Particle Swarm Optimization Based Reactive Power Optimization
Sujin, P R; Linda, M Mary
2010-01-01
Reactive power plays an important role in supporting the real power transfer by maintaining voltage stability and system reliability. It is a critical element for a transmission operator to ensure the reliability of an electric system while minimizing the cost associated with it. The traditional objectives of reactive power dispatch are focused on the technical side of reactive support such as minimization of transmission losses. Reactive power cost compensation to a generator is based on the incurred cost of its reactive power contribution less the cost of its obligation to support the active power delivery. In this paper an efficient Particle Swarm Optimization (PSO) based reactive power optimization approach is presented. The optimal reactive power dispatch problem is a nonlinear optimization problem with several constraints. The objective of the proposed PSO is to minimize the total support cost from generators and reactive compensators. It is achieved by maintaining the whole system power loss as minimum...
Voronoi Diagram Based Optimization of Dynamic Reactive Power Sources
Energy Technology Data Exchange (ETDEWEB)
Huang, Weihong [University of Tennessee (UT); Sun, Kai [University of Tennessee (UT); Qi, Junjian [University of Tennessee (UT); Xu, Yan [ORNL
2015-01-01
Dynamic var sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues or even voltage collapse. This paper proposes a new approach to optimization of the sizes of dynamic var sources at candidate locations by a Voronoi diagram based algorithm. It first disperses sample points of potential solutions in a searching space, evaluates a cost function at each point by barycentric interpolation for the subspaces around the point, and then constructs a Voronoi diagram about cost function values over the entire space. Accordingly, the final optimal solution can be obtained. Case studies on the WSCC 9-bus system and NPCC 140-bus system have validated that the new approach can quickly identify the boundary of feasible solutions in searching space and converge to the global optimal solution.
Opposition-Based Improved PSO for Optimal Reactive Power Dispatch and Voltage Control
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Shengrang Cao
2015-01-01
Full Text Available An opposition-based improved particle swarm optimization algorithm (OIPSO is presented for solving multiobjective reactive power optimization problem. OIPSO uses the opposition learning to improve search efficiency, adopts inertia weight factors to balance global and local exploration, and takes crossover and mutation and neighborhood model strategy to enhance population diversity. Then, a new multiobjective model is built, which includes system network loss, voltage dissatisfaction, and switching operation. Based on the market cost prices, objective functions are converted to least-cost model. In modeling process, switching operation cost is described according to the life cycle cost of transformer, and voltage dissatisfaction penalty is developed considering different voltage quality requirements of customers. The experiment is done on the new mathematical model. Through the simulation of IEEE 30-, 118-bus power systems, the results prove that OIPSO is more efficient to solve reactive power optimization problems and the model is more accurate to reflect the real power system operation.
Optimizing the Pore Structure of Bio-Based ACFs through a Simple KOH–Steam Reactivation
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Yuxiang Huang
2016-05-01
Full Text Available Highly microporous bio-based activated carbon fibers (ACFs were prepared through a simple reactivation method. Sawdust, as the starting material, was liquefied and melt-spun to produce the precursor fibers. Then, the precursor fibers were activated by KOH and reactivated by steam. By varying the conditions of the two activation processes, the formation mechanism of the pore structure was studied, and the result showed that steam reactivation has a positive effect on the development of microporosity. The sample with the optimal condition exhibited the highest specific surface area of 2578 m2·g−1 as well as the largest pore volume of 1.425 cm3·g−1, where micropores contributed 70.3%. Due to its excellent texture properties, the ACF exhibited a high adsorption capacity of 1934 mg/g for iodine.
Distribution Grid Reactive Power Optimization Based on Improved Cloud Particle Swarm Algorithm
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Hongsheng Su
2013-01-01
Full Text Available To resolve the problems that cloud particle swarm optimization(CPSO was easily trapped in local minimum and possessed slow convergence speed and early-maturing during distribution grid reactive power optimization, CPSO algorithm was improved based on cloud digital features in this paper. The method firstly combined Local search with global search together based on solution space transform, where the crossover and mutation operation of the particles were implemented based on normal cloud operator. And then the dramatic achievements were acquired in time-consuming and storage-cost using the improved algorithm. Finally, applied in bus IEEE30 system, the simulation results show that the better global solution is attained using the improved CPSO algorithm, and its convergence speed and accuracy possesses a dramatic improvement.
Hashemi-Dezaki, Hamed; Mohammadalizadeh-Shabestary, Masoud; Askarian-Abyaneh, Hossein; Rezaei-Jegarluei, Mohammad
2014-01-01
In electrical distribution systems, a great amount of power are wasting across the lines, also nowadays power factors, voltage profiles and total harmonic distortions (THDs) of most loads are not as would be desired. So these important parameters of a system play highly important role in wasting money and energy, and besides both consumers and sources are suffering from a high rate of distortions and even instabilities. Active power filters (APFs) are innovative ideas for solving of this adversity which have recently used instantaneous reactive power theory. In this paper, a novel method is proposed to optimize the allocation of APFs. The introduced method is based on the instantaneous reactive power theory in vectorial representation. By use of this representation, it is possible to asses different compensation strategies. Also, APFs proper placement in the system plays a crucial role in either reducing the losses costs and power quality improvement. To optimize the APFs placement, a new objective function has been defined on the basis of five terms: total losses, power factor, voltage profile, THD and cost. Genetic algorithm has been used to solve the optimization problem. The results of applying this method to a distribution network illustrate the method advantages.
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Wanxing Sheng
2016-05-01
Full Text Available In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. Load similarity (LS is defined to measure the degree of similarity between the loads in different days and the calculation method of the load similarity of load random matrix (LRM is presented. By calculating the load similarity between the forecasting random matrix and the random matrix of historical load, the historical reactive power optimization dispatching scheme that most matches the forecasting load can be found for reactive power control usage. The differences of daily load curves between working days and weekends in different seasons are considered in the proposed method. The proposed method is tested on a standard 14 nodes distribution network with three different types of load. The computational result demonstrates that the proposed method for reactive power optimization is fast, feasible and effective in distribution network.
Ant colony search algorithm for optimal reactive power optimization
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Lenin K.
2006-01-01
Full Text Available The paper presents an (ACSA Ant colony search Algorithm for Optimal Reactive Power Optimization and voltage control of power systems. ACSA is a new co-operative agents’ approach, which is inspired by the observation of the behavior of real ant colonies on the topic of ant trial formation and foraging methods. Hence, in the ACSA a set of co-operative agents called "Ants" co-operates to find good solution for Reactive Power Optimization problem. The ACSA is applied for optimal reactive power optimization is evaluated on standard IEEE, 30, 57, 191 (practical test bus system. The proposed approach is tested and compared to genetic algorithm (GA, Adaptive Genetic Algorithm (AGA.
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Bin Zhao
2014-05-01
Full Text Available This study presents the auxiliary damping control with the reactive power loop on the rotor-side converter of doubly-fed induction generator (DFIG-based wind farms to depress the sub-synchronous resonance oscillations in nearby turbogenerators. These generators are connected to a series capacitive compensation transmission system. First, the damping effect of the reactive power control of the DFIG-based wind farms was theoretically analyzed, and a transfer function between turbogenerator speed and the output reactive power of the wind farms was introduced to derive the analytical expression of the damping coefficient. The phase range to obtain positive damping was determined. Second, the PID phase compensation parameters of the auxiliary damping controller were optimized by a genetic algorithm to obtain the optimum damping in the entire subsynchronous frequency band. Finally, the validity and effectiveness of the proposed auxiliary damping control were demonstrated on a modified version of the IEEE first benchmark model by time domain simulation analysis with the use of DigSILENT/PowerFactory. Theoretical analysis and simulation results show that this derived damping factor expression and the condition of the positive damping can effectively analyze their impact on the system sub-synchronous oscillations, the proposed wind farms reactive power additional damping control strategy can provide the optimal damping effect over the whole sub-synchronous frequency band, and the control effect is better than the active power additional damping control strategy based on the power system stabilizator.
基于解空间分解的电力系统无功优化%Reactive Power Optimization of Power System Based on Solution Space Partition
Institute of Scientific and Technical Information of China (English)
胡廷鹤; 孟安波
2014-01-01
为解决大型电力系统无功控制变量维数灾的问题，提出一种基于解空间分解的方法对电力系统进行无功优化。通过摄动分析选出无功优化中最活跃的控制变量，根据该控制变量分解解空间，最后在JADE(Java agent development)平台上对分解后的问题进行并行计算。应用该方法对 IEEE 30节点系统进行无功优化计算，结果表明基于解空间分解的办法在电网无功优化计算中具有较强的全局搜索能力和较高的收敛精度。%To mitigate curse of dimensionality in reactive power control variables of large power system,the paper proposes a method based on solution space partition for reactive power optimization.By disturbance analysis,the most active control variables are selected in reactive power optimization,in compliance with which the solution space is partitioned.In the final, the problems after partition are calculated on Java agent development (JADE)platform.The method is applied for calcula-tion of reactive power optimization of IEEE 30 node system,and the result shows that the method is of high global research capability and convergence precision in reactive power optimization of power grid.
Reactive Power Optimization with SVC & TCSC using Genetic Algorithm
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Biplab Bhattacharyya
2014-01-01
Full Text Available In this paper Genetic Algorithm (GA is used as an evolutionary tecthniques for the optimal placement of flexible AC transmission systems (FACTS devices in an interconnected power system. Here two types of FACTS devices has been discussed nemely, Thyristor Controlled Series Capacitor (TCSC and Static Var Compensator (SVC for the economic operation and to reduce the transmission loss. Reactively loading of the system is taken from base to 200% of base loading and the system performance is observed without and with FACTS devices. Optimal placement of FACTS devices in the system is determined by calculating active and reactive power flow in lines. FACTS devices along with reactive generation of generators and transformer tap setting are used for the power transfer capacity using GA. The proposed approach is applied on IEEE 14 and IEEE 30-bus test systems. Finally the effectiveness of the proposed GA based method of placement of FACTS devices is established by comparing the results with another standard method of optimization like Particle Swarm Optimization (PSO technique.
Optimal Reactive Power Dispatch using Improved Differential Evolution Algorithm
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Hamid Falaghi
2014-12-01
Full Text Available Reactive power dispatch plays a key role in secure and economic operation of power systems. Optimal reactive power dispatch (ORPD is a non-linear optimization problem which includes both continues and discrete variables. Due to complex characteristics, heuristic and evolutionary based optimization approaches have become effective tools to solve the ORPD problem. In this paper, a new optimization approach based on improved differential evolution (IDE has been proposed to solve the ORPD problem. IDE is an improved version of differential evolution optimization algorithm in which new solutions are produced in respect to global best solution. In the proposed approach, IDE determines the optimal combination of control variables including generator voltages, transformer taps and setting of VAR compensation devices to obtain minimum real power losses. In order to demonstrate the applicability and efficiency of the proposed IDE based approach, it has been tested on the IEEE 14 and 57-bus test systems and obtained results are compared with those obtained using other existing methods. Simulation results show that the proposed approach is superior to the other existing methods.
Optimal Reactive Power Dispatch Considering FACTS Devices
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Ismail MAROUANI
2011-06-01
Full Text Available Because their capability to change the network parameters with a rapid response and enhanced flexibility, flexible AC transmission system (FACTS devices have taken more attention in power systems operations as improvement of voltage profile and minimizing system losses. In this way, this paper presents a multi-objective evolutionary algorithm (MOEA to solve optimal reactive power dispatch (ORPD problem with FACTS devices. This nonlinear multi-objective problem (MOP consists to minimize simultaneously real power loss in transmission lines and voltage deviation at load buses, by tuning parameters and searching the location of FACTS devices. The constraints of this MOP are divided to equality constraints represented by load flow equations and inequality constraints such as, generation reactive power sources and security limits at load buses. Two types of FACTS devices, static synchronous series compensator (SSSC and unified power flow controller (UPFC are considered. A comparative study regarding the effects of an SSSC and an UPFC on voltage deviation and total transmission real losses is carried out. The design problem is tested on a 6-bus system.
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L. Krichen
2007-03-01
Full Text Available In this paper, we develop a method to maintain an acceptable voltages profile and minimization of active losses of a power system including wind generators in real time. These tasks are ensured by acting on capacitor and inductance benches implemented in the consuming nodes. To solve this problem, we minimize an objective function associated to active losses under constraints imposed on the voltages and the reactive productions of the various benches. The minimization procedure was realised by the use of genetic algorithms (GA. The major disadvantage of this technique is that it requires a significant computing time thus not making it possible to deal with the problem in real time. After a training phase, a neural model has the capacity to provide a good estimation of the voltages, the reactive productions and the losses for forecast curves of the load and the wind speed, in real time.
Local Grid Reactive Power Optimization Based on Improved Interior Point Method%基于改进内点法的区域电网无功优化
Institute of Scientific and Technical Information of China (English)
刘曦; 庞霞; 刘崇新
2014-01-01
Introduction was made to the branch primal-dual path tracking method of interior point method. Aiming at reactive volt-age present state of a local grid, this paper established the objective function with the minimum network loss for reactive power op-timization in concurrent of best voltage quality carrying out reactive power optimization to effectively reduce active network loss of the system. The optimization method for reactive power optimization of large-scaled grid has certain guiding significance.%介绍了内点法的分支原对偶路径跟踪法，并针对某区域电网的无功电压现状，建立以网损最小为目标函数，并兼顾电压质量最好进行无功优化，有效降低了系统的有功网损，同时电压质量也得到提高。该优化方法对于大规模电网的无功优化具有一定的指导意义。
Zhou, Dan; Li, Yan; Zhang, Yinbo; Zhang, Chang; Li, Xiongfei; Chen, Zhiliang; Huang, Junyi; Li, Xia; Flores, Giancarlo; Kamon, Masashi
2014-11-01
We investigated the optimum composition of permeable reactive barrier (PRB) materials for remediating groundwater heavily contaminated by landfill leachate, in column tests using various mixtures of zero-valent iron (ZVI), zeolite (Zeo) and activated carbon (AC) with 0.01-0.25, 3.0-5.0 and 0.7-1.0 mm grain sizes, respectively. The main contributors to the removal of organic/inorganic contaminants were ZVI and AC, and the optimum weight ratio of the three PRB materials for removing the contaminants and maintaining adequate hydraulic conductivity was found to be 5:1:4. Average reductions in chemical oxygen demand (COD) and contents of total nitrogen (TN), ammonium, Ni, Pb and 16 polycyclic aromatic hydrocarbons (PAHs) from test samples using this mixture were 55.8%, 70.8%, 89.2%, 70.7%, 92.7% and 94.2%, respectively. We also developed a systematic method for estimating the minimum required thickness and longevity of the PRB materials. A ≥ 309.6 cm layer with the optimum composition is needed for satisfactory longevity, defined here as meeting the Grade III criteria (the Chinese National Bureau of Standards: GB/T14848/93) for in situ treatment of the sampled groundwater for ≥ 10 years.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problem
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Kanagasabai Lenin
2015-03-01
Full Text Available This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
Session-based concurrency, reactively
M. Cano (Mauricio); J. Arias (Jaime); J.A. Pérez Parra (Jorge)
2017-01-01
textabstractThis paper concerns formal models for the analysis of communication-centric software systems that feature declarative and reactive behaviors. We focus on session-based concurrency, the interaction model induced by session types, which uses (variants of) the Π-calculus as specification
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 capacitive...... compensation transmission system. First, the damping effect of the reactive power control of the DFIG-based wind farms was theoretically analyzed, and a transfer function between turbogenerator speed and the output reactive power of the wind farms was introduced to derive the analytical expression...... and effectiveness of the proposed auxiliary damping control were demonstrated on a modified version of the IEEE first benchmark model by time domain simulation analysis with the use of DigSILENT/PowerFactory. Theoretical analysis and simulation results show that this derived damping factor expression...
Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem
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Kanagasabai Lenin
2015-04-01
Full Text Available In this paper, a novel approach Modified Monkey optimization (MMO algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases. The proposed (MMO algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.
Institute of Scientific and Technical Information of China (English)
王一杰; 赵舫; 丁颖; 李丰伟; 蔡振华
2011-01-01
为有效寻找电网无功补偿配置的薄弱点,提出了一种新的无功补偿设备优化配置的方法.该方法根据110 kV变电站全年的无功负荷情况统计出无功负荷概率分布曲线,采用最优覆盖法建立无功补偿配置优化模型,并通过全局搜索寻求优化配置方案.通过对优化配置方案与实际补偿容量配置的比较,给出了无功补偿配置相对薄弱的变电站,为电力系统规划人员提供决策依据.%To find the weak points of power system reactive power compensation allocation, this paper presents an optimized configuration of the method, which gathers reactive power loads of 110 kV substation throughout the year to get the optimal probability curve, adopts optimal cover method to establish the optimized configuration model, and uses global search to find the optimal solution. Through the comparison between the optimized configuation scheme and the actual compensation capacity, this paper presents the substation with insufficient reactive power compensation allocation, which supplies effective recommendations for the power system planners.
Meta-Regression: A Framework for Robust Reactive Optimization
DEFF Research Database (Denmark)
McClary, Dan; Syrotiuk, Violet R.; Kulahci, Murat
2007-01-01
Maintaining optimal performance as the conditions of a system change is a challenging problem. To solve this problem, we present meta-regression, a general methodology for alleviating traditional difficulties in nonlinear regression modelling. Meta-regression allows for reactive optimization, in ...... of a nonlinear system....
Institute of Scientific and Technical Information of China (English)
洪筱; 丁晓群; 杨海东
2013-01-01
In recent years, power electronic devices are widely used and cause harmonic pollution. Optimizing directly on the power system reactive power will cause harmonic amplification problems. To this problem, proposed the mathematical model of reactive power optimization considering harmonic pollution,and applied GSO/TS to reactive power optimization for the first time. Finally, tested the feasibility and the superiority of this method by simulating IEEE 30-bus example. The results of the optimization show that this method reduces the network loss and all kinds of harmonic distortions, at the same time, it has a better convergence efficiency and a higher computational precision.%近年来,电力电子装置的广泛应用引起了谐波污染.如果直接对电力系统进行无功优化,将会引起谐波放大.针对这一问题,提出考虑谐波污染的无功优化的数学模型,首次将萤火虫禁忌算法(GSO/TS)运用到无功优化中.最后通过对IEEE 30节点算例进行仿真分析,验证了可行性和优越性,在减小了网损和各次谐波畸变率的同时,提高了收敛速度和计算精度.
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K. Lenin
2013-03-01
Full Text Available Reactive Power Optimization is a complex combinatorial optimization problem involving non-linear function having multiple local minima, non-linear and discontinuous constrains. This paper presents Attractive and repulsive Particle Swarm Optimization (ARPSO and Random Virus Algorithm (RVA in trying to overcome the Problem of premature convergence. RVA and ARPSO is applied to Reactive Power Optimization problem and is evaluated on standard IEEE 30Bus System. The results show that RVA prevents premature convergence to high degree but still keeps a rapid convergence. It gives best solution when compared to Attractive and repulsive Particle Swarm Optimization (ARPSO and Particle Swarm Optimization (PSO.
