT....... controlled to achieve a positive damping contribution. It is investigated how a park level voltage, reactive power, and power factor control at different grid strengths interact with the Q POD in terms of a resulting phase shift. A WPP is modular and distributed and a WPP Q POD necessitate that each WT...

  10. Calculations of reactivity based in the solution of the Neutron transport equation in X Y geometry and Lineal perturbation theory

    International Nuclear Information System (INIS)

    Valle G, E. del; Mugica R, C.A.

    2005-01-01

    In our country, in last congresses, Gomez et al carried out reactivity calculations based on the solution of the diffusion equation for an energy group using nodal methods in one dimension and the TPL approach (Lineal Perturbation Theory). Later on, Mugica extended the application to the case of multigroup so much so much in one as in two dimensions (X Y geometry) with excellent results. Presently work is carried out similar calculations but this time based on the solution of the neutron transport equation in X Y geometry using nodal methods and again the TPL approximation. The idea is to provide a calculation method that allows to obtain in quick form the reactivity solving the direct problem as well as the enclosed problem of the not perturbed problem. A test problem for the one that results are provided for the effective multiplication factor is described and its are offered some conclusions. (Author)

  11. Optimizing Maintenance of Constraint-Based Database Caches

    Science.gov (United States)

    Klein, Joachim; Braun, Susanne

    Caching data reduces user-perceived latency and often enhances availability in case of server crashes or network failures. DB caching aims at local processing of declarative queries in a DBMS-managed cache close to the application. Query evaluation must produce the same results as if done at the remote database backend, which implies that all data records needed to process such a query must be present and controlled by the cache, i. e., to achieve “predicate-specific” loading and unloading of such record sets. Hence, cache maintenance must be based on cache constraints such that “predicate completeness” of the caching units currently present can be guaranteed at any point in time. We explore how cache groups can be maintained to provide the data currently needed. Moreover, we design and optimize loading and unloading algorithms for sets of records keeping the caching units complete, before we empirically identify the costs involved in cache maintenance.

  12. Density-based penalty parameter optimization on C-SVM.

    Science.gov (United States)

    Liu, Yun; Lian, Jie; Bartolacci, Michael R; Zeng, Qing-An

    2014-01-01

    The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system's outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall.

  13. SVM-based glioma grading. Optimization by feature reduction analysis

    International Nuclear Information System (INIS)

    Zoellner, Frank G.; Schad, Lothar R.; Emblem, Kyrre E.; Harvard Medical School, Boston, MA; Oslo Univ. Hospital

    2012-01-01

    We investigated the predictive power of feature reduction analysis approaches in support vector machine (SVM)-based classification of glioma grade. In 101 untreated glioma patients, three analytic approaches were evaluated to derive an optimal reduction in features; (i) Pearson's correlation coefficients (PCC), (ii) principal component analysis (PCA) and (iii) independent component analysis (ICA). Tumor grading was performed using a previously reported SVM approach including whole-tumor cerebral blood volume (CBV) histograms and patient age. Best classification accuracy was found using PCA at 85% (sensitivity = 89%, specificity = 84%) when reducing the feature vector from 101 (100-bins rCBV histogram + age) to 3 principal components. In comparison, classification accuracy by PCC was 82% (89%, 77%, 2 dimensions) and 79% by ICA (87%, 75%, 9 dimensions). For improved speed (up to 30%) and simplicity, feature reduction by all three methods provided similar classification accuracy to literature values (∝87%) while reducing the number of features by up to 98%. (orig.)

  14. Multilevel Thresholding Segmentation Based on Harmony Search Optimization

    Directory of Open Access Journals (Sweden)

    Diego Oliva

    2013-01-01

    Full Text Available In this paper, a multilevel thresholding (MT algorithm based on the harmony search algorithm (HSA is introduced. HSA is an evolutionary method which is inspired in musicians improvising new harmonies while playing. Different to other evolutionary algorithms, HSA exhibits interesting search capabilities still keeping a low computational overhead. The proposed algorithm encodes random samples from a feasible search space inside the image histogram as candidate solutions, whereas their quality is evaluated considering the objective functions that are employed by the Otsu’s or Kapur’s methods. Guided by these objective values, the set of candidate solutions are evolved through the HSA operators until an optimal solution is found. Experimental results demonstrate the high performance of the proposed method for the segmentation of digital images.

  15. Optimization of arterial age prediction models based in pulse wave

    Energy Technology Data Exchange (ETDEWEB)

    Scandurra, A G [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Meschino, G J [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Passoni, L I [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Dai Pra, A L [Engineering Aplied Artificial Intelligence Group, Mathematics Department, Mar del Plata University (Argentina); Introzzi, A R [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Clara, F M [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina)

    2007-11-15

    We propose the detection of early arterial ageing through a prediction model of arterial age based in the coherence assumption between the pulse wave morphology and the patient's chronological age. Whereas we evaluate several methods, a Sugeno fuzzy inference system is selected. Models optimization is approached using hybrid methods: parameter adaptation with Artificial Neural Networks and Genetic Algorithms. Features selection was performed according with their projection on main factors of the Principal Components Analysis. The model performance was tested using the bootstrap error type .632E. The model presented an error smaller than 8.5%. This result encourages including this process as a diagnosis module into the device for pulse analysis that has been developed by the Bioengineering Laboratory staff.

