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%.

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

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

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...

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...

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

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

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.

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.

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

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.

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.

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...

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.

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.

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.

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.

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....

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)

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.

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.

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)

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

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...

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

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...

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.

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.

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

Reactive Power Pricing Model Considering the Randomness of Wind Power Output

Science.gov (United States)

Dai, Zhong; Wu, Zhou

2018-01-01

With the increase of wind power capacity integrated into grid, the influence of the randomness of wind power output on the reactive power distribution of grid is gradually highlighted. Meanwhile, the power market reform puts forward higher requirements for reasonable pricing of reactive power service. Based on it, the article combined the optimal power flow model considering wind power randomness with integrated cost allocation method to price reactive power. Meanwhile, considering the advantages and disadvantages of the present cost allocation method and marginal cost pricing, an integrated cost allocation method based on optimal power flow tracing is proposed. The model realized the optimal power flow distribution of reactive power with the minimal integrated cost and wind power integration, under the premise of guaranteeing the balance of reactive power pricing. Finally, through the analysis of multi-scenario calculation examples and the stochastic simulation of wind power outputs, the article compared the results of the model pricing and the marginal cost pricing, which proved that the model is accurate and effective.

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

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.

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)

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

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...

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)

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.

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.

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....

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.

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.

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.

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

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...

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.

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

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.

A New Framework for Reactive Power Market Considering Power System Security

Directory of Open Access Journals (Sweden)

A. Rabiee

2009-09-01

Full Text Available This paper presents a new framework for the day-ahead reactive power market based on the uniform auction price. Voltage stability and security have been considered in the proposed framework. Total Payment Function (TPF is suggested as the objective function of the Optimal Power Flow (OPF used to clear the reactive power market. Overload, voltage drop and voltage stability margin (VSM are included in the constraints of the OPF. Another advantage of the proposed method is the exclusion of Lost Opportunity Cost (LOC concerns from the reactive power market. The effectiveness of the proposed reactive power market is studied based on the CIGRÉ-32 bus test system.

Optimal allocation of SVC and TCSC using quasi-oppositional chemical reaction optimization for solving multi-objective ORPD problem

Directory of Open Access Journals (Sweden)

Susanta Dutta

2018-05-01

Full Text Available This paper presents an efficient quasi-oppositional chemical reaction optimization (QOCRO technique to find the feasible optimal solution of the multi objective optimal reactive power dispatch (RPD problem with flexible AC transmission system (FACTS device. The quasi-oppositional based learning (QOBL is incorporated in conventional chemical reaction optimization (CRO, to improve the solution quality and the convergence speed. To check the superiority of the proposed method, it is applied on IEEE 14-bus and 30-bus systems and the simulation results of the proposed approach are compared to those reported in the literature. The computational results reveal that the proposed algorithm has excellent convergence characteristics and is superior to other multi objective optimization algorithms. Keywords: Quasi-oppositional chemical reaction optimization (QOCRO, Reactive power dispatch (RPD, TCSC, SVC, Multi-objective optimization

A stochastic framework for clearing of reactive power market

International Nuclear Information System (INIS)

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

2010-01-01

This paper presents a new stochastic framework for clearing of day-ahead reactive power market. The uncertainty of generating units in the form of system contingencies are considered in the reactive power market-clearing procedure by the stochastic model in two steps. The Monte-Carlo Simulation (MCS) is first used to generate random scenarios. Then, in the second step, the stochastic market-clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. In each of these deterministic optimization problems, the objective function is total payment function (TPF) of generators which refers to the payment paid to the generators for their reactive power compensation. The effectiveness of the proposed model is examined based on the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS). (author)

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.

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...

Secure provision of reactive power ancillary services in competitive electricity markets

Science.gov (United States)

El-Samahy, Ismael

The research work presented in this thesis discusses various complex issues associated with reactive power management and pricing in the context of new operating paradigms in deregulated power systems, proposing appropriate policy solutions. An integrated two-level framework for reactive power management is set forth, which is both suitable for a competitive market and ensures a secure and reliable operation of the associated power system. The framework is generic in nature and can be adopted for any electricity market structure. The proposed hierarchical reactive power market structure comprises two stages: procurement of reactive power resources on a seasonal basis, and real-time reactive power dispatch. The main objective of the proposed framework is to provide appropriate reactive power support from service providers at least cost, while ensuring a secure operation of the power system. The proposed procurement procedure is based on a two-step optimization model. First, the marginal benefits of reactive power supply from each provider, with respect to system security, are obtained by solving a loadability-maximization problem subject to transmission security constraints imposed by voltage and thermal limits. Second, the selected set of generators is determined by solving an optimal power flow (OPF)-based auction. This auction maximizes a societal advantage function comprising generators' offers and their corresponding marginal benefits with respect to system security, and considering all transmission system constraints. The proposed procedure yields the selected set of generators and zonal price components, which would form the basis for seasonal contracts between the system operator and the selected reactive power service providers. The main objective of the proposed reactive power dispatch model is to minimize the total payment burden on the Independent System Operator (ISO), which is associated with reactive power dispatch. The real power generation is

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.)

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

Statistical Optimization of Conditions for Decolorization of Synthetic Dyes by Cordyceps militaris MTCC 3936 Using RSM

Directory of Open Access Journals (Sweden)

Baljinder Kaur

2015-01-01

Full Text Available In the present study, the biobleaching potential of white rot fungus Cordyceps militaris MTCC3936 was investigated. For preliminary screening, decolorization properties of C. militaris were comparatively studied using whole cells in agar-based and liquid culture systems. Preliminary investigation in liquid culture systems revealed 100% decolorization achieved within 3 days of incubation for reactive yellow 18, 6 days for reactive red 31, 7 days for reactive black 8, and 11 days for reactive green 19 and reactive red 74. RSM was further used to study the effect of three independent variables such as pH, incubation time, and concentration of dye on decolorization properties of cell free supernatant of C. militaris. RSM based statistical analysis revealed that dye decolorization by cell free supernatants of C. militaris is more efficient than whole cell based system. The optimized conditions for decolorization of synthetic dyes were identified as dye concentration of 300 ppm, incubation time of 48 h, and optimal pH value as 5.5, except for reactive red 31 (for which the model was nonsignificant. The maximum dye decolorizations achieved under optimized conditions for reactive yellow 18, reactive green 19, reactive red 74, and reactive black 8 were 73.07, 65.36, 55.37, and 68.59%, respectively.

Dynamic Reactive Power Compensation of Large Scale Wind Integrated Power System

DEFF Research Database (Denmark)

Rather, Zakir Hussain; Chen, Zhe; Thøgersen, Paul

2015-01-01

wind turbines especially wind farms with additional grid support functionalities like dynamic support (e,g dynamic reactive power support etc.) and ii) refurbishment of existing conventional central power plants to synchronous condensers could be one of the efficient, reliable and cost effective option......Due to progressive displacement of conventional power plants by wind turbines, dynamic security of large scale wind integrated power systems gets significantly compromised. In this paper we first highlight the importance of dynamic reactive power support/voltage security in large scale wind...... integrated power systems with least presence of conventional power plants. Then we propose a mixed integer dynamic optimization based method for optimal dynamic reactive power allocation in large scale wind integrated power systems. One of the important aspects of the proposed methodology is that unlike...

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.

Reactive power supply by distributed generators

OpenAIRE

Braun, M.

2008-01-01

Distributed reactive power supply is necessary in distribution networks for an optimized network operation. This paper presents first the reactive power supply capabilities of generators connected to the distribution network (distributed generators). In a second step an approach is proposed of determining the energy losses resulting from reactive power supply by distributed generators. The costs for compensating these losses represent the operational costs of reactive power supply. These cost...

Coupled energy and reactive power market clearing considering power system security

International Nuclear Information System (INIS)

Rabiee, Abdorreza; Shayanfar, Heidarali; Amjady, Nima

2009-01-01

In a deregulated environment, when talking about electricity markets, one usually refers to energy market, paying less attention to the reactive power market. Active and reactive powers are, however, coupled through the AC power flow equations and branch loading limits as well as the synchronous generators capability curves. However, the sequential approach for energy and reactive power markets cannot present the optimal solution due to the interactions between these markets. For instance, clearing of the reactive power market can change active power dispatch (e.g. due to a change of transmission system losses and the capability curve limitation), which can lead to degradation of the energy market clearing point. This paper presents a coupled day ahead energy and reactive power market based on the pay-at-MCP settlement mechanism. Besides, the proposed coupled framework considers voltage stability and security issues and branch loading limits. The coupled market is cleared through optimal power flow (OPF). Its objective function includes total payment of generating units for their active power production along with the total payment function (TPF) of units for their reactive power compensation. Moreover, lost opportunity cost (LOC) of the units is also considered. The effectiveness of the proposed framework is examined on the IEEE 24 bus Reliability Test System

Coupled energy and reactive power market clearing considering power system security

Energy Technology Data Exchange (ETDEWEB)

Rabiee, Abdorreza; Shayanfar, Heidarali [Center of Excellence for Power System Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology (IUST), Tehran (Iran); Amjady, Nima [Department of Electrical Engineering, Semnan University, Semnan (Iran)

2009-04-15

In a deregulated environment, when talking about electricity markets, one usually refers to energy market, paying less attention to the reactive power market. Active and reactive powers are, however, coupled through the AC power flow equations and branch loading limits as well as the synchronous generators capability curves. However, the sequential approach for energy and reactive power markets cannot present the optimal solution due to the interactions between these markets. For instance, clearing of the reactive power market can change active power dispatch (e.g. due to a change of transmission system losses and the capability curve limitation), which can lead to degradation of the energy market clearing point. This paper presents a coupled day ahead energy and reactive power market based on the pay-at-MCP settlement mechanism. Besides, the proposed coupled framework considers voltage stability and security issues and branch loading limits. The coupled market is cleared through optimal power flow (OPF). Its objective function includes total payment of generating units for their active power production along with the total payment function (TPF) of units for their reactive power compensation. Moreover, lost opportunity cost (LOC) of the units is also considered. The effectiveness of the proposed framework is examined on the IEEE 24 bus Reliability Test System. (author)

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.

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

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.

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.

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...

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...

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...

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.

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

Approximate photochemical dynamics of azobenzene with reactive force fields

Science.gov (United States)

Li, Yan; Hartke, Bernd

2013-12-01

We have fitted reactive force fields of the ReaxFF type to the ground and first excited electronic states of azobenzene, using global parameter optimization by genetic algorithms. Upon coupling with a simple energy-gap transition probability model, this setup allows for completely force-field-based simulations of photochemical cis→trans- and trans→cis-isomerizations of azobenzene, with qualitatively acceptable quantum yields. This paves the way towards large-scale dynamics simulations of molecular machines, including bond breaking and formation (via the reactive force field) as well as photochemical engines (presented in this work).

Real-Time Reactive Power Distribution in Microgrids by Dynamic Programing

DEFF Research Database (Denmark)

Levron, Yoash; Beck, Yuval; Katzir, Liran

2017-01-01

In this paper a new real-time optimization method for reactive power distribution in microgrids is proposed. The method enables location of a globally optimal distribution of reactive power under normal operating conditions. The method exploits the typical compact structure of microgrids to obtain...... combination of reactive powers, by means of dynamic programming. Since every single step involves a one-dimensional problem, the complexity of the solution is only linear with the number of clusters, and as a result, a globally optimal solution may be obtained in real time. The paper includes the results...

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.

Optimal Allocation of Power-Electronic Interfaced Wind Turbines Using a Genetic Algorithm - Monte Carlo Hybrid Optimization Method

DEFF Research Database (Denmark)

Chen, Peiyuan; Siano, Pierluigi; Chen, Zhe

2010-01-01

determined by the wind resource and geographic conditions, the location of wind turbines in a power system network may significantly affect the distribution of power flow, power losses, etc. Furthermore, modern WTs with power-electronic interface have the capability of controlling reactive power output...... limit requirements. The method combines the Genetic Algorithm (GA), gradient-based constrained nonlinear optimization algorithm and sequential Monte Carlo simulation (MCS). The GA searches for the optimal locations and capacities of WTs. The gradient-based optimization finds the optimal power factor...... setting of WTs. The sequential MCS takes into account the stochastic behaviour of wind power generation and load. The proposed hybrid optimization method is demonstrated on an 11 kV 69-bus distribution system....

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%.

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)

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.

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...

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)

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...

Cardiac parasympathetic reactivation following exercise: implications for training prescription.

Science.gov (United States)

Stanley, Jamie; Peake, Jonathan M; Buchheit, Martin

2013-12-01

The objective of exercise training is to initiate desirable physiological adaptations that ultimately enhance physical work capacity. Optimal training prescription requires an individualized approach, with an appropriate balance of training stimulus and recovery and optimal periodization. Recovery from exercise involves integrated physiological responses. The cardiovascular system plays a fundamental role in facilitating many of these responses, including thermoregulation and delivery/removal of nutrients and waste products. As a marker of cardiovascular recovery, cardiac parasympathetic reactivation following a training session is highly individualized. It appears to parallel the acute/intermediate recovery of the thermoregulatory and vascular systems, as described by the supercompensation theory. The physiological mechanisms underlying cardiac parasympathetic reactivation are not completely understood. However, changes in cardiac autonomic activity may provide a proxy measure of the changes in autonomic input into organs and (by default) the blood flow requirements to restore homeostasis. Metaboreflex stimulation (e.g. muscle and blood acidosis) is likely a key determinant of parasympathetic reactivation in the short term (0-90 min post-exercise), whereas baroreflex stimulation (e.g. exercise-induced changes in plasma volume) probably mediates parasympathetic reactivation in the intermediate term (1-48 h post-exercise). Cardiac parasympathetic reactivation does not appear to coincide with the recovery of all physiological systems (e.g. energy stores or the neuromuscular system). However, this may reflect the limited data currently available on parasympathetic reactivation following strength/resistance-based exercise of variable intensity. In this review, we quantitatively analyse post-exercise cardiac parasympathetic reactivation in athletes and healthy individuals following aerobic exercise, with respect to exercise intensity and duration, and fitness

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

Optimal Power Transmission of Offshore Wind Power Using a VSC-HVdc Interconnection

Directory of Open Access Journals (Sweden)

Miguel E. Montilla-DJesus

2017-07-01

Full Text Available High-voltage dc transmission based on voltage-source converter (VSC-HVdc is quickly increasing its power rating, and it can be the most appropriate link for the connection of offshore wind farms (OWFs to the grid in many locations. This paper presents a steady-state operation model to calculate the optimal power transmission of an OWF connected to the grid through a VSC-HVdc link. The wind turbines are based on doubly fed induction generators (DFIGs, and a detailed model of the internal OWF grid is considered in the model. The objective of the optimization problem is to maximize the active power output of the OWF, i.e., the reduction of losses, by considering the optimal reactive power allocation while taking into account the restrictions imposed by the available wind power, the reactive power capability of the DFIG, the DC link model, and the operating conditions. Realistic simulations are performed to evaluate the proposed model and to execute optimal operation analyses. The results show the effectiveness of the proposed method and demonstrate the advantages of using the reactive control performed by DFIG to achieve the optimal operation of the VSC-HVdc.