Institute of Scientific and Technical Information of China (English)
陈蒙伟; 章坚民; 徐谦; 吴鑫淼; 叶义
2013-01-01
Reactive power control in distribution system is an important and effective method to make the power loss less and voltage condition better. Dynamic reactive power optimization solution generally is taken reasonable section optimization in accordance with the day short-term forecast load curve, that is the dynamic reactive power optimization is transformed into the multi-period static reactive power optimization problems. Aiming at the actual load's irregular change resulting in reactive power over compensation and owe compensation problem on the distribution network, a kind of the dynamic reactive power optimization of hybrid control strategy was proposed based on the real-time measured data and the prediction data. Secondly, in order to improve the distribution network reactive power optimization calculation speed, make optimization algorithm better applicable to the actual on-line environment, ordinal optimization theory framework was introduced, improved tabu search algorithm was taken as reactive power optimization. Through 34-node distribution system study, the results indicate that the proposed control strategy is practicable feasible and its calculation speed is fast.%配电网无功优化控制是解决配电网电能损耗大、电压水平低这一问题的有效手段,采用动态无功优化求解时一般按照各节点全天短期预测负荷曲线合理分段优化,即将动态无功优化控制转化为多时段静态无功优化问题.针对现有配电网实际负荷的不规则变化会给该优化方法带来无功过补偿和欠补偿的问题,提出了一种基于实测负荷数据和预测负荷数据的动态无功优化混合控制策略；为了提高配电网无功优化的计算速度,使优化算法更好地适用于实际在线环境,引入了序优化理论框架,采用了改进的禁忌搜索算法作为无功优化算法；通过对34节点配电系统进行了算例分析.研究结果表明,该控制策略和优化算法在实用
Institute of Scientific and Technical Information of China (English)
左元锋; 耿光飞
2014-01-01
In order to unify the two models of optimal power flow (OPF) and reactive power optimization (RPO)so that the extended OPF model has broader applicability and add new function for solving RPO problem in the free software based on MATLAB, the equivalent conditions between OPF and RPO models were demonstrated and corresponding approaches were proposed in the paper. Two often used objective functions of RPO, which were the minimum power loss and the minimum annual operating cost, were considered in the study. Two examples of RPO, which objective functions were minimum power loss and minimum annual operating costs respectively, were calculated and compared with existing results. Thus the effectiveness and the practicality of the proposed methods were verified. Further application on the IEEE 33 nodes showed that the methods could make full use of optimization in existing software to solve RPO problem. The software development cost is decreased while adding functions and improving its reliability.%为了将最优潮流与无功优化两种数学模型统一起来，使形成的扩展最优潮流具有更广泛的适用性，并增加基于MATLAB的电力系统分析自由软件求解无功优化问题的功能，针对目标函数为网损最小和年运行费用最小的无功优化问题，论证了最优潮流模型与这两种无功优化模型等效的条件，并提出了相应的处理方法。应用该优化方法对两个算例分别进行网损最小和年运行费用最小的无功优化计算，并和已有结果进行对比，验证了方法的有效性和实用性。进而应用本研究方法对IEEE-33节点系统进行优化计算，结果表明：该方法可以充分利用现有软件在优化分析方面的优点解决无功优化问题，增加软件功能的同时既减少了开发成本，又提高了可靠性。
Directory of Open Access Journals (Sweden)
Aouss Gabash
2016-02-01
Full Text Available It has recently been shown that using battery storage systems (BSSs to provide reactive power provision in a medium-voltage (MV active distribution network (ADN with embedded wind stations (WSs can lead to a huge amount of reverse power to an upstream transmission network (TN. However, unity power factors (PFs of WSs were assumed in those studies to analyze the potential of BSSs. Therefore, in this paper (Part-I, we aim to further explore the pure reactive power potential of WSs (i.e., without BSSs by investigating the issue of variable reverse power flow under different limits on PFs in an electricity market model. The main contributions of this work are summarized as follows: (1 Introducing the reactive power capability of WSs in the optimization model of the active-reactive optimal power flow (A-R-OPF and highlighting the benefits/impacts under different limits on PFs. (2 Investigating the impacts of different agreements for variable reverse power flow on the operation of an ADN under different demand scenarios. (3 Derivation of the function of reactive energy losses in the grid with an equivalent-π circuit and comparing its value with active energy losses. (4 Balancing the energy curtailment of wind generation, active-reactive energy losses in the grid and active-reactive energy import-export by a meter-based method. In Part-II, the potential of the developed model is studied through analyzing an electricity market model and a 41-bus network with different locations of WSs.
Institute of Scientific and Technical Information of China (English)
陈兰芝; 王克文
2016-01-01
对于电力系统24小时无功协调优化来说，优化方法是使用粒子群优化算法及罚函数法，将所有的不等式约束方程式引入原目标函数作为惩罚项；优化目标是以全天经济费用最小作为目标函数；优化过程为静态优化和综合优化两个阶段。并根据在线负荷预测来确定24个时刻的并联电容器组的投切状态和变压器分接头的位置。将粒子群算法用于求解多目标无功优化问题中能够有效降低有功网损，减少无功补偿成本，而且其收敛性能好、收敛速度快、稳定性好。%For 24 hours reactive power optimization and coordination in the power system , the optimization method is used in particle swarm optimization algorithm and penalty function method to bring all the inequality constraint equa -tions into the original objective function , which is optimized as a penalty term .The optimization goal is the minimum economic cost as the objective function throughout the day , and the optimization procedure is composed of two stages of static and comprehensive optimization .Based on the on-online forecasted load powers , the shunt capacitors switc-hing states and transform tap stalls for 24 hours are determined .The particle swarm algorithm is used to solve the multi-objective reactive power optimization problem , which can not only reduce the active power loss effectively and the cost of reactive power compensation , but also improve the convergence performance , the convergence speed and the stability .
Gao, F.; Song, X. H.; Zhang, Y.; Li, J. F.; Zhao, S. S.; Ma, W. Q.; Jia, Z. Y.
2017-05-01
In order to reduce the adverse effects of uncertainty on optimal dispatch in active distribution network, an optimal dispatch model based on chance-constrained programming is proposed in this paper. In this model, the active and reactive power of DG can be dispatched at the aim of reducing the operating cost. The effect of operation strategy on the cost can be reflected in the objective which contains the cost of network loss, DG curtailment, DG reactive power ancillary service, and power quality compensation. At the same time, the probabilistic constraints can reflect the operation risk degree. Then the optimal dispatch model is simplified as a series of single stage model which can avoid large variable dimension and improve the convergence speed. And the single stage model is solved using a combination of particle swarm optimization (PSO) and point estimate method (PEM). Finally, the proposed optimal dispatch model and method is verified by the IEEE33 test system.
Distributed Optimal Control of Reactive Power and Voltage in Islanded Microgrids
DEFF Research Database (Denmark)
Wang, Yanbo; Wang, Xiongfei; Chen, Zhe
2016-01-01
The paper proposes a distributed optimal control strategy for islanded microgrids, which allows to perform reactive power sharing and voltage regulation without communication system. To realize the twofold objective, an improved small signal model is developed first to reconstruct the system input...... power sharing and system voltage restoration. And the dynamic performance of the optimal controller is analyzed, from which the guideline for choosing controller parameters is formulated. The results obtained from sensitivity analysis, simulations and experiments show that the proposed approach provides......-output relationship, where the relationship is evaluated with sensitivity analysis. A state estimator is then constructed based on the new input-output relationship in order to observe reactive power distribution and system voltages by local measurement. An optimal regulator is developed to perform both reactive...
Institute of Scientific and Technical Information of China (English)
张沙清; 陈新度; 陈庆新; 陈新
2011-01-01
This paper proposed a reactive scheduling algorithm based on optimized resource flow constraints, which was used to repair multiple mould and die projects baseline schedule that suffer from multiple tasks taking long time than planning during projects execution. Firstly, a baseline schedule minimizing weighted sum duration of projects was built with priority rules based particle swarm optimization and a resource flow network was built and optimized for the baseline schedule with heuristic algorithm. By combining critical chain technology and resource flow network, the baseline schedule was improved by setting proper time buffers. Then, a heuristic reactive scheduling model with the optimization object of minimizing the disruptions cost when tasks starting time changed during projects execution was constructed and priority rules based particle swarm optimization was used to solve it. Finally, the feasibility and reliability of the above reactive algorithm were analyzed by simulations and the results show that this algorithm could effectively solve dynamic scheduling problems for multiple mould and die projects with multiple tasks duration enlarging.%针对模具多项目执行过程中由于任务拖期而导致的调度计划变更,提出了一种基于优化的资源流约束的反应调度算法.首先利用基于优先规则的微粒群算法构建一个项目加权工期之和最小的初始调度计划,采用启发式算法建立并优化初始调度计划的资源流网络,并将关键链技术与资源流网络相结合,对初始调度计划进行合理的时间缓冲设置.然后建立了以调度计划扰动费用最小为优化目标的反应调度模型,并用基于优先规则的微粒群算法进行求解.最后,通过仿真计算分析了算法的可行性与可靠性,结果表明该反应调度算法在模具多项目动态调度中具有一定的应用价值.
Distributed control for optimal reactive power compensation in smart microgrids
Bolognani, Saverio
2011-01-01
We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We also show how this model provides the tools for a distributed approach, in which agents have a partial knowledge of the problem parameters and state, and can only perform local measurements. Then, we design a randomized, gossip-like optimization algorithm, providing conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that the best performance can be achieved when we command cooperation among agents that are neighbors in the smart microgrid topology. Numerical simulations are included to validate the proposed model and to confirm the analytic results about the performance of the proposed algorithm.
Institute of Scientific and Technical Information of China (English)
祝洪博; 徐刚刚; 海冉冉; 余立平
2012-01-01
Power system reactive power optimisation is regarded as a typical high-dimesional, nonlinear and discontinuous problem. Swarm optimization （PSO） algorithm converges rapidly and is easy to implement, how ever it has the defect of prematurity during the optimisation process and it makes the PSO easy to fall into the local minimum. To cope with this defect, firstly the cloud model is led into PSO, and the particles are divided into two parts, i.e., the part adjacent to the optimal particle and the part distant from the optimal particle, in which the inertia weight of the population adjacent to the optimal particle is adaptatively adjusted by the X-condition generator of cloud model; then the idea of gradient is led in and an algorithm named as cloud adaptive gradient particle swarm optimization, CAGPSO） algorithm is proposed. Taking the minimum network loss as objective function, simulation for the proposed CAGPSO algorithm by standard IEEE 14-bus system and IEEE 30-bus system are performed, simulation results show that a better optimal solution can be attained by the proposed CAGPSO algorithm.%粒子群算法存在着早熟的现象，易陷入局部最小点，为了克服这个缺点，文章首先将云模型引入粒子群算法，将粒子分成2部分，靠近最优粒子和远离最优粒子的部分，其中靠近最优粒子种群的惯性权重由云模型的X-条件发生器自适应调整，提出了云自适应粒子群算法（cloud adaptive particle swarm optimization，CAPSO），然后引入梯度的思想，提出云自适应梯度粒子群算法（cloud adaptive gradien tpanicle swarm optimization，CAGPSO）。以网损最小为目标函数，对标准IEEE14和IEEE30节点系统进行仿真计算，结果表明改进后的CAGPSO算法能够获得更好的优化解。
Application of Newton's optimal power flow in voltage/reactive power control
Energy Technology Data Exchange (ETDEWEB)
Bjelogrlic, M.; Babic, B.S. (Electric Power Board of Serbia, Belgrade (YU)); Calovic, M.S. (Dept. of Electrical Engineering, University of Belgrade, Belgrade (YU)); Ristanovic, P. (Institute Nikola Tesla, Belgrade (YU))
1990-11-01
This paper considers an application of Newton's optimal power flow to the solution of the secondary voltage/reactive power control in transmission networks. An efficient computer program based on the latest achievements in the sparse matrix/vector techniques has been developed for this purpose. It is characterized by good robustness, accuracy and speed. A combined objective function appropriate for various system load levels with suitable constraints, for treatment of the power system security and economy is also proposed. For the real-time voltage/reactive power control, a suboptimal power flow procedure has been derived by using the reduced set of control variables. This procedure is based on the sensitivity theory applied to the determination of zones for the secondary voltage/reactive power control and corresponding reduced set of regulating sources, whose reactive outputs represent control variables in the optimal power flow program. As a result, the optimal power flow program output becomes a schedule to be used by operators in the process of the real-time voltage/reactive power control in both normal and emergency operating states.
An investigation about the impact of the optimal reactive power dispatch solved by DE
Energy Technology Data Exchange (ETDEWEB)
Ramirez, Juan M. [Cinvestav-Guadalajara, Av. Cientifica 1145, Col El Bajio, Zapopan, Jal. 45015 (Mexico); Gonzalez, Juan M. [Universidad Tecnologica de Manzanillo, Manzanillo (Mexico); Ruben, Tapia O. [Universidad Politecnica de Tulancingo, Hidalgo (Mexico)
2011-02-15
With the advent of new technology based on power electronics, power systems may attain better voltage profile. This implies the proposition of careful strategies to dispatch reactive power in order to take advantage of all reactive sources, depending on size, location, and availability. This paper proposes an optimal reactive power dispatch strategy taking care of the steady state voltage stability implications. Two power systems of the open publications are studied. Power flow analysis has been carried out, which are the initial conditions for Transient Stability (TS), Small Disturbance (SD), and Continuation Power Flow (CPF) studies. Steady state voltage stability analysis is used to verify the impact of the optimization strategy. To demonstrate the proposal, PV curves, eigenvalue analyses, and time domain simulations, are utilized. (author)
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.
Directory of Open Access Journals (Sweden)
J.Jithendranath
2013-07-01
Full Text Available This paper presents an evolutionary based algorithm for solving optimal reactive power dispatch problem in power system. The problem was designed as a Multi-Objective case with loss minimization and voltage stability as objectives. Generator terminal voltages, tap setting of transformers and reactive power generation of capacitor banks were taken as optimization variables. Modal analysis method is adopted to assess the voltage stability of system. The above presented problem was solved on basis of efficient and reliable technique among all evolutionary based algorithms, the Differential Evolution Technique. The proposed method has been tested on IEEE 30 bus system where the obtained results were found satisfactorily to a large extent that of reported earlier.
Directory of Open Access Journals (Sweden)
V. Tamilselvan
2015-05-01
Full Text Available This study addresses a shuffled frog leaping algorithm for solving the multi-objective reactive power dispatch problem in a power system. Optimal Reactive Power Dispatch (ORPD is formulated as a nonlinear, multi-modal and mixed-variable problem. The intended technique is based on the minimization of the real power loss, minimization of voltage deviation and maximization of the voltage stability margin. Generator voltages, capacitor banks and tap positions of tap changing transformers are used as optimization variables of this problem. A memetic meta-heuristic named as shuffled frog-leaping algorithm is intended to solve multi-objective optimal reactive power dispatch problems considering voltage stability margin and voltage deviation. The Shuffled Frog-Leaping Algorithm (SFLA is a population-based cooperative search metaphor inspired by natural memetics. The algorithm contains elements of local search and global information exchange. The most important benefit of this algorithm is higher speed of convergence to a better solution. The intended method is applied to ORPD problem on IEEE 57 bus power systems and compared with two versions of differential evolutionary algorithm. The simulation results show the effectiveness of the intended method.
Institute of Scientific and Technical Information of China (English)
钟鸣; 文波; 洪彬倬
2015-01-01
This paper introduces mathematic model for optimization on reactive power of power system,discusses application of modern intelligent algorithm in solving nonlinear planning of reactive power optimization and analyzes realization of ap-plication of particle swarm optimization (PSO)algorithm in optimization on reactive power of power system. Discrete parti-cle swarm optimization (DPSO)algorithm was introduced and these two methods were used for processing discrete variables. Example analysis on IEEE-30 node system verified feasibility of PSO and DPSO. It was proved that these two algorithms were of similar optimizing effectiveness but astringency of PSO was better that DPSO while DPSO was more correct and suit-able to process discrete variables than PSO.%介绍了电力系统无功优化的数学模型,论述了现代智能算法在解决无功优化的非线性规划问题中的应用,实现了粒子群优化(particle swarm optimization,PSO)算法在电力系统无功优化问题中的应用。引入离散粒子群(discrete particle swarm optimization,DPSO)算法,采用两种方法对离散变量进行处理。IEEE-30节点系统的算例分析验证了 PSO和DPSO 的可行性。这两种算法具有相近的优化效果,但 PSO 的收敛性优于 DPSO,而DPSO对离散变量的处理比 PSO更准确,也更切合实际。
Institute of Scientific and Technical Information of China (English)
朱文强
2011-01-01
无功补偿优化规划在配电网规划设计中主要考虑的优化目标网损最小、投资最省、综合经济效益最大等。对不同的目标，采用不同的无功配置规划。文中建立了针对配电网络的线性规划求解法的数学模型，以综合经济效益最大为目标函数，以无功平衡、电压为约束条件，结合无功潮流的最优化，计算出运行参数后通过多次迭代计算可获得最佳无功优化。%As the optimization of reactive power compensation plays a key role in planning and design of the distribution network, the chief considerations of optimization targets are the minimum transmission loss ,the minimum investment and the maximum overall economic efficiency, adopting different reactive configuration planning according to different targets. A mathematical model is built in accordance with linear programming method of distribution network. It makes the maximum overall economic efficiency as the objective function, takes reactive power balance and voltage qualification as constraints and combines the optimization of reactive power flow. Through repeatedly using the iterative method after calculating the operating parameters, we obtain reactive power optimization.
基于地面反力最优规划的双足机器人姿态控制%Attitude Control of Biped Robot Based on Optimal Reactive Force Distribution
Institute of Scientific and Technical Information of China (English)
田海英; 任志玲
2001-01-01
提出了一种基于地面反力最优规划的双足步行机器人上体姿态控制算法，以实现上体轨迹准确跟踪及为分级递阶控制结构中的地面反力/位混合控制提供参考输入。由于上体只安装了加速度器并未安装陀螺仪，文中采用线性观测器来重构沿偏转轴和俯仰轴的偏转速度，利用无源性理论控制器-观测器设计了保持上体姿态跟踪特性及系统为最终有界和局部指数稳定有界的地面反力期望值。%A new approach of designing attitude controller is developed based on the optimal reactive force distribution between the robot and environment. The function of the attitude controller is providing input for the force/position controller of the biped robot's Hierarchical Control System. Only get the angle of roll/pitch axis,passivity-based controller-observer is used for velocity of two axis. The idea external force input, which ensure the system of biped robot's body uniformly bounded and locally exponentially stability is get.
Multi-Objective Reactive Power Optimization of Distribution Network with Distributed Generation
Directory of Open Access Journals (Sweden)
Zhao Hui
2016-01-01
Full Text Available Distributed generation (DG is considered to be a very promising alternative of power generation because of its tremendous environmental, social, and economic benefits. But the randomness and intermittent of DGs brings new problems to the system. This paper analyzes the reactive power optimization problem of distribution network with correlative DGs based on scenario analysis method. A new scenario division rule according to the joint distribution function of wind-PV power outputs is proposed in the paper. Then a multi-objective reactive power optimization model whose objects include the minimum active power losses, the minimum voltage deviation and the maximum static voltage stability margin is established. Non-dominated sorting genetic algorithm-II is used to solve the model. At the last of the paper, the model and the algorithm proposed are verified with an improved IEEE 33-bus system. The results show that the model will be a reference to the reactive power optimization problem in distribution system.
Institute of Scientific and Technical Information of China (English)
沈天时; 刘崇新; 岳青; 王李娟
2015-01-01
Introduction was made to the basic principles and methods of reactive power optimization. Analysis was made to the features of reactive power optimization, such as multi-variable, multiple-constraint, non-convex and nonlinear. This paper built the target function with minimum grid losses, which made a compromise between the quality of voltage and the cost of device. The tabu search method in artificial intelligence and its improved algorithm were adopted and the IEEE30 node model was used to program, so as to carry out reactive power optimization for the system at certain definitive time. The results show that this reactive power optimization method can upgrade the economic effectiveness of grid.%介绍了电网无功优化的基本原则及方法，分析了电力系统无功优化多变量、多约束、非凸非线性的特性，建立了网损最小、兼顾电压稳定性和设备费用的目标函数。采用人工智能方法中的禁忌搜索法及其改进算法，利用IEEE30节点模型编制程序，针对某一确定时刻的系统进行无功优化，结果表明，该方法明显提升了电网的经济效益。
Institute of Scientific and Technical Information of China (English)
魏宇存; 庞霞; 贺晓; 刘崇新; 冯卫
2013-01-01
Introduction was made to the improved genetic algorithm, and it was combined with the reactive optimization theory. In virtue of Matlab, this method was applied in multi-goal reactive optimization of wind-generation-set-contained IEEE-14 node and IEEE-30 node system. Algorithm example analysis shows that with the improved genetic algorithm, the active net loss of the goal function was reduced, calculation speed raised. There is theoretical application significance in reactive optimization of wind-power-contained power network.% 介绍了改进遗传算法，将其与无功优化理论结合，借助Matlab软件，将该方法运用在含风电机组的IEEE-14节点和IEEE-30节点系统的多目标无功优化，算例分析结果表明，该改进遗传算法不仅目标函数的有功网损减小，而且计算速度也有所提高，故在含风电网的无功优化中有理论应用意义。
Reactive Power Dispatch for Loss Minimization of a Doubly Fed Induction Generator Based Wind Farm
DEFF Research Database (Denmark)
Zhang, Baohua; Hu, Weihao; Hou, Peng;
2014-01-01
This paper proposes an optimal reactive power dispatching strategy in order to minimize the total losses in a DFIG based wind farm, including the copper loss of the generators, the losses of converters, filters, transformers and the losses of cables. The reactive power constraints, bus voltage...