  16. Efficacy of Code Optimization on Cache-Based Processors

    Science.gov (United States)

    VanderWijngaart, Rob F.; Saphir, William C.; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    In this paper a number of techniques for improving the cache performance of a representative piece of numerical software is presented. Target machines are popular processors from several vendors: MIPS R5000 (SGI Indy), MIPS R8000 (SGI PowerChallenge), MIPS R10000 (SGI Origin), DEC Alpha EV4 + EV5 (Cray T3D & T3E), IBM RS6000 (SP Wide-node), Intel PentiumPro (Ames' Whitney), Sun UltraSparc (NERSC's NOW). The optimizations all attempt to increase the locality of memory accesses. But they meet with rather varied and often counterintuitive success on the different computing platforms. We conclude that it may be genuinely impossible to obtain portable performance on the current generation of cache-based machines. At the least, it appears that the performance of modern commodity processors cannot be described with parameters defining the cache alone.

  17. Optimization-based particle filter for state and parameter estimation

    Institute of Scientific and Technical Information of China (English)

    Li Fu; Qi Fei; Shi Guangming; Zhang Li

    2009-01-01

    In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

  18. Regularized Regression and Density Estimation based on Optimal Transport

    KAUST Repository

    Burger, M.

    2012-03-11

    The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).

  19. Optimization of arterial age prediction models based in pulse wave

    International Nuclear Information System (INIS)

    Scandurra, A G; Meschino, G J; Passoni, L I; Dai Pra, A L; Introzzi, A R; Clara, F M

    2007-01-01

    We propose the detection of early arterial ageing through a prediction model of arterial age based in the coherence assumption between the pulse wave morphology and the patient's chronological age. Whereas we evaluate several methods, a Sugeno fuzzy inference system is selected. Models optimization is approached using hybrid methods: parameter adaptation with Artificial Neural Networks and Genetic Algorithms. Features selection was performed according with their projection on main factors of the Principal Components Analysis. The model performance was tested using the bootstrap error type .632E. The model presented an error smaller than 8.5%. This result encourages including this process as a diagnosis module into the device for pulse analysis that has been developed by the Bioengineering Laboratory staff

  20. Optimizing Human Diet Problem Based on Price and Taste Using

    Directory of Open Access Journals (Sweden)

    Hossein EGHBALI

    2012-07-01

    Full Text Available Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Due to price fluctuations and taste diversity, these two factors cannot be certainly and determinately evaluated. This problem must be viewed from another perspective because of the uncertainty about the amount of nutrients per unit of foods and also diversity of people’s daily needs to receive them.This paper discusses human diet problem in fuzzy environment. The approach deals with multi-objective fuzzy linear programming problem using a fuzzy programming technique for its solution. By prescribing a diet merely based on crisp data, some ofthe realities are neglected. For the same reason, we dealt with human diet problem through fuzzy approach. Results indicated uncertainty about factors of nutrition diet -including taste and price, amount of nutrients and their intake- would affect diet quality, making the proposed diet more realistic.

  1. Oracle-based online robust optimization via online learning

    NARCIS (Netherlands)

    Ben-Tal, A.; Hazan, E.; Koren, T.; Shie, M.

    2015-01-01

    Robust optimization is a common optimization framework under uncertainty when problem parameters are unknown, but it is known that they belong to some given uncertainty set. In the robust optimization framework, a min-max problem is solved wherein a solution is evaluated according to its performance

  2. C-reactive protein, insulin resistance and risk of cardiovascular disease: a population-based study

    DEFF Research Database (Denmark)

    Hansen, T.W.; Olsen, M.H.; Rasmussen, S.

    2008-01-01

    BACKGROUND: C-reactive protein (CRP), a marker of inflammation, and insulin resistance (IR), a metabolic disorder, are closely related. CRP and IR have both been identified as significant risk factors of cardiovascular disease (CVD) after adjustment for conventional CVD risk factors...

  3. Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment

    Czech Academy of Sciences Publication Activity Database

    Krejsa, Jiří; Věchet, S.; Ripel, T.

    2013-01-01

    Roč. 198, č. 2013 (2013), s. 108-113 ISSN 1012-0394 Institutional research plan: CEZ:AV0Z20760514 Institutional support: RVO:61388998 Keywords : mobile robot * reactive navigation * artificial neural networks Subject RIV: JD - Computer Applications, Robotics

  4. Model-Based Requirements Analysis for Reactive Systems with UML Sequence Diagrams and Coloured Petri Nets

    DEFF Research Database (Denmark)

    Tjell, Simon; Lassen, Kristian Bisgaard

    2008-01-01

    In this paper, we describe a formal foundation for a specialized approach to automatically checking traces against real-time requirements. The traces are obtained from simulation of Coloured Petri Net (CPN) models of reactive systems. The real-time requirements are expressed in terms of a derivat...