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.

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.

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.

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...

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...

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...

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.

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

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''

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.

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).

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).

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.

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.

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...

A Reactive and Cycle-True IP Emulator for MPSoC Exploration

DEFF Research Database (Denmark)

Mahadevan, Shankar; Angiolini, Federico; Sparsø, Jens

2008-01-01

The design of MultiProcessor Systems-on-Chip (MPSoC) emphasizes intellectual-property (IP)-based communication-centric approaches. Therefore, for the optimization of the MPSoC interconnect, the designer must develop traffic models that realistically capture the application behavior as executing...... on the IP core. In this paper, we introduce a Reactive IP Emulator (RIPE) that enables an effective emulation of the IP-core behavior in multiple environments, including bit and cycle-true simulation. The RIPE is built as a multithreaded abstract instruction-set processor, and it can generate reactive...

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.

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.

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...

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.

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.

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

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.

Design of reactive power procurement in deregulated electricity market

African Journals Online (AJOL)

user

novel reactive power procurement model is proposed, which ensure secure and ..... The simulation is performed in the Matlab. .... focus of this paper is a reactive procurement market model, which is a basically two-step optimization process.

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...

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)

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.

Engine combustion control via fuel reactivity stratification

Science.gov (United States)

Reitz, Rolf Deneys; Hanson, Reed M; Splitter, Derek A; Kokjohn, Sage L

2013-12-31

A compression ignition engine uses two or more fuel charges having two or more reactivities to control the timing and duration of combustion. In a preferred implementation, a lower-reactivity fuel charge is injected or otherwise introduced into the combustion chamber, preferably sufficiently early that it becomes at least substantially homogeneously dispersed within the chamber before a subsequent injection is made. One or more subsequent injections of higher-reactivity fuel charges are then made, and these preferably distribute the higher-reactivity matter within the lower-reactivity chamber space such that combustion begins in the higher-reactivity regions, and with the lower-reactivity regions following thereafter. By appropriately choose the reactivities of the charges, their relative amounts, and their timing, combustion can be tailored to achieve optimal power output (and thus fuel efficiency), at controlled temperatures (and thus controlled NOx), and with controlled equivalence ratios (and thus controlled soot).

Methodology for Design and Analysis of Reactive Distillation Involving Multielement Systems

DEFF Research Database (Denmark)

Jantharasuk, Amnart; Gani, Rafiqul; Górak, Andrzej

2011-01-01

A new methodology for design and analysis of reactive distillation has been developed. In this work, the elementbased approach, coupled with a driving force diagram, has been extended and applied to the design of a reactive distillation column involving multielement (multicomponent) systems...... consisting of two components. Based on this methodology, an optimal design configuration is identified using the equivalent binary-element-driving force diagram. Two case studies of methyl acetate (MeOAc) synthesis and methyl-tert-butyl ether (MTBE) synthesis have been considered to demonstrate...... the successful applications of the methodology. Moreover, energy requirements for various column configurations corresponding to different feed locatio...

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)

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...

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

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.

Wheeling rates evaluation using optimal power flows

International Nuclear Information System (INIS)

Muchayi, M.; El-Hawary, M. E.

1998-01-01

Wheeling is the transmission of electrical power and reactive power from a seller to a buyer through a transmission network owned by a third party. The wheeling rates are then the prices charged by the third party for the use of its network. This paper proposes and evaluates a strategy for pricing wheeling power using a pricing algorithm that in addition to the fuel cost for generation incorporates the optimal allocation of the transmission system operating cost, based on time-of-use pricing. The algorithm is implemented for the IEEE standard 14 and 30 bus system which involves solving a modified optimal power flow problem iteratively. The base of the proposed algorithm is the hourly spot price. The analysis spans a total time period of 24 hours. Unlike other algorithms that use DC models, the proposed model captures wheeling rates of both real and reactive power. Based on the evaluation, it was concluded that the model has the potential for wide application in calculating wheeling rates in a deregulated competitive power transmission environment. 9 refs., 3 tabs

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

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.

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 .

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

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.

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.

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.

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

Control parameter optimization for AP1000 reactor using Particle Swarm Optimization

International Nuclear Information System (INIS)

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

2016-01-01

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

Further Controversies About Brain Tissue Oxygenation Pressure-Reactivity After Traumatic Brain Injury

DEFF Research Database (Denmark)

Andresen, Morten; Donnelly, Joseph; Aries, Marcel

2018-01-01

arterial pressure and intracranial pressure. A new ORx index based on brain tissue oxygenation and cerebral perfusion pressure (CPP) has been proposed that similarly allows for evaluation of cerebrovascular reactivity. Conflicting results exist concerning its clinical utility. METHODS: Retrospective......BACKGROUND: Continuous monitoring of cerebral autoregulation is considered clinically useful due to its ability to warn against brain ischemic insults, which may translate to a relationship with adverse outcome. It is typically performed using the pressure reactivity index (PRx) based on mean...... analysis was performed in 85 patients with traumatic brain injury (TBI). ORx was calculated using three time windows of 5, 20, and 60 min. Correlation coefficients and individual "optimal CPP" (CPPopt) were calculated using both PRx and ORx, and relation to patient outcome investigated. RESULTS...

Reactive power management of power networks with wind generation

CERN Document Server

Amaris, Hortensia; Ortega, Carlos Alvarez

2012-01-01

As the energy sector shifts and changes to focus on renewable technologies, the optimization of wind power becomes a key practical issue. Reactive Power Management of Power Networks with Wind Generation brings into focus the development and application of advanced optimization techniques to the study, characterization, and assessment of voltage stability in power systems. Recent advances on reactive power management are reviewed with particular emphasis on the analysis and control of wind energy conversion systems and FACTS devices. Following an introduction, distinct chapters cover the 5 key

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.

Optimization of reload core design for PWR

International Nuclear Information System (INIS)

Shen Wei; Xie Zhongsheng; Yin Banghua

1995-01-01

A direct efficient optimization technique has been effected for automatically optimizing the reload of PWR. The objective functions include: maximization of end-of-cycle (EOC) reactivity and maximization of average discharge burnup. The fuel loading optimization and burnable poison (BP) optimization are separated into two stages by using Haling principle. In the first stage, the optimum fuel reloading pattern without BP is determined by the linear programming method using enrichments as control variable, while in the second stage the optimum BP allocation is determined by the flexible tolerance method using the number of BP rods as control variable. A practical and efficient PWR reloading optimization program based on above theory has been encoded and successfully applied to Qinshan Nuclear Power Plant (QNP) cycle 2 reloading design

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.

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.

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

Automatized Assessment of Protective Group Reactivity: A Step Toward Big Reaction Data Analysis.

Science.gov (United States)

Lin, Arkadii I; Madzhidov, Timur I; Klimchuk, Olga; Nugmanov, Ramil I; Antipin, Igor S; Varnek, Alexandre

2016-11-28

We report a new method to assess protective groups (PGs) reactivity as a function of reaction conditions (catalyst, solvent) using raw reaction data. It is based on an intuitive similarity principle for chemical reactions: similar reactions proceed under similar conditions. Technically, reaction similarity can be assessed using the Condensed Graph of Reaction (CGR) approach representing an ensemble of reactants and products as a single molecular graph, i.e., as a pseudomolecule for which molecular descriptors or fingerprints can be calculated. CGR-based in-house tools were used to process data for 142,111 catalytic hydrogenation reactions extracted from the Reaxys database. Our results reveal some contradictions with famous Greene's Reactivity Charts based on manual expert analysis. Models developed in this study show high accuracy (ca. 90%) for predicting optimal experimental conditions of protective group deprotection.

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.

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.

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...

A New Optimization Framework To Solve The Optimal Feeder Reconfiguration And Capacitor Placement Problems

Directory of Open Access Journals (Sweden)

Mohammad-Reza Askari

2015-07-01

Full Text Available Abstract This paper introduces a new stochastic optimization framework based bat algorithm BA to solve the optimal distribution feeder reconfiguration DFR as well as the shunt capacitor placement and sizing in the distribution systems. The objective functions to be investigated are minimization of the active power losses and minimization of the total network costs an. In order to consider the uncertainties of the active and reactive loads in the problem point estimate method PEM with 2m scheme is employed as the stochastic tool. The feasibility and good performance of the proposed method are examined on the IEEE 69-bus test system.

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.

Active and reactive power neurocontroller for grid-connected photovoltaic generation system

Directory of Open Access Journals (Sweden)

I. Abadlia

2016-03-01

Full Text Available Many researchers have contributed to the development of a firm foundation for analysis and design of control applications in grid-connected renewable energy sources. This paper presents an intelligent control algorithm fond on artificial neural networks for active and reactive power controller in grid-connected photovoltaic generation system. The system is devices into two parts in which each part contains an inverter with control algorithm. A DC/DC converter in output voltage established by control magnitude besides maximum power point tracker algorithm always finds optimal power of the PV array in use. A DC/AC hysteresis inverter designed can synchronize a sinusoidal current output with the grid voltage and accurate an independent active and reactive power control. Simulation results confirm the validation of the purpose. Neurocontroller based active and reactive power presents an efficiency control that guarantees good response to the steps changing in active and reactive power with an acceptable current/voltage synchronism. In this paper the power circuit and the control system of the presented grid-connected photovoltaic generation system is simulated and tested by MatLab/Simulink.

CANDU-6 fuel optimization for advanced cycles

Energy Technology Data Exchange (ETDEWEB)

St-Aubin, Emmanuel, E-mail: emmanuel.st-aubin@polymtl.ca; Marleau, Guy, E-mail: guy.marleau@polymtl.ca

2015-11-15

Highlights: • New fuel selection process proposed for advanced CANDU cycles. • Full core time-average CANDU modeling with independent refueling and burnup zones. • New time-average fuel optimization method used for discrete on-power refueling. • Performance metrics evaluated for thorium-uranium and thorium-DUPIC cycles. - Abstract: We implement a selection process based on DRAGON and DONJON simulations to identify interesting thorium fuel cycles driven by low-enriched uranium or DUPIC dioxide fuels for CANDU-6 reactors. We also develop a fuel management optimization method based on the physics of discrete on-power refueling and the time-average approach to maximize the economical advantages of the candidates that have been pre-selected using a corrected infinite lattice model. Credible instantaneous states are also defined using a channel age model and simulated to quantify the hot spots amplitude and the departure from criticality with fixed reactivity devices. For the most promising fuels identified using coarse models, optimized 2D cell and 3D reactivity device supercell DRAGON models are then used to generate accurate reactor databases at low computational cost. The application of the selection process to different cycles demonstrates the efficiency of our procedure in identifying the most interesting fuel compositions and refueling options for a CANDU reactor. The results show that using our optimization method one can obtain fuels that achieve a high average exit burnup while respecting the reference cycle safety limits.

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

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.

Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

Science.gov (United States)

Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

2018-02-01

A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method

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)

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...

Electrocoagulation/electroflotation of reactive, disperse and mixture dyes in an external-loop airlift reactor

International Nuclear Information System (INIS)

Balla, Wafaa; Essadki, A.H.; Gourich, B.; Dassaa, A.; Chenik, H.; Azzi, M.

2010-01-01

This paper studied the efficiency of electrocoagulation/electroflotation in removing colour from synthetic and real textile wastewater by using aluminium and iron electrodes in an external-loop airlift reactor of 20 L. The disperse dye is a mixture of Yellow terasil 4G, Red terasil 343 150% and Blue terasil 3R02, the reactive dye is a mixture of Red S3B 195, Yellow SPD, Blue BRFS. For disperse dye, the removal efficiency was better using aluminium electrodes, whereas, the iron electrodes showed more efficiency for removing colour for reactive dye and mixed synthetic dye. Both for disperse, reactive and mixed dye, 40 mA cm -2 and 20 min were respectively the optimal current density and electrolysis time. 7.5 was an optimal initial pH for both reactive and mixed synthetic dye and 6.2 was an optimal initial pH for disperse dye. The colour efficiency reached in general 90%. The results showed also that Red and Blue disappeared quickly comparatively to the Yellow component both for reactive and disperse dyes. The real textile wastewater was then used. Three effluents were also used: disperse, reactive and the mixture. The colour efficiency is between 70 and 90% and COD efficiency reached 78%. The specific electrical energy consumption per kg dye removed (E dye ) in optimal conditions for real effluent was calculated. 170 kWh/kg dye was required for a reactive dye, 120 kWh/kg dye for disperse and 50 kWh/kg dye for the mixture.

Electrocoagulation/electroflotation of reactive, disperse and mixture dyes in an external-loop airlift reactor

Energy Technology Data Exchange (ETDEWEB)

Balla, Wafaa [Ecole Superieure de Technologie, Laboratoire Genie des Procedes et Environnement, B.P. 8012, Oasis, Casablanca (Morocco); Faculte des sciences Ain Chock, Laboratoire d' Electrochimie et chimie de l' environnement, B.P. 5366, Maarif, Casablanca (Morocco); Essadki, A.H., E-mail: essadki@est-uh2c.ac.ma [Ecole Superieure de Technologie, Laboratoire Genie des Procedes et Environnement, B.P. 8012, Oasis, Casablanca (Morocco); Gourich, B. [Ecole Superieure de Technologie, Laboratoire Genie des Procedes et Environnement, B.P. 8012, Oasis, Casablanca (Morocco); Dassaa, A. [Faculte des sciences Ain Chock, Laboratoire d' Electrochimie et chimie de l' environnement, B.P. 5366, Maarif, Casablanca (Morocco); Chenik, H. [Ecole Superieure de Technologie, Laboratoire Genie des Procedes et Environnement, B.P. 8012, Oasis, Casablanca (Morocco); Faculte des sciences Ain Chock, Laboratoire d' Electrochimie et chimie de l' environnement, B.P. 5366, Maarif, Casablanca (Morocco); Azzi, M. [Faculte des sciences Ain Chock, Laboratoire d' Electrochimie et chimie de l' environnement, B.P. 5366, Maarif, Casablanca (Morocco)

2010-12-15

This paper studied the efficiency of electrocoagulation/electroflotation in removing colour from synthetic and real textile wastewater by using aluminium and iron electrodes in an external-loop airlift reactor of 20 L. The disperse dye is a mixture of Yellow terasil 4G, Red terasil 343 150% and Blue terasil 3R02, the reactive dye is a mixture of Red S3B 195, Yellow SPD, Blue BRFS. For disperse dye, the removal efficiency was better using aluminium electrodes, whereas, the iron electrodes showed more efficiency for removing colour for reactive dye and mixed synthetic dye. Both for disperse, reactive and mixed dye, 40 mA cm{sup -2} and 20 min were respectively the optimal current density and electrolysis time. 7.5 was an optimal initial pH for both reactive and mixed synthetic dye and 6.2 was an optimal initial pH for disperse dye. The colour efficiency reached in general 90%. The results showed also that Red and Blue disappeared quickly comparatively to the Yellow component both for reactive and disperse dyes. The real textile wastewater was then used. Three effluents were also used: disperse, reactive and the mixture. The colour efficiency is between 70 and 90% and COD efficiency reached 78%. The specific electrical energy consumption per kg dye removed (E{sub dye}) in optimal conditions for real effluent was calculated. 170 kWh/kg{sub dye} was required for a reactive dye, 120 kWh/kg{sub dye} for disperse and 50 kWh/kg{sub dye} for the mixture.