Optimization Criteria for Reactive Power Compensation in Distribution Networks
Directory of Open Access Journals (Sweden)
Waldemar Szpyra
2014-12-01
Full Text Available This paper describes the effects of reactive power flow through the power transmission and distribution networks. It also presents the dependencies allowing calculating the costs and effects of reactive power compensation. Additionally, selected methods for assessing economic efficiency were discussed. The paper presents calculation results for different variants of reactive power compensation in a real, medium voltage feeder. The results indicate that maximum profit from the reduction of losses due to reactive power compensation does not necessarily mean the most efficient solution from the economic point of view.
Optimization of coproduction of ethyl acetate and n-butyl acetate by reactive distillation☆
Institute of Scientific and Technical Information of China (English)
Hui Tian; Suying Zhao; Huidong Zheng; Zhixian Huang
2015-01-01
Based on a previous investigation, a simulation model was used for optimization of coproduction of ethyl acetate and n-butyl acetate by reactive distil ation. An experimental setup was established to verify the simulated results. The effects of various operating variables, such as ethanol feed location, acetic acid feed location, feed stage of reaction mixture of acetic acid and n-butanol, reflux ratio of ethyl acetate reactive distillation column, and distil-late to feed ratio of n-butyl acetate column, on the ethanol/n-butanol conversions, ethyl acetate/n-butyl acetate purity, and energy consumption were investigated. The optimal results in the simulation study are as follows:ethanol feed location, 15th stage;acetic acid feed location, eighth stage;feed location of reaction mixture of acetic acid and n-butanol, eighth stage;reflux ratio of ethyl acetate reactive distillation column, 2.0;and distillate to feed ratio of n-butyl acetate, 0.6.
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 of the maxi......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...
Institute of Scientific and Technical Information of China (English)
罗毅; 多靖赟
2012-01-01
结合免疫记忆学说和克隆选择原理,提出了一种解决多目标无功优化问题的免疫记忆克隆选择算法.该算法针对多目标无功优化问题的特点,采用以拥挤距离为适应度的自适应克隆方式,实现了种群的扩张,保证了所得解集的均匀性；引入非一致性变异算子,使该算法同时具备全局均匀搜索能力和局部精确寻优能力；采用交叉重组算子实现了抗体间的协作,促进不同抗体间信息的交流;通过抗体群更新操作,一方面保证了算法的收敛速度,另一方面确保了所得解集均匀分布；引入记忆单元概念,可以有效抑制寻优过程中出现的退化现象,确保了种群的多样性.以IEEE-14和IEEE-118节点测试系统为例进行仿真计算,结果表明该算法可以有效提高系统运行的安全性和经济性,是求解多目标无功优化问题的有效方法.%Based on immune memory theory and colonial selection principle, a new immune memory colonial selection algorithm is put forward to solve the problem of multi-objective reactive power optimization. Crowded distance is used as fitness in the adaptive cloning operation to realize the population expansion and ensure the uniformity of solution sets. By use of non consistent variation operation, the algorithm has both global well-distributed search ability and local accurate optimization ability. The cross restructuring operator can promote the information communication between different antibodies. It effectively increases the speed of the algorithm and ensures the uniformity of solution sets by use of antibody group update operation. The introduction of memory unit concept has contributed to suppression of degeneration, ensuring the diversity of population. IEEE-14 bus system and IEEE-118 bus system are used to verify the performance of the proposed algorithm, and the results show that it is an effective method for multi-objective reactive power optimization.
Fish School Search Algorithm for Solving Optimal Reactive Power Dispatch Problem
Directory of Open Access Journals (Sweden)
K. Lenin
2013-01-01
Full Text Available This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. This paper presents fish school search a novel method of swarm intelligence for solving above problem. Fish school search Algorithm, which was inspired by the natural schooling behaviours of fish, a powerful stochastic optimization technique has been utilised to solve the reactive power optimization problem.
Visual Programming of Subsumption - Based Reactive Behaviour
Directory of Open Access Journals (Sweden)
Philip T. Cox
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.
Event-based modularization of reactive systems
Malakuti, 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 ana
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
user
Particle swarm optimization based optimal bidding strategy in an open ... relaxation-based approach for strategic bidding in England-Wales pool type electricity market has ... presents the mathematical formulation of optimal bidding problem.
A pooled-neighbor swarm intelligence approach to optimal reactive power dispatch
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This paper presents a pooled-neighbor swarm intelligence approach (PNSIA) to optimal reactive power dispatch and voltage control of power systems. The proposed approach uses more particles' information to control the mutation operation. The proposed PNSIA algorithm is also extended to handle mixed variables, such as transformer taps and reactive power source installation, using a simple scheme. PNSIA applied for optimal power system reactive power dispatch is evaluated on an IEEE 30-bus power system and a practical 118-bus power system in which the control of bus voltages, tap position of transformers and reactive power sources are involved to minimize the transmission loss of the power system. Simulation results showed that the proposed approach is superior to current methods for finding the optimal solution, in terms of both solution quality and algorithm robustness.
Index-based reactive power compensation scheme for voltage regulation
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
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 continu...
Design Analysis for Optimal Calibration of Diffusivity in Reactive Multilayers
Vohra, Manav; Weihs, Timothy P; Knio, Omar M
2016-01-01
Calibration of the uncertain Arrhenius diffusion parameters for quantifying mixing rates in Zr-Al nanolaminate foils was performed in a Bayesian setting [Vohra et al., 2014]. The parameters were inferred in a low temperature regime characterized by homogeneous ignition and a high temperature regime characterized by self-propagating reactions in the multilayers. In this work, we extend the analysis to find optimal experimental designs that would provide the best data for inference. We employ a rigorous framework that quantifies the expected in- formation gain in an experiment, and find the optimal design conditions using numerical techniques of Monte Carlo, 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 sharper posterior distributions of the diffusion parameters. For the high temperature regime, we demonstrate potential for increase in the expecte...
Study on Optimization Strategy for Voltage and Reactive Power Control of Wind Farm
Lu, Q.; Shi, L.; Chen, N.
A method for calculating reactive power limit of wind farm comprised of doubly-fed induction generators (DFIG) is proposed. The reactive power limit of wind farm is the sum of reactive power limit of DFIGs which is calculated by the method considering static stability margin. Based on this, reactive power control of wind farm is discussed and proposed. The proposed reactive power control is divided into different control modes according to power factor of high voltage side in wind farm substation and voltage of low voltage side in point of interconnection(POI). In different control modes, different control objects are applied on reactive power regulation. After reactive power regulation is finished, some reactive power of wind farm should be released. At last, numerical test system is established, the result shows that the proposed method is effective to support voltage of POI
Institute of Scientific and Technical Information of China (English)
杨悦; 袁超; 李国庆
2011-01-01
Reactive power optimization is the basis of stability and economy of power system.The neighborhood topology cultural differential evolution algorithm is proposed.The premature convergence and easy to fall into local optimal solution of the Cultural differential evolution algorithm are improved.The algorithm is the first time applied to reactive power optimization,and the model of reactive power optimization based on the algorithm is established.The neighborhood topology cultural differential evolution algorithm is a directly and randomly searching method.The study shows that the algorithm can quickly obtain the global optimal solution,have a good property of global convergence,and meet the requirements for reactive power optimization goals.The algorithm of reactive power optimization is on a check with IEEE 30 buses system,and is analyzed with common cultural differential evolution algorithm.The results of simulation shows that the neighborhood topology cultural differential evolution algorithm has the better ability for optimization.%提出了求解无功优化问题的一种新算法——基于邻域拓扑文化差分进化算法。将邻域拓扑结构纳入了文化差分进化算法,改进了文化差分进化算法过早收敛,易于陷入局部最优解的问题。并首次将该算法应用到无功优化问题中,使其能迅速获得全局优化解,具有很好的全局收敛性能和更好的优化能力。最后,将该算法在IEEE 30节点系统上进行了无功优化问题的求解,并与应用普通文化差分进化算法的结果进行了比较分析。仿真结果验证了基于邻域拓扑文化差分进化算法在无功优化应用中的有效性。
Distributed Optimal Control of Reactive Power and Voltage in Islanded Microgrids
DEFF Research Database (Denmark)
Wang, Yanbo; Wang, Xiongfei; Chen, Zhe
2017-01-01
This paper presents a distributed optimal control strategy for islanded microgrids, which allows to perform reactive power sharing and voltage regulation without using communication system. To perform the twofold objectives, a small signal model is first developed to reconstruct the system input...... performance of the optimal controller is analyzed, from which the guideline for choosing controller parameters is formulated. The results obtained from sensitivity analysis, simulations and experiments show that the proposed approach provides the expected reliability and flexibility for optimizing......-output relationship, which is evaluated through sensitivity analysis. A state estimator is then constructed to observe reactive power distribution and system voltages by local measurement. An optimal regulator is developed to perform both reactive power sharing and system voltage restoration. And the dynamic...
Review of reactive power dispatch strategies for loss minimization in a DFIG-based wind farm
DEFF Research Database (Denmark)
Zhang, Baohua; Hu, Weihao; Hou, Peng
2017-01-01
This paper reviews and compares the performance of reactive power dispatch strategies for the loss minimization of Doubly Fed Induction Generator (DFIG)-based Wind Farms (WFs). Twelve possible combinations of three WF level reactive power dispatch strategies and fourWind Turbine (WT) level reactive...... power control strategies are investigated. All of the combined strategies are formulated based on the comprehensive loss models of WFs, including the loss models of DFIGs, converters, filters, transformers, and cables of the collection system. Optimization problems are solved by a Modified Particle...... Swarm Optimization (MPSO) algorithm. The effectiveness of these strategies is evaluated by simulations on a carefully designed WF under a series of cases with different wind speeds and reactive power requirements of the WF. The wind speed at each WT inside the WF is calculated using the Jensen wake...
Design analysis for optimal calibration of diffusivity in reactive multilayers
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.
Global optimization of parameters in the reactive force field ReaxFF for SiOH.
Larsson, Henrik R; van Duin, Adri C T; Hartke, Bernd
2013-09-30
We have used unbiased global optimization to fit a reactive force field to a given set of reference data. Specifically, we have employed genetic algorithms (GA) to fit ReaxFF to SiOH data, using an in-house GA code that is parallelized across reference data items via the message-passing interface (MPI). Details of GA tuning turn-ed out to be far less important for global optimization efficiency than using suitable ranges within which the parameters are varied. To establish these ranges, either prior knowledge can be used or successive stages of GA optimizations, each building upon the best parameter vectors and ranges found in the previous stage. We have finally arrive-ed at optimized force fields with smaller error measures than those published previously. Hence, this optimization approach will contribute to converting force-field fitting from a specialist task to an everyday commodity, even for the more difficult case of reactive force fields.
Directory of Open Access Journals (Sweden)
Yujiao Zeng
2014-01-01
Full Text Available This study presents a novel hybrid multiobjective particle swarm optimization (HMOPSO algorithm to solve the optimal reactive power dispatch (ORPD problem. This problem is formulated as a challenging nonlinear constrained multiobjective optimization problem considering three objectives, that is, power losses minimization, voltage profile improvement, and voltage stability enhancement simultaneously. In order to attain better convergence and diversity, this work presents the use of combing the classical MOPSO with Gaussian probability distribution, chaotic sequences, dynamic crowding distance, and self-adaptive mutation operator. Moreover, multiple effective strategies, such as mixed-variable handling approach, constraint handling technique, and stopping criteria, are employed. The effectiveness of the proposed algorithm for solving the ORPD problem is validated on the standard IEEE 30-bus and IEEE 118-bus systems under nominal and contingency states. The obtained results are compared with classical MOPSO, nondominated sorting genetic algorithm (NSGA-II, multiobjective evolutionary algorithm based on decomposition (MOEA/D, and other methods recently reported in the literature from the point of view of Pareto fronts, extreme, solutions and multiobjective performance metrics. The numerical results demonstrate the superiority of the proposed HMOPSO in solving the ORPD problem while strictly satisfying all the constraints.
Zhuang, H. M.; Jiang, X. J.
2016-08-01
This paper presents an active and reactive power dynamic optimization model for active distribution network (ADN), whose control variables include the output of distributed generations (DGs), charge or discharge power of energy storage system (ESS) and reactive power from capacitor banks. To solve the high-dimension nonlinear optimization model, a new heuristic swarm intelligent method, namely wolf pack algorithm (WPA) with better global convergence and computational robustness, is adapted so that the network loss minimization can be achieved. In this paper, the IEEE33-bus system is used to show the effectiveness of WPA technique compared with other techniques. Numerical tests on the modified IEEE 33-bus system show that WPA for active and reactive multi-period optimization of ADN is exact and effective.
Real and Reactive Power Compensation Using UPFC by Bacterial Foraging Optimization Algorithm (BFOA
Directory of Open Access Journals (Sweden)
E. Nandakumar
2015-04-01
Full Text Available This study presents a finding an optimal location and best parameter setting of Unified Power Flow Controller (UPFC by Bacterial Foraging Optimization Algorithm (BFOA for minimizing the active and reactive power loss in power system. The UPFC is one of the important Flexible Alternating Current Transmission System (FACTS device that control simultaneously voltage magnitude at the sending end and the active and reactive power at the receiving end bus. The FACTS devices have been proposed to be effective for controlling the power flow in transmission lines. However the cost of installing the UPFC is too high. Therefore the objective functions used in this study consider a way to find the compromise solution to a problem. Simulations have been implemented in MATLAB software and IEEE 30 bus system is used. Installing the UPFC in the optimal location by BFO Algorithm can significantly minimize the active and reactive power loss in the power system network.
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...... and capacitors, and subject to constraints such as minimum and maximum reactive power limits of distributed generators, maximum deviation of bus voltages, maximum allowable daily switching operation number (MADSON). Particle swarm optimization (PSO) is used to solve the corresponding mixed integer non......-linear programming problem (MINLP) and the hybrid PSO method (HPSO), consisting of three PSO variants, is presented. In order to mitigate the local convergence problem, fuzzy adaptive inference is used to improve the searching process and the final fuzzy adaptive inference based hybrid PSO is proposed. The proposed...
Dusanter, S.; Michoud, V.; Hansen, R. F.; Leonardis, T.; Locoge, N.; Stevens, P. S.; Blocquet, M.; Schoemaecker, C.; Fittschen, C. M.; Zannoni, N.; Gros, V.; Sarda Esteve, R.; Sinha, V.
2015-12-01
Assessing the oxidative capacity of the atmosphere is important to address fundamental issues related to both air quality and climate change. However, recent measurements of total OH reactivity have highlighted an incomplete understanding of the hydroxyl radical (OH) budget, the main oxidizing agent in the atmosphere. This context has led to the development of several techniques for measuring total OH reactivity to better constrain atmospheric chemistry. This presentation will review the development of an OH reactivity instrument developed at Mines Douai, France. This instrument, based on the Comparative Reactivity Method (CRM), has been carefully characterized in the laboratory and has been compared to other OH reactivity instruments during two different field campaigns. These studies will be summarized to show that CRM instruments can perform reliable measurements in urban and remote areas providing that a few measurement artefacts are well characterized and accounted for during field campaigns.
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...... of the non-linear behaviour of throughput. The intermediate models obtained in this modelling effort are used to adapt the parameters as the network conditions change, in order to maximize throughput. The improvements in throughput range from 10-26 times the use of the default parameter settings...
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.
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 prob...
Siade, A. J.; Prommer, H.; Welter, D.
2014-12-01
Groundwater management and remediation requires the implementation of numerical models in order to evaluate the potential anthropogenic impacts on aquifer systems. In many situations, the numerical model must, not only be able to simulate groundwater flow and transport, but also geochemical and biological processes. Each process being simulated carries with it a set of parameters that must be identified, along with differing potential sources of model-structure error. Various data types are often collected in the field and then used to calibrate the numerical model; however, these data types can represent very different processes and can subsequently be sensitive to the model parameters in extremely complex ways. Therefore, developing an appropriate weighting strategy to address the contributions of each data type to the overall least-squares objective function is not straightforward. This is further compounded by the presence of potential sources of model-structure errors that manifest themselves differently for each observation data type. Finally, reactive transport models are highly nonlinear, which can lead to convergence failure for algorithms operating on the assumption of local linearity. In this study, we propose a variation of the popular, particle swarm optimization algorithm to address trade-offs associated with the calibration of one data type over another. This method removes the need to specify weights between observation groups and instead, produces a multi-dimensional Pareto front that illustrates the trade-offs between data types. We use the PEST++ run manager, along with the standard PEST input/output structure, to implement parallel programming across multiple desktop computers using TCP/IP communications. This allows for very large swarms of particles without the need of a supercomputing facility. The method was applied to a case study in which modeling was used to gain insight into the mobilization of arsenic at a deepwell injection site
Displacement based multilevel structural optimization
Striz, Alfred G.
1995-01-01
Multidisciplinary design optimization (MDO) is expected to play a major role in the competitive transportation industries of tomorrow, i.e., in the design of aircraft and spacecraft, of high speed trains, boats, and automobiles. All of these vehicles require maximum performance at minimum weight to keep fuel consumption low and conserve resources. Here, MDO can deliver mathematically based design tools to create systems with optimum performance subject to the constraints of disciplines such as structures, aerodynamics, controls, etc. Although some applications of MDO are beginning to surface, the key to a widespread use of this technology lies in the improvement of its efficiency. This aspect is investigated here for the MDO subset of structural optimization, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures (here, statically indeterminate trusses and beams for proof of concept) is performed. In the system level optimization, the design variables are the coefficients of assumed displacement functions, and the load unbalance resulting from the solution of the stiffness equations is minimized. Constraints are placed on the deflection amplitudes and the weight of the structure. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. This approach is expected to prove very efficient, especially for complex structures, since the design task is broken down into a large number of small and efficiently handled subtasks, each with only a small number of variables. This partitioning will also allow for the use of parallel computing, first, by sending the system and subsystems level computations to two different processors, ultimately, by performing all subsystems level optimizations in a massively parallel manner on separate
OCEAN: Optimized Cross rEActivity estimatioN.
Czodrowski, Paul; Bolick, Wolf-Guido
2016-10-24
The prediction of molecular targets is highly beneficial during the drug discovery process, be it for off-target elucidation or deconvolution of phenotypic screens. Here, we present OCEAN, a target prediction tool exclusively utilizing publically available ChEMBL data. OCEAN uses a heuristics approach based on a validation set containing almost 1000 drug ← → target relationships. New ChEMBL data (ChEMBL20 as well as ChEMBL21) released after the validation was used for a prospective OCEAN performance check. The success rates of OCEAN to predict correctly the targets within the TOP10 ranks are 77% for recently marketed drugs and 62% for all new ChEMBL20 compounds and 51% for all new ChEMBL21 compounds. OCEAN is also capable of identifying polypharmacological compounds; the success rate for molecules simultaneously hitting at least two targets is 64% to be correctly predicted within the TOP10 ranks. The source code of OCEAN can be found at http://www.github.com/rdkit/OCEAN.
Optimization-Based Layout Design
Directory of Open Access Journals (Sweden)
K. Abdel-Malek
2005-01-01
Full Text Available The layout problem is of importance to ergonomists, vehicle/cockpit packaging engineers, designers of manufacturing assembly lines, designers concerned with the placement of levers, knobs, controls, etc. in the reachable workspace of a human, and also to users of digital human modeling code, where digital prototyping has become a valuable tool. This paper proposes a hybrid optimization method (gradient-based optimization and simulated annealing to obtain the layout design. We implemented the proposed algorithm for a project at Oral-B Laboratories, where a manufacturing cell involves an operator who handles three objects, some with the left hand, others with the right hand.