  5. Study of the cross-reactivity of fish allergens based on a questionnaire and blood testing

    Directory of Open Access Journals (Sweden)

    Yukihiro Kobayashi

    2016-07-01

    Conclusions: Most patients with fish allergies displayed allergic symptoms following the intake of various fish species. In addition, fish parvalbumin and collagen were causative factors of fish allergy and were highly cross-reactive fish panallergens. Therefore, current laws should be revised in Japan and South Korea.

  6. Optimization of conditions for gene delivery system based on PEI

    Directory of Open Access Journals (Sweden)

    Roya Cheraghi

    2017-01-01

    Full Text Available Objective(s: PEI based nanoparticle (NP due to dual capabilities of proton sponge and DNA binding is known as powerful tool for nucleic acid delivery to cells. However, serious cytotoxicity and complicated conditions, which govern NPs properties and its interactions with cells practically, hindered achievement to high transfection efficiency. Here, we have tried to optimize the properties of PEI/ firefly luciferase plasmid complexes and cellular condition to improve transfection efficiency. Materials and Methods: For this purpose, firefly luciferase, as a robust gene reporter, was complexed with PEI to prepare NPs with different size and charge. The physicochemical properties of nanoparticles were evaluated using agarose gel retardation and dynamic light scattering.  MCF7 and BT474 cells at different confluency were also transfected with prepared nanoparticles at various concentrations for short and long times. Results: The branched PEI can instantaneously bind to DNA and form cationic NPs. The results demonstrated the production of nanoparticles with size about 100-500 nm dependent on N/P ratio. Moreover, increase of nanoparticles concentration on the cell surface drastically improved the transfection rate, so at a concentration of 30 ng/ìl, the highest transfection efficiency was achieved. On the other side, at confluency between 40-60%, the maximum efficiency was obtained. The result demonstrated that N/P ratio of 12 could establish an optimized ratio between transfection efficiency and cytotoxicity of PEI/plasmid nanoparticles. The increase of NPs N/P ratio led to significant cytotoxicity. Conclusion: Obtained results verified the optimum conditions for PEI based gene delivery in different cell lines.

  7. Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

    Science.gov (United States)

    Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

    2017-04-01

    In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

  8. An Integral Model to Provide Reactive and Proactive Services in an Academic CSIRT Based on Business Intelligence

    OpenAIRE

    Walter Fuertes; Francisco Reyes; Paúl Valladares; Freddy Tapia; Theofilos Toulkeridis; Ernesto Pérez

    2017-01-01

    Cyber-attacks have increased in severity and complexity. That requires, that the CERT/CSIRT research and develops new security tools. Therefore, our study focuses on the design of an integral model based on Business Intelligence (BI), which provides reactive and proactive services in a CSIRT, in order to alert and reduce any suspicious or malicious activity on information systems and data networks. To achieve this purpose, a solution has been assembled, that generates information stores, bein...

  9. Effects of Video-Based Visual Training on Decision-Making and Reactive Agility in Adolescent Football Players

    Directory of Open Access Journals (Sweden)

    Alfred Nimmerichter

    2015-12-01

    Full Text Available This study investigated the trainability of decision-making and reactive agility via video-based visual training in young athletes. Thirty-four members of a national football academy (age: 14.4 ± 0.1 years were randomly assigned to a training (VIS; n = 18 or a control group (CON; n = 16. In addition to the football training, the VIS completed a video-based visual training twice a week over a period of six weeks during the competition phase. Using the temporal occlusion technique, the players were instructed to react on one-on-one situations shown in 40 videos. The number of successful decisions and the response time were measured with a video-based test. In addition, the reactive-agility sprint test was used. VIS significantly improved the number of successful decisions (22.2 ± 3.6 s vs. 29.8 ± 4.5 s; p < 0.001, response time (0.41 ± 0.10 s vs. 0.31 ± 0.10 s; p = 0.006 and reactive agility (2.22 ± 0.33 s vs. 1.94 ± 0.11 s; p = 0.001 pre- vs. post-training. No significant differences were found for CON. The results have shown that video-based visual training improves the time to make decisions as well as reactive agility sprint-time, accompanied by an increase in successful decisions. It remains to be shown whether or not such training can improve simulated or actual game performance.