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.

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.

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

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.

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

Optimal Switching Table-Based Sliding Mode Control of an Energy Recovery Li-Ion Power Accumulator Battery Pack Testing System

Directory of Open Access Journals (Sweden)

Kil To Chong

2013-10-01

Full Text Available The main objective of the present work is to apply a sliding mode controller (SMC to medium voltage and high power output energy recovery Li-ion power accumulator battery pack testing systems (ERLPABTSs, which are composed of a three-level neutral-point-clamped (NPC three-phase voltage source inverter (VSI and a two-level buck-boost converter without an isolating transformer. An inner current decoupled control scheme for the aforementioned system is proposed and two sliding mode planes for active and reactive current control are designed based on the control scheme. An optimized switching table for current convergence is used according to the error sign of the equivalent input voltage and feedback voltage. The proposed ERLPABTS could be used to integrate discharging energy into the power grid when performing high accuracy current testing. The active and reactive power references for the grid-connected inverter are determined based on the discharging energy from the DC-DC converter. Simulations and experiments on a laboratory hardware platform using a 175 kW insulated gate bipolar transistor (IGBT-based ERLPABTS have been implemented and verified, and the performance is found satisfactory and superior to conventional ERLPABPTS.

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

One-Bath Pretreatment for Enhanced Color Yield of Ink-Jet Prints Using Reactive Inks

Directory of Open Access Journals (Sweden)

Wei Ma

2017-11-01

Full Text Available In order to facilely increase the color yield of ink-jet prints using reactive inks, one-bath pretreatment of cotton fabrics with pretreatment formulation containing sodium alginate, glycidyltrimethylammonium chloride (GTA, sodium hydroxide, and urea is designed for realizing sizing and cationization at the same time. The pretreatment conditions, including the concentrations of GTA and alkali, baking temperature, and time are optimized based on the result of thecolor yield on cationic cotton for magenta ink. The mechanism for color yield enhancement on GTA-modified fabrics is discussed and the stability of GTA in the print paste is investigated. Scanning electron microscopey, tear strength, and thermogravimetric analysis of the modified and unmodified cotton are studied and compared. Using the optimal pretreatment conditions, color yield on the cationic cotton for magenta, cyan, yellow, and black reactive inks are increased by 128.7%, 142.5%, 71.0%, and 38.1%, respectively, compared with the corresponding color yield on the uncationized cotton. Much less wastewater is produced using this one-bath pretreatment method. Colorfastness of the reactive dyes on the modified and unmodified cotton is compared and boundary clarity between different colors is evaluated by ink-jet printing of colorful patterns.

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,...

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...

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.

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

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...

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

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.

Waterflooding optimization in uncertain geological scenarios

DEFF Research Database (Denmark)

Capolei, Andrea; Suwartadi, Eka; Foss, Bjarne

2013-01-01

, robust optimization has been suggested to improve and robustify optimal control strategies. In robust optimization of an oil reservoir, the water injection and production borehole pressures (bhp) are computed such that the predicted net present value (NPV) of an ensemble of permeability field...... inherits the features of both the reactive and the RO strategy. Simulations reveal that the modified RO strategy results in operations with larger returns and less risk than the reactive strategy, the RO strategy, and the certainty equivalent strategy. The returns are measured by the expected NPV...... of most reservoir engineers. Feedback reduces the uncertainty and this is the reason for the similar performance of the two strategies....

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.

Permeable bio-reactive barriers for hydrocarbon remediation in Antarctica

Energy Technology Data Exchange (ETDEWEB)

Mumford, K.A.; Stevens, G.W.; Gore, D.B. [Melbourne Univ., Victoria (Australia). Dept. of Chemical and Biomoleculuar Engineering, Particulate Fluids Processing Centre; Snape, I.; Rayner, J.L. [Australian Antarctic Div., Kingston, Tasmania (Australia); Gore, D.B. [Macquarie Univ., Sydney, NSW (Australia). Dept. of Environmental Science

2010-07-01

This study assessed the performance of a permeable bio-reactive barrier designed to treat contaminated water. The bio-reactive barrier was installed at a fuel spill site located in the Windmill Islands, Antarctica. A funnel and gate design was used to prevent contaminant migration beyond the barrier location as well as to ensure controlled nutrient delivery. The study also investigated the performance of the bio-reactive barrier in regions with freeze-thaw conditions. The 4-year project was also conducted to assess optimal conditions for enhancing the barrier's ability to degrade hydrocarbons.

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.

Application of the ant colony search algorithm to reactive power pricing in an open electricity market

International Nuclear Information System (INIS)

Ketabi, Abbas; Alibabaee, Ahmad; Feuillet, R.

2010-01-01

Reactive power management is essential to transfer real energy and support power system security. Developing an accurate and feasible method for reactive power pricing is important in the electricity market. In conventional optimal power flow models the production cost of reactive power was ignored. In this paper, the production cost of reactive power and investment cost of capacitor banks were included into the objective function of the OPF problem. Then, using ant colony search algorithm, the optimal problem was solved. Marginal price theory was used for calculation of the cost of active and reactive power at each bus in competitive electric markets. Application of the proposed method on IEEE 14-bus system confirms its validity and effectiveness. Results from several case studies show clearly the effects of various factors on reactive power price. (author)

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)

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.

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.

Assessment of solid reactive mixtures for the development of biological permeable reactive barriers

International Nuclear Information System (INIS)

Pagnanelli, Francesca; Viggi, Carolina Cruz; Mainelli, Sara; Toro, Luigi

2009-01-01

Solid reactive mixtures were tested as filling material for the development of biological permeable reactive barriers for the treatment of heavy metals contaminated waters. Mixture selection was performed by taking into account the different mechanisms operating in sulphate and cadmium removal with particular attention to bioprecipitation and sorption onto the organic matrices in the mixtures. Suspensions of eight reactive mixtures were tested for sulphate removal (initial concentration 3 g L -1 ). Each mixture was made up of four main functional components: a mix of organic sources for bacterial growth, a neutralizing agent, a porous medium and zero-valent iron. The best mixture among the tested ones (M8: 6% leaves, 9% compost, 3% zero-valent iron, 30% silica sand, 30% perlite, 22% limestone) presented optimal conditions for SRB growth (pH 7.8 ± 0.1; E h = -410 ± 5 mV) and 83% sulphate removal in 22 days (25% due to bioreduction, 32% due to sorption onto compost and 20% onto leaves). M8 mixture allowed the complete abatement of cadmium with a significant contribution of sorption over bioprecipitation (6% Cd removal due to SRB activity). Sorption properties, characterised by potentiometric titrations and related modelling, were mainly due to carboxylic sites of organic components used in reactive mixtures.

Reactivity studies of rice husk combustion using TGA

International Nuclear Information System (INIS)

Ismail, A.F.; Shamsuddin, A.H.; Mahdi, F.M.A.

2000-01-01

The reactivity of rice husks combustion is systematically studied the thermogravimetric analyzer (TGA). The kinetic parameters are determined from the Arrhenius plots based on the data of weight loss over temperature at different combustion heating rates. The results of proximate analysis (the moisture, volatile matters, fixed carbon, and ash contents) are also presented in this paper. The effects of process conditions on the self-ignition phenomenon of rice husk combustion are quantified. Finally, these results and compared with results for coal combustion. This research is part of the work to determine the optimal process conditions of rice husk combustion for energy production. (Author)

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

Generation of reactive species in atmospheric pressure dielectric barrier discharge with liquid water

Science.gov (United States)

Zelong, ZHANG; Jie, SHEN; Cheng, CHENG; Zimu, XU; Weidong, XIA

2018-04-01

Atmospheric pressure helium/water dielectric barrier discharge (DBD) plasma is used to investigate the generation of reactive species in a gas-liquid interface and in a liquid. The emission intensity of the reactive species is measured by optical emission spectroscopy (OES) with different discharge powers at the gas-liquid interface. Spectrophotometry is used to analyze the reactive species induced by the plasma in the liquid. The concentration of OH radicals reaches 2.2 μm after 3 min of discharge treatment. In addition, the concentration of primary long-lived reactive species such as H2O2, {{{{NO}}}3}- and O3 are measured based on plasma treatment time. After 5 min of discharge treatment, the concentration of H2O2, {{{{NO}}}3}-, and O3 increased from 0 mg · L-1 to 96 mg · L-1, 19.5 mg · L-1, and 3.5 mg · L-1, respectively. The water treated by plasma still contained a considerable concentration of reactive species after 6 h of storage. The results will contribute to optimizing the DBD plasma system for biological decontamination.

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...

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

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.

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.

Immobilization of cesium in cement containing reactive silica and pozzolans

International Nuclear Information System (INIS)

McCulloch, C.E.; Angus, M.J.; Glasser, F.P.; Rahman, A.A.

1984-01-01

High surface area silicas, ground blast furnace slag, fly ash, and natural pozzolan markedly enhance the sorption of Cs in cement-based systems. Fly ash low in alkali and silicas are considered to be most suitable for Cs immobilization. Since these materials are chemically reactive with the cement components, the optimal level of addition must be sufficiently high, probably 20-30 wt%, to provide a permanent excess of sorbent. The sorptive mechanism is demonstrated and shown to be enhanced by the alkaline cement environment

Integrated Process Design and Control of Reactive Distillation Processes

DEFF Research Database (Denmark)

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

2015-01-01

on the element concept, which is used to translate a system of compounds into elements. The operation of the reactive distillation column at the highest driving force and other candidate points is analyzed through analytical solution as well as rigorous open-loop and closed-loop simulations. By application...... of this approach, it is shown that designing the reactive distillation process at the maximum driving force results in an optimal design in terms of controllability and operability. It is verified that the reactive distillation design option is less sensitive to the disturbances in the feed at the highest driving...

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

Cure Cycle Design Methodology for Fabricating Reactive Resin Matrix Fiber Reinforced Composites: A Protocol for Producing Void-free Quality Laminates

Science.gov (United States)

Hou, Tan-Hung

2014-01-01

For the fabrication of resin matrix fiber reinforced composite laminates, a workable cure cycle (i.e., temperature and pressure profiles as a function of processing time) is needed and is critical for achieving void-free laminate consolidation. Design of such a cure cycle is not trivial, especially when dealing with reactive matrix resins. An empirical "trial and error" approach has been used as common practice in the composite industry. Such an approach is not only costly, but also ineffective at establishing the optimal processing conditions for a specific resin/fiber composite system. In this report, a rational "processing science" based approach is established, and a universal cure cycle design protocol is proposed. Following this protocol, a workable and optimal cure cycle can be readily and rationally designed for most reactive resin systems in a cost effective way. This design protocol has been validated through experimental studies of several reactive polyimide composites for a wide spectrum of usage that has been documented in the previous publications.

Sensitivity analysis of reactive ecological dynamics.

Science.gov (United States)

Verdy, Ariane; Caswell, Hal

2008-08-01

Ecological systems with asymptotically stable equilibria may exhibit significant transient dynamics following perturbations. In some cases, these transient dynamics include the possibility of excursions away from the equilibrium before the eventual return; systems that exhibit such amplification of perturbations are called reactive. Reactivity is a common property of ecological systems, and the amplification can be large and long-lasting. The transient response of a reactive ecosystem depends on the parameters of the underlying model. To investigate this dependence, we develop sensitivity analyses for indices of transient dynamics (reactivity, the amplification envelope, and the optimal perturbation) in both continuous- and discrete-time models written in matrix form. The sensitivity calculations require expressions, some of them new, for the derivatives of equilibria, eigenvalues, singular values, and singular vectors, obtained using matrix calculus. Sensitivity analysis provides a quantitative framework for investigating the mechanisms leading to transient growth. We apply the methodology to a predator-prey model and a size-structured food web model. The results suggest predator-driven and prey-driven mechanisms for transient amplification resulting from multispecies interactions.

Treating water-reactive wastes

International Nuclear Information System (INIS)

Lussiez, G.W.

1993-01-01

Some compounds and elements, such as lithium hydride, magnesium, sodium, and calcium react violently with water to generate much heat and produce hydrogen. The hydrogen can ignite or even form an explosive mixture with air. Other metals may react rapidly only if they are finely divided. Some of the waste produced at Los Alamos National Laboratory includes these metals that are contaminated with radioactivity. By far the greatest volume of water-reactive waste is lithium hydride contaminated with depleted uranium. Reactivity of the water-reactive wastes is neutralized with an atmosphere of humid nitrogen, which prevents the formation of an explosive mixture of hydrogen and air. When we adjust the temperature of the nitrogen and the humidifier, the nitrogen can be more or less humid, and the rate of reaction can be adjusted and controlled. Los Alamos has investigated the rates of reaction of lithium hydride as a function of the temperature and humidity, and, as anticipated, they in with in temperature and humidity. Los Alamos will investigate other variables. For example, the nitrogen flow will be optimized to conserve nitrogen and yet keep the reaction rates high. Reaction rates will be determined for various forms of lithium waste, from small chips to powder. Bench work will lead to the design of a skid-mounted process for treating wastes. Other water-reactive wastes will also be investigated

Reactive solute transport in physically and chemically heterogeneous porous media with multimodal reactive mineral facies: the Lagrangian approach.

Science.gov (United States)

Soltanian, Mohamad Reza; Ritzi, Robert W; Dai, Zhenxue; Huang, Chao Cheng

2015-03-01

Physical and chemical heterogeneities have a large impact on reactive transport in porous media. Examples of heterogeneous attributes affecting reactive mass transport are the hydraulic conductivity (K), and the equilibrium sorption distribution coefficient (Kd). This paper uses the Deng et al. (2013) conceptual model for multimodal reactive mineral facies and a Lagrangian-based stochastic theory in order to analyze the reactive solute dispersion in three-dimensional anisotropic heterogeneous porous media with hierarchical organization of reactive minerals. An example based on real field data is used to illustrate the time evolution trends of reactive solute dispersion. The results show that the correlation between the hydraulic conductivity and the equilibrium sorption distribution coefficient does have a significant effect on reactive solute dispersion. The anisotropy ratio does not have a significant effect on reactive solute dispersion. Furthermore, through a sensitivity analysis we investigate the impact of changing the mean, variance, and integral scale of K and Kd on reactive solute dispersion. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Literature Survey on Operational Voltage Control and Reactive Power Management on Transmission and Sub-Transmission Networks

Energy Technology Data Exchange (ETDEWEB)

Elizondo, Marcelo A.; Samaan, Nader A.; Makarov, Yuri V.; Holzer, Jesse T.; Vallem, Mallikarjuna R.; Huang, Renke; Vyakaranam, Bharat GNVSR; Ke, Xinda; Pan, Feng

2017-10-02

Voltage and reactive power system control is generally performed following usual patterns of loads, based on off-line studies for daily and seasonal operations. This practice is currently challenged by the inclusion of distributed renewable generation, such as solar. There has been focus on resolving this problem at the distribution level; however, the transmission and sub-transmission levels have received less attention. This paper provides a literature review of proposed methods and solution approaches to coordinate and optimize voltage control and reactive power management, with an emphasis on applications at transmission and sub-transmission level. The conclusion drawn from the survey is that additional research is needed in the areas of optimizing switch shunt actions and coordinating all available resources to deal with uncertain patterns from increasing distributed renewable generation in the operational time frame. These topics are not deeply explored in the literature.