Simulation-based optimization parametric optimization techniques and reinforcement learning
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...
Institute of Scientific and Technical Information of China (English)
周德东
2014-01-01
针对现阶段中国配电网无功补偿问题，提出了一种改进邻域搜索范围的禁忌搜索算法来确定并联电容器的安装位置和补偿容量，以此提高电压质量和降低系统有功损耗。采用电压合格目标函数搜索满足电压约束条件的初始解，使之在电压可行范围内寻优，然后以减少的有功网损最大为目标函数，从而得到全局最优解，并以未来24 h负荷预测曲线为背景确定了电容器的投切时刻。算例表明，提出的改进算法是可行和有效的。%Aiming at the problem of distribution network reactive power compensation in China, a Taboo search-ing algorithm which can improve the neighborhood searching is proposed to determine the optimal location and the size of shunt capacitors on distributed system, improve the voltage profile and reduce the active power loss.In this paper, voltage qualified objective function is used to search an initial solution that meets the voltage con-straints so that it is feasible in practicable voltage range, then the global optimum solution can be got when taking the reduced maximum of active power loss as objective function.And capacitor switching can be confirmed by set-ting the background of load prediction curve in coming 24 hours.The flow charts and the examples given in this paper show that the improved algorithm is feasible and effective.
Directory of Open Access Journals (Sweden)
A. R. Mesdaghinia
2011-09-01
Full Text Available Because conventional wastewater treatment of effluent containing anthraquinone dye causes notable environmental problems, it is important to find effective alternative methods for dye removal. This study evaluated the efficacy of ozonation for dye removal and Chemical Oxygen Demand reduction and identified optimal operational conditions for parameters such as pH, contact time and concentration of C.I. Reactive Blue 29 dye in a semi-batch reactor. Values of pH between 3 and 11 and contact times between 15 and 120 minutes were investigated. Dye concentrations were based on the American Dye Manufacture Institute standards and ranged from 1000 to 5000. Although results showed that Chemical Oxygen Demand removal by ozone alone was not very efficient (58%, ozonation proved to be an efficient method for decolorizing Reactive Blue 29 (96%. pH was found to significantly influence the effectiveness of Chemical Oxygen Demand removal, and optimal pH conditions (95% confidence interval were between 9 and 11. For decolorization, pH adjustment was not necessary. Degradation and decolorization of dye were found to be strongly influenced by the contact time, optimal conditions (95% confidence interval for degradation and decolorization were 60 and 30 minutes, respectively. The optimal dye concentration was 1000 American Dye Manufacture Institute.
Directory of Open Access Journals (Sweden)
S. R.
2015-12-01
Full Text Available Research was aimed at the optimization of the urease biosensor for analysis of heavy metals and determining the opportunities of its reactivation. A differential pair of gold interdigitated electrodes deposited on a ceramic substrate was used as the conductometric transducer. As a bioselective membrane served urease, coimmobilized with bovine serum albumin by glutaraldehyde cross-linking on the surface of conductometric transducer. 1.0 mM urea was selected as an optimal substrate concentration for the inhibition analysis of heavy metals. The biosensor was tested for its sensitivity to different heavy metals, the calibration curves were plotted. The proposed biosensor was shown to have high reproducibility of signals prior and after inhibition, the measurement error was less than 3%. It was proved a possibility of reactivation of the bioselective membrane after urease irreversible inhibition by heavy metals, using the ethylenediamine tetraacetic acid solution. The optimum conditions of reactivation, i.e. the dependence of its level on time and concentration of heavy metals, were determined. The additional stage, post-inhibition reactivation, was shown to increase significantly the selectivity of biosensor determination of heavy metals.
Optimized Local Trigonometric Bases with Nonuniform Partitions
Institute of Scientific and Technical Information of China (English)
Qiao Fang LIAN; Yong Ge WANG; Dun Yan YAN
2006-01-01
The authors provide optimized local trigonometric bases with nonuniform partitions which efficiently compress trigonometric functions. Numerical examples demonstrate that in many cases the proposed bases provide better compression than the optimized bases with uniform partitions obtained by Matviyenko.
Atmosphere Clouds Model Algorithm for Solving Optimal Reactive Power Dispatch Problem
Directory of Open Access Journals (Sweden)
Lenin Kanagasabai
2014-04-01
Full Text Available In this paper, a new method, called Atmosphere Clouds Model (ACM algorithm, used for solving optimal reactive power dispatch problem. ACM stochastic optimization algorithm stimulated from the behavior of cloud in the natural earth. ACM replicate the generation behavior, shift behavior and extend behavior of cloud. The projected (ACM algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the superior performance of the proposed algorithm in plummeting the real power loss. Normal 0 false false false EN-IN X-NONE X-NONE
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.
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.
Optimal Program for Reactive on Electical Market%电力市场下的无功优化规划
Institute of Scientific and Technical Information of China (English)
王正风; 徐先勇; 唐宗全
2000-01-01
All kinds of economical theories will be altered when the economical market realizes.This paer proposed a mathematical model fo r reactive optimal program based on the price of reactive.The rationality and th e effectiveness of the mathematical model are proved by computation example.This model has major theoretical mean and practical value.%随着电力市场的不断深入，电力系统各种经济调度 理论将随着电力市场的实现而相应地改变。在计及系统无功电价的基础上提出无功补偿优化 的数学模型。通过算例证明，该目标函数及其算法合理有效。
Solid Propellant Burn Rate Modifiers Based on Reactive Nanocomposite Materials
2010-10-26
NaNO3 Al x x* x* x x x x** Mg x x x Al0.5Mg0.5 x MgH2 x x Si x x x Zr x x x x 2B·Ti*** x** Reactive Metal-Metalloid...composites B Reactive metals: Ti, Zr, Hf Nanostructured Al-based alloys Al Alloying components: W, Hf, Mg, MgH2 , Ti, Li, Zr, C * Metal-rich
Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm
Energy Technology Data Exchange (ETDEWEB)
Zhang, Baohua; Hu, Weihao; Hou, Peng; Tan, Jin; Soltani, Mohsen; Chen, Zhe
2017-06-27
This paper reviews and compares the performance of reactive power dispatch strategies for the loss minimization of Doubly Fed Induction Generator (DFIG)-based Wind Farms (WFs). Twelve possible combinations of three WF level reactive power dispatch strategies and four Wind Turbine (WT) level reactive power control strategies are investigated. All of the combined strategies are formulated based on the comprehensive loss models of WFs, including the loss models of DFIGs, converters, filters, transformers, and cables of the collection system. Optimization problems are solved by a Modified Particle Swarm Optimization (MPSO) algorithm. The effectiveness of these strategies is evaluated by simulations on a carefully designed WF under a series of cases with different wind speeds and reactive power requirements of the WF. The wind speed at each WT inside the WF is calculated using the Jensen wake model. The results show that the best reactive power dispatch strategy for loss minimization comes when the WF level strategy and WT level control are coordinated and the losses from each device in the WF are considered in the objective.
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.
Duality based contact shape optimization
DEFF Research Database (Denmark)
Vondrák, Vít; Dostal, Zdenek; Rasmussen, John
2001-01-01
An implementation of semi-analytic method for the sensitivity analysis in contact shape optimization without friction is described. This method is then applied to the contact shape optimization.......An implementation of semi-analytic method for the sensitivity analysis in contact shape optimization without friction is described. This method is then applied to the contact shape optimization....
Directory of Open Access Journals (Sweden)
Mireia Sala
2014-11-01
Full Text Available 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.
Hubbard, C. G.; Hubbard, S. S.; Wu, Y.; Surasani, V.; Ajo Franklin, J. B.; Commer, M.; Dou, S.; Kwon, T.; Li, L.; Fouke, B. W.; Coates, J. D.
2012-12-01
Bioclogging and biocementation offer exciting opportunities for solutions to diverse problems ranging from soil stabilization to microbially enhanced hydrocarbon recovery. The effectiveness of bioclogging and biocementation strategies is governed by processes and properties ranging from microbial metabolism at the submicron scale, to changes in pore geometry at the pore scale, to geological heterogeneities at the field scale. Optimization of these strategies requires advances in mechanistic reactive transport modeling and geophysical monitoring methodologies. Our research focuses on (i) performing laboratory experiments to refine understanding of reaction networks and to quantify changes in hydrological properties (e.g. permeability), the evolution of biominerals and geophysical responses (focusing on seismic and electrical techniques); (ii) developing and using a reactive transport simulator capable of predicting the induced metabolic processes to numerically explore how to optimize the desired effect; and (iii) using loosely coupled reactive transport and geophysical simulators to explore detectability and resolvability of induced bioclogging and biocementation processes at the field scale using time-lapse geophysical methods. Here we present examples of our research focused on three different microbially-mediated methods to enhance hydrocarbon recovery through selective clogging of reservior thief zones, including: (a) biopolymer clogging through dextran production; (b) biomineral clogging through iron oxide precipitation; and (c) biomineral clogging through carbonate precipitation. We will compare the utility of these approaches for enhancing hydrocarbon recovery and will describe the utility of geophysical methods to remotely monitor associated field treatments.
DEFF Research Database (Denmark)
Zhou, Dao; Blaabjerg, Frede; Franke, Toke
2015-01-01
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...
DEFF Research Database (Denmark)
Zhou, Dao; Blaabjerg, Frede; Franke, Toke
2014-01-01
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...
Security region based real and reactive power pricing of power system
Institute of Scientific and Technical Information of China (English)
YU YiXin; WANG YanJun
2008-01-01
This paper develops a novel model and an algorithm of security region based real and reactive power pricing of power systems. In the proposed model, the reactive power production cost is represented as the opportunity cost. The static voltage stability region in the cut set power space (CVSR) and the practical dynamic secu-rity region (PDSR) in the injection power space are used to represent the con-straints of voltage stability and transient stability, so that the consideration of this kind of constraints in the optimization becomes very easy. In the proposed algo-rithm, a decoupled optimization and iteration method of active power production cost and reactive power production cost is suggested. According to the K-T opti-mality conditions, the prices of active power and reactive power, and the different components corresponding to the concerned security constraints are derived. The components of spot prices can reflect the influence of different node power injec-tions on each kind of security constraints, so that through the node price all of the participants in power market can be stimulated to take an active part in maintaining the system security. An illustrative example on the New England 10-generator 39-bus System is used to demonstrate the proposed method.
Security region based real and reactive power pricing of power system
Institute of Scientific and Technical Information of China (English)
2008-01-01
This paper develops a novel model and an algorithm of security region based real and reactive power pricing of power systems.In the proposed model,the reactive power production cost is represented as the opportunity cost.The static voltage stability region in the cut set power space(CVSR) and the practical dynamic security region(PDSR) in the injection power space are used to represent the constraints of voltage stability and transient stability,so that the consideration of this kind of constraints in the optimization becomes very easy.In the proposed algorithm,a decoupled optimization and iteration method of active power production cost and reactive power production cost is suggested.According to the K-T optimality conditions,the prices of active power and reactive power,and the different components corresponding to the concerned security constraints are derived.The components of spot prices can reflect the influence of different node power injections on each kind of security constraints,so that through the node price all of the participants in power market can be stimulated to take an active part in maintaining the system security.An illustrative example on the New England 10-genetator 39-bus System is used to demonstrate the proposed method.
Directory of Open Access Journals (Sweden)
Yong-Cheol Kang
2013-10-01
Full Text Available This paper presents a novel probabilistic optimization algorithm for simultaneous active and reactive power dispatch in power systems with significant wind power integration. Two types of load and wind-speed uncertainties have been assumed that follow normal and Weibull distributions, respectively. A PV bus model for wind turbines and the wake effect for correlated wind speed are used to achieve accurate AC power flow analysis. The power dispatch algorithm for a wind-power integrated system is modeled as a probabilistic optimal power flow (P-OPF problem, which is operated through fixed power factor control to supply reactive power. The proposed P-OPF framework also considers emission information, which clearly reflects the impact of the energy source on the environment. The P-OPF was tested on a modified IEEE 118-bus system with two wind farms. The results show that the proposed technique provides better system operation performance evaluation, which is helpful in making decisions about power system optimal dispatch under conditions of uncertainty.
Multiobjective Optimization Based Vessel Collision Avoidance Strategy Optimization
Directory of Open Access Journals (Sweden)
Qingyang Xu
2014-01-01
Full Text Available The vessel collision accidents cause a great loss of lives and property. In order to reduce the human fault and greatly improve the safety of marine traffic, collision avoidance strategy optimization is proposed to achieve this. In the paper, a multiobjective optimization algorithm NSGA-II is adopted to search for the optimal collision avoidance strategy considering the safety as well as economy elements of collision avoidance. Ship domain and Arena are used to evaluate the collision risk in the simulation. Based on the optimization, an optimal rudder angle is recommended to navigator for collision avoidance. In the simulation example, a crossing encounter situation is simulated, and the NSGA-II searches for the optimal collision avoidance operation under the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS. The simulation studies exhibit the validity of the method.
Anggriani, N.; Wicaksono, B. C.; Supriatna, A. K.
2016-06-01
Tuberculosis (TB) is one of the deadliest infectious disease in the world which caused by Mycobacterium tuberculosis. The disease is spread through the air via the droplets from the infectious persons when they are coughing. The World Health Organization (WHO) has paid a special attention to the TB by providing some solution, for example by providing BCG vaccine that prevent an infected person from becoming an active infectious TB. In this paper we develop a mathematical model of the spread of the TB which assumes endogeneous reactivation and exogeneous reinfection factors. We also assume that some of the susceptible population are vaccinated. Furthermore we investigate the optimal vaccination level for the disease.
Optimal separable bases and molecular collisions
Energy Technology Data Exchange (ETDEWEB)
Poirier, L W [Univ. of California, Berkeley, CA (United States)
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{sub 2} {yields} H{sub 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.
Optimal separable bases and molecular collisions
Energy Technology Data Exchange (ETDEWEB)
Poirier, Lionel W. [Univ. of California, Berkeley, CA (United States)
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.
Drilling Path Optimization Based on Particle Swarm Optimization Algorithm
Institute of Scientific and Technical Information of China (English)
ZHU Guangyu; ZHANG Weibo; DU Yuexiang
2006-01-01
This paper presents a new approach based on the particle swarm optimization (PSO) algorithm for solving the drilling path optimization problem belonging to discrete space. Because the standard PSO algorithm is not guaranteed to be global convergence or local convergence, based on the mathematical algorithm model, the algorithm is improved by adopting the method of generate the stop evolution particle over again to get the ability of convergence to the global optimization solution. And the operators are improved by establishing the duality transposition method and the handle manner for the elements of the operator, the improved operator can satisfy the need of integer coding in drilling path optimization. The experiment with small node numbers indicates that the improved algorithm has the characteristics of easy realize, fast convergence speed, and better global convergence characteristics, hence the new PSO can play a role in solving the problem of drilling path optimization in drilling holes.
Complex System Optimization Using Biogeography-Based Optimization
Directory of Open Access Journals (Sweden)
Dawei Du
2013-01-01
Full Text Available Complex systems are frequently found in modern industry. But with their multisubsystems, multiobjectives, and multiconstraints, the optimization of complex systems is extremely hard. In this paper, a new algorithm adapted from biogeography-based optimization (BBO is introduced for complex system optimization. BBO/Complex is the combination of BBO with a multiobjective ranking system, an innovative migration approach, and effective diversity control. Based on comparisons with three complex system optimization algorithms (multidisciplinary feasible (MDF, individual discipline feasible (IDF, and collaborative optimization (CO on four real-world benchmark problems, BBO/Complex demonstrates competitive performance. BBO/Complex provides the best performance in three of the benchmark problems and the second best in the fourth problem.
Application of reactive acrylate microgels in water-base coatings
Institute of Scientific and Technical Information of China (English)
SA Sheng-shu; ZHANG Bao-hua; YANG Qing; WANG Xia-qin; MAO Zhi-ping
2009-01-01
Reactive acrylate microgels with different reactive groups such as carboxyl, hydroxide groups had excellent prop-erties such as quick-dry, low viscosity, high adhesion and hardness, which made them extensively used in preparing paints or in coating-modification. Reactive acrylate microgels were prepared by emulsion co-polymerization with zwitterions surfactant, anionic surfactant and nonionic surfactant as co-emulsifier. The water-base baking paints made from reactive acrylate micro-gels and melamine-formaldehyde resin had excellent combination properties. The aluminium powder can be well-dispersed in the paints. The influences of monomer components on the properties of the water-base baking paints were discussed in this paper. And the baking paints were also compared with the marketing solvent acrylate baking paints. It was found that the water-base acrylate amino baking paints had better combination properties than the organic solvent acrylate baking paints, which means that the water-base baking paints had a bright marketing future.
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%.
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.
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.
Reliability-based concurrent subspace optimization method
Institute of Scientific and Technical Information of China (English)
FAN Hui; LI Wei-ji
2008-01-01
To avoid the high computational cost and much modification in the process of applying traditional re-liability-based design optimization method, a new reliability-based concurrent subspace optimization approach is proposed based on the comparison and analysis of the existing muhidisciplinary optimization techniques and reli-ability assessment methods. It is shown through a canard configuration optimization for a three-surface transport that the proposed method is computationally efficient and practical with the least modification to the current de-terministic optimization process.
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)
Production Planning Based on BOM Optimization
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
According to a prototype enterprise, a rulebased Bill of Materials (BOM) structure is designed in order to get optimal design and management of product BOM. The constraint rules and optional objects for product data structure optimization are considered by associating customer demands with product BOM. Furthermore, the functional model of production planning system for assembling enterprise is given based on customization and BOM optimization.
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...... be used in interactive optimization....
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.
Modelling and Optimization for Deposition of SiOxNy Films by Radio-Frequency Reactive Sputtering
Institute of Scientific and Technical Information of China (English)
XU Wen-Bin; DONG Shu-Rong; WANG De-Miao
2007-01-01
SiOxNy films are deposited by reactive sputtering from a Si target in Ar/O2/N2 atmospheres. In order to achieve the control of film composition and to keep a high deposition rate at the same time, a new sputtering model based on Berg's work is provided for the condition of double reactive gases. Analysis based on this model shows that the deposition process can easily enter the target-poisoning mode when the preset gas flow (N2 in this work)is too high, and the film composition will change from nitrogen-rich to SiO2-like with the increase of oxygen supply while keeping the N2 supply constant. The modelling results are confirmed in the deposition process of SiOxNy. Target self-bias voltages during sputtering are measured to characterize the different sputtering modes.FTIR-spectra and dielectric measurements are used to testify the model prediction of composition. Finally, an optimized sputtering condition is selected with the O2/N2 flow ratio varying from 0 to 1 and N2 supply fixed at 1 sccm. Average deposition rate of 17nm/min is obtained under this selected condition, which has suggested the model validity and potential for industry applications.
Reliability based design optimization: Formulations and methodologies
Agarwal, Harish
Modern products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modern engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Simulation based design plays an important role in designing almost any kind of automotive, aerospace, and consumer products under these competitive conditions. Single discipline simulations used for analysis are being coupled together to create complex coupled simulation tools. This investigation focuses on the development of efficient and robust methodologies for reliability based design optimization in a simulation based design environment. Original contributions of this research are the development of a novel efficient and robust unilevel methodology for reliability based design optimization, the development of an innovative decoupled reliability based design optimization methodology, the application of homotopy techniques in unilevel reliability based design optimization methodology, and the development of a new framework for reliability based design optimization under epistemic uncertainty. The unilevel methodology for reliability based design optimization is shown to be mathematically equivalent to the traditional nested formulation. Numerical test problems show that the unilevel methodology can reduce computational cost by at least 50% as compared to the nested approach. The decoupled reliability based design optimization methodology is an approximate technique to obtain consistent reliable designs at lesser computational expense. Test problems show that the methodology is computationally efficient compared to the nested approach. A framework for performing reliability based design optimization under epistemic uncertainty is also developed
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
2014-01-21
showing the relative positions of i, i + 3, and i + 4 residues in the helix. Fig. 2 Reactive tags RT1–4 for library screening . Fig. 3 Two-step...activity. Library screening identified two high activity peptides (Chart 3), one containing three Aib resi- dues, Hit2a, and a second containing two
This research reveals the optimal use of the C -21 in support of Distinguished Visitor transport of the highest ranking military and civilians in our...a more effective use of time. This research project analyzed over 1000 flights on over 350 missions conducted in 2014. Eight C -21s are currently
Reliability-Based Optimization in Structural Engineering
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1994-01-01
-based optimal inspection planning and reliability-based experiment planning. It is explained how these optimization problems can be solved by application of similar techniques. The reliability estimation is limited to first order reliability methods (FORM) for both component and systems reliability evaluation......, inclusion of the finite element method as the response evaluation tool and how the size of the problem can be made practicable. Finally, the important task of model evaluation and sensitivity analysis of the optimal solution is treated including a strategy for model-making with both pre and post-analysis.......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...