  10. Optimization of a nanotechnology based antimicrobial platform for food safety applications using Engineered Water Nanostructures (EWNS)

    Science.gov (United States)

    Pyrgiotakis, Georgios; Vedantam, Pallavi; Cirenza, Caroline; McDevitt, James; Eleftheriadou, Mary; Leonard, Stephen S.; Demokritou, Philip

    2016-02-01

    A chemical free, nanotechnology-based, antimicrobial platform using Engineered Water Nanostructures (EWNS) was recently developed. EWNS have high surface charge, are loaded with reactive oxygen species (ROS), and can interact-with, and inactivate an array of microorganisms, including foodborne pathogens. Here, it was demonstrated that their properties during synthesis can be fine tuned and optimized to further enhance their antimicrobial potential. A lab based EWNS platform was developed to enable fine-tuning of EWNS properties by modifying synthesis parameters. Characterization of EWNS properties (charge, size and ROS content) was performed using state-of-the art analytical methods. Further their microbial inactivation potential was evaluated with food related microorganisms such as Escherichia coli, Salmonella enterica, Listeria innocua, Mycobacterium parafortuitum, and Saccharomyces cerevisiae inoculated onto the surface of organic grape tomatoes. The results presented here indicate that EWNS properties can be fine-tuned during synthesis resulting in a multifold increase of the inactivation efficacy. More specifically, the surface charge quadrupled and the ROS content increased. Microbial removal rates were microorganism dependent and ranged between 1.0 to 3.8 logs after 45 mins of exposure to an EWNS aerosol dose of 40,000 #/cm3.

  11. Optimization of a nanotechnology based antimicrobial platform for food safety applications using Engineered Water Nanostructures (EWNS)

    Science.gov (United States)

    Pyrgiotakis, Georgios; Vedantam, Pallavi; Cirenza, Caroline; McDevitt, James; Eleftheriadou, Mary; Leonard, Stephen S.; Demokritou, Philip

    2016-01-01

    A chemical free, nanotechnology-based, antimicrobial platform using Engineered Water Nanostructures (EWNS) was recently developed. EWNS have high surface charge, are loaded with reactive oxygen species (ROS), and can interact-with, and inactivate an array of microorganisms, including foodborne pathogens. Here, it was demonstrated that their properties during synthesis can be fine tuned and optimized to further enhance their antimicrobial potential. A lab based EWNS platform was developed to enable fine-tuning of EWNS properties by modifying synthesis parameters. Characterization of EWNS properties (charge, size and ROS content) was performed using state-of-the art analytical methods. Further their microbial inactivation potential was evaluated with food related microorganisms such as Escherichia coli, Salmonella enterica, Listeria innocua, Mycobacterium parafortuitum, and Saccharomyces cerevisiae inoculated onto the surface of organic grape tomatoes. The results presented here indicate that EWNS properties can be fine-tuned during synthesis resulting in a multifold increase of the inactivation efficacy. More specifically, the surface charge quadrupled and the ROS content increased. Microbial removal rates were microorganism dependent and ranged between 1.0 to 3.8 logs after 45 mins of exposure to an EWNS aerosol dose of 40,000 #/cm3. PMID:26875817

  12. Optimization of a nanotechnology based antimicrobial platform for food safety applications using Engineered Water Nanostructures (EWNS).

    Science.gov (United States)

    Pyrgiotakis, Georgios; Vedantam, Pallavi; Cirenza, Caroline; McDevitt, James; Eleftheriadou, Mary; Leonard, Stephen S; Demokritou, Philip

    2016-02-15

    A chemical free, nanotechnology-based, antimicrobial platform using Engineered Water Nanostructures (EWNS) was recently developed. EWNS have high surface charge, are loaded with reactive oxygen species (ROS), and can interact-with, and inactivate an array of microorganisms, including foodborne pathogens. Here, it was demonstrated that their properties during synthesis can be fine tuned and optimized to further enhance their antimicrobial potential. A lab based EWNS platform was developed to enable fine-tuning of EWNS properties by modifying synthesis parameters. Characterization of EWNS properties (charge, size and ROS content) was performed using state-of-the art analytical methods. Further their microbial inactivation potential was evaluated with food related microorganisms such as Escherichia coli, Salmonella enterica, Listeria innocua, Mycobacterium parafortuitum, and Saccharomyces cerevisiae inoculated onto the surface of organic grape tomatoes. The results presented here indicate that EWNS properties can be fine-tuned during synthesis resulting in a multifold increase of the inactivation efficacy. More specifically, the surface charge quadrupled and the ROS content increased. Microbial removal rates were microorganism dependent and ranged between 1.0 to 3.8 logs after 45 mins of exposure to an EWNS aerosol dose of 40,000 #/cm(3).

  13. Optimal power flow based on glow worm-swarm optimization for three-phase islanded microgrids

    DEFF Research Database (Denmark)

    Quang, Ninh Nguyen; Sanseverino, Eleonora Riva; Di Silvestre, Maria Luisa

    2014-01-01

    This paper presents an application of the Glowworm Swarm Optimization method (GSO) to solve the optimal power flow problem in three-phase islanded microgrids equipped with power electronics dc-ac inverter interfaced distributed generation units. In this system, the power injected by the distribut...

  14. Sensor Calibration Design Based on D-Optimality Criterion

    Directory of Open Access Journals (Sweden)

    Hajiyev Chingiz

    2016-09-01

    Full Text Available In this study, a procedure for optimal selection of measurement points using the D-optimality criterion to find the best calibration curves of measurement sensors is proposed. The coefficients of calibration curve are evaluated by applying the classical Least Squares Method (LSM. As an example, the problem of optimal selection for standard pressure setters when calibrating a differential pressure sensor is solved. The values obtained from the D-optimum measurement points for calibration of the differential pressure sensor are compared with those from actual experiments. Comparison of the calibration errors corresponding to the D-optimal, A-optimal and Equidistant calibration curves is done.