Optimization-based topology identification of complex networks

International Nuclear Information System (INIS)

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

2011-01-01

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

A 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.

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.

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.

Shape optimization of a sodium cooled fast reactor

International Nuclear Information System (INIS)

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

2013-01-01

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

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....

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....

Reactivity effect of non-uniformly distributed fuel in fuel solution systems

International Nuclear Information System (INIS)

Hirano, Yasushi; Yamane, Yoshihiro; Nishina, Kojiro; Mitsuhashi, Ishi.

1991-01-01

A numerical method to determine the optimal fuel distribution for minimum critical mass, or maximum k-effective, is developed using the Maximum Principle in order to evaluate the maximum effect of non-uniformly distributed fuel on reactivity. This algorithm maximizes the Hamiltonian directly by an iterative method under a certain constraint-the maintenance of criticality or total fuel mass. It ultimately reaches the same optimal state of a flattened fuel importance distribution as another algorithm by Dam based on perturbation theory. This method was applied to two kinds of spherical cores with water reflector in the simulating reprocessing facility. In the slightly-enriched uranyl nitrate solution core, the minimum critical mass decreased by less than 1% at the optimal moderation state. In the plutonium nitrate solution core, the k-effective increment amounted up to 4.3% Δk within the range of present study. (author)

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.

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.

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

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Biwei Tang

2016-01-01

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

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

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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.

Label-assisted mass spectrometry for the acceleration of reaction discovery and optimization

Science.gov (United States)

Cabrera-Pardo, Jaime R.; Chai, David I.; Liu, Song; Mrksich, Milan; Kozmin, Sergey A.

2013-05-01

The identification of new reactions expands our knowledge of chemical reactivity and enables new synthetic applications. Accelerating the pace of this discovery process remains challenging. We describe a highly effective and simple platform for screening a large number of potential chemical reactions in order to discover and optimize previously unknown catalytic transformations, thereby revealing new chemical reactivity. Our strategy is based on labelling one of the reactants with a polyaromatic chemical tag, which selectively undergoes a photoionization/desorption process upon laser irradiation, without the assistance of an external matrix, and enables rapid mass spectrometric detection of any products originating from such labelled reactants in complex reaction mixtures without any chromatographic separation. This method was successfully used for high-throughput discovery and subsequent optimization of two previously unknown benzannulation reactions.

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...

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.

Regarding KUR Reactivity Measurement System

International Nuclear Information System (INIS)

Nakamori, Akira; Hasegawa, Kei; Tsuchiyama, Tatsuo; Yamamoto, Toshihiro; Okumura, Ryo; Sano, Tadafumi

2012-01-01

This article reported: (1) the outline of the reactivity measurement system of Kyoto University Research Reactor (KUR), (2) the calibration data of control rod, (3) the problems and the countermeasures for range switching of linear output meter. For the laptop PC for the reactivity measurement system, there are four input signals: (1) linear output meter, (2) logarithmic output meter, (3) core temperature gauge, and (4) control rod position. The hardware of reactivity measurement system is controlled with Labview installed on the laptop. Output, reactivity, reactor period, and the change in reactivity due to temperature effect or Xenon effect are internally calculated and displayed in real-time with Labview based on the four signals above. Calculation results are recorded in the form of a spreadsheet. At KUR, the reactor core arrangement was changed, so the control rod was re-calibrated. At this time, calculated and experimental values of reactivity based on the reactivity measurement system were compared, and it was confirmed that the reactivity calculation by Labview was accurate. The range switching of linear output meter in the nuclear instrumentation should automatically change within the laptop, however sometimes this did not function properly in the early stage. It was speculated that undefined percent values during the transition of percent value were included in the calculation and caused calculation errors. The range switching started working properly after fixing this issue. (S.K.)

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...

An Optimal Integrated Control Scheme for Permanent Magnet Synchronous Generator-Based Wind Turbines under Asymmetrical Grid Fault Conditions

Directory of Open Access Journals (Sweden)

Dan Wang

2016-04-01

Full Text Available In recent years, the increasing penetration level of wind energy into power systems has brought new issues and challenges. One of the main concerns is the issue of dynamic response capability during outer disturbance conditions, especially the fault-tolerance capability during asymmetrical faults. In order to improve the fault-tolerance and dynamic response capability under asymmetrical grid fault conditions, an optimal integrated control scheme for the grid-side voltage-source converter (VSC of direct-driven permanent magnet synchronous generator (PMSG-based wind turbine systems is proposed in this paper. The optimal control strategy includes a main controller and an additional controller. In the main controller, a double-loop controller based on differential flatness-based theory is designed for grid-side VSC. Two parts are involved in the design process of the flatness-based controller: the reference trajectories generation of flatness output and the implementation of the controller. In the additional control aspect, an auxiliary second harmonic compensation control loop based on an improved calculation method for grid-side instantaneous transmission power is designed by the quasi proportional resonant (Quasi-PR control principle, which is able to simultaneously restrain the second harmonic components in active power and reactive power injected into the grid without the respective calculation for current control references. Moreover, to reduce the DC-link overvoltage during grid faults, the mathematical model of DC-link voltage is analyzed and a feedforward modified control factor is added to the traditional DC voltage control loop in grid-side VSC. The effectiveness of the optimal control scheme is verified in PSCAD/EMTDC simulation software.

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

External equivalent type Ward aiming optimization studies in power systems; Equivalentes externos tipo Ward visando estudos de otimizacao em sistemas de potencia

Energy Technology Data Exchange (ETDEWEB)

Nepomuceno, Leonardo

1993-07-01

The execution of functions such as contingency analysis, optimization, reactive dispatch, etc, at the control centers requires appropriate models representing the non-observable parts (external system). The classical external equivalents have been developed considering basically the contingency analysis. This work points out the performance of the Extended Ward Equivalent (W.E.), which currently represents the state of art concerning reduced circuit based models. the work analyzes the W.E. response to changes occurred in optimization studied. Moreover, a new model, named INTERNAL REACTIVE WARD (WRINT), resulting from an adaptation of the W.E. is proposed focusing on the improvement of the equivalent in case of changes occurs in optimization studies. The model's general idea is to reflect the equivalent's capacity of reactive response into the internal system. Comparative computational test results are shown. The details of routines implementation are also pointed out. (author)

Matrix-reinforcement reactivity in P/M titanium matrix composites

International Nuclear Information System (INIS)

Amigo, V.; Romero, F.; Salvador, M. D.; Busquets, D.

2007-01-01

The high reactivity of titanium and the facility of the same one to form intermetallics makes difficult obtaining composites with this material and brings the need in any case of covering the principal fibres used as reinforcement. To obtain composites of titanium reinforced with ceramic particles ins proposed in this paper, for this reason it turns out to be fundamental to evaluate the reactivity between the matrix and reinforcement. Both titanium nitride and carbide (TiN and TiC) are investigated as materials of low reactivity whereas titanium silicide (TiSi 2 ) is also studied as materials of major reactivity, already stated by the scientific community. This reactivity will be analysed by means of scanning electron microscopy (SEM) there being obtained distribution maps of the elements that allow to establish the possible influence of the sintering temperature and time. Hereby the matrix-reinforcement interactions are optimized to obtain suitable mechanical properties. (Author) 39 refs

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

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.

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.

Quantitative 3D Fluorescence Imaging of Single Catalytic Turnovers Reveals Spatiotemporal Gradients in Reactivity of Zeolite H-ZSM-5 Crystals upon Steaming

NARCIS (Netherlands)

Ristanovic, Zoran|info:eu-repo/dai/nl/328233005; Hofmann, Jan P.|info:eu-repo/dai/nl/355351110; De Cremer, Gert; Kubarev, Alexey V.; Rohnke, Marcus; Meirer, Florian; Hofkens, Johan; Roeffaers, Maarten B. J.; Weckhuysen, Bert M.|info:eu-repo/dai/nl/285484397

2015-01-01

Optimizing the number, distribution, and accessibility of Bronsted acid sites in zeolite-based catalysts is of a paramount importance to further improve their catalytic performance. However, it remains challenging to measure real-time changes in reactivity of single zeolite catalyst particles by

Optimization of Grillages Using Genetic Algorithms for Integrating Matlab and Fortran Environments

Directory of Open Access Journals (Sweden)

Darius Mačiūnas

2013-02-01

Full Text Available The purpose of the paper is to present technology applied for the global optimization of grillage-type pile foundations (further grillages. The goal of optimization is to obtain the optimal layout of pile placement in the grillages. The problem can be categorized as a topology optimization problem. The objective function is comprised of maximum reactive force emerging in a pile. The reactive force is minimized during the procedure of optimization during which variables enclose the positions of piles beneath connecting beams. Reactive forces in all piles are computed utilizing an original algorithm implemented in the Fortran programming language. The algorithm is integrated into the MatLab environment where the optimization procedure is executed utilizing a genetic algorithm. The article also describes technology enabling the integration of MatLab and Fortran environments. The authors seek to evaluate the quality of a solution to the problem analyzing experimental results obtained applying the proposed technology.

Optimization of Grillages Using Genetic Algorithms for Integrating Matlab and Fortran Environments

Directory of Open Access Journals (Sweden)

Darius Mačiūnas

2012-12-01

Full Text Available The purpose of the paper is to present technology applied for the global optimization of grillage-type pile foundations (further grillages. The goal of optimization is to obtain the optimal layout of pile placement in the grillages. The problem can be categorized as a topology optimization problem. The objective function is comprised of maximum reactive force emerging in a pile. The reactive force is minimized during the procedure of optimization during which variables enclose the positions of piles beneath connecting beams. Reactive forces in all piles are computed utilizing an original algorithm implemented in the Fortran programming language. The algorithm is integrated into the MatLab environment where the optimization procedure is executed utilizing a genetic algorithm. The article also describes technology enabling the integration of MatLab and Fortran environments. The authors seek to evaluate the quality of a solution to the problem analyzing experimental results obtained applying the proposed technology.

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

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.

Multi-Objective Optimization of Grillages Applying the Genetic Algorithm

Directory of Open Access Journals (Sweden)

Darius Mačiūnas

2012-01-01

Full Text Available The article analyzes the optimization of grillage-type foundations seeking for the least possible reactive forces in the poles for a given number of poles and for the least possible bending moments of absolute values in the connecting beams of the grillage. Therefore, we suggest using a compromise objective function (to be minimized that consists of the maximum reactive force arising in all poles and the maximum bending moment of the absolute value in connecting beams; both components include the given weights. The variables of task design are pole positions under connecting beams. The optimization task is solved applying the algorithm containing all the initial data of the problem. Reactive forces and bending moments are calculated using an original program (finite element method is applied. This program is integrated into the optimization algorithm using the “black-box” principle. The “black-box” finite element program sends back the corresponding value of the objective function. Numerical experiments revealed the optimal quantity of points to compute bending moments. The obtained results show a certain ratio of weights in the objective function where the contribution of reactive forces and bending moments to the objective function are equivalent. This solution can serve as a pilot project for more detailed design.Article in Lithuanian

Core design of long life-cycle fast reactors operating without reactivity margin

International Nuclear Information System (INIS)

Aristova, E. N.; Baydin, D. F.; Gol'din, V. Y.; Pestryakova, G. A.; Stoynov, M. I.

2012-01-01

In this paper we consider a possibility of designing a fast reactor core that operates without reactivity margin for a long time. This study is based on the physical principle of fast reactor operating in a self-adjustable neutron-nuclear regime (SANNR-1) introduced by L.P. Feoktistov (1988-1993) and improved by V. Ya. Gol'din SANNR-2 (1995). The mathematical modeling of active zones of fast reactors in SANNR modes is held by authors since 1992. The numerical simulation is based on solving the neutron transport equation coupled with quasi-diffusion equations. The calculations have been performed using standard 26 energy groups. We use a hierarchy of spatial models of 1D, 1.5D, 2D, and 3D geometries. The spatial models of higher dimensionality are used for verification of results. The calculations showed that operation of the reactor in this mode increases its efficiency, safety and simplifies management. It is possible to achieve continuous work of the reactor in SANNR-2 during 7-10 years without fuel overloads by means of further optimization of the mode. Small reactivity margin is used only for the reactor start up. After first 10-15 days the reactor in SANNR-2 operates without reactivity margin. (authors)

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

Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm

Directory of Open Access Journals (Sweden)

Feifei Dong

2014-01-01

Full Text Available Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC. The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.

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

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...

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.

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.

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

High-resolution temperature-based optimization for hyperthermia treatment planning

International Nuclear Information System (INIS)

Kok, H P; Haaren, P M A van; Kamer, J B Van de; Wiersma, J; Dijk, J D P Van; Crezee, J

2005-01-01

In regional hyperthermia, optimization techniques are valuable in order to obtain amplitude/phase settings for the applicators to achieve maximal tumour heating without toxicity to normal tissue. We implemented a temperature-based optimization technique and maximized tumour temperature with constraints on normal tissue temperature to prevent hot spots. E-field distributions are the primary input for the optimization method. Due to computer limitations we are restricted to a resolution of 1 x 1 x 1 cm 3 for E-field calculations, too low for reliable treatment planning. A major problem is the fact that hot spots at low-resolution (LR) do not always correspond to hot spots at high-resolution (HR), and vice versa. Thus, HR temperature-based optimization is necessary for adequate treatment planning and satisfactory results cannot be obtained with LR strategies. To obtain HR power density (PD) distributions from LR E-field calculations, a quasi-static zooming technique has been developed earlier at the UMC Utrecht. However, quasi-static zooming does not preserve phase information and therefore it does not provide the HR E-field information required for direct HR optimization. We combined quasi-static zooming with the optimization method to obtain a millimetre resolution temperature-based optimization strategy. First we performed a LR (1 cm) optimization and used the obtained settings to calculate the HR (2 mm) PD and corresponding HR temperature distribution. Next, we performed a HR optimization using an estimation of the new HR temperature distribution based on previous calculations. This estimation is based on the assumption that the HR and LR temperature distributions, though strongly different, respond in a similar way to amplitude/phase steering. To verify the newly obtained settings, we calculate the corresponding HR temperature distribution. This method was applied to several clinical situations and found to work very well. Deviations of this estimation method for

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.

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...

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.

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)

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.

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.