Ram, A; Arkin, R C; Moorman, K; Clark, R J
1997-01-01
We present a new line of research investigating on-line adaptive reactive control mechanisms for autonomous intelligent agents. We discuss a case-based method for dynamic selection and modification of behavior assemblages for a navigational system. The case-based reasoning module is designed as an addition to a traditional reactive control system, and provides more flexible performance in novel environments without extensive high level reasoning that would otherwise slow the system down. The method is implemented in the ACBARR (case-based reactive robotic) system and evaluated through empirical simulation of the system on several different environments, including "box canyon" environments known to be problematic for reactive control systems in general.
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....
Classifiers based on optimal decision rules
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).
A new optimization algorithm based on chaos
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In this article, some methods are proposed for enhancing the converging velocity of the COA (chaos optimization algorithm) based on using carrier wave two times, which can greatly increase the speed and efficiency of the first carrier wave's search for the optimal point in implementing the sophisticated searching during the second carrier wave is faster and more accurate.In addition, the concept of using the carrier wave three times is proposed and put into practice to tackle the multi-variables optimization problems, where the searching for the optimal point of the last several variables is frequently worse than the first several ones.
Rule-Based Optimization of Reversible Circuits
Arabzadeh, Mona; Zamani, Morteza Saheb
2010-01-01
Reversible logic has applications in various research areas including low-power design and quantum computation. In this paper, a rule-based optimization approach for reversible circuits is proposed which uses both negative and positive control Toffoli gates during the optimization. To this end, a set of rules for removing NOT gates and optimizing sub-circuits with common-target gates are proposed. To evaluate the proposed approach, the best-reported synthesized circuits and the results of a recent synthesis algorithm which uses both negative and positive controls are used. Our experiments reveal the potential of the proposed approach in optimizing synthesized circuits.
Algorithmic Differentiation for Calculus-based Optimization
Walther, Andrea
2010-10-01
For numerous applications, the computation and provision of exact derivative information plays an important role for optimizing the considered system but quite often also for its simulation. This presentation introduces the technique of Algorithmic Differentiation (AD), a method to compute derivatives of arbitrary order within working precision. Quite often an additional structure exploitation is indispensable for a successful coupling of these derivatives with state-of-the-art optimization algorithms. The talk will discuss two important situations where the problem-inherent structure allows a calculus-based optimization. Examples from aerodynamics and nano optics illustrate these advanced optimization approaches.
Verma, H. K.; Mafidar, P.
2013-09-01
In view of growing concern towards environment, power system engineers are forced to generate quality green energy. Hence the economic dispatch (ED) aims at the power generation to meet the load demand at minimum fuel cost with environmental and voltage constraints along with essential constraints on real and reactive power. The emission control which reduces the negative impact on environment is achieved by including the additional constraints in ED problem. Presently, the power system mostly operates near its stability limits, therefore with increased demand the system faces voltage problem. The bus voltages are brought within limit in the present work by placement of static var compensator (SVC) at weak bus which is identified from bus participation factor. The optimal size of SVC is determined by univariate search method. This paper presents the use of Teaching Learning based Optimization (TLBO) algorithm for voltage stable environment friendly ED problem with real and reactive power constraints. The computational effectiveness of TLBO is established through test results over particle swarm optimization (PSO) and Big Bang-Big Crunch (BB-BC) algorithms for the ED problem.
Unifying Model-Based and Reactive Programming within a Model-Based Executive
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.
DEFF Research Database (Denmark)
Ding, Tao; Yang, Qingrun; Yang, Yongheng
2017-01-01
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...
A Reactive Power Dispatch Strategy with Loss Minimization for a DFIG Based Wind Farm
DEFF Research Database (Denmark)
Zhang, Baohua; Hou, Peng; Hu, Weihao;
2016-01-01
An optimal reactive power dispatch strategy is proposed to minimize the total electrical losses of a Wind Farm (WF), including not only losses in the transmission cables and Wind Turbine (WT) transformers, but also losses inside wind energy generation systems. The reactive power dispatch inside a...
Degardin, A.; Bodin, C.; Dolin, C.; Kreisler, A.
1998-01-01
In situ elaboration of YBaCuO thin films, on polycrystalline yttria doped zirconia substrates, has been optimized. A reactive sputtering model has been developed and the electrical conductivity of the substrate has been studied as a function of temperature and doping. The J_c value of ≈ 3× 10^4~A/cm^2 at 77 K, measured on microbridges, is among the best reported in the literature for this substrate type. L'élaboration in situ de films minces d'YBaCuO, sur substrats de zircone polycristalline dopée à l'oxyde d'yttrium, a été optimisée en développant un modèle de pulvérisation réactive et en étudiant la conductivité électrique du substrat en fonction du dopage et de la température. La valeur de J_c ≈ 3× 10^4 ~A/cm^2 à 77 K, mesurée sur microponts, se situe parmi les meilleures citées dans la littérature pour ce type de substrat.
Optimization of multi-constrained structures based on optimality criteria
Rizzi, P.
1976-01-01
A weight-reduction algorithm is developed for the optimal design of structures subject to several multibehavioral inequality constraints. The structural weight is considered to depend linearly on the design variables. The algorithm incorporates a simple recursion formula derived from the Kuhn-Tucker necessary conditions for optimality, associated with a procedure to delete nonactive constraints based on the Gauss-Seidel iterative method for linear systems. A number of example problems is studied, including typical truss structures and simplified wings subject to static loads and with constraints imposed on stresses and displacements. For one of the latter structures, constraints on the fundamental natural frequency and flutter speed are also imposed. The results obtained show that the method is fast, efficient, and general when compared to other competing techniques. Extensions to the generality of the method to include equality constraints and nonlinear merit functions is discussed.
Optimal Hops-Based Adaptive Clustering Algorithm
Xuan, Xin; Chen, Jian; Zhen, Shanshan; Kuo, Yonghong
This paper proposes an optimal hops-based adaptive clustering algorithm (OHACA). The algorithm sets an energy selection threshold before the cluster forms so that the nodes with less energy are more likely to go to sleep immediately. In setup phase, OHACA introduces an adaptive mechanism to adjust cluster head and load balance. And the optimal distance theory is applied to discover the practical optimal routing path to minimize the total energy for transmission. Simulation results show that OHACA prolongs the life of network, improves utilizing rate and transmits more data because of energy balance.
Reliability-Based Topology Optimization With Uncertainties
Energy Technology Data Exchange (ETDEWEB)
Bae, Kyoungryun [JAEIK Information and Communication Co. Ltd., Seoul (Korea, Republic of); Wang, Semyung [Kwangju Institute of Science and Technology, Kwangju (Korea, Republic of); Choi, Kyung K. [Univ. of Iowa, Iowa (United States)
2002-11-15
A probabilistic optimal design modeled with finite elements is presented. A 2-D finite element model is constructed for topology optimization. Young's modulus, thickness and loading are considered as uncertain variables. The uncertain variable means that the variable has a variance on a certain point. In order to compute reliability constraints, two methods-RIA, PMA-are widely used. To find reliability index easily, the limit state function is linearly approximated at the each iteration. This approximation method is called as the first order reliability method (FORM), which is widely used in reliability based design optimizations (RBDO)
Optimization for manufacturing system based on Pheromone
Directory of Open Access Journals (Sweden)
Lei Wang
2011-06-01
Full Text Available A new optimization approach, called pheromone, which comes from the collective behavior of ant colonies for food foraging is proposed to optimize task allocation. These ants spread pheromone information and make global information available locally; thus, an ant agent only needs to observe its local environment in order to account for nonlocal concerns in its decisions. This approach has the capacity for task allocation model to automatically find efficient routing paths for processing orders and to reduce communication overhead, which exists in contract net protocol, in shop floor control system. An example confirms that a pheromone-based optimization approach has an excellent allocation performance in shop floor.
Parameter Optimization Based on GA and HFSS
Institute of Scientific and Technical Information of China (English)
SUN Shu-hui; WANG Bing-zhong
2005-01-01
A new project based on genetic algorithm (GA) and high frequency simulation software (HFSS) is proposed to optimize microwave passive devices effectively. This project is realized with a general program named as optimization program. The program is compiled by Matlab and the macro language of HFSS which is a fast and effective way to accomplish tasks. In the paper, two examples are used to show the project's feasibility.
Control of Interfacial Reactivity Between ZrB2 and Ni-Based Brazing Alloys
Valenza, F.; Muolo, M. L.; Passerone, A.; Cacciamani, G.; Artini, C.
2012-05-01
Transition metals diborides (Ti,Zr,Hf)B2 play a key role in applications where stability at extremely high temperatures and damage tolerance are required; however, much research has still to be done to optimize the joining of these materials to themselves or to other high-temperature materials. In this study, the reactivity at the solid-liquid interface between ZrB2 ceramics and Ni-based brazing alloys has been addressed; it is shown how the reactivity and the dissolution of the solid phase can be controlled and even suppressed by adjusting the brazing alloy composition on the basis of thermodynamic calculations. Wetting experiments on ZrB2 ceramics by Ni, Ni-B 17 at.%, and Ni-B 50 at.% were performed at 1500 and 1200 °C by the sessile drop technique. The obtained interfaces were characterized by optical microscopy and SEM-EDS, and interpreted by means of the ad hoc-calculated B-Ni-Zr ternary diagram. A correlation among microstructures, substrate dissolution, shape of the drops, spreading kinetics, and the phase diagram was found. The effect on the interfacial reactivity of Si3Ni4 used as a sintering aid and issues related to Si diffusion into the brazing alloy are discussed as well.
Directory of Open Access Journals (Sweden)
Nitin Kumar Saxena
2016-12-01
Full Text Available Multi units of wind and diesel based generators in isolated hybrid power system have technical and operational advantages over single units system. They require dynamic reactive power compensation for fast recovery of voltage under load and input changes. In developing countries like India, investors’ prime concern is to provide continuous electricity at low rate while quality degradation can be permitted within pre defined acceptable range. The use of static compensator along with dynamic compensator may give cost effective reactive power participation for system. This paper presented pricing of reactive power compensation under steady state and transient conditions of system with fixed capacitor and STATCOM. The main contributions of the paper are; (i evaluating reactive power balance equation for generalized multi units of wind and diesel based isolated hybrid power system, (ii reactive power compensation using fixed capacitor and STATCOM in presence of composite load model, (ii fast recovery of voltage response using genetic algorithm based tuning of STATCOM controller, (iii evaluation of reactive power compensation cost for steady and dynamic conditions due to probabilistic change in load and/or input demand and (iv comparison of results with existing reference compensation method.
Tiwary, Aditya; Arya, L. D.; Arya, Rajesh; Choube, S. C.
2016-09-01
This paper describes a technique for optimizing inspection and repair based availability of distribution systems. Optimum duration between two inspections has been obtained for each feeder section with respect to cost function and subject to satisfaction of availability at each load point. Teaching learning based optimization has been used for availability optimization. The developed algorithm has been implemented on radial and meshed distribution systems. The result obtained has been compared with those obtained with differential evolution.
Directory of Open Access Journals (Sweden)
Dehghani
2015-04-01
Full Text Available Background Reactive dyes, anionic compounds with high water solubility, are widely used in textile industries. Objectives The present study aimed to assess the feasibility of the photo-Fenton process in removing Reactive Red 198 dye from aqueous solutions and determine the optimal conditions for maximum removal. Materials and Methods This study was performed on a laboratory scale using a 4-liter photochemical reactor. The spectrophotometer DR5000 (wavelength 520 nm was used to determine the dye concentration. The effect of the influencing parameters, including pH (3–9, Fe (II concentration (10–200 mg/L, H2O2 concentration (25 - 150 mg/L, initial dye concentration (50–200 mg/L, and reaction time (15 - 120 minutes were studied. Results According to the results, the photo-Fenton (UV/ H2O2/Fe (II process significantly removed dye from the aqueous solution. The Reactive Red 198 dye removal efficiency from aqueous solutions was more than 99% at optimal conditions (pH = 3, Fe (II = 10 mg/L, H2O2 = 75 mg/L, initial dye concentration = 50 mg/L, and reaction time = 120 minutes. Conclusions The present study demonstrated that the UV/ H2O2/Fe (II process could be used as an efficient, reliable method for removing Reactive Red 198 dye from textile wastewater.
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...
Optimal T cell cross-reactivity and the role of regulatory T cells
Saeki, Koichi; Doekes, Hilje M.; De Boer, Rob J.
2015-01-01
The T lymphocytes of the adaptive immune system constitute a highly diverse repertoire of clones expressing a unique T cell receptor (TCR). It has been argued that TCRs are cross-reactive, meaning that one receptor can recognize a multitude of epitopes. Cross-reactivity between self and foreign
Optimal T cell cross-reactivity and the role of regulatory T cells
Saeki, Koichi; Doekes, Hilje M; De Boer, Rob J; Sub Theoretical Biology; Sub Theoretical Biology & Bioinformatics; Theoretical Biology and Bioinformatics
2014-01-01
The T lymphocytes of the adaptive immune system constitute a highly diverse repertoire of clones expressing a unique T cell receptor (TCR). It has been argued that TCRs are cross-reactive, meaning that one receptor can recognize a multitude of epitopes. Cross-reactivity between self and foreign
Thermal behavior optimization in multi-MW wind power converter by reactive power circulation
DEFF Research Database (Denmark)
Zhou, Dao; Blaabjerg, Frede; Lau, Mogens
2013-01-01
In the paper, an actively controlled reactive power influence to the thermal behavior of multi-MW wind power converter with Doubly-Fed Induction Generator (DFIG) is investigated. The allowable range of internal reactive power circulation is firstly mapped depending on the DC-link voltage as well...... as the induction generator and power device capacity. Then the effects of reactive power circulation towards current characteristic and thermal distribution of the two-level back-to-back power converter is analyzed and compared. Finally the thermal-oriented reactive power is introduced to the system...... in the conditions of constant wind speed and during wind gust. It is concluded that the thermal performance will be improved by injecting proper reactive power circulation in the wind turbine system and thereby be able to reduce the thermal cycling and enhance the reliability....
Thermal Behavior Optimization in Multi-MW Wind Power Converter by Reactive Power Circulation
DEFF Research Database (Denmark)
Zhou, Dao; Blaabjerg, Frede; Lau, Mogens
2014-01-01
The influence of actively controlled reactive power on the thermal behavior of multi-MW wind power converter with a Doubly-Fed Induction Generator (DFIG) is investigated. First, the allowable range of internal reactive power circulation is mapped depending on the DC-link voltage as well...... as the induction generator and power device capacity. Then, the effects of reactive power circulation on current characteristic and thermal distribution of the two-level back-to-back power converter are analyzed and compared. Finally, the thermal-oriented reactive power control method is introduced to the system...... for the conditions of constant wind speed and during wind gust. It is concluded that the thermal performance will be improved by injecting proper reactive power circulation within the wind turbine system, thereby being able to reduce the thermal cycling and enhance the reliability of the power converter....
Directory of Open Access Journals (Sweden)
Xiao-lei Li
2015-01-01
Full Text Available Intergranular corrosion (IGC of Nb-Ti stabilized ferritic stainless steel (FSS 429 was investigated using the double loop electrochemical potentiokinetic reactivation (DL-EPR test combined with the microstructure observation. The results indicated that the optimized DL-EPR test condition for FSS 429 was the solution of 0.5 M H2SO4 + 0.0001 M KSCN with a scanning rate of 100 mV/min at 30°C. Based on this condition, the specimens aging at 400–700°C for different duration were tested and a time-temperature-sensitization (TTS curve for FSS 429 was obtained, which reveals the sensitization nose was located around 550°C. The critical Ir/Ia value was determined to be about 3% above which IGC occurred. After aging treatment, Cr depletion zone was detected using energy dispersive spectroscopy (EDS, most possibly due to Cr segregation around intergranular TiC and NbC.
Directory of Open Access Journals (Sweden)
Wellington M. Fakanya
2014-10-01
Full Text Available The development of an electrochemical immunosensor for the biomarker, C-reactive protein (CRP, is reported in this work. CRP has been used to assess inflammation and is also used in a multi-biomarker system as a predictive biomarker for cardiovascular disease risk. A gold-based working electrode sensor was developed, and the types of electrode printing inks and ink curing techniques were then optimized. The electrodes with the best performance parameters were then employed for the construction of an immunosensor for CRP by immobilizing anti-human CRP antibody on the working electrode surface. A sandwich enzyme-linked immunosorbent assay (ELISA was then constructed after sample addition by using anti-human CRP antibody labelled with horseradish peroxidase (HRP. The signal was generated by the addition of a mediator/substrate system comprised of 3,3,5',5'-Tetramethylbenzidine dihydrochloride (TMB and hydrogen peroxide (H2O2. Measurements were conducted using chronoamperometry at −200 mV against an integrated Ag/AgCl reference electrode. A CRP limit of detection (LOD of 2.2 ng·mL−1 was achieved in spiked serum samples, and performance agreement was obtained with reference to a commercial ELISA kit. The developed CRP immunosensor was able to detect a diagnostically relevant range of the biomarker in serum without the need for signal amplification using nanoparticles, paving the way for future development on a cardiac panel electrochemical point-of-care diagnostic device.
Affordance Learning Based on Subtask's Optimal Strategy
Directory of Open Access Journals (Sweden)
Huaqing Min
2015-08-01
Full Text Available Affordances define the relationships between the robot and environment, in terms of actions that the robot is able to perform. Prior work is mainly about predicting the possibility of a reactive action, and the object's affordance is invariable. However, in the domain of dynamic programming, a robot’s task could often be decomposed into several subtasks, and each subtask could limit the search space. As a result, the robot only needs to replan its sub strategy when an unexpected situation happens, and an object’s affordance might change over time depending on the robot’s state and current subtask. In this paper, we propose a novel affordance model linking the subtask, object, robot state and optimal action. An affordance represents the first action of the optimal strategy under the current subtask when detecting an object, and its influence is promoted from a primitive action to the subtask strategy. Furthermore, hierarchical reinforcement learning and state abstraction mechanism are introduced to learn the task graph and reduce state space. In the navigation experiment, the robot equipped with a camera could learn the objects’ crucial characteristics, and gain their affordances in different subtasks.
Optimal pricing decision model based on activity-based costing
Institute of Scientific and Technical Information of China (English)
王福胜; 常庆芳
2003-01-01
In order to find out the applicability of the optimal pricing decision model based on conventional costbehavior model after activity-based costing has given strong shock to the conventional cost behavior model andits assumptions, detailed analyses have been made using the activity-based cost behavior and cost-volume-profitanalysis model, and it is concluded from these analyses that the theory behind the construction of optimal pri-cing decision model is still tenable under activity-based costing, but the conventional optimal pricing decisionmodel must be modified as appropriate to the activity-based costing based cost behavior model and cost-volume-profit analysis model, and an optimal pricing decision model is really a product pricing decision model construc-ted by following the economic principle of maximizing profit.