  15. Topology Optimization in Electric Car Body Frame Based on Optistruct

    Directory of Open Access Journals (Sweden)

    Ge Dongdong

    2017-01-01

    Full Text Available In order to optimize the structure of the electric car body frame, the static analysis of the car frame were carried on. For the goal of the frame’s weight minimum, OptiStruct software was used to topology optimization design. And the optimal material distribution program of the frame structure was got. Static strength before and after optimization was comprehensive compared through the stress, deformation. The results showed that the weight of frame after optimization was reduced by 18.96%, and the requirements of the strength and stiffness were ensured.

  16. Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices

    Directory of Open Access Journals (Sweden)

    Naser El-Sheimy

    2012-09-01

    Full Text Available Inertial Navigation Systems (INS consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth’s magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS applications.

  17. Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

    Directory of Open Access Journals (Sweden)

    Danping Wang

    2017-01-01

    Full Text Available A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional, 10 CEC2005 benchmark functions (30-dimensional, and a real-world problem (multilevel image segmentation problems. Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.

  18. Parallel Performance Optimizations on Unstructured Mesh-based Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Sarje, Abhinav; Song, Sukhyun; Jacobsen, Douglas; Huck, Kevin; Hollingsworth, Jeffrey; Malony, Allen; Williams, Samuel; Oliker, Leonid

    2015-01-01

    © The Authors. Published by Elsevier B.V. This paper addresses two key parallelization challenges the unstructured mesh-based ocean modeling code, MPAS-Ocean, which uses a mesh based on Voronoi tessellations: (1) load imbalance across processes, and (2) unstructured data access patterns, that inhibit intra- and inter-node performance. Our work analyzes the load imbalance due to naive partitioning of the mesh, and develops methods to generate mesh partitioning with better load balance and reduced communication. Furthermore, we present methods that minimize both inter- and intranode data movement and maximize data reuse. Our techniques include predictive ordering of data elements for higher cache efficiency, as well as communication reduction approaches. We present detailed performance data when running on thousands of cores using the Cray XC30 supercomputer and show that our optimization strategies can exceed the original performance by over 2×. Additionally, many of these solutions can be broadly applied to a wide variety of unstructured grid-based computations.

  19. Optimization of Cholinesterase-Based Catalytic Bioscavengers Against Organophosphorus Agents.

    Science.gov (United States)

    Lushchekina, Sofya V; Schopfer, Lawrence M; Grigorenko, Bella L; Nemukhin, Alexander V; Varfolomeev, Sergei D; Lockridge, Oksana; Masson, Patrick

    2018-01-01

    new groups that create a stable H-bonded network susceptible to activate and orient water molecule, stabilize transition states (TS), and intermediates may determine whether dephosphylation is favored over aging. Mutations on key residues (L286, F329, F398) were considered. QM/MM calculations suggest that mutation L286H combined to other mutations favors water attack from apical position. However, the aging reaction is competing. Axial direction of water attack is not favorable to aging. QM/MM calculation shows that F329H+F398H-based multiple mutants display favorable energy barrier for fast reactivation without aging.

  20. Optimization of Cholinesterase-Based Catalytic Bioscavengers Against Organophosphorus Agents

    Directory of Open Access Journals (Sweden)

    Sofya V. Lushchekina

    2018-03-01

    introducing new groups that create a stable H-bonded network susceptible to activate and orient water molecule, stabilize transition states (TS, and intermediates may determine whether dephosphylation is favored over aging. Mutations on key residues (L286, F329, F398 were considered. QM/MM calculations suggest that mutation L286H combined to other mutations favors water attack from apical position. However, the aging reaction is competing. Axial direction of water attack is not favorable to aging. QM/MM calculation shows that F329H+F398H-based multiple mutants display favorable energy barrier for fast reactivation without aging.

  1. CASTING IMPROVEMENT BASED ON METAHEURISTIC OPTIMIZATION AND NUMERICAL SIMULATION

    Directory of Open Access Journals (Sweden)

    Radomir Radiša

    2017-12-01

    Full Text Available This paper presents the use of metaheuristic optimization techniques to support the improvement of casting process. Genetic algorithm (GA, Ant Colony Optimization (ACO, Simulated annealing (SA and Particle Swarm Optimization (PSO have been considered as optimization tools to define the geometry of the casting part’s feeder. The proposed methodology has been demonstrated in the design of the feeder for casting Pelton turbine bucket. The results of the optimization are dimensional characteristics of the feeder, and the best result from all the implemented optimization processes has been adopted. Numerical simulation has been used to verify the validity of the presented design methodology and the feeding system optimization in the casting system of the Pelton turbine bucket.