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

International Nuclear Information System (INIS)

Punnathanam, Varun; Kotecha, Prakash

2017-01-01

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

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.

External equivalent type Ward aiming optimization studies in power systems; Equivalentes externos tipo Ward visando estudos de otimizacao em sistemas de potencia

Energy Technology Data Exchange (ETDEWEB)

Nepomuceno, Leonardo

1993-07-01

The execution of functions such as contingency analysis, optimization, reactive dispatch, etc, at the control centers requires appropriate models representing the non-observable parts (external system). The classical external equivalents have been developed considering basically the contingency analysis. This work points out the performance of the Extended Ward Equivalent (W.E.), which currently represents the state of art concerning reduced circuit based models. the work analyzes the W.E. response to changes occurred in optimization studied. Moreover, a new model, named INTERNAL REACTIVE WARD (WRINT), resulting from an adaptation of the W.E. is proposed focusing on the improvement of the equivalent in case of changes occurs in optimization studies. The model's general idea is to reflect the equivalent's capacity of reactive response into the internal system. Comparative computational test results are shown. The details of routines implementation are also pointed out. (author)

Extremum-Seeking Control and Applications A Numerical Optimization-Based Approach

CERN Document Server

Zhang, Chunlei

2012-01-01

Extremum seeking control tracks a varying maximum or minimum in a performance function such as a cost. It attempts to determine the optimal performance of a control system as it operates, thereby reducing downtime and the need for system analysis. Extremum Seeking Control and Applications is divided into two parts. In the first, the authors review existing analog optimization based extremum seeking control including gradient, perturbation and sliding mode based control designs. They then propose a novel numerical optimization based extremum seeking control based on optimization algorithms and state regulation. This control design is developed for simple linear time-invariant systems and then extended for a class of feedback linearizable nonlinear systems. The two main optimization algorithms – line search and trust region methods – are analyzed for robustness. Finite-time and asymptotic state regulators are put forward for linear and nonlinear systems respectively. Further design flexibility is achieved u...

Cross-reactivity of human nickel-reactive T-lymphocyte clones with copper and palladium

NARCIS (Netherlands)

Pistoor, F. H.; Kapsenberg, M. L.; Bos, J. D.; Meinardi, M. M.; von Blomberg, M. E.; Scheper, R. J.

1995-01-01

Twenty Ni-reactive T-lymphocyte clones were obtained from eight different donors and analyzed for their ability to cross-react with other metals. All Ni-reactive T-lymphocyte clones were CD4+CD8- and recognized Ni in association with either HLA-DR or -DQ molecules. Based on the periodic table of the

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.

Multi-Band Cable Antenna with Irregular Reactive Loading

Science.gov (United States)

2014-11-04

antenna 10 consists of an insulated solid conductor 12 of radius a. Preferably, this element is made from copper ; however, any highly conductive metal...Docket No. 300035 5 of 12 improved flotation . A low dielectric constant is essential for optimal RF performance. Reactive elements (not shown, see

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

Design study of Thorium-232 and Protactinium-231 based fuel for long life BWR

Energy Technology Data Exchange (ETDEWEB)

Trianti, N.; Su' ud, Z.; Riyana, E. S. [Nuclear Physics and Biophysics Research Division Department of Physics - Institut Teknologi Bandung (ITB) Jalan Ganeca 10 Bandung 40132 (Indonesia)

2012-06-06

A preliminary design study for the utilization of thorium added with {sup 231}Pa based fuel on BWR type reactor has been performed. In the previous research utilization of fuel based Thorium-232 and Uranium-233 show 10 years operation time with maximum excess-reactivity about 4.075% dk/k. To increase reactor operation time and reduce excess-reactivity below 1% dk/k, Protactinium (Pa-231) is used as Burnable Poison. Protactinium-231 has very interesting neutronic properties, which enable the core to reduce initial excess-reactivity and simultaneously increase production of {sup 233}U to {sup 231}Pa in burn-up process. Optimizations of the content of {sup 231}Pa in the core enables the BWR core to sustain long period of operation time with reasonable burn-up reactivity swing. Based on the optimization of fuel element composition (Th and Pa) in various moderation ratio we can get reactor core with longer operation time, 20 {approx} 30 years operation without fuel shuffling or refuelling, with average power densities maximum of about 35 watt/cc, and maximum excess-reactivity 0.56% dk/k.

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...

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...

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 ...

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.

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.

Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

L. DJEROU,

2012-01-01

Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

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.

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.

Void reactivity decomposition for the Sodium-cooled Fast Reactor in equilibrium fuel cycle

Energy Technology Data Exchange (ETDEWEB)

Sun Kaichao, E-mail: kaichao.sun@psi.ch [Paul Scherrer Institut (PSI), 5232 Villigen PSI (Switzerland); Ecole Polytechnique Federale de Lausanne (EPFL), 1015 Lausanne (Switzerland); Krepel, Jiri; Mikityuk, Konstantin; Pelloni, Sandro [Paul Scherrer Institut (PSI), 5232 Villigen PSI (Switzerland); Chawla, Rakesh [Paul Scherrer Institut (PSI), 5232 Villigen PSI (Switzerland); Ecole Polytechnique Federale de Lausanne (EPFL), 1015 Lausanne (Switzerland)

2011-07-15

Highlights: > We analyze the void reactivity effect for three ESFR core fuel cycle states. > The void reactivity effect is decomposed by neutron balance method. > Novelly, the normalization to the integral flux in the active core is applied. > The decomposition is compared with the perturbation theory based results. > The mechanism and the differences of the void reactivity effect are explained. - Abstract: The Sodium-cooled Fast Reactor (SFR) is one of the most promising Generation IV systems with many advantages, but has one dominating neutronic drawback - a positive sodium void reactivity. The aim of this study is to develop and apply a methodology, which should help better understand the causes and consequences of the sodium void effect. It focuses not only on the beginning-of-life (BOL) state of the core, but also on the beginning of open and closed equilibrium (BOC and BEC, respectively) fuel cycle conditions. The deeper understanding of the principal phenomena involved may subsequently lead to appropriate optimization studies. Various voiding scenarios, corresponding to different spatial zones, e.g. node or assembly, have been analyzed, and the most conservative case - the voiding of both inner and outer fuel zones - has been selected as the reference scenario. On the basis of the neutron balance method, the corresponding SFR void reactivity has been decomposed reaction-, isotope-, and energy-group-wise. Complementary results, based on generalized perturbation theory and sensitivity analysis, are also presented. The numerical analysis for both neutron balance and perturbation theory methods has been carried out using appropriate modules of the ERANOS code system. A strong correlation between the flux worth, i.e. the product of flux and adjoint flux, and the void reactivity importance distributions has been found for the node- and assembly-wise voiding scenarios. The neutron balance based decomposition has shown that the void effect is caused mainly by the

Void reactivity decomposition for the Sodium-cooled Fast Reactor in equilibrium fuel cycle

International Nuclear Information System (INIS)

Sun Kaichao; Krepel, Jiri; Mikityuk, Konstantin; Pelloni, Sandro; Chawla, Rakesh

2011-01-01

Highlights: → We analyze the void reactivity effect for three ESFR core fuel cycle states. → The void reactivity effect is decomposed by neutron balance method. → Novelly, the normalization to the integral flux in the active core is applied. → The decomposition is compared with the perturbation theory based results. → The mechanism and the differences of the void reactivity effect are explained. - Abstract: The Sodium-cooled Fast Reactor (SFR) is one of the most promising Generation IV systems with many advantages, but has one dominating neutronic drawback - a positive sodium void reactivity. The aim of this study is to develop and apply a methodology, which should help better understand the causes and consequences of the sodium void effect. It focuses not only on the beginning-of-life (BOL) state of the core, but also on the beginning of open and closed equilibrium (BOC and BEC, respectively) fuel cycle conditions. The deeper understanding of the principal phenomena involved may subsequently lead to appropriate optimization studies. Various voiding scenarios, corresponding to different spatial zones, e.g. node or assembly, have been analyzed, and the most conservative case - the voiding of both inner and outer fuel zones - has been selected as the reference scenario. On the basis of the neutron balance method, the corresponding SFR void reactivity has been decomposed reaction-, isotope-, and energy-group-wise. Complementary results, based on generalized perturbation theory and sensitivity analysis, are also presented. The numerical analysis for both neutron balance and perturbation theory methods has been carried out using appropriate modules of the ERANOS code system. A strong correlation between the flux worth, i.e. the product of flux and adjoint flux, and the void reactivity importance distributions has been found for the node- and assembly-wise voiding scenarios. The neutron balance based decomposition has shown that the void effect is caused mainly

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.

Recent Progress on Data-Based Optimization for Mineral Processing Plants

Directory of Open Access Journals (Sweden)

Jinliang Ding

2017-04-01

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

A roadmap for OH reactivity research

Science.gov (United States)

Williams, Jonathan; Brune, William

2015-04-01

A fundamental property of the atmosphere is the frequency of gas-phase reactions with the OH radical, the atmosphere's primary oxidizing agent. This reaction frequency is called the OH reactivity and is the inverse the lifetime of the OH radical itself, which varies from a few seconds in the clean upper troposphere to below 10 ms in forests and polluted city environments. Ever since the discovery of the OH radical's importance to tropospheric chemistry, the characterization of its overall loss rate (OH reactivity) has remained a key question. At first, this property was assessed by summing the reactivity contributions of individually measured compounds; however, as improving analytical technology revealed ever more reactive species in ambient air, it became clear that this approach could provide only a lower limit. Approximately 15 years ago, the direct measurement of total OH reactivity was conceived independently by two groups. The first publications demonstrated direct OH reactivity measurements in the laboratory (Calpini et al., 1999) based on LIDAR and in the ambient air (Kovacs and Brune, 2001) based on in situ laser induced fluorescence detection of OH.

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.

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)

Reactive Programming in Standard ML

OpenAIRE

Pucella, Riccardo

2004-01-01

Reactive systems are systems that maintain an ongoing interaction with their environment, activated by receiving input events from the environment and producing output events in response. Modern programming languages designed to program such systems use a paradigm based on the notions of instants and activations. We describe a library for Standard ML that provides basic primitives for programming reactive systems. The library is a low-level system upon which more sophisticated reactive behavi...

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.

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

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.

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.

Hepatitis B virus reactivation during immunosuppressive therapy: Appropriate risk stratification.

Science.gov (United States)

Seto, Wai-Kay

2015-04-28

Our understanding of hepatitis B virus (HBV) reactivation during immunosuppresive therapy has increased remarkably during recent years. HBV reactivation in hepatitis B surface antigen (HBsAg)-positive individuals has been well-described in certain immunosuppressive regimens, including therapies containing corticosteroids, anthracyclines, rituximab, antibody to tumor necrosis factor (anti-TNF) and hematopoietic stem cell transplantation (HSCT). HBV reactivation could also occur in HBsAg-negative, antibody to hepatitis B core antigen (anti-HBc) positive individuals during therapies containing rituximab, anti-TNF or HSCT.For HBsAg-positive patients, prophylactic antiviral therapy is proven to the effective in preventing HBV reactivation. Recent evidence also demonstrated entecavir to be more effective than lamivudine in this aspect. For HBsAg-negative, anti-HBc positive individuals, the risk of reactivations differs with the type of immunosuppression. For rituximab, a prospective study demonstrated the 2-year cumulative risk of reactivation to be 41.5%, but prospective data is still lacking for other immunosupressive regimes. The optimal management in preventing HBV reactivation would involve appropriate risk stratification for different immunosuppressive regimes in both HBsAg-positive and HBsAg-negative, anti-HBc positive individuals.

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

Elements of calculation of reactivity by numerical processing

International Nuclear Information System (INIS)

Hedde, J.

1968-01-01

In order to explore the new opportunities provided by numerical techniques, the author describes the theoretical optimal conditions of a calculation in real time of reactivity from counting samples produced by a nuclear reactor. These optimal conditions can be the better approached if a more complex processing is adopted. A compromise is to be searched between the desired precision and simplicity of the numerical processing hardware. An example is reported to assess result accuracy on a wide power evolution range with a structure of reduced complexity [fr

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.

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

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.

Contralateral Vocal Fold Reactive Lesions: Nomenclature, Treatment Choice, and Outcome.

Science.gov (United States)

Koss, Shira L; Kidwai, Sarah M; Pitman, Michael J

2016-06-01

Contralateral reactive lesions (RLs) represent a distinct entity among benign bilateral vocal fold (VF) lesions. Lack of uniform nomenclature and a myriad of surgical options have hampered attempts to develop treatment guidelines. The objective of this study is to better define RLs and their prognosis, through the development of a standard nomenclature, with an aim to guide treatment and delineate the role of phonosurgery. Case series with chart review. Tertiary care center. Analysis was performed on patients with Current Procedural Terminology code 31545. Operative reports with a primary lesion and contralateral RL were included. Outcomes included the Voice Handicap Index-10 (VHI-10) and GRBAS (grade, roughness, breathiness, asthenia, and strain) scale, lesion persistence/recurrence, mucosal wave, and edge character based on blinded videostroboscopy review. A nomenclature was developed based on intraoperative RLs (n = 30), defined by lesion consistency (fibrous or polypoid) and relationship to normal VF edge (gradual or steep). Reactive lesion treatment included no intervention, excision, potassium titanyl phosphate laser, steroid injection, or a combination thereof. Observations included the following: inconsistent treatment modalities were employed, excision of RLs did not yield better outcomes, fibrous RLs were more likely to persist and polypoid lesions more likely to recur, gradual lesions were more likely to remain disease free, and most treatments showed improved mucosal wave, VHI-10, and GRBAS. Reactive lesions have not been well classified, and treatments are based on subjective intraoperative decision making with unpredictable outcomes. The nomenclature proposed will allow for a better definition of the RL and provide a framework for future research to identify optimal treatment. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

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.

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 ...

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....

Stochastic reactive power market with volatility of wind power considering voltage security

International Nuclear Information System (INIS)

Kargarian, A.; Raoofat, M.

2011-01-01

While wind power generation is growing rapidly around the globe; its stochastic nature affects the system operation in many different aspects. In this paper, the impact of wind power volatility on the reactive power market is taken into account. The paper presents a novel stochastic method for optimal reactive power market clearing considering voltage security and volatile nature of the wind. The proposed optimization algorithm uses a multiobjective nonlinear programming technique to minimize market payment and simultaneously maximize voltage security margin. Considering a set of probable wind speeds, in the first stage, the proposed algorithm seeks to minimize expected system payment which is summation of reactive power payment and transmission loss cost. The object of the second stage is maximization of expected voltage security margin to increase the system loadability and security. Finally, in the last stage, a multiobjective function is presented to schedule the stochastic reactive power market using results of two previous stages. The proposed algorithm is applied to IEEE 14-bus test system. As a benchmark, Monte Carlo Simulation method is utilized to simulate the actual market of given period of time to evaluate results of the proposed algorithm, and satisfactory results are achieved. -- Highlights: →The paper proposes a new algorithm for stochastic reactive power market clearing. →The stochastic nature of the wind which impacts the system operation and market clearing process, is taken into account. →The paper suggests an expected voltage stability margin and optimizes it in conjunction with expected total market payment. →To clear the market with two mentioned objective functions, a three-stage multiobjective nonlinear programming is implemented. →Also, a simple method is suggested to determine a suitable priority coefficient between two individual objective functions.