Gaborit, Étienne; Anctil, François; Vanrolleghem, Peter A.; Pelletier, Geneviève
2013-04-01
Dry detention ponds have been widely implemented in U.S.A (National Research Council, 1993) and Canada (Shammaa et al. 2002) to mitigate the impacts of urban runoff on receiving water bodies. The aim of such structures is to allow a temporary retention of the water during rainfall events, decreasing runoff velocities and volumes (by infiltration in the pond) as well as providing some water quality improvement from sedimentation. The management of dry detention ponds currently relies on static control through a fixed pre-designed limitation of their maximum outflow (Middleton and Barrett 2008), for example via a proper choice of their outlet pipe diameter. Because these ponds are designed for large storms, typically 1- or 2-hour duration rainfall events with return periods comprised between 5 and 100 years, one of their main drawbacks is that they generally offer almost no retention for smaller rainfall events (Middleton and Barrett 2008), which are by definition much more common. Real-Time Control (RTC) has a high potential for optimizing retention time (Marsalek 2005) because it allows adopting operating strategies that are flexible and hence more suitable to the prevailing fluctuating conditions than static control. For dry ponds, this would basically imply adapting the outlet opening percentage to maximize water retention time, while being able to open it completely for severe storms. This study developed several enhanced RTC scenarios of a dry detention pond located at the outlet of a small urban catchment near Québec City, Canada, following the previous work of Muschalla et al. (2009). The catchment's runoff quantity and TSS concentration were simulated by a SWMM5 model with an improved wash-off formulation. The control procedures rely on rainfall detection and measures of the pond's water height for the reactive schemes, and on rainfall forecasts in addition to these variables for the predictive schemes. The automatic reactive control schemes implemented
Reactively sputtered Fe3O4-based films for spintronics
Institute of Scientific and Technical Information of China (English)
Li Peng; Jin Chao; Mi Wen-Bo; Bai Hai-Li
2013-01-01
Half metallic polycrystalline,epitaxial Fe3O4 films and Fe3O4-based heterostructures for spintronics were fabricated by DC reactive magnetron sputtering.Large tunneling magnetoresistance was found in the polycrystalline Fe3O4 films and attributed to the insulating grain boundaries.The pinning effect of the moments at the grain boundaries leads to a significant exchange bias.Frozen interfacial/surface moments induce weak saturation of the high-field magnetoresistance.The films show a moment rotation related butterfly-shaped magnetoresistance.It was found that in the films,natural growth defects,antiphase boundaries,and magnetocrystaltine anisotropy play important roles in high-order anisotropic magnetoresistance.Spin injection from Fe3O4 films to semiconductive Si and ZnO was measured to be 45％ and 28.5％,respectively.The positive magnetoresistance in the Fe3O4-based heterostructures is considered to be caused by a shift of the Fe3O4 eg ↑ band near the interface.Enhanced magnetization was observed in Fe3O4/BiFeO3 heterostructures experimentally and further proved by first principle calculations.The enhanced magnetization can be explained by spin moments of the thin BiFeO3 layer substantially reversing into a ferromagnetic arrangement under a strong coupling that is principally induced by electronic orbital reconstruction at the interface.
Reactive underwater object inspection based on artificial electric sense.
Lebastard, Vincent; Boyer, Frédéric; Lanneau, Sylvain
2016-07-26
Weakly electric fish can perform complex cognitive tasks based on extracting information from blurry electric images projected from their immediate environment onto their electro-sensitive skin. In particular they can be trained to recognize the intrinsic properties of objects such as their shape, size and electric nature. They do this by means of novel perceptual strategies that exploit the relations between the physics of a self-generated electric field, their body morphology and the ability to perform specific movement termed probing motor acts (PMAs). In this article we artificially reproduce and combine these PMAs to build an autonomous control strategy that allows an artificial electric sensor to find electrically contrasted objects, and to orbit around them based on a minimum set of measurements and simple reactive feedback control laws of the probe's motion. The approach does not require any simulation models and could be implemented on an autonomous underwater vehicle (AUV) equipped with artificial electric sense. The AUV has only to satisfy certain simple geometric properties, such as bi-laterally (left/right) symmetrical electrodes and possess a reasonably high aspect (length/width) ratio.
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...
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...
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.
Bajgar, Jirí
2010-01-01
The studies dealing with mechanism of organophosphates (OP)/nerve agent action, prophylaxis and treatment of intoxications is a very hot topic at present. Though the research is very intensive, unfortunately, up to now, there is not universal or significantly better reactivator sufficiently effective against all nerve agents/OP when compared with presently available oximes (pralidoxime, methoxime, obidoxime, trimedoxime, HI-6). The use of the most effective reactivator (HI-6) using simple type of autoinjector (e.g. ComboPen) is strictly limited because of decomposition of HI-6 in solution. Thanks to better solubility it is clear that another salt of HI-6 (dimethanesulfonate, HI-6 DMS) is more convenient for the use as antidote against nerve agents in the autoinjector than HI-6 chloride (Cl). It was clearly demonstrated that reactivation potency of HI-6 DMS in comparison with HI-6 Cl in vivo was the same and bioavailability of HI-6 DMS is better than that of HI-6 Cl. Three chambered autoinjector allows administration of all three antidotes (atropine, reactivator, diazepam) simultaneously. Moreover, the content of chambers can be changed according to proposed requirements. Possible way to solve the problem of universal reactivator could be the use of two reactivators. Three chambered autoinjector is an ideal device for this purpose.
Optimization-Based Wearable Tactile Rendering.
Perez, Alvaro G; Lobo, Daniel; Chinello, Francesco; Cirio, Gabriel; Malvezzi, Monica; San Martin, Jose; Prattichizzo, Domenico; Otaduy, Miguel A
2016-10-20
Novel wearable tactile interfaces offer the possibility to simulate tactile interactions with virtual environments directly on our skin. But, unlike kinesthetic interfaces, for which haptic rendering is a well explored problem, they pose new questions about the formulation of the rendering problem. In this work, we propose a formulation of tactile rendering as an optimization problem, which is general for a large family of tactile interfaces. Based on an accurate simulation of contact between a finger model and the virtual environment, we pose tactile rendering as the optimization of the device configuration, such that the contact surface between the device and the actual finger matches as close as possible the contact surface in the virtual environment. We describe the optimization formulation in general terms, and we also demonstrate its implementation on a thimble-like wearable device. We validate the tactile rendering formulation by analyzing its force error, and we show that it outperforms other approaches.
Reactive oxygen species in iridium-based OER catalysts.
Pfeifer, Verena; Jones, Travis E; Wrabetz, Sabine; Massué, Cyriac; Velasco Vélez, Juan J; Arrigo, Rosa; Scherzer, Michael; Piccinin, Simone; Hävecker, Michael; Knop-Gericke, Axel; Schlögl, Robert
2016-11-18
Tremendous effort has been devoted towards elucidating the fundamental reasons for the higher activity of hydrated amorphous Ir(III/IV) oxyhydroxides (IrO x ) in the oxygen evolution reaction (OER) in comparison with their crystalline counterpart, rutile-type IrO2, by focusing on the metal oxidation state. Here we demonstrate that, through an analogy to photosystem II, the nature of this reactive species is not solely a property of the metal but is intimately tied to the electronic structure of oxygen. We use a combination of synchrotron-based X-ray photoemission and absorption spectroscopies, ab initio calculations, and microcalorimetry to show that holes in the O 2p states in amorphous IrO x give rise to a weakly bound oxygen that is extremely susceptible to nucleophilic attack, reacting stoichiometrically with CO already at room temperature. As such, we expect this species to play the critical role of the electrophilic oxygen involved in O-O bond formation in the electrocatalytic OER on IrO x . We propose that the dynamic nature of the Ir framework in amorphous IrO x imparts the flexibility in Ir oxidation state required for the formation of this active electrophilic oxygen.
Improved dental adhesive formulations based on reactive nanogel additives.
Morães, R R; Garcia, J W; Wilson, N D; Lewis, S H; Barros, M D; Yang, B; Pfeifer, C S; Stansbury, J W
2012-02-01
Current challenges in adhesive dentistry include over-hydrophilic bonding formulations, which facilitate water percolation through the hybrid layer and result in unreliable bonded interfaces. This study introduces nanogel-modified adhesives as a way to control the material's hydrophobic character without changing the basic monomer formulation (keeping water-chasing capacity and operatory techniques unaltered). Nanogel additives of varied hydrophobicity were synthesized in solution, rendering 10- to 100-nm-sized particles. A model BisGMA/HEMA solvated adhesive was prepared (control), to which reactive nanogels were added. The increase in adhesive viscosity did not impair solvent removal by air-thinning. The degree of conversion in the adhesive was similar between control and nanogel-modified materials, while the bulk dry and, particularly, the wet mechanical properties were significantly improved through nanogel-based network reinforcement and reduced water solubility. As preliminary validation of this approach, short-term micro-tensile bond strengths to acid-etched and primed dentin were significantly enhanced by nanogel inclusion in the adhesive resins.
RPOA Model-Based Optimal Resource Provisioning
Directory of Open Access Journals (Sweden)
Noha El. Attar
2014-01-01
Full Text Available Optimal utilization of resources is the core of the provisioning process in the cloud computing. Sometimes the local resources of a data center are not adequate to satisfy the users’ requirements. So, the providers need to create several data centers at different geographical area around the world and spread the users’ applications on these resources to satisfy both service providers and customers QoS requirements. By considering the expansion of the resources and applications, the transmission cost and time have to be concerned as significant factors in the allocation process. According to the work of our previous paper, a Resource Provision Optimal Algorithm (RPOA based on Particle Swarm Optimization (PSO has been introduced to find the near optimal resource utilization with considering the customer budget and suitable for deadline time. This paper is considered an enhancement to RPOA algorithm to find the near optimal resource utilization with considering the data transfer time and cost, in addition to the customer budget and deadline time, in the performance measurement.
地区电网无功优化研究%Regional power grid reactive power optimization research
Institute of Scientific and Technical Information of China (English)
张小敏; 林晓宇; 黄良俊; 吴信文; 郑健睿; 刘苏云
2014-01-01
为了更有效快速的处理电力系统配网无功优化问题，文中建立了配电网无功优化的数学模型，利用改进遗传算法以网损目标函数，以无功平衡、电压合格等为约束条件，通过使用PSASP仿真软件对山东某市的电网进行仿真模拟，证明方案的正确性和实际可行性。%In order to more effectively deal with power system distribution reactive- power optimization problem, reactive- power optimization mathematical model is established. This model uses the minimum network losses as the objective function and takes reactive power balance, satisfaction voltage quality as the constraints. By using PSASP simulation software to simulation a city in Shandong power grid and prove the correctness and practical feasibility.
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.
Isotretinoin Oil-Based Capsule Formulation Optimization
Directory of Open Access Journals (Sweden)
Pi-Ju Tsai
2013-01-01
Full Text Available The purpose of this study was to develop and optimize an isotretinoin oil-based capsule with specific dissolution pattern. A three-factor-constrained mixture design was used to prepare the systemic model formulations. The independent factors were the components of oil-based capsule including beeswax (X1, hydrogenated coconut oil (X2, and soybean oil (X3. The drug release percentages at 10, 30, 60, and 90 min were selected as responses. The effect of formulation factors including that on responses was inspected by using response surface methodology (RSM. Multiple-response optimization was performed to search for the appropriate formulation with specific release pattern. It was found that the interaction effect of these formulation factors (X1X2, X1X3, and X2X3 showed more potential influence than that of the main factors (X1, X2, and X3. An optimal predicted formulation with Y10 min, Y30 min, Y60 min, and Y90 min release values of 12.3%, 36.7%, 73.6%, and 92.7% at X1, X2, and X3 of 5.75, 15.37, and 78.88, respectively, was developed. The new formulation was prepared and performed by the dissolution test. The similarity factor f2 was 54.8, indicating that the dissolution pattern of the new optimized formulation showed equivalence to the predicted profile.
Weather forecast-based optimization of integrated energy systems.
Energy Technology Data Exchange (ETDEWEB)
Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.
2009-03-01
In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.
Under-Exposed Image Enhancement Based on Relaxed Luminance Optimization
National Research Council Canada - National Science Library
Chunxiao Liu; Feng Yang
2013-01-01
... optimization based under-exposed image clearness enhancement algorithm, which treats it as the simultaneous augmentation of luminance and contrast, and combines them in an optimization framework under...
Optimization-based controller design for rotorcraft
Tsing, N.-K.; Fan, M. K. H.; Barlow, J.; Tits, A. L.; Tischler, M. B.
1993-01-01
An optimization-based methodology for linear control system design is outlined by considering the design of a controller for a UH-60 rotorcraft in hover. A wide range of design specifications is taken into account: internal stability, decoupling between longitudinal and lateral motions, handling qualities, and rejection of windgusts. These specifications are investigated while taking into account physical limitations in the swashplate displacements and rates of displacement. The methodology crucially relies on user-machine interaction for tradeoff exploration.
Afshari Pour, Elnaz; Shafai, Cyrus
2017-02-01
The variation of oxygen concentration in the Indium Tin Oxide (ITO) structure highly impacts its electrical and optical characteristics. In this work, we investigated the effect of oxygen partial flow (O2/O2+Ar) and deposition pressure (p) on the refractive index (n) of reactive sputtered ITO thin films. A statistical study with a Genetic Algorithm (GA) optimization was implemented to find optimal deposition conditions for obtaining particular refractive indices. Several samples of ITO thin films with refractive indices ranging from 1.69 - 2.1 were deposited by DC sputtering technique at various oxygen concentrations and deposition pressures, in order to develop the statistical database. A linear polynomial surface was locally fitted to the data of O2/O2+Ar, p, and n of deposited films. This surface was then used as the fitness function of the GA. By defining the desired n as the objective value of the GA, the optimized deposition conditions can be found. Two cases were experimentally demonstrated, with the GA determining the needed process parameters to deposit ITO with n=2.2 and n=1.6. Measured results were very close to desired values, with n=2.25 and n=1.62, demonstrating the effectiveness of this method for predicting needed reactive sputtering conditions to enable arbitrary refractive indices.
Optimal interference code based on machine learning
Qian, Ye; Chen, Qian; Hu, Xiaobo; Cao, Ercong; Qian, Weixian; Gu, Guohua
2016-10-01
In this paper, we analyze the characteristics of pseudo-random code, by the case of m sequence. Depending on the description of coding theory, we introduce the jamming methods. We simulate the interference effect or probability model by the means of MATLAB to consolidate. In accordance with the length of decoding time the adversary spends, we find out the optimal formula and optimal coefficients based on machine learning, then we get the new optimal interference code. First, when it comes to the phase of recognition, this study judges the effect of interference by the way of simulating the length of time over the decoding period of laser seeker. Then, we use laser active deception jamming simulate interference process in the tracking phase in the next block. In this study we choose the method of laser active deception jamming. In order to improve the performance of the interference, this paper simulates the model by MATLAB software. We find out the least number of pulse intervals which must be received, then we can make the conclusion that the precise interval number of the laser pointer for m sequence encoding. In order to find the shortest space, we make the choice of the greatest common divisor method. Then, combining with the coding regularity that has been found before, we restore pulse interval of pseudo-random code, which has been already received. Finally, we can control the time period of laser interference, get the optimal interference code, and also increase the probability of interference as well.
Heat exchanger design based on economic optimization
Energy Technology Data Exchange (ETDEWEB)
Caputo, Antonio C.; Pelagagge, Marcello P.; Salini, Paolo [University of l' Aquila (Italy). Faculty of Engineering], e-mail: caputo@ing.inivaq.it, e-mail: pelmar@ing.inivaq.it, e-mail: salini@ing.inivaq.it
2006-07-01
Owing to the wide utilization of heat exchangers in industrial processes their cost minimization is an important target for both designers and users. Traditional design approaches are based on iterative procedures which assume a configuration and gradually change design parameters until a satisfying solution is reached which meets the design specifications. However, such methods, besides being time consuming, do not guarantee the reach of an optimal solution. In this paper a procedure for optimal design for shell and tube heat exchangers is proposed which utilizes a genetic algorithm to minimize the total discounted cost of the equipment including the capital investment and pumping related annual energy expenditures. In order to verify the performances of the proposed method four case studies are also presented showing that total cost reductions greater than 15% are feasible respect traditionally designed exchangers. (author)
Grouping Optimization Based on Social Relationships
Directory of Open Access Journals (Sweden)
Rong-Chang Chen
2012-01-01
Full Text Available Grouping based on social relationships is a complex problem since the social relationships within a group usually form a complicated network. To solve the problem, a novel approach which uses a combined sociometry and genetic algorithm (CSGA is presented. A new nonlinear relation model derived from the sociometry is established to measure the social relationships, which are then used as the basis in genetic algorithm (GA program to optimize the grouping. To evaluate the effectiveness of the proposed approach, three real datasets collected from a famous college in Taiwan were utilized. Experimental results show that CSGA optimizes the grouping effectively and efficiently and students are very satisfied with the grouping results, feel the proposed approach interesting, and show a high repeat intention of using it. In addition, a paired sample t-test shows that the overall satisfaction on the proposed CSGA approach is significantly higher than the random method.
Model based optimization of EMC input filters
Energy Technology Data Exchange (ETDEWEB)
Raggl, K; Kolar, J. W. [Swiss Federal Institute of Technology, Power Electronic Systems Laboratory, Zuerich (Switzerland); Nussbaumer, T. [Levitronix GmbH, Zuerich (Switzerland)
2008-07-01
Input filters of power converters for compliance with regulatory electromagnetic compatibility (EMC) standards are often over-dimensioned in practice due to a non-optimal selection of number of filter stages and/or the lack of solid volumetric models of the inductor cores. This paper presents a systematic filter design approach based on a specific filter attenuation requirement and volumetric component parameters. It is shown that a minimal volume can be found for a certain optimal number of filter stages for both the differential mode (DM) and common mode (CM) filter. The considerations are carried out exemplarily for an EMC input filter of a single phase power converter for the power levels of 100 W, 300 W, and 500 W. (author)
Quadratic models of AC-DC power flow and optimal reactive power flow with HVDC and UPFC controls
Energy Technology Data Exchange (ETDEWEB)
Yu, Juan; Yan, Wei; Wen, Lili [The Key Laboratory of High Voltage Engineering and Electrical New Technology, Ministry of Education, Electrical Engineering College of Chongqing University, Chongqing 400030 (China); Li, Wenyuan [British Columbia Transmission Corporation (BCTC), Suite 1100, Four Bentall Center, 1055 Dunsmuir Street, P.O. Box 49260, Vancouver, BC (Canada)
2008-03-15
Quadratic models of power flow (PF) and optimal reactive power flow (ORPF) for AC-DC power systems are proposed in the paper. Voltage magnitudes at the two sides of ideal converter transformers are used as additional state variables to build the quadratic models. Effects of converter controls on equality constraints are considered. The quadratic expression of unified power flow controller (UPFC) is also developed and incorporated into the proposed models. The proposed PF model retaining nonlinearity has a better convergence feature and requires less CPU time compared to traditional PF models. The Hessian matrices in the quadratic AC-DC ORPF model are constant and need to be calculated only once in the entire optimization process, which speeds up the calculation greatly. Results obtained from the four IEEE test systems and an actual utility system indicate that the proposed quadratic models achieve a superior performance than conventional models. (author)
Chitradevi, V; Sivakumar, V
2011-10-01
Wastewater containing direct dyes discharged from various industries, in particular, textile industry, often cause many environmental problems. Among the various effluent treatment methods, biological methods found to be cost effective and do not end up in secondary pollutants. In this study, an attempt has been made to study the decolorization of cibacron yellow S-3R, an azo reactive dye by using fungal cultures such as Coriolus versicolor, Phanerochaete chrysosporium, Pleurotus ostreatus, and Myrothecium verrucaria. The fungi were able to decolorize individually the azo reactive dye cibacron yellow S-3R to an extent of nearly in the range 75 - 85%, whereas the mixed fungal consortium was able to decolorize to an extent of nearly 95%.The study is extended with the kinetics of decolorization of Cibacron yellow S-3R using mixed fungal consortium containing equal proportions of the cultures. The experimental results show that decolorization kinetics follow second order rate equation.
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...
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.
Stress reactivity and personality in extreme sport athletes: The psychobiology of BASE jumpers.
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.
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 .