  2. $H_2$ optimal controllers with observer based architecture for continuous-time systems : separation principle

    NARCIS (Netherlands)

    Saberi, A.; Sannuti, P.; Stoorvogel, A.A.

    1994-01-01

    For a general H2 optimal control problem, at first all Hz optimal measurement feedback controllers are characterized and parameterized, and then attention is focused on controllers with observer based architecture. Both full order as well as reduced order observer based H2 optimal controllers are

  3. Optimal Allocation of Water Resources Based on Water Supply Security

    Directory of Open Access Journals (Sweden)

    Jianhua Wang

    2016-06-01

    Full Text Available Under the combined impacts of climate change and human activities, a series of water issues, such as water shortages, have arisen all over the world. According to current studies in Science and Nature, water security has become a frontier critical topic. Water supply security (WSS, which is the state of water resources and their capacity and their capacity to meet the demand of water users by water supply systems, is an important part of water security. Currently, WSS is affected by the amount of water resources, water supply projects, water quality and water management. Water shortages have also led to water supply insecurity. WSS is now evaluated based on the balance of the supply and demand under a single water resources condition without considering the dynamics of the varying conditions of water resources each year. This paper developed an optimal allocation model for water resources that can realize the optimal allocation of regional water resources and comprehensively evaluate WSS. The objective of this model is to minimize the duration of water shortages in the long term, as characterized by the Water Supply Security Index (WSSI, which is the assessment value of WSS, a larger WSSI value indicates better results. In addition, the simulation results of the model can determine the change process and dynamic evolution of the WSS. Quanzhou, a city in China with serious water shortage problems, was selected as a case study. The allocation results of the current year and target year of planning demonstrated that the level of regional comprehensive WSS was significantly influenced by the capacity of water supply projects and the conditions of the natural water resources. The varying conditions of the water resources allocation results in the same year demonstrated that the allocation results and WSSI were significantly affected by reductions in precipitation, decreases in the water yield coefficient, and changes in the underlying surface.

  4. Efficacy of Code Optimization on Cache-based Processors

    Science.gov (United States)

    VanderWijngaart, Rob F.; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    The current common wisdom in the U.S. is that the powerful, cost-effective supercomputers of tomorrow will be based on commodity (RISC) micro-processors with cache memories. Already, most distributed systems in the world use such hardware as building blocks. This shift away from vector supercomputers and towards cache-based systems has brought about a change in programming paradigm, even when ignoring issues of parallelism. Vector machines require inner-loop independence and regular, non-pathological memory strides (usually this means: non-power-of-two strides) to allow efficient vectorization of array operations. Cache-based systems require spatial and temporal locality of data, so that data once read from main memory and stored in high-speed cache memory is used optimally before being written back to main memory. This means that the most cache-friendly array operations are those that feature zero or unit stride, so that each unit of data read from main memory (a cache line) contains information for the next iteration in the loop. Moreover, loops ought to be 'fat', meaning that as many operations as possible are performed on cache data-provided instruction caches do not overflow and enough registers are available. If unit stride is not possible, for example because of some data dependency, then care must be taken to avoid pathological strides, just ads on vector computers. For cache-based systems the issues are more complex, due to the effects of associativity and of non-unit block (cache line) size. But there is more to the story. Most modern micro-processors are superscalar, which means that they can issue several (arithmetic) instructions per clock cycle, provided that there are enough independent instructions in the loop body. This is another argument for providing fat loop bodies. With these restrictions, it appears fairly straightforward to produce code that will run efficiently on any cache-based system. It can be argued that although some of the important

  5. Influence of iridium on the reactivity of LaFeO3 base perovskites

    DEFF Research Database (Denmark)

    Kindermann, L.; Das, D.; Bahadur, D.

    1998-01-01

    The influence of iridium on the reactivity of powder mixtures made of perovskites and 8 mol% yttria stabilized zirconia (8 YSZ) is reported. Iridium is added to the perovskites of the composition (La0.6M0.4)(z)Fe0.8TM0.2O3-delta (M = Sr, Ca; TM = Mn, Co; z = 0.90, 1.00) via the gaseous phase....... Iridium is present in the perovskite lattice as Ir4+ replacing iron as is evident from XRD and TEM/EDX results. Compatibility studies carried out at 1000 degrees C demonstrate that iridium has considerable influence on the reactivity. The results are discussed with respect to the stability...... of the perovskites, thermodynamic activities, Ir(IV)-O bonding, tolerance factor and oxygen migration....

  6. InTaO4-based nanostructures synthesized by reactive pulsed laser ablation

    International Nuclear Information System (INIS)

    Yoshida, Takehito; Toyoyama, Hirokazu; Umezu, Ikurou; Sugimura, Akira

    2008-01-01

    Nanostructured Ni-doped indium-tantalum-oxides (InTaO 4 ) were synthesized by a reactive pulsed laser ablation process, aiming at the final goal of direct splitting of water under visible sunbeam irradiation. The third harmonics beam of a Nd:YAG laser was focused onto a sintered In 0.9 Ni 0.1 TaO 4-δ target in pure oxygen background gases (0.05-1.00 Torr). Increasing the oxygen gas pressure, via thin films having nanometer-sized strong morphologies, single-crystalline nanoparticles were synthesized in the reactive vapor phases. The nanostructured deposited materials have the monoclinic layered wolframite-type structure of bulk InTaO 4 , without oxygen deficiency. (orig.)