Prediction of BP Reactivity to Talking Using Hybrid Soft Computing Approaches

Directory of Open Access Journals (Sweden)

Gurmanik Kaur

2014-01-01

Full Text Available High blood pressure (BP is associated with an increased risk of cardiovascular diseases. Therefore, optimal precision in measurement of BP is appropriate in clinical and research studies. In this work, anthropometric characteristics including age, height, weight, body mass index (BMI, and arm circumference (AC were used as independent predictor variables for the prediction of BP reactivity to talking. Principal component analysis (PCA was fused with artificial neural network (ANN, adaptive neurofuzzy inference system (ANFIS, and least square-support vector machine (LS-SVM model to remove the multicollinearity effect among anthropometric predictor variables. The statistical tests in terms of coefficient of determination (R2, root mean square error (RMSE, and mean absolute percentage error (MAPE revealed that PCA based LS-SVM (PCA-LS-SVM model produced a more efficient prediction of BP reactivity as compared to other models. This assessment presents the importance and advantages posed by PCA fused prediction models for prediction of biological variables.

Prediction of BP reactivity to talking using hybrid soft computing approaches.

Science.gov (United States)

Kaur, Gurmanik; Arora, Ajat Shatru; Jain, Vijender Kumar

2014-01-01

High blood pressure (BP) is associated with an increased risk of cardiovascular diseases. Therefore, optimal precision in measurement of BP is appropriate in clinical and research studies. In this work, anthropometric characteristics including age, height, weight, body mass index (BMI), and arm circumference (AC) were used as independent predictor variables for the prediction of BP reactivity to talking. Principal component analysis (PCA) was fused with artificial neural network (ANN), adaptive neurofuzzy inference system (ANFIS), and least square-support vector machine (LS-SVM) model to remove the multicollinearity effect among anthropometric predictor variables. The statistical tests in terms of coefficient of determination (R (2)), root mean square error (RMSE), and mean absolute percentage error (MAPE) revealed that PCA based LS-SVM (PCA-LS-SVM) model produced a more efficient prediction of BP reactivity as compared to other models. This assessment presents the importance and advantages posed by PCA fused prediction models for prediction of biological variables.

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

MOS-Based Multiuser Multiapplication Cross-Layer Optimization for Mobile Multimedia Communication

Directory of Open Access Journals (Sweden)

Shoaib Khan

2007-01-01

Full Text Available We propose a cross-layer optimization strategy that jointly optimizes the application layer, the data-link layer, and the physical layer of a wireless protocol stack using an application-oriented objective function. The cross-layer optimization framework provides efficient allocation of wireless network resources across multiple types of applications run by different users to maximize network resource usage and user perceived quality of service. We define a novel optimization scheme based on the mean opinion score (MOS as the unifying metric over different application classes. Our experiments, applied to scenarios where users simultaneously run three types of applications, namely voice communication, streaming video and file download, confirm that MOS-based optimization leads to significant improvement in terms of user perceived quality when compared to conventional throughput-based optimization.

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.

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.

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.

Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods

Science.gov (United States)

Gong, W.; Duan, Q.; Huo, X.

2017-12-01

Parameter calibration has been demonstrated as an effective way to improve the performance of dynamic models, such as hydrological models, land surface models, weather and climate models etc. Traditional optimization algorithms usually cost a huge number of model evaluations, making dynamic model calibration very difficult, or even computationally prohibitive. With the help of a serious of recently developed adaptive surrogate-modelling based optimization methods: uni-objective optimization method ASMO, multi-objective optimization method MO-ASMO, and probability distribution estimation method ASMO-PODE, the number of model evaluations can be significantly reduced to several hundreds, making it possible to calibrate very expensive dynamic models, such as regional high resolution land surface models, weather forecast models such as WRF, and intermediate complexity earth system models such as LOVECLIM. This presentation provides a brief introduction to the common framework of adaptive surrogate-based optimization algorithms of ASMO, MO-ASMO and ASMO-PODE, a case study of Common Land Model (CoLM) calibration in Heihe river basin in Northwest China, and an outlook of the potential applications of the surrogate-based optimization methods.

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

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2014-01-01

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

A comparative study on stress and compliance based structural topology optimization

Science.gov (United States)

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

2017-10-01

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

Three-dimensional core analysis on a super fast reactor with negative local void reactivity

International Nuclear Information System (INIS)

Cao Liangzhi; Oka, Yoshiaki; Ishiwatari, Yuki; Ikejiri, Satoshi

2009-01-01

Keeping negative void reactivity throughout the cycle life is one of the most important requirements for the design of a supercritical water-cooled fast reactor (super fast reactor). Previous conceptual design has negative overall void reactivity. But the local void reactivity, which is defined as the reactivity change when the coolant of one fuel assembly disappears, also needs to be kept negative throughout the cycle life because the super fast reactor is designed with closed fuel assemblies. The mechanism of the local void reactivity is theoretically analyzed from the neutrons balance point of view. Three-dimensional neutronics/thermal-hydraulic coupling calculation is employed to analyze the characteristics of the super fast reactor including the local void reactivity. Some configurations of the core are optimized to decrease the local void reactivity. A reference core is successfully designed with keeping both overall and local void reactivity negative. The maximum local void reactivity is less than -30 pcm

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

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).

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).

Genetic fuzzy system predicting contractile reactivity patterns of small arteries

DEFF Research Database (Denmark)

Tang, J; Sheykhzade, Majid; Clausen, B F

2014-01-01

strategies. Results show that optimized fuzzy systems (OFSs) predict contractile reactivity of arteries accurately. In addition, OFSs identified significant differences that were undetectable using conventional analysis in the responses of arteries between groups. We concluded that OFSs may be used...

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.

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.

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...

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

Optimization of reload core design for PWR and application to Qinshan Nuclear Power Plant

International Nuclear Information System (INIS)

Shen Wei; Zhongsheng Xie; Banghua Yin

1995-01-01

A direct efficient optimization technique has been effected for automatically optimizing the reload of PWR. The objective functions include: maximization of end-of-cycle (EOC) reactivity and maximization of average discharge burnup. The fuel loading optimization and burnable poison (BP) optimization are separated into two stages by using Haling principle. In the first stage, the optimum fuel reloading pattern without BP is determined by the Linear Programming method using enrichments as control variable. In the second stage the optimum BP allocation is determined by the Flexible Tolerance Method using the number of BP rods as control variable. A practical and efficient PWR reloading optimization program based on above theory has been encoded and successfully applied to Qinshan Nuclear Power Plant(QNP)cycle 2 reloading design

Sleeping on the rubber-hand illusion: Memory reactivation during sleep facilitates multisensory recalibration.

Science.gov (United States)

Honma, Motoyasu; Plass, John; Brang, David; Florczak, Susan M; Grabowecky, Marcia; Paller, Ken A

2016-01-01

Plasticity is essential in body perception so that physical changes in the body can be accommodated and assimilated. Multisensory integration of visual, auditory, tactile, and proprioceptive signals contributes both to conscious perception of the body's current state and to associated learning. However, much is unknown about how novel information is assimilated into body perception networks in the brain. Sleep-based consolidation can facilitate various types of learning via the reactivation of networks involved in prior encoding or through synaptic down-scaling. Sleep may likewise contribute to perceptual learning of bodily information by providing an optimal time for multisensory recalibration. Here we used methods for targeted memory reactivation (TMR) during slow-wave sleep to examine the influence of sleep-based reactivation of experimentally induced alterations in body perception. The rubber-hand illusion was induced with concomitant auditory stimulation in 24 healthy participants on 3 consecutive days. While each participant was sleeping in his or her own bed during intervening nights, electrophysiological detection of slow-wave sleep prompted covert stimulation with either the sound heard during illusion induction, a counterbalanced novel sound, or neither. TMR systematically enhanced feelings of bodily ownership after subsequent inductions of the rubber-hand illusion. TMR also enhanced spatial recalibration of perceived hand location in the direction of the rubber hand. This evidence for a sleep-based facilitation of a body-perception illusion demonstrates that the spatial recalibration of multisensory signals can be altered overnight to stabilize new learning of bodily representations. Sleep-based memory processing may thus constitute a fundamental component of body-image plasticity.

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.

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.

Process intensification for biodiesel production from Jatropha curcas L. seeds: Supercritical reactive extraction process parameters study

International Nuclear Information System (INIS)

Lim, Steven; Lee, Keat Teong

2013-01-01

Highlights: ► Investigation of supercritical reactive extraction process for biodiesel production. ► Focus is given on optimizing methyl esters yield for Jatropha curcas L. seeds. ► Influence of process parameters to the reaction are discussed thoroughly. ► Comparison between the novel reaction with conventional process are studied. ► High methyl esters yield can be obtained without pre-extraction and catalyst. -- Abstract: In a bid to increase the cost competitiveness of biodiesel production against mineral diesel, process intensification has been studied for numerous biodiesel processing technologies. Subsequently, reactive extraction or in situ transesterification is actively being explored in which the solid oil-bearing seeds are used as the reactant directly with short-chain alcohol. This eliminates separate oil extraction process and combines both extraction and transesterification in a single unit. Supercritical reactive extraction takes one step further by substituting the role of catalyst with supercritical conditions to achieve higher yield and shorter processing time. In this work, supercritical reactive extraction with methanol was carried out in a high-pressure batch reactor to produce fatty acid methyl esters (FAMEs) from Jatropha curcas L. seeds. Material and process parameters including space loading, solvent to seed ratio, co-solvent (n-hexane) to seed ratio, reaction temperature, reaction time and mixing intensity were varied one at a time and optimized based on two responses i.e. extraction efficiency, M extract and FAME yield, F y . The optimum responses for supercritical reactive extraction obtained were 104.17% w/w and 99.67% w/w (relative to 100% lipid extraction with n-hexane) for M extract and F y respectively under the following conditions: 54.0 ml/g space loading, 5.0 ml/g methanol to seeds ratio, 300 °C, 9.5 MPa (Mega Pascal), 30 min reaction time and without n-hexane as co-solvent or any agitation source. This proved that

Blackout risk prevention in a smart grid based flexible optimal strategy using Grey Wolf-pattern search algorithms

International Nuclear Information System (INIS)

Mahdad, Belkacem; Srairi, K.

2015-01-01

Highlights: • A generalized optimal security power system planning strategy for blackout risk prevention is proposed. • A Grey Wolf Optimizer dynamically coordinated with Pattern Search algorithm is proposed. • A useful optimized database dynamically generated considering margin loading stability under severe faults. • The robustness and feasibility of the proposed strategy is validated in the standard IEEE 30 Bus system. • The proposed planning strategy will be useful for power system protection coordination and control. - Abstract: Developing a flexible and reliable power system planning strategy under critical situations is of great importance to experts and industrials to minimize the probability of blackouts occurrence. This paper introduces the first stage of this practical strategy by the application of Grey Wolf Optimizer coordinated with pattern search algorithm for solving the security smart grid power system management under critical situations. The main objective of this proposed planning strategy is to prevent the practical power system against blackout due to the apparition of faults in generating units or important transmission lines. At the first stage the system is pushed to its margin stability limit, the critical loads shedding are selected using voltage stability index. In the second stage the generator control variables, the reactive power of shunt and dynamic compensators are adjusted in coordination with minimization the active and reactive power at critical loads to maintain the system at security state to ensure service continuity. The feasibility and efficiency of the proposed strategy is applied to IEEE 30-Bus test system. Results are promising and prove the practical efficiency of the proposed strategy to ensure system security under critical situations

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.

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....

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)

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.

Reliability-based trajectory optimization using nonintrusive polynomial chaos for Mars entry mission

Science.gov (United States)

Huang, Yuechen; Li, Haiyang

2018-06-01

This paper presents the reliability-based sequential optimization (RBSO) method to settle the trajectory optimization problem with parametric uncertainties in entry dynamics for Mars entry mission. First, the deterministic entry trajectory optimization model is reviewed, and then the reliability-based optimization model is formulated. In addition, the modified sequential optimization method, in which the nonintrusive polynomial chaos expansion (PCE) method and the most probable point (MPP) searching method are employed, is proposed to solve the reliability-based optimization problem efficiently. The nonintrusive PCE method contributes to the transformation between the stochastic optimization (SO) and the deterministic optimization (DO) and to the approximation of trajectory solution efficiently. The MPP method, which is used for assessing the reliability of constraints satisfaction only up to the necessary level, is employed to further improve the computational efficiency. The cycle including SO, reliability assessment and constraints update is repeated in the RBSO until the reliability requirements of constraints satisfaction are satisfied. Finally, the RBSO is compared with the traditional DO and the traditional sequential optimization based on Monte Carlo (MC) simulation in a specific Mars entry mission to demonstrate the effectiveness and the efficiency of the proposed method.

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.

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.

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.

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.

Three-Phase AC Optimal Power Flow Based Distribution Locational Marginal Price: Preprint

Energy Technology Data Exchange (ETDEWEB)

Yang, Rui; Zhang, Yingchen

2017-05-17

Designing market mechanisms for electricity distribution systems has been a hot topic due to the increased presence of smart loads and distributed energy resources (DERs) in distribution systems. The distribution locational marginal pricing (DLMP) methodology is one of the real-time pricing methods to enable such market mechanisms and provide economic incentives to active market participants. Determining the DLMP is challenging due to high power losses, the voltage volatility, and the phase imbalance in distribution systems. Existing DC Optimal Power Flow (OPF) approaches are unable to model power losses and the reactive power, while single-phase AC OPF methods cannot capture the phase imbalance. To address these challenges, in this paper, a three-phase AC OPF based approach is developed to define and calculate DLMP accurately. The DLMP is modeled as the marginal cost to serve an incremental unit of demand at a specific phase at a certain bus, and is calculated using the Lagrange multipliers in the three-phase AC OPF formulation. Extensive case studies have been conducted to understand the impact of system losses and the phase imbalance on DLMPs as well as the potential benefits of flexible resources.

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.

Fuel cycles with high fuel burn-up: analysis of reactivity coefficients

International Nuclear Information System (INIS)

Kryuchkov, E.F.; Shmelev, A.N.; Ternovykh, M.J.; Tikhomirov, G.V.; Jinhong, L.; Saito, M.