Approaches to optimization of core reactivity coefficirnts for the “MASTER” heat supply reactor
Directory of Open Access Journals (Sweden)
D.M. Titov
2015-09-01
Full Text Available After increasing the power output of heat supply reactor «MASTER» by insertion of the annular channel with coolant, feedback coefficients are deteriorated. Thereby, there was need to find ways for changing reactivity coefficients in new reactor design and at the same time to save natural circulation, low core pressure and outlet core temperature of coolant. Reactivity coefficients have been calculated depending on width and locations radius of annular coolant channel at once to fuel enrichment. Neutron-physical code WIMS-D4 was used as calculation tool. The results showed that the feedback coefficients optimum can be achieved by reducing of annular channel width and increasing of fuel enrichment. At the same time reactivity coefficients are insensitive to location of annular coolant channel radius changes. Restrictions for fuel enrichment (IAEA requirements coupled with geometry restrictions of annular channel listed above (impossible to remove the thermal power or significant increasing of heat exchangers height have shown that prospect of feedbacks improving via width and location of annular channel is used up. Possible improvements can be achieved by changing type of burnable poison and neutron spectrum.
Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids
DEFF Research Database (Denmark)
Chen, Feixiong; Chen, Minyou; Li, Qiang
2016-01-01
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...
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.
Wass, U; Nilsson, R; Nordlinder, R; Belin, L
1990-03-01
Methods of assaying reactive dye-specific IgE antibodies were investigated with a RAST. Sera from three patients, occupationally exposed to a reactive dye, Remazol black B (Chemical Abstract registry number 17095-24-8), were used. Directly dyed disks, that is, disks without any carrier protein, resulted in poor and unreliable measures of specific IgE. In contrast, optimized preparation of conjugates between the dye and human serum albumin resulted in efficient binding of specific IgE. The patients' RAST results were strongly positive, whereas sera from 36 exposed workers but without symptoms and sera from unexposed subjects with high levels of total IgE were negative. The hapten and carrier specificity of the IgE antibodies was studied by direct RAST and RAST inhibition. In one patient, the antibodies were principally hapten specific, whereas another patient was found to have antibodies with a high degree of specificity to the carrier. The third patient's antibodies were intermediate between the other two patients' antibodies in this respect, suggesting that antibody specificity is dependent not only on the nature of the hapten but also on individual immune response factors. The study demonstrates that it is important to use an optimized preparation of dye-protein conjugates to elicit reliable results and a high degree of specific IgE binding in the RAST.
Directory of Open Access Journals (Sweden)
Rongxiang Yuan
2016-04-01
Full Text Available In the traditional paradigm, large power plants provide active and reactive power required for the transmission system and the distribution network purchases grid power from it. However, with more and more distributed energy resources (DERs connected at distribution levels, it is necessary to schedule DERs to meet their demand and participate in the electricity markets at the distribution level in the near future. This paper proposes a comprehensive operational scheduling model to be used in the distribution management system (DMS. The model aims to determine optimal decisions on active elements of the network, distributed generations (DGs, and responsive loads (RLs, seeking to minimize the day-ahead composite economic cost of the distribution network. For more detailed simulation, the composite cost includes the aspects of the operation cost, emission cost, and transmission loss cost of the network. Additionally, the DMS effectively utilizes the reactive power support capabilities of wind and solar power integrated in the distribution, which is usually neglected in previous works. The optimization procedure is formulated as a nonlinear combinatorial problem and solved with a modified differential evolution algorithm. A modified 33-bus distribution network is employed to validate the satisfactory performance of the proposed methodology.
Robust optimization based upon statistical theory.
Sobotta, B; Söhn, M; Alber, M
2010-08-01
Organ movement is still the biggest challenge in cancer treatment despite advances in online imaging. Due to the resulting geometric uncertainties, the delivered dose cannot be predicted precisely at treatment planning time. Consequently, all associated dose metrics (e.g., EUD and maxDose) are random variables with a patient-specific probability distribution. The method that the authors propose makes these distributions the basis of the optimization and evaluation process. The authors start from a model of motion derived from patient-specific imaging. On a multitude of geometry instances sampled from this model, a dose metric is evaluated. The resulting pdf of this dose metric is termed outcome distribution. The approach optimizes the shape of the outcome distribution based on its mean and variance. This is in contrast to the conventional optimization of a nominal value (e.g., PTV EUD) computed on a single geometry instance. The mean and variance allow for an estimate of the expected treatment outcome along with the residual uncertainty. Besides being applicable to the target, the proposed method also seamlessly includes the organs at risk (OARs). The likelihood that a given value of a metric is reached in the treatment is predicted quantitatively. This information reveals potential hazards that may occur during the course of the treatment, thus helping the expert to find the right balance between the risk of insufficient normal tissue sparing and the risk of insufficient tumor control. By feeding this information to the optimizer, outcome distributions can be obtained where the probability of exceeding a given OAR maximum and that of falling short of a given target goal can be minimized simultaneously. The method is applicable to any source of residual motion uncertainty in treatment delivery. Any model that quantifies organ movement and deformation in terms of probability distributions can be used as basis for the algorithm. Thus, it can generate dose
GPU-based ultrafast IMRT plan optimization
Men, Chunhua; Gu, Xuejun; Choi, Dongju; Majumdar, Amitava; Zheng, Ziyi; Mueller, Klaus; Jiang, Steve B.
2009-11-01
The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California, San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity-modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evaluate our implementation. On an NVIDIA Tesla C1060 GPU card, we have achieved speedup factors of 20-40 without losing accuracy, compared to the results from an Intel Xeon 2.27 GHz CPU. For a specific nine-field prostate IMRT case with 5 × 5 mm2 beamlet size and 2.5 × 2.5 × 2.5 mm3 voxel size, our GPU implementation takes only 2.8 s to generate an optimal IMRT plan. Our work has therefore solved a major problem in developing online re-planning technologies for adaptive radiotherapy.
Institute of Scientific and Technical Information of China (English)
邓长虹; 马庆; 肖永; 游佳斌; 李世春
2014-01-01
针对粒子群算法在求解无功优化问题时存在早熟收敛,易陷于局部最优的现象,提出了自学习迁移粒子群算法(self-learning migration particle swarm optimization,SLMPSO).该算法在采用混沌序列对粒子群进行初始化操作,基于云模型理论的X-条件云发生器对粒子的惯性权重进行自适应调整的基础上,引入一种迁移操作,以引导全局最优粒子的飞行方向,解决粒子群后期朝单一进化方向进化的问题,有效地增强了算法的全局寻优能力.针对电力系统无功优化中的离散变量归整问题,首先将离散变量完全化为连续变量进行迭代求解,在寻求至全局最优解后引入高斯罚函数对离散变量进行归整操作.以网损和电压偏离最小为目标,对IEEE标准30节点算例进行仿真计算,验证了所提算法的有效性和可行性.
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.
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...
Optimizing mesenchymal stem cell-based therapeutics.
Wagner, Joseph; Kean, Thomas; Young, Randell; Dennis, James E; Caplan, Arnold I
2009-10-01
Mesenchymal stem cell (MSC)-based therapeutics are showing significant benefit in multiple clinical trials conducted by both academic and commercial organizations, but obstacles remain for their large-scale commercial implementation. Recent studies have attempted to optimize MSC-based therapeutics by either enhancing their potency or increasing their delivery to target tissues. Overexpression of trophic factors or in vitro exposure to potency-enhancing factors are two approaches that are demonstrating success in preclinical animal models. Delivery enhancement strategies involving tissue-specific cytokine pathways or binding sites are also showing promise. Each of these strategies has its own set of distinct advantages and disadvantages when viewed with a mindset of ultimate commercialization and clinical utility.
Reactive power optimization in distribution system combined garbage power plant%计入分布式垃圾发电的配网无功优化
Institute of Scientific and Technical Information of China (English)
邓启; 吕林; 刘俊勇; 刘友波; 许晓锋
2011-01-01
Reactive power optimization problem in distribution system combined garbage power plant was studied. Two mathematical models which involve garbage incineration and city rubbish fuel cell are constructed based on waste heating value. A new model for reactive power optimization was proposed,in which waste quantity was used as a additional control variable and waste processing capability was considered as a new constraint. Niche Particle Swarm Optimization (NPSO) was applied to solve the reactive power optimization problem. The study case showed that the proposed model is feasible and provide a reference value for the garbage power's further study. And garbage power is more economical and environmental than thermal power plant,which can provide a theoretical basis for promoting garbage power.%研究了垃圾电站并入配网后的无功优化问题,提出了基于垃圾热值的发电数学模型,分为焚烧发电和沼气燃料电池发电两类.据此模型提出了一种新的配电网无功优化模型,该模型把垃圾处理量作为附加控制变量,把垃圾处理能力作为新的约束条件.在求解方法上,采用小生境粒子群算法进行求解,得到了含有垃圾发电的配网无功优化方案.算例表明,提出的垃圾发电模型和无功优化模型具有较好的准确性和实用性,对垃圾电站的进一步研究具有一定的参考价值,且垃圾发电较燃煤发电具有更好的经济性和环保性,也为垃圾发电在其它方面的应用提供了一些理论依据.
Reactive oxygen species in iridium-based OER catalysts
Pfeifer, Verena; Jones, Travis E.; Wrabetz, Sabine; Massué, Cyriac; Velasco Vélez, Juan J.; Arrigo, Rosa; Scherzer, Michael; Piccinin, Simone; Hävecker, Michael; Knop-Gericke, Axel; Schlögl, Robert
2016-01-01
Tremendous effort has been devoted towards elucidating the fundamental reasons for the higher activity of hydrated amorphous IrIII/IV oxyhydroxides (IrOx) in the oxygen evolution reaction (OER) in comparison with their crystalline counterpart, rutile-type IrO2, by focusing on the metal oxidation state. Here we demonstrate that, through an analogy to photosystem II, the nature of this reactive species is not solely a property of the metal but is intimately tied to the electronic structure of o...
Reactivation of a Ruthenium-Based Olefin Metathesis Catalyst
Tabari, Daniel S.; Tolentino, Daniel R.; Schrodi, Yann
2013-01-01
1st Generation Hoveyda-Grubbs olefin metathesis catalyst was purposely decomposed in the presence of ethylene yielding inorganic species that are inactive in the ring-closing metathesis (RCM) of benchmark substrate diethyldiallyl malonate (DEDAM). The decomposed catalyst was treated with 1-(3,5-diisopropoxyphenyl)-1-phenylprop-2-yn-1-ol (3) to generate an olefin metathesis active ruthenium indenylidene-ether complex in 43 % yield. This complex was also prepared independently by reacting RuCl2(p-cymene)(PCy3) with organic precursor 3. The activity of the isolated reactivated catalyst in the RCM of DEDAM is similar to that of the independently prepared complex. PMID:23355756
Reactivation of a Ruthenium-Based Olefin Metathesis Catalyst.
Tabari, Daniel S; Tolentino, Daniel R; Schrodi, Yann
2013-01-14
1(st) Generation Hoveyda-Grubbs olefin metathesis catalyst was purposely decomposed in the presence of ethylene yielding inorganic species that are inactive in the ring-closing metathesis (RCM) of benchmark substrate diethyldiallyl malonate (DEDAM). The decomposed catalyst was treated with 1-(3,5-diisopropoxyphenyl)-1-phenylprop-2-yn-1-ol (3) to generate an olefin metathesis active ruthenium indenylidene-ether complex in 43 % yield. This complex was also prepared independently by reacting RuCl(2)(p-cymene)(PCy(3)) with organic precursor 3. The activity of the isolated reactivated catalyst in the RCM of DEDAM is similar to that of the independently prepared complex.
Function Optimization Based on Quantum Genetic Algorithm
Directory of Open Access Journals (Sweden)
Ying Sun
2014-01-01
Full Text Available Optimization method is important in engineering design and application. Quantum genetic algorithm has the characteristics of good population diversity, rapid convergence and good global search capability and so on. It combines quantum algorithm with genetic algorithm. A novel quantum genetic algorithm is proposed, which is called Variable-boundary-coded Quantum Genetic Algorithm (vbQGA in which qubit chromosomes are collapsed into variable-boundary-coded chromosomes instead of binary-coded chromosomes. Therefore much shorter chromosome strings can be gained. The method of encoding and decoding of chromosome is first described before a new adaptive selection scheme for angle parameters used for rotation gate is put forward based on the core ideas and principles of quantum computation. Eight typical functions are selected to optimize to evaluate the effectiveness and performance of vbQGA against standard Genetic Algorithm (sGA and Genetic Quantum Algorithm (GQA. The simulation results show that vbQGA is significantly superior to sGA in all aspects and outperforms GQA in robustness and solving velocity, especially for multidimensional and complicated functions.
Directory of Open Access Journals (Sweden)
K. Rewatkar
2017-04-01
Full Text Available Gallic acid is a major phenolic pollutant present in the wastewater generated from cork boiling, olive mill, and pharmaceutical industries. Experimental and statistical modelling using response surface methodology (RSM and artificial neural network (ANN were carried out for reactive separation of gallic acid from aqueous stream using tri-nbutyl phosphate (TBP in hexanol. TBP has a more significant effect on extraction efficiency as compared to temperature and pH. The optimum conditions of 2.34 g L–1, 65.65 % v/v, 19 oC, and 1.8 of initial concentration of gallic acid, concentration of TBP, temperature, and pH, respectively, were obtained using RSM. Under optimum conditions, extraction efficiency of 99.45 % was obtained for gallic acid. The ANN and RSM results were compared with experimental unseen data. Error analysis suggested the better performance of ANN for extraction efficiency predictions.
2007-04-12
Scholars in psychology and related disciplines incorporated optimistic or pessimistic views of human nature into their theories. For example, Sigmund ... Freud (1856-1939) included both optimism and pessimism as concepts in his theory of human nature and development. He asserted that humans have a drive...drive towards death represents the pessimistic aspect of human nature ( Freud , 1964). Psychologist William James (1842-1910), was the first to consider
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.
Reliability-Based Optimization of Structural Elements
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
In this paper structural elements from an optimization point of view are considered, i.e. only the geometry of a structural element is optimized. Reliability modelling of the structural element is discussed both from an element point of view and from a system point of view. The optimization...
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.
Directory of Open Access Journals (Sweden)
Mansooreh Dehghani
2015-10-01
Full Text Available Background: Recently, there has been a great concern about the consumption of dyes because of their toxicity, mutagenicity, carcinogenicity, and persistence in the aquatic environment. Reactive dyes are widely used in textile industry. Advanced oxidation processes are one of the cost-effective methods for the removal of these dyes. The main aims of this study were determining the feasibility of using Fenton process in removing Reactive Red 198 (RR-198 dye from aqueous solution and determining the optimal conditions. Methods: This is a cross-sectional study conducted at a laboratory scale. A total of 69 samples were considered and the effect of pH, Fe (II concentration, H2O2 concentration, initial dye concentration and reaction time were investigated. Results: According to the results, a maximum removal efficiency of 92% was obtained at pH of 3 and the reaction time of 90 min; also, the concentration of Fe (II, H2O2, initial dye concentration were 100 mg/L, 50 mg/L, and 100 mg/L, respectively. The results revealed that by increasing the concentration of Fe (II, H2O2 and initial dye, the removal efficiency was increased. Conclusions: The results showed that Fenton process could be used as a cost-effective method for removing RR-198 dye from textile wastewater efficiently.
Directory of Open Access Journals (Sweden)
Abdarrazak OUALI
2011-12-01
Full Text Available Because their capability to change the network parameters with a rapid response and enhanced flexibility, flexible AC transmission system (FACTS devices have taken more attention in power systems operations as improvement of voltage profile and minimizing system losses. In this way, this paper presents a multi-objective evolutionary algorithm (MOEA to solve optimal reactive power dispatch (ORPD problem with FACTS devices. This nonlinear multi-objective problem (MOP consists to minimize simultaneously real power loss in transmission lines and voltage deviation at load buses, by tuning parameters and searching the location of FACTS devices. The constraints of this MOP are divided to equality constraints represented by load flow equations and inequality constraints such as, generation reactive power sources and security limits at load buses. Two types of FACTS devices, static synchronous series compensator (SSSC and unified power flow controller (UPFC are considered. A comparative study regarding the effects of an SSSC and an UPFC on voltage deviation and total transmission real losses is carried out. The design problem is tested on a 6-bus system.
Numerical design optimization of compressor blade based on ADOP
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
An aerodynamic design optimization platform (ADOP) has been developed. The numerical optimization method is based on genetic algorithm (GA), Pareto ranking and fitness sharing technique. The platform was used for design optimization of the stator of an advanced transonic stage to seek high adiabatic efficiency. The compressor stage efficiency is increased by 0.502% at optimal point and the stall margin is enlarged by nearly 1.0% at design rotating speed. The flow fields of the transonic stage were simulated with FINE/Turbo software package. The optimization result indicates that the optimization platform is effective in 3D numerical design optimization problems.
Xu, Guoxi; Huang, Zihan; Chen, Pengyu; Cui, Tianqi; Zhang, Xinghua; Miao, Bing; Yan, Li-Tang
2017-04-01
Structurally dynamic polymers are recognized as a key potential to revolutionize technologies ranging from design of self-healing materials to numerous biomedical applications. Despite intense research in this area, optimizing reactivity and thereby improving self-healing ability at the most fundamental level pose urgent issue for wider applications of such emerging materials. Here, the authors report the first mechanistic investigation of the fundamental principle for the dependence of reactivity and self-healing capabilities on the properties inherent to dynamic polymers by combining large-scale computer simulation, theoretical analysis, and experimental discussion. The results allow to reveal how chain stiffness and spatial organization regulate reactivity of dynamic polymers grafted on Janus nanoparticles and mechanically mediated reaction in their reverse chemistry, and, particularly, identify that semiflexible dynamic polymers possess the optimal reactivity and self-healing ability. The authors also develop an analytical model of blob theory of polymer chains to complement the simulation results and reveal essential scaling laws for optimal reactivity. The findings offer new insights into the physical mechanism in various systems involving reverse/dynamic chemistry. These studies highlight molecular engineering of polymer architecture and intrinsic property as a versatile strategy in control over the structural responses and functionalities of emerging materials with optimized self-healing capabilities. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
An optimization method for metamorphic mechanisms based on multidisciplinary design optimization
Directory of Open Access Journals (Sweden)
Zhang Wuxiang
2014-12-01
Full Text Available The optimization of metamorphic mechanisms is different from that of the conventional mechanisms for its characteristics of multi-configuration. There exist complex coupled design variables and constraints in its multiple different configuration optimization models. To achieve the compatible optimized results of these coupled design variables, an optimization method for metamorphic mechanisms is developed in the paper based on the principle of multidisciplinary design optimization (MDO. Firstly, the optimization characteristics of the metamorphic mechanism are summarized distinctly by proposing the classification of design variables and constraints as well as coupling interactions among its different configuration optimization models. Further, collaborative optimization technique which is used in MDO is adopted for achieving the overall optimization performance. The whole optimization process is then proposed by constructing a two-level hierarchical scheme with global optimizer and configuration optimizer loops. The method is demonstrated by optimizing a planar five-bar metamorphic mechanism which has two configurations, and results show that it can achieve coordinated optimization results for the same parameters in different configuration optimization models.
An optimization method for metamorphic mechanisms based on multidisciplinary design optimization
Institute of Scientific and Technical Information of China (English)
Zhang Wuxiang; Wu Teng; Ding Xilun
2014-01-01
The optimization of metamorphic mechanisms is different from that of the conventional mechanisms for its characteristics of multi-configuration. There exist complex coupled design vari-ables and constraints in its multiple different configuration optimization models. To achieve the compatible optimized results of these coupled design variables, an optimization method for meta-morphic mechanisms is developed in the paper based on the principle of multidisciplinary design optimization (MDO). Firstly, the optimization characteristics of the metamorphic mechanism are summarized distinctly by proposing the classification of design variables and constraints as well as coupling interactions among its different configuration optimization models. Further, collabora-tive optimization technique which is used in MDO is adopted for achieving the overall optimization performance. The whole optimization process is then proposed by constructing a two-level hierar-chical scheme with global optimizer and configuration optimizer loops. The method is demon-strated by optimizing a planar five-bar metamorphic mechanism which has two configurations, and results show that it can achieve coordinated optimization results for the same parameters in different configuration optimization models.