  7. Particle swarm optimization algorithm based low cost magnetometer calibration

    Science.gov (United States)

    Ali, A. S.; Siddharth, S., Syed, Z., El-Sheimy, N.

    2011-12-01

    Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments

  8. Credibilistic multi-period portfolio optimization based on scenario tree

    Science.gov (United States)

    Mohebbi, Negin; Najafi, Amir Abbas

    2018-02-01

    In this paper, we consider a multi-period fuzzy portfolio optimization model with considering transaction costs and the possibility of risk-free investment. We formulate a bi-objective mean-VaR portfolio selection model based on the integration of fuzzy credibility theory and scenario tree in order to dealing with the markets uncertainty. The scenario tree is also a proper method for modeling multi-period portfolio problems since the length and continuity of their horizon. We take the return and risk as well cardinality, threshold, class, and liquidity constraints into consideration for further compliance of the model with reality. Then, an interactive dynamic programming method, which is based on a two-phase fuzzy interactive approach, is employed to solve the proposed model. In order to verify the proposed model, we present an empirical application in NYSE under different circumstances. The results show that the consideration of data uncertainty and other real-world assumptions lead to more practical and efficient solutions.

  9. Task-based optimization of image reconstruction in breast CT

    Science.gov (United States)

    Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

    2014-03-01

    We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.

  10. Study of the cross-reactivity of fish allergens based on a questionnaire and blood testing

    OpenAIRE

    Kobayashi, Yukihiro; Huge, Jiletu; Imamura, Shintaro; Hamada-Sato, Naoko

    2016-01-01

    Background: Parvalbumin and collagen have been identified as cross-reactive allergens for fish allergies. Although doctors realize that various fish elicit allergies, the targets of food allergen labeling laws were only mackerels and salmons in Japan and mackerels in South Korea. This study aimed to reveal the causative species for fish allergy via questionnaires and blood tests. Methods: Questionnaire research was conducted in Japan via the internet concerning allergies for fish-allergic ...

  11. Chemical conjugation of cowpea mosaic viruses with reactive HPMA-based polymers

    Czech Academy of Sciences Publication Activity Database

    Laga, Richard; Koňák, Čestmír; Šubr, Vladimír; Ulbrich, Karel; Suthiwangcharoen, N.; Niu, Q.; Wang, Q.

    2010-01-01

    Roč. 21, č. 12 (2010), s. 1669-1685 ISSN 0920-5063 R&D Projects: GA AV ČR KJB400500803; GA ČR GA202/09/2078; GA AV ČR KAN200200651 Institutional research plan: CEZ:AV0Z40500505 Keywords : acylthiazolidine-2-thione reactive groups * bioconjugation * coating Subject RIV: CD - Macromolecular Chemistry Impact factor: 1.842, year: 2010

  12. C-reactive protein levels and treatment resistance in schizophrenia - A Danish population-based cohort study

    DEFF Research Database (Denmark)

    Horsdal, Henriette Thisted; Wimberley, Theresa; Benros, Michael Eriksen

    2017-01-01

    -time schizophrenia diagnosis and a baseline C-reactive protein measurement (a commonly available marker of systemic inflammation) from 2000 to 2012. We defined treatment resistance as the earliest observed instance of either clozapine initiation or hospital admission due to schizophrenia after having received......OBJECTIVE: Schizophrenia is associated with increased levels of inflammatory markers. However, it remains unclear whether inflammatory markers are associated with treatment-resistant schizophrenia. METHODS: We conducted a population-based follow-up study among individuals with a first...... (4.0 vs. 3.1 mg/L, p = .13) was observed among the 52 (13.3%) treatment-resistant individuals. Increased levels of C-reactive protein (above 3 mg/L) at baseline were not associated with treatment resistance (adjusted hazard ratio = 0.99, 95% confidence interval [0.56, 1.73]). CONCLUSIONS: C...

  13. Containment and Consensus-based Distributed Coordination Control for Voltage Bound and Reactive Power Sharing in AC Microgrid

    DEFF Research Database (Denmark)

    Han, Renke; Meng, Lexuan; Ferrari-Trecate, Giancarlo

    2017-01-01

    This paper offers a highly flexible and reliable control strategy to achieve voltage bounded regulation and accurate reactive power sharing coordinately in AC Micro-Grids. A containment and consensus-based distributed coordination controller is proposed, by which each output voltage magnitude can...... be bounded within a reasonable range and the accurate reactive power sharing among distributed generators can be also achieved. Combined with the two proposed controllers and electrical part of the AC Micro-Grid, a small signal model is fully developed to analyze the sensitivity of different control...... parameters. The effectiveness of the proposed controller in case of load variation, communication failure, plug-and-play capability are verified by the experimental setup as an islanded Micro-Grid....