2003-01-01

Fuel cycles of light-water reactors (LWR) with high fuel burn-up (above 100 MWd/kg), as a rule, involve large amounts of fissionable materials. It leads to forming the neutron spectrum harder than that in traditional LWR. Change of neutron spectrum and significant amount of non-traditional isotopes (for example, 237 Np, 238 Pu, 231 Pa, 232 U) in such fuel compositions can alter substantially reactivity coefficients as compared with traditional uranium-based fuel. The present work addresses the fuel cycles with high fuel burn-up which are based on Th-Pa-U and U-Np-Pu fuel compositions. Numerical analyses are carried out to determine effective neutron multiplication factor and void reactivity coefficient (VRC) for different values of fuel burn-up and different lattice parameters. The algorithm is proposed for analysis of isotopes contribution to these coefficients. Various ways are considered to upgrade safety of nuclear fuel cycles with high fuel burn-up. So, the results obtained in this study have demonstrated that: -1) Non-traditional fuel compositions developed for achievement of high fuel burn-up in LWR can possess positive values of reactivity coefficients that is unacceptable from the reactor operation safety point of view; -2) The lattice pitch of traditional LWR is not optimal for non-traditional fuel compositions, the increased value of the lattice pitch leads to larger value of initial reactivity margin and provides negative VRC within sufficiently broad range of coolant density; -3) Fuel burn-up has an insignificant effect on VRC dependence on coolant density, so, the measures undertaken to suppress positive VRC of fresh fuel will be effective for partially burnt-up fuel compositions also and; -4) Increase of LWR core height and introduction of additional moderators into the fuel lattice can be used as the ways to reach negative VRC values for full range of possible coolant density variations

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...

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

Composition Optimization of Lithium-Based Ternary Alloy Blankets for Fusion Reactors

Science.gov (United States)

Jolodosky, Alejandra

The goal of this dissertation is to examine the neutronic properties of a novel type of fusion reactor blanket material in the form of lithium-based ternary alloys. Pure liquid lithium, first proposed as a blanket for fusion reactors, is utilized as both a tritium breeder and a coolant. It has many attractive features such as high heat transfer and low corrosion properties, but most importantly, it has a very high tritium solubility and results in very low levels of tritium permeation throughout the facility infrastructure. However, lithium metal vigorously reacts with air and water and presents plant safety concerns including degradation of the concrete containment structure. The work of this thesis began as a collaboration with Lawrence Livermore National Laboratory in an effort to develop a lithium-based ternary alloy that can maintain the beneficial properties of lithium while reducing the reactivity concerns. The first studies down-selected alloys based on the analysis and performance of both neutronic and activation characteristics. First, 3-D Monte Carlo calculations were performed to evaluate two main neutronics performance parameters for the blanket: tritium breeding ratio (TBR), and energy multiplication factor (EMF). Alloys with adequate results based on TBR and EMF calculations were considered for activation analysis. Activation simulations were executed with 50 years of irradiation and 300 years of cooling. It was discovered that bismuth is a poor choice due to achieving the highest decay heat, contact dose rates, and accident doses. In addition, it does not meet the waste disposal ratings (WDR). The straightforward approach to obtain Monte Carlo TBR and EMF results required 231 simulations per alloy and became computationally expensive, time consuming, and inefficient. Consequently, alternate methods were pursued. A collision history-based methodology recently developed for the Monte Carlo code Serpent, calculates perturbation effects on practically

Reactive power compensator

Science.gov (United States)

El-Sharkawi, Mohamed A.; Venkata, Subrahmanyam S.; Chen, Mingliang; Andexler, George; Huang, Tony

1992-01-01

A system and method for determining and providing reactive power compensation for an inductive load. A reactive power compensator (50,50') monitors the voltage and current flowing through each of three distribution lines (52a, 52b, 52c), which are supplying three-phase power to one or more inductive loads. Using signals indicative of the current on each of these lines when the voltage waveform on the line crosses zero, the reactive power compensator determines a reactive power compensator capacitance that must be connected to the lines to maintain a desired VAR level, power factor, or line voltage. Alternatively, an operator can manually select a specific capacitance for connection to each line, or the capacitance can be selected based on a time schedule. The reactive power compensator produces control signals, which are coupled through optical fibers (102/106) to a switch driver (110, 110') to select specific compensation capacitors (112) for connections to each line. The switch driver develops triggering signals that are supplied to a plurality of series-connected solid state switches (350), which control charge current in one direction in respect to ground for each compensation capacitor. During each cycle, current flows from ground to charge the capacitors as the voltage on the line begins to go negative from its positive peak value. The triggering signals are applied to gate the solid state switches into a conducting state when the potential on the lines and on the capacitors reaches a negative peak value, thereby minimizing both the potential difference and across the charge current through the switches when they begin to conduct. Any harmonic distortion on the potential and current carried by the lines is filtered out from the current and potential signals used by the reactive power compensator so that it does not affect the determination of the required reactive compensation.

Reactive power compensator

Energy Technology Data Exchange (ETDEWEB)

El-Sharkawi, Mohamed A. (Renton, WA); Venkata, Subrahmanyam S. (Woodinville, WA); Chen, Mingliang (Kirkland, WA); Andexler, George (Everett, WA); Huang, Tony (Seattle, WA)

1992-01-01

A system and method for determining and providing reactive power compensation for an inductive load. A reactive power compensator (50,50') monitors the voltage and current flowing through each of three distribution lines (52a, 52b, 52c), which are supplying three-phase power to one or more inductive loads. Using signals indicative of the current on each of these lines when the voltage waveform on the line crosses zero, the reactive power compensator determines a reactive power compensator capacitance that must be connected to the lines to maintain a desired VAR level, power factor, or line voltage. Alternatively, an operator can manually select a specific capacitance for connection to each line, or the capacitance can be selected based on a time schedule. The reactive power compensator produces control signals, which are coupled through optical fibers (102/106) to a switch driver (110, 110') to select specific compensation capacitors (112) for connections to each line. The switch driver develops triggering signals that are supplied to a plurality of series-connected solid state switches (350), which control charge current in one direction in respect to ground for each compensation capacitor. During each cycle, current flows from ground to charge the capacitors as the voltage on the line begins to go negative from its positive peak value. The triggering signals are applied to gate the solid state switches into a conducting state when the potential on the lines and on the capacitors reaches a negative peak value, thereby minimizing both the potential difference and across the charge current through the switches when they begin to conduct. Any harmonic distortion on the potential and current carried by the lines is filtered out from the current and potential signals used by the reactive power compensator so that it does not affect the determination of the required reactive compensation.

A QFD-based optimization method for a scalable product platform

Science.gov (United States)

Luo, Xinggang; Tang, Jiafu; Kwong, C. K.

2010-02-01

In order to incorporate the customer into the early phase of the product development cycle and to better satisfy customers' requirements, this article adopts quality function deployment (QFD) for optimal design of a scalable product platform. A five-step QFD-based method is proposed to determine the optimal values for platform engineering characteristics (ECs) and non-platform ECs of the products within a product family. First of all, the houses of quality (HoQs) for all product variants are developed and a QFD-based optimization approach is used to determine the optimal ECs for each product variant. Sensitivity analysis is performed for each EC with respect to overall customer satisfaction (OCS). Based on the obtained sensitivity indices of ECs, a mathematical model is established to simultaneously optimize the values of the platform and the non-platform ECs. Finally, by comparing and analysing the optimal solutions with different number of platform ECs, the ECs with which the worst OCS loss can be avoided are selected as platform ECs. An illustrative example is used to demonstrate the feasibility of this method. A comparison between the proposed method and a two-step approach is conducted on the example. The comparison shows that, as a kind of single-stage approach, the proposed method yields better average degree of customer satisfaction due to the simultaneous optimization of platform and non-platform ECs.

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.

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.

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....

The interactions of design, control and operability in reactive distillation systems

DEFF Research Database (Denmark)

Georgiadis, M.C.; Schenk, Myrian Andrea; Pistikopoulos, Stratos

2002-01-01

is a strong function of the process design and potential operability bottlenecks are identified. In the second approach, the process design and the control system are optimized simultaneously leading to a more economically beneficial and better controlled system than that obtained using the sequential......In this work the design and control of a reactive distillation column, described by a rigorous dynamic model, is tackled via two different optimization approaches. In the first, the steady-state process design and the control system are optimized sequentially. It is shown that operability...

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

Voltage Profile Enhancement and Reduction of Real Power loss by Hybrid Biogeography Based Artificial Bee Colony algorithm

Directory of Open Access Journals (Sweden)

K. Lenin

2014-04-01

Full Text Available This paper presents Hybrid Biogeography algorithm for solving the multi-objective reactive power dispatch problem in a power system. Real Power Loss minimization and maximization of voltage stability margin are taken as the objectives. Artificial bee colony optimization (ABC is quick and forceful algorithm for global optimization. Biogeography-Based Optimization (BBO is a new-fangled biogeography inspired algorithm. It mainly utilizes the biogeography-based relocation operator to share the information among solutions. In this work, a hybrid algorithm with BBO and ABC is projected, and named as HBBABC (Hybrid Biogeography based Artificial Bee Colony Optimization, for the universal numerical optimization problem. HBBABC merge the searching behavior of ABC with that of BBO. Both the algorithms have different solution probing tendency like ABC have good exploration probing tendency while BBO have good exploitation probing tendency.  HBBABC used to solve the reactive power dispatch problem and the proposed technique has been tested in standard IEEE30 bus test system.

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...

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.

A New Approach to Site Demand-Based Level Inventory Optimization

Science.gov (United States)

2016-06-01

Note: If probability distributions are estimated based on mean and variance , use ˆ qix  and 2ˆ( )qi to generate these. q in , number of...TO SITE DEMAND-BASED LEVEL INVENTORY OPTIMIZATION by Tacettin Ersoz June 2016 Thesis Advisor: Javier Salmeron Second Reader: Emily...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE A NEW APPROACH TO SITE DEMAND-BASED LEVEL INVENTORY OPTIMIZATION 5. FUNDING NUMBERS 6

General structure and functions of the OPAL optimization system

International Nuclear Information System (INIS)

Mikolas, P.; Sustek, J.; Svarny, J.

2005-01-01

Presented version of OPAL - the in core fuel management system is under development also for core loading optimization of NPP Temelin (WWER-1000 type reactor). Description of the algorithm of separate modules was presented in several AER papers. The optimization process of NPP Temelin loading patterns comprises problems like preparation input data for NPP SW, loading searching, fixing and splitting of fuel enrichments, BP-assignment, FA rotation and fuel cycle economics. In application for NPP Temelin has been used NPP Temelin code system (spectral code with macrocode). The objective of fuel management is to design a fuel-loading scheme that is capable of producing the required energy at the minimum cost while satisfying the safety constraints. Usually the objectives are: a) To meet the energy production requirements (loaded fuel should have sufficient reactivity that covers reactivity defects associated with startup as well as reactivity loss due to the fuel depletion); b) To satisfy all safety-related limits (loaded fuel should preserve adequate power peaking limits (given namely LOCA), shutdown margins and no positive Moderator Temperature Coefficient (MTC); c) To minimize the power generation cost ($/kWh(e)). Flow of optimization process OPAL management system is in detail described and application for NPP Temelin cores optimization presented (Authors)

External Quality Control for Dried Blood Spot Based C-reactive Protein Assay: Experience from the Indonesia Family Life Survey and the Longitudinal Aging Study in India

Science.gov (United States)

Hu, Peifeng; Herningtyas, Elizabeth H.; Kale, Varsha; Crimmins, Eileen M.; Risbud, Arun R.; McCreath, Heather; Lee, Jinkook; Strauss, John; O’Brien, Jennifer C.; Bloom, David E.; Seeman, Teresa E.

2015-01-01

Measurement of C-reactive protein, a marker of inflammation, in dried blood spots has been increasingly incorporated in community-based social surveys internationally. Although the dried blood spot based CRP assay protocol has been validated in the United States, it remains unclear whether laboratories in other less developed countries can generate C-reactive protein results of similar quality. We therefore conducted external quality monitoring for dried blood spot based C-reactive protein measurement for the Indonesia Family Life Survey and the Longitudinal Aging Study in India. Our results show that dried blood spot based C-reactive protein results in these two countries have excellent and consistent correlations with serum-based values and dried blood spot based results from the reference laboratory in the United States. Even though the results from duplicate samples may have fluctuations in absolute values over time, the relative order of C-reactive protein levels remains similar and the estimates are reasonably precise for population-based studies that investigate the association between socioeconomic factors and health. PMID:25879265

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)

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)

A market-based optimization approach to sensor and resource management

Science.gov (United States)

Schrage, Dan; Farnham, Christopher; Gonsalves, Paul G.

2006-05-01

Dynamic resource allocation for sensor management is a problem that demands solutions beyond traditional approaches to optimization. Market-based optimization applies solutions from economic theory, particularly game theory, to the resource allocation problem by creating an artificial market for sensor information and computational resources. Intelligent agents are the buyers and sellers in this market, and they represent all the elements of the sensor network, from sensors to sensor platforms to computational resources. These agents interact based on a negotiation mechanism that determines their bidding strategies. This negotiation mechanism and the agents' bidding strategies are based on game theory, and they are designed so that the aggregate result of the multi-agent negotiation process is a market in competitive equilibrium, which guarantees an optimal allocation of resources throughout the sensor network. This paper makes two contributions to the field of market-based optimization: First, we develop a market protocol to handle heterogeneous goods in a dynamic setting. Second, we develop arbitrage agents to improve the efficiency in the market in light of its dynamic nature.

Development of a UNIX network compatible reactivity computer

International Nuclear Information System (INIS)

Sanchez, R.F.; Edwards, R.M.

1996-01-01

A state-of-the-art UNIX network compatible controller and UNIX host workstation with MATLAB/SIMULINK software were used to develop, implement, and validate a digital reactivity calculation. An objective of the development was to determine why a Macintosh-based reactivity computer reactivity output drifted intolerably

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.

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.

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.

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.

Multi-objective optimal planning of the stand-alone microgrid system based on different benefit subjects

International Nuclear Information System (INIS)

Guo, Li; Wang, Nan; Lu, Hai; Li, Xialin; Wang, Chengshan

2016-01-01

As an important means to realize the energetic complementarity and improve the efficiency of renewable resources, the stand-alone microgrid (SAMG) system gains attention increasingly, especially in islands and remote areas. In this paper, considering the interest conflict of the distribution company and the distributed generation owner, a new multi-objective optimal planning model is formulated for medium voltage SAMG. Besides, to avoid the power constraint of distributed generation (DG) once the over-limit voltage occurs, a novel two-step power dispatch control method including the voltage regulation strategy is proposed, in which the absorption of distributed power by energy storage system (ESS) and the reactive power adjustment though its power control system are used to regulate voltage. The goal of this paper is to search the Pareto-optimal front of the site and capacity of DG as well as the contract price between both parties, and thus can provide effective references for practical planning of SAMG. Considering the high cost of ESS, the investment analysis of ESS is also discussed in the paper. - Highlights: • A multi-objective planning model based on different benefit subjects is proposed. • A two-step power dispatch method including the voltage regulation is proposed. • The economical efficiency of the proposed model is analyzed. • The effective reference for the stand-alone microgrid planning is provided.

Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

OpenAIRE

Yumin, Dong; Li, Zhao

2014-01-01

Quantum behaved particle swarm algorithm is a new intelligent optimization algorithm; the algorithm has less parameters and is easily implemented. In view of the existing quantum behaved particle swarm optimization algorithm for the premature convergence problem, put forward a quantum particle swarm optimization algorithm based on artificial fish swarm. The new algorithm based on quantum behaved particle swarm algorithm, introducing the swarm and following activities, meanwhile using the a...