Logic-based methods for optimization combining optimization and constraint satisfaction
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
Energy Technology Data Exchange (ETDEWEB)
Peng, Fang Zheng [Tennessee Univ., Knoxville, TN (United States); Lai, Jih-Sheng [Oak Ridge National Lab., TN (United States)
1996-10-01
A generalized theory of instantaneous reactive power for three-phase power systems is proposed in this paper. This theory gives a generalized definition of instantaneous reactive power, which is valid for sinusoidal or nonsinusoidal, balanced or unbalanced, three- phase power systems with or without zero-sequence currents and/or voltages. The properties and physical meanings of the newly defined instantaneous reactive power are discussed in detail. With this new reactive power theory, it is very easy to calculate and decompose all components, such as fundamental active/reactive power and current, harmonic current, etc. Reactive power and/or harmonic compensation systems for a three-phase distorted power system with and without zero-sequence components in the source voltage and/or load current are then used as examples to demonstrate the measurement, decomposition, and compensation of reactive power and harmonics.
Multiobjective optimization of the reactive power compensation in electric distribution systems
Directory of Open Access Journals (Sweden)
Manoel Socorro Santos-Azevedo
2014-01-01
Full Text Available Se han empleado diferentes métodos de optimización para la sele cción y localización de bancos de capacitores en circuitos de distribución. Sin embargo, hay que considerar la distorsión pro ducida por los armónicos de las cargas no-lineales y la posible aparición de resonancias entre los elementos inductivos del sistema y los bancos de capacitores existentes. Por otra parte, no se ha int egrado en una sola metodología la utilización de bancos de capacitores y de f iltros pasivos de harmónicos para compensar la potencia reactiv a en sistemas de distribución contaminados por armónicos. El present e trabajo se propone como objetivo desarrollar dicha metodologí a. El programa desarrollado se basa en el algoritmo de optimización m ultiobjetivo NSGA-II que se prueba con éxito en varios ejemplos prácticos.
Institute of Scientific and Technical Information of China (English)
郭康; 徐玉琴; 张丽; 岳建房; 孙利芳
2012-01-01
This paper considers reactive power of PV station as reactive power optimization control variables, and discusses the reactive power optimization problem in distribution power system with photovoltaic power station. Due to the randomness output of photovoltaic power station, the voltage of distribution network with photovoltaic power station distribution also shows randomness, as a result, the constraint of the determined voltage in traditional reactive power optimization model is inaccurate. For the randomness of the output of PV power plant, we use random flow algorithm to obtain the probability distribution of each node voltage, put chance constraints on the voltage, take the minimum of power loss as the objective function and then build mathematical model of reactive power optimization for distribution network connected with PV power plant. Using the above reactive power optimization mathematical model based on random constraints, we optimize an example by using the stardard particle swarm algorithm. The optimization results verify the accuracy and the effectiveness of the model and algorithm.%将光伏电站的无功功率作为无功优化的控制变量,研究了含光伏电站配电网无功优化问题.由于光伏电站出力的随机性,使得含光伏电站配电网各节点的电压也具有随机性,所以传统无功优化模型中对确定电压的约束已不精确.在此采用随机潮流算法,求得各节点电压的概率分布,对电压进行机会约束,以有功损耗期望值最小为目标函数,建立了含光伏电站配电网的无功优化数学模型.运用上述基于随机约束的无功优化数学模型,采用标准的粒子群算法对算例进行优化,优化结果验证了该模型与算法的准确性与有效性.
Energy Technology Data Exchange (ETDEWEB)
Dona, Victor M.; Paredes, Andres [Universidad Nacional de San Juan (Argentina). Instituto de Energia Electrica]. E-mail: vdona@iee.unsj.edu.ar
2001-07-01
This paper presents the development and application of a methodology based on the marginal cost theory of reactive and active power, and also on optimization techniques. The methodology allows to find economic signals of active and reactive power at nodal level, and allows the defining of rewarding criteria of the reactive power transportation detecting responsibilities among the transporters and distributors in the generation-consuming of reactive power. The paper also shows main methodological design and the results of the application interconnection argentin system.
Optimized Grid Based e-Learning Framework
Directory of Open Access Journals (Sweden)
Suresh Jaganathan
2014-12-01
Full Text Available E-Learning is the process of extending the resources to different locations by using multimedia communications. Many e-Learning methodologies are available and based on client-server, peer-to-peer and using Grid Computing concepts. To establish e-Learning process, systems should satisfy these needs, i high storage for storing, ii high network throughput for faster transfer and iii efficient streaming of materials. The first and second needs are satisfied by using Grid and P2P technologies and the third need can be achieved by an efficient video compression algorithm. This study proposes a framework, called Optimized Grid Based e-Learning (OgBeL , which adopts both Grid and P2P technology. To reduce the e-Learning material size for efficient streaming, a light weight compression algorithm called (dWave is embedded in (OgBeL . The behavior of framework is analyzed in terms of time taken to transfer files using in-use grid protocols and in networks combined with grid and P2P.
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...... executed tasks are specified at a high levelof abstraction and test traces are collected through state space analysis of the model....
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.
Photo-reactive charge trapping memory based on lanthanide complex.
Zhuang, Jiaqing; Lo, Wai-Sum; Zhou, Li; Sun, Qi-Jun; Chan, Chi-Fai; Zhou, Ye; Han, Su-Ting; Yan, Yan; Wong, Wing-Tak; Wong, Ka-Leung; Roy, V A L
2015-10-09
Traditional utilization of photo-induced excitons is popularly but restricted in the fields of photovoltaic devices as well as photodetectors, and efforts on broadening its function have always been attempted. However, rare reports are available on organic field effect transistor (OFET) memory employing photo-induced charges. Here, we demonstrate an OFET memory containing a novel organic lanthanide complex Eu(tta)3ppta (Eu(tta)3 = Europium(III) thenoyltrifluoroacetonate, ppta = 2-phenyl-4,6-bis(pyrazol-1-yl)-1,3,5-triazine), in which the photo-induced charges can be successfully trapped and detrapped. The luminescent complex emits intense red emission upon ultraviolet (UV) light excitation and serves as a trapping element of holes injected from the pentacene semiconductor layer. Memory window can be significantly enlarged by light-assisted programming and erasing procedures, during which the photo-induced excitons in the semiconductor layer are separated by voltage bias. The enhancement of memory window is attributed to the increasing number of photo-induced excitons by the UV light. The charges are stored in this luminescent complex for at least 10(4) s after withdrawing voltage bias. The present study on photo-assisted novel memory may motivate the research on a new type of light tunable charge trapping photo-reactive memory devices.
Dasgupta, J; Singh, M; Sikder, J; Padarthi, V; Chakraborty, S; Curcio, S
2015-11-01
Retention of toxic dyes with molecular weights lower than the molecular weight cut-off (MWCO) of the ultrafiltration membranes can be improved through selective binding of the target dyes to a water-soluble polymer, followed by ultrafiltration of the macromolecular complexes formed. This method, often referred to as polymer enhanced ultrafiltration (PEUF), was investigated in the present study, using polyethyleneimine (PEI) as the chelating agent. Model azo dye Reactive Red 120 was selected as the poorly biodegradable, target contaminant, because of its frequent recalcitrant presence in colored effluents, and its eventual ecotoxicological impacts on the environment. The effects of the governing process factors, namely, cross flow rate, transmembrane pressure polymer to dye ratio and pH, on target dye rejection efficiency were meticulously examined. Additionally, each parameter level was statistically optimized using central composite design (CCD) from the response surface methodology (RSM) toolkit, with an objective to maximize performance efficiency. The results revealed high dye retention efficiency over 99%, accompanied with reasonable permeate flux over 100L/m(2)h under optimal process conditions. The estimated results were elucidated graphically through response surface (RS) plots and validated experimentally. The analyses clearly established PEUF as a novel, reasonably efficient and economical route for recalcitrant dye treatment.
Fuzzy entropy image segmentation based on particle Swarm optimization
Institute of Scientific and Technical Information of China (English)
Linyi Li; Deren Li
2008-01-01
Partide swaFnl optimization is a stochastic global optimization algorithm that is based on swarm intelligence.Because of its excellent performance,particle swarm optimization is introduced into fuzzy entropy image segmentation to select the optimal fuzzy parameter combination and fuzzy threshold adaptively.In this study,the particles in the swarm are constructed and the swarm search strategy is proposed to meet the needs of the segmentation application.Then fuzzy entropy image segmentation based on particle swarm opti-mization is implemented and the proposed method obtains satisfactory results in the segmentation experiments.Compared with the exhaustive search method,particle swarm optimization can give the salne optimal fuzzy parameter combination and fuzzy threshold while needing less search time in the segmentation experiments and also has good search stability in the repeated experiments.Therefore,fuzzy entropy image segmentation based on particle swarm optimization is an efficient and promising segmentation method.
An Optimization Model Based on Game Theory
Directory of Open Access Journals (Sweden)
Yang Shi
2014-04-01
Full Text Available Game Theory has a wide range of applications in department of economics, but in the field of computer science, especially in the optimization algorithm is seldom used. In this paper, we integrate thinking of game theory into optimization algorithm, and then propose a new optimization model which can be widely used in optimization processing. This optimization model is divided into two types, which are called “the complete consistency” and “the partial consistency”. In these two types, the partial consistency is added disturbance strategy on the basis of the complete consistency. When model’s consistency is satisfied, the Nash equilibrium of the optimization model is global optimal and when the model’s consistency is not met, the presence of perturbation strategy can improve the application of the algorithm. The basic experiments suggest that this optimization model has broad applicability and better performance, and gives a new idea for some intractable problems in the field of artificial intelligence
Warehouse Optimization Model Based on Genetic Algorithm
Directory of Open Access Journals (Sweden)
Guofeng Qin
2013-01-01
Full Text Available This paper takes Bao Steel logistics automated warehouse system as an example. The premise is to maintain the focus of the shelf below half of the height of the shelf. As a result, the cost time of getting or putting goods on the shelf is reduced, and the distance of the same kind of goods is also reduced. Construct a multiobjective optimization model, using genetic algorithm to optimize problem. At last, we get a local optimal solution. Before optimization, the average cost time of getting or putting goods is 4.52996 s, and the average distance of the same kinds of goods is 2.35318 m. After optimization, the average cost time is 4.28859 s, and the average distance is 1.97366 m. After analysis, we can draw the conclusion that this model can improve the efficiency of cargo storage.
Institute of Scientific and Technical Information of China (English)
邱一苇; 吴浩; 宋永华; 孙维真
2015-01-01
Based on the effectiveness and directionality of generator reactive power reserve(GRPR),an optimization model for minimizing effective GRPR considering static shunt reactive power compensation is proposed.Using the theory of Benders decomposition algorithm,the original problem is decomposed into a master problem that corresponds to normal operation condition and several sub-problems that correspond to anticipated contingency and stressed operation conditions.In order to reduce the scale of model solving,a screening algorithm for sub-problems is designed,which is capable of improving the overall model solving efficiency of Benders algorithm. In the end, case studies on an IEEE 39-bus system have verified the effectiveness of the proposed algorithm.%基于考虑有效性和方向性的发电机无功储备定义，提出了考虑静态并联无功补偿的最小发电机有效无功储备优化模型。采用 Benders 分解算法的思想，将原问题分解为正常运行方式下的主问题和预想非正常运行方式下的子问题，并设计了降低模型求解规模的子问题筛选算法，提高了Benders 算法的求解效率。最后，由针对 IEEE 39节点系统的算例分析验证了所提算法的有效性。
Smeets, K C; Oostermeijer, S; Lappenschaar, M; Cohn, M; van der Meer, J M J; Popma, A; Jansen, L M C; Rommelse, N N J; Scheepers, F E; Buitelaar, J K
2017-01-01
This study was designed to examine whether proactive and reactive aggression are meaningful distinctions at the variable- and person-based level, and to determine their associated behavioral profiles. Data from 587 adolescents (mean age 15.6; 71.6 % male) from clinical samples of four different sites with differing levels of aggression problems were analyzed. A multi-level Latent Class Analysis (LCA) was conducted to identify classes of individuals (person-based) with similar aggression profiles based on factor scores (variable-based) of the Reactive Proactive Questionnaire (RPQ) scored by self-report. Associations were examined between aggression factors and classes, and externalizing and internalizing problem behavior scales by parent report (CBCL) and self-report (YSR). Factor-analyses yielded a three factor solution: 1) proactive aggression, 2) reactive aggression due to internal frustration, and 3) reactive aggression due to external provocation. All three factors showed moderate to high correlations. Four classes were detected that mainly differed quantitatively (no 'proactive-only' class present), yet also qualitatively when age was taken into account, with reactive aggression becoming more severe with age in the highest affected class yet diminishing with age in the other classes. Findings were robust across the four samples. Multiple regression analyses showed that 'reactive aggression due to internal frustration' was the strongest predictor of YSR and CBCL internalizing problems. However, results showed moderate to high overlap between all three factors. Aggressive behavior can be distinguished psychometrically into three factors in a clinical sample, with some differential associations. However, the clinical relevance of these findings is challenged by the person-based analysis showing proactive and reactive aggression are mainly driven by aggression severity.
Institute of Scientific and Technical Information of China (English)
郭金明; 李欣然; 邓威; 何春光; 刘卫健
2013-01-01
目前分布式风电(distributed wind generation, DWG)、光伏电池(photovoltaic, PV)等间歇性分布式电源(distributed generation, DG)优化配置对象单一而难以全面反映间歇性DG优化配置的综合效益，且不宜采用确定性的变量和约束来处理间歇性DG出力不确定性和波动性的问题，针对此状况，采用机会约束规划方法，基于随机潮流计算结果，建立2层优化配置模型，对间歇性DG和补偿电容进行综合优化配置，并选择带精英策略的遗传算法进行优化求解。算例结果表明，补偿电容的优化投切效益会影响间歇性DG和补偿电容的优化配置，而补偿电容的配置容量及其最大日允许投切次数、间歇性DG出力和负荷功率期望值的季节性变化对补偿电容的优化投切效益均有显著的影响。2层优化配置的最优方案在兼顾间歇性 DG 和补偿电容的规划经济效益与补偿电容优化投切效益的同时，还可利用补偿电容进一步改善系统的电压质量，从而获得经济效益与电压质量的综合最优，算例分析结果验证了该模型的有效性和合理性。%The optimal allocation of current distributed generations (DG) such as distributed wind generation (DWG) and photovoltaic (PV) is usually single-object oriented, as a result, it is hard to reflect overall benefits of intermittent DGs`optimal allocation. And it is also inappropriate to use fixed variables and constraints to handle the uncertainty and fluctuation of DGs` power output. Aiming to solve the problems, based on the calculation of probabilistic power flow, a bilevel optimal allocation model was established with opportunity-constrained planning method to carry out comprehensive optimal allocation of intermittent DGs and compensation capacitors. And genetic algorithm with elitist strategy was used for the optimal solution. Results of the example demonstrated that optimized operational benefit of
Topology Optimization of Metamaterial-Based Electrically Small Antennas
DEFF Research Database (Denmark)
Erentok, Aycan; Sigmund, Ole
2007-01-01
A topology optimized metamaterial-based electrically small antenna configuration that is independent of a specific spherical and/or cylindrical metamaterial shell design is demonstrated. Topology optimization is shown to provide the optimal value and placement of a given ideal metamaterial in space...
Optimization of Equipment Maintenance Strategy Based on Availability
Institute of Scientific and Technical Information of China (English)
张友诚
2001-01-01
It is very important to optimize maintenance strategy in maintenance plan. Proper parameters play a decisive role for the optimization. In the opinion of writer, availability is a basic parameter, failure consequence cost and failure characteristic are also important parameters. Maintenance strategy can be optimized on the base by means of quantitative analysis and diagram.
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...
Helmdach, Daniel; Yaseneva, Polina; Heer, Parminder K; Schweidtmann, Artur M; Lapkin, Alexei A
2017-09-22
A decision support tool has been developed that uses global multiobjective optimization based on 1) the environmental impacts, evaluated within the framework of full life cycle assessment; and 2) process costs, evaluated by using rigorous process models. This approach is particularly useful in developing biorenewable-based energy solutions and chemicals manufacturing, for which multiple criteria must be evaluated and optimization-based decision-making processes are particularly attractive. The framework is demonstrated by using a case study of the conversion of terpenes derived from biowaste feedstocks into reactive intermediates. A two-step chemical conversion/separation sequence was implemented as a rigorous process model and combined with a life cycle model. A life cycle inventory for crude sulfate turpentine was developed, as well as a conceptual process of its separation into pure terpene feedstocks. The performed single- and multiobjective optimizations demonstrate the functionality of the optimization-based process development and illustrate the approach. The most significant advance is the ability to perform multiobjective global optimization, resulting in identification of a region of Pareto-optimal solutions. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Optimal design of steel portal frames based on genetic algorithms
Institute of Scientific and Technical Information of China (English)
Yue CHEN; Kai HU
2008-01-01
As for the optimal design of steel portal frames, due to both the complexity of cross selections of beams and columns and the discreteness of design variables, it is difficult to obtain satisfactory results by traditional optimization. Based on a set of constraints of the Technical Specification for Light-weighted Steel Portal Frames of China, a genetic algorithm (GA) optimization program for portal frames, written in MATLAB code, was proposed in this paper. The graph user interface (GUI) is also developed for this optimal program, so that it can be used much more conveniently. Finally, some examples illustrate the effectiveness and efficiency of the genetic-algorithm-based optimal program.
An Efficient Method for Reliability-based Multidisciplinary Design Optimization
Institute of Scientific and Technical Information of China (English)
Fan Hui; Li Weiji
2008-01-01
Design for modem engineering system is becoming multidisciplinary and incorporates practical uncertainties; therefore, it is necessary to synthesize reliability analysis and the multidiscipLinary design optimization (MDO) techniques for the design of complex engineering system. An advanced first order second moment method-based concurrent subspace optimization approach is proposed based on the comparison and analysis of the existing multidisciplinary optimization techniques and the reliability analysis methods. It is seen through a canard configuration optimization for a three-surface transport that the proposed method is computationally efficient and practical with the least modification to the current deterministic optimization process.
Topology Optimization in Damping Structure Based on ESO
Institute of Scientific and Technical Information of China (English)
GUO Zhong-ze; CHEN Yu-ze; HOU Qiang
2008-01-01
The damping material optimal placement for the structure with damping layer is studied based on evolutionary structural optimization (ESO) to maximize modal loss factors. A mathematical model is constructed with the objective function defined as the maximum of modal loss factors of the structure and design constraints function defined as volume fraction ofdamping material. The optimal placement is found. Several examples are presented for verification. The results demonstratethat the method based on ESO is effective in solving the topology optimization of the structure with uncon-strained damping layer and constrained damping layer. This optimization method suits for free and constrained damping structures.
Structural Optimization of Machine Gun Based on Dynamic Stability Concept
Institute of Scientific and Technical Information of China (English)
LI Yong-jian; WANG Rui-lin; ZHANG Ben-jun
2008-01-01
Improving the firing accuracy is a final goal of structural optimization of machine guns. The main factors which affect the dispersion accuracy of machine gun are analyzed. Based on the concept of dynamic stability, a structural optimization model is built up, and the sensitivity of dispersion accuracy to design variables is analyzed. The optimization results of a type of machine gun show that the method is valid, feasible, and can be used as a guide to the structural optimization of other automatic weapons.
Model-based multiobjective evolutionary algorithm optimization for HCCI engines
Ma, He; Xu, Hongming; Wang, Jihong; Schnier, Thorsten; Neaves, Ben; Tan, Cheng; Wang, Zhi
2014-01-01
Modern engines feature a considerable number of adjustable control parameters. With this increasing number of Degrees of Freedom (DoF) for engines, and the consequent considerable calibration effort required to optimize engine performance, traditional manual engine calibration or optimization methods are reaching their limits. An automated engine optimization approach is desired. In this paper, a self-learning evolutionary algorithm based multi-objective globally optimization approach for a H...
Weigh in Motion Based on Parameters Optimization
Institute of Scientific and Technical Information of China (English)
ZHOU Zhi-feng; CAI Ping; CHEN Ri-xing
2009-01-01
Dynamic tire forces are the main factor affecting the measurement accuracy of the axle weight of moving vehicle. This paper presents a novel method to reduce the influence of the dynamic tire forces on the weighing accuracy. On the basis of analyzing the characteristic of the dynamic tire forces, the objective optimization equation is constructed. The optimization algorithm is presented to get the optimal estimations of the objective parameters. According to the estimations of the parameters, the dynamic