  14. An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

    Science.gov (United States)

    Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

    2016-01-01

    For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

  15. Application of surrogate-based global optimization to aerodynamic design

    CERN Document Server

    Pérez, Esther

    2016-01-01

    Aerodynamic design, like many other engineering applications, is increasingly relying on computational power. The growing need for multi-disciplinarity and high fidelity in design optimization for industrial applications requires a huge number of repeated simulations in order to find an optimal design candidate. The main drawback is that each simulation can be computationally expensive – this becomes an even bigger issue when used within parametric studies, automated search or optimization loops, which typically may require thousands of analysis evaluations. The core issue of a design-optimization problem is the search process involved. However, when facing complex problems, the high-dimensionality of the design space and the high-multi-modality of the target functions cannot be tackled with standard techniques. In recent years, global optimization using meta-models has been widely applied to design exploration in order to rapidly investigate the design space and find sub-optimal solutions. Indeed, surrogat...

  16. RJMCMC based Text Placement to Optimize Label Placement and Quantity

    Science.gov (United States)

    Touya, Guillaume; Chassin, Thibaud

    2018-05-01

    Label placement is a tedious task in map design, and its automation has long been a goal for researchers in cartography, but also in computational geometry. Methods that search for an optimal or nearly optimal solution that satisfies a set of constraints, such as label overlapping, have been proposed in the literature. Most of these methods mainly focus on finding the optimal position for a given set of labels, but rarely allow the removal of labels as part of the optimization. This paper proposes to apply an optimization technique called Reversible-Jump Markov Chain Monte Carlo that enables to easily model the removal or addition during the optimization iterations. The method, quite preliminary for now, is tested on a real dataset, and the first results are encouraging.

  17. Recursive Pyramid Algorithm-Based Discrete Wavelet Transform for Reactive Power Measurement in Smart Meters

    Directory of Open Access Journals (Sweden)

    Mahin K. Atiq

    2013-09-01

    Full Text Available Measurement of the active, reactive, and apparent power is one of the most fundamental tasks of smart meters in energy systems. Recently, a number of studies have employed the discrete wavelet transform (DWT for power measurement in smart meters. The most common way to implement DWT is the pyramid algorithm; however, this is not feasible for practical DWT computation because it requires either a log N cascaded filter or O (N word size memory storage for an input signal of the N-point. Both solutions are too expensive for practical applications of smart meters. It is proposed that the recursive pyramid algorithm is more suitable for smart meter implementation because it requires only word size storage of L × Log (N-L, where L is the length of filter. We also investigated the effect of varying different system parameters, such as the sampling rate, dc offset, phase offset, linearity error in current and voltage sensors, analog to digital converter resolution, and number of harmonics in a non-sinusoidal system, on the reactive energy measurement using DWT. The error analysis is depicted in the form of the absolute difference between the measured and the true value of the reactive energy.

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

    Directory of Open Access Journals (Sweden)

    Xun Zhang

    2014-01-01

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

  19. Multiphase Return Trajectory Optimization Based on Hybrid Algorithm

    Directory of Open Access Journals (Sweden)

    Yi Yang

    2016-01-01

    Full Text Available A hybrid trajectory optimization method consisting of Gauss pseudospectral method (GPM and natural computation algorithm has been developed and utilized to solve multiphase return trajectory optimization problem, where a phase is defined as a subinterval in which the right-hand side of the differential equation is continuous. GPM converts the optimal control problem to a nonlinear programming problem (NLP, which helps to improve calculation accuracy and speed of natural computation algorithm. Through numerical simulations, it is found that the multiphase optimal control problem could be solved perfectly.

  20. OPTIMIZED PARTICLE SWARM OPTIMIZATION BASED DEADLINE CONSTRAINED TASK SCHEDULING IN HYBRID CLOUD

    Directory of Open Access Journals (Sweden)

    Dhananjay Kumar

    2016-01-01

    Full Text Available Cloud Computing is a dominant way of sharing of computing resources that can be configured and provisioned easily. Task scheduling in Hybrid cloud is a challenge as it suffers from producing the best QoS (Quality of Service when there is a high demand. In this paper a new resource allocation algorithm, to find the best External Cloud provider when the intermediate provider’s resources aren’t enough to satisfy the customer’s demand is proposed. The proposed algorithm called Optimized Particle Swarm Optimization (OPSO combines the two metaheuristic algorithms namely Particle Swarm Optimization and Ant Colony Optimization (ACO. These metaheuristic algorithms are used for the purpose of optimization in the search space of the required solution, to find the best resource from the pool of resources and to obtain maximum profit even when the number of tasks submitted for execution is very high. This optimization is performed to allocate job requests to internal and external cloud providers to obtain maximum profit. It helps to improve the system performance by improving the CPU utilization, and handle multiple requests at the same time. The simulation result shows that an OPSO yields 0.1% - 5% profit to the intermediate cloud provider compared with standard PSO and ACO algorithms and it also increases the CPU utilization by 0.1%.