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

Directory of Open Access Journals (Sweden)

Shouheng Tuo

Full Text Available Harmony Search (HS and Teaching-Learning-Based Optimization (TLBO as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

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.

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.

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.

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.

Feasibility and parametric study of tetrahydrofuran dehydration using reactive distillation with low energy requirement

International Nuclear Information System (INIS)

Tavan, Yadollah

2014-01-01

A new configuration of a RD (reactive distillation) process is investigated to break the THF (tetrahydrofuran)/water azeotrope using Hysys process software. The main module is a column system containing the reaction of EO (ethylene oxide) with water, in which top and bottom streams are the desired products, THF and EG (ethylene glycol), respectively. This contribution explores feasibility of using the reaction in the RD column and also describes the influence of reflux ratio, reaction trays, operating pressure and feed–inlet locations of the RD column in simulation environment. The results show that high purities of EG and THF are simultaneously obtained by this novel technique leading to more profits of the RD process. The optimal design of the RD process is obtained by minimizing the energy demand and the optimum number of reactive trays is found to be 10. Furthermore, minimum energy demand is observed when the column operates at atmospheric pressure with reflux ratio of 1.25. Particularly, it is found that the optimal reboiler duty per unit THF produced is reduced from 32 to 3.7% for the new process as compared to the conventional one, while both schemes predict similar outputs. - Highlights: • A reactive distillation column is proposed to produce pure tetrahydrofuran. • The tetrahydrofuran-water azeotrope is broken using reactive distillation column. • High energy saving (88%) is found for the reactive distillation process

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

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.

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...

Design and Development of Virtual Reactivity System for PWR

International Nuclear Information System (INIS)

Anwar, M. I.

2012-01-01

The reactivity monitoring and investigation is an important mean to ensure the safety operation of a nuclear power plant. But the reactivity of the nuclear reactor usually cannot be directly measured. It should be computed with certain estimation method. In this thesis, an effort has been made using an artificial neural network and highly fluctuating experimental data for predicting the total reactivity of the nuclear reactor based on all components of net reactivity. This virtual reactivity system is designed by taking advantage of neural network's nonlinear mapping capability. Based on analysis of the reactivity contributing factors, several neural network models are built separately for control rod, boron, poisons, fuel Doppler Effect and moderator effect. Extensive simulation and validation tests for PWR show that satisfied results have been obtained with the proposed approach. It presents a new idea to estimate the PWR's reactivity using artificial intelligence. All the design and simulation work is carried out in MATLAB and a real time programming environment is chosen for the computation and prediction of reactivity. (author)

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.

Portfolio optimization by using linear programing models based on genetic algorithm

Science.gov (United States)

Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

2018-01-01

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

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.

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.

Phase-Division-Based Dynamic Optimization of Linkages for Drawing Servo Presses

Science.gov (United States)

Zhang, Zhi-Gang; Wang, Li-Ping; Cao, Yan-Ke

2017-11-01

Existing linkage-optimization methods are designed for mechanical presses; few can be directly used for servo presses, so development of the servo press is limited. Based on the complementarity of linkage optimization and motion planning, a phase-division-based linkage-optimization model for a drawing servo press is established. Considering the motion-planning principles of a drawing servo press, and taking account of work rating and efficiency, the constraints of the optimization model are constructed. Linkage is optimized in two modes: use of either constant eccentric speed or constant slide speed in the work segments. The performances of optimized linkages are compared with those of a mature linkage SL4-2000A, which is optimized by a traditional method. The results show that the work rating of a drawing servo press equipped with linkages optimized by this new method improved and the root-mean-square torque of the servo motors is reduced by more than 10%. This research provides a promising method for designing energy-saving drawing servo presses with high work ratings.

Twelve Theses on Reactive Rules for the Web

OpenAIRE

Bry, François; Eckert, Michael; Patranjan, Paula-Lavinia

2006-01-01

Reactivity, the ability to detect events and respond to them automatically through reactive programs, is a key requirement in many present-day information systems. Work on Web Services re ects the need for support of reactivity on a higher abstraction level than just message exchange by HTTP. This article presents the composite event query facilities of the reactive rule-based programming language XChange. Composite events are important in the dynamic world of the Web whe...

Efficient approach for reliability-based optimization based on weighted importance sampling approach

International Nuclear Information System (INIS)

Yuan, Xiukai; Lu, Zhenzhou

2014-01-01

An efficient methodology is presented to perform the reliability-based optimization (RBO). It is based on an efficient weighted approach for constructing an approximation of the failure probability as an explicit function of the design variables which is referred to as the ‘failure probability function (FPF)’. It expresses the FPF as a weighted sum of sample values obtained in the simulation-based reliability analysis. The required computational effort for decoupling in each iteration is just single reliability analysis. After the approximation of the FPF is established, the target RBO problem can be decoupled into a deterministic one. Meanwhile, the proposed weighted approach is combined with a decoupling approach and a sequential approximate optimization framework. Engineering examples are given to demonstrate the efficiency and accuracy of the presented methodology

Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

International Nuclear Information System (INIS)

Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

2011-01-01

The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species, multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

Reinforcement Learning Based Web Service Compositions for Mobile Business

Science.gov (United States)

Zhou, Juan; Chen, Shouming

In this paper, we propose a new solution to Reactive Web Service Composition, via molding with Reinforcement Learning, and introducing modified (alterable) QoS variables into the model as elements in the Markov Decision Process tuple. Moreover, we give an example of Reactive-WSC-based mobile banking, to demonstrate the intrinsic capability of the solution in question of obtaining the optimized service composition, characterized by (alterable) target QoS variable sets with optimized values. Consequently, we come to the conclusion that the solution has decent potentials in boosting customer experiences and qualities of services in Web Services, and those in applications in the whole electronic commerce and business sector.

Developments in model-based optimization and control distributed control and industrial applications

CERN Document Server

Grancharova, Alexandra; Pereira, Fernando

2015-01-01

This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and desi...

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

Multi-objective optimal dispatch of distributed energy resources

Science.gov (United States)

Longe, Ayomide

This thesis is composed of two papers which investigate the optimal dispatch for distributed energy resources. In the first paper, an economic dispatch problem for a community microgrid is studied. In this microgrid, each agent pursues an economic dispatch for its personal resources. In addition, each agent is capable of trading electricity with other agents through a local energy market. In this paper, a simple market structure is introduced as a framework for energy trades in a small community microgrid such as the Solar Village. It was found that both sellers and buyers benefited by participating in this market. In the second paper, Semidefinite Programming (SDP) for convex relaxation of power flow equations is used for optimal active and reactive dispatch for Distributed Energy Resources (DER). Various objective functions including voltage regulation, reduced transmission line power losses, and minimized reactive power charges for a microgrid are introduced. Combinations of these goals are attained by solving a multiobjective optimization for the proposed ORPD problem. Also, both centralized and distributed versions of this optimal dispatch are investigated. It was found that SDP made the optimal dispatch faster and distributed solution allowed for scalability.

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...

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.

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.

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.

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

Scenario-based stochastic optimal operation of wind, photovoltaic, pump-storage hybrid system in frequency- based pricing

International Nuclear Information System (INIS)

Zare Oskouei, Morteza; Sadeghi Yazdankhah, Ahmad

2015-01-01

Highlights: • Two-stage objective function is proposed for optimization problem. • Hourly-based optimal contractual agreement is calculated. • Scenario-based stochastic optimization problem is solved. • Improvement of system frequency by utilizing PSH unit. - Abstract: This paper proposes the operating strategy of a micro grid connected wind farm, photovoltaic and pump-storage hybrid system. The strategy consists of two stages. In the first stage, the optimal hourly contractual agreement is determined. The second stage corresponds to maximizing its profit by adapting energy management strategy of wind and photovoltaic in coordination with optimum operating schedule of storage device under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources and market prices, generation scheduling is modeled by a stochastic optimization problem. Uncertainties of parameters are modeled by scenario generation and scenario reduction method. A powerful optimization algorithm is proposed using by General Algebraic Modeling System (GAMS)/CPLEX. In order to verify the efficiency of the method, the algorithm is applied to various scenarios with different wind and photovoltaic power productions in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.

Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks.

Science.gov (United States)

Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

2016-07-07

In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles.

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

Science.gov (United States)

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

Spring 5 & reactive streams

CERN Multimedia

CERN. Geneva; Clozel, Brian

2017-01-01

Spring is a framework widely used by the world-wide Java community, and it is also extensively used at CERN. The accelerator control system is constituted of 10 million lines of Java code, spread across more than 1000 projects (jars) developed by 160 software engineers. Around half of this (all server-side Java code) is based on the Spring framework. Warning: the speakers will assume that people attending the seminar are familiar with Java and Spring’s basic concepts. Spring 5.0 and Spring Boot 2.0 updates (45 min) This talk will cover the big ticket items in the 5.0 release of Spring (including Kotlin support, @Nullable and JDK9) and provide an update on Spring Boot 2.0, which is scheduled for the end of the year. Reactive Spring (1h) Spring Framework 5.0 has been released - and it now supports reactive applications in the Spring ecosystem. During this presentation, we'll talk about the reactive foundations of Spring Framework with the Reactor project and the reactive streams specification. We'll al...

Stochastic reactive power dispatch in hybrid power system with intermittent wind power generation

International Nuclear Information System (INIS)

Taghavi, Reza; Seifi, Ali Reza; Samet, Haidar

2015-01-01

Environmental concerns besides fuel costs are the predominant reasons for unprecedented escalating integration of wind turbine on power systems. Operation and planning of power systems are affected by this type of energy due to the intermittent nature of wind speed inputs with high uncertainty in the optimization output variables. Consequently, in order to model this high inherent uncertainty, a PRPO (probabilistic reactive power optimization) framework should be devised. Although MC (Monte-Carlo) techniques can solve the PRPO with high precision, PEMs (point estimate methods) can preserve the accuracy to attain reasonable results when diminishing the computational effort. Also, this paper introduces a methodology for optimally dispatching the reactive power in the transmission system, while minimizing the active power losses. The optimization problem is formulated as a LFP (linear fuzzy programing). The core of the problem lay on generation of 2m + 1 point estimates for solving PRPO, where n is the number of input stochastic variables. The proposed methodology is investigated using the IEEE-14 bus test system equipped with HVDC (high voltage direct current), UPFC (unified power flow controller) and DFIG (doubly fed induction generator) devices. The accuracy of the method is demonstrated in the case study. - Highlights: • This paper uses stochastic loads in optimization process. • AC–DC load flow is modified to use some advantages of DC part in optimization process. • UPFC and DFIG are simulated in a way that could be effective in optimization process. • Fuzzy set has been used as an uncertainty analysis tool in the optimization

Structural Determinants of Alkyne Reactivity in Copper-Catalyzed Azide-Alkyne Cycloadditions

Directory of Open Access Journals (Sweden)

Xiaoguang Zhang

2016-12-01

Full Text Available This work represents our initial effort in identifying azide/alkyne pairs for optimal reactivity in copper-catalyzed azide-alkyne cycloaddition (CuAAC reactions. In previous works, we have identified chelating azides, in particular 2-picolyl azide, as “privileged” azide substrates with high CuAAC reactivity. In the current work, two types of alkynes are shown to undergo rapid CuAAC reactions under both copper(II- (via an induction period and copper(I-catalyzed conditions. The first type of the alkynes bears relatively acidic ethynyl C-H bonds, while the second type contains an N-(triazolylmethylpropargylic moiety that produces a self-accelerating effect. The rankings of reactivity under both copper(II- and copper(I-catalyzed conditions are provided. The observations on how other reaction parameters such as accelerating ligand, reducing agent, or identity of azide alter the relative reactivity of alkynes are described and, to the best of our ability, explained.

Reactive power compensation and loss reduction in large industrial enterprises

Energy Technology Data Exchange (ETDEWEB)

Jovanovic, S; Gajic, B; Mijailovic, S [Institute Nikola Tesla, Beograd (Yugoslavia)

1991-12-01

This paper considers the reactive power compensation and the active power and energy loss reduction of large radial power networks in the Serbian mine and smelting industry. It gives an efficient optimization procedure for positioning and sizing capacitors in large industrial systems integrated with a simple network analysis method. (Author).

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...

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.

DRO: domain-based route optimization scheme for nested mobile networks

Directory of Open Access Journals (Sweden)

Chuang Ming-Chin

2011-01-01

Full Text Available Abstract The network mobility (NEMO basic support protocol is designed to support NEMO management, and to ensure communication continuity between nodes in mobile networks. However, in nested mobile networks, NEMO suffers from the pinball routing problem, which results in long packet transmission delays. To solve the problem, we propose a domain-based route optimization (DRO scheme that incorporates a domain-based network architecture and ad hoc routing protocols for route optimization. DRO also improves the intra-domain handoff performance, reduces the convergence time during route optimization, and avoids the out-of-sequence packet problem. A detailed performance analysis and simulations were conducted to evaluate the scheme. The results demonstrate that DRO outperforms existing mechanisms in terms of packet transmission delay (i.e., better route-optimization, intra-domain handoff latency, convergence time, and packet tunneling overhead.

Demand-Based Optimal Design of Storage Tank with Inerter System

Directory of Open Access Journals (Sweden)

Shiming Zhang

2017-01-01

Full Text Available A parameter optimal design method for a tank with an inerter system is proposed in this study based on the requirements of tank vibration control to improve the effectiveness and efficiency of vibration control. Moreover, a response indicator and a cost control indicator are selected based on the control targets for liquid storage tanks for simultaneously minimizing the dynamic response and controlling costs. These indicators are reformulated through a random vibration analysis under virtual excitation. The problem is then transformed from a multiobjective optimization problem to a single-objective nonlinear problem using the ε-constraint method, which is consistent with the demand-based method. White noise excitation can be used to design the tank with the inerter system under seismic excitation to simplify the calculation. Subsequently, a MATLAB-based calculation program is compiled, and several optimization cases are examined under different excitation conditions. The effectiveness of the demand-based method is proven through a time history analysis. The results show that specific vibration control requirements can be met at the lowest cost with a simultaneous reduction in base shears and overturning base moments.

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.

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.

Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm

International Nuclear Information System (INIS)

Rao, R. Venkata; Rai, Dhiraj P.

2017-01-01

Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).

Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm

Energy Technology Data Exchange (ETDEWEB)

Rao, R. Venkata; Rai, Dhiraj P. [Sardar Vallabhbhai National Institute of Technology, Gujarat (India)

2017-05-15

Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).

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

The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model

Science.gov (United States)

Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

2016-05-01

Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.

A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model

International Nuclear Information System (INIS)

Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao

2014-01-01

Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP. (paper)

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.

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

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).

TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization

Energy Technology Data Exchange (ETDEWEB)

Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

2014-06-15

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, rough beamlet dose calculations is conducted with only a small number of particles 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, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} 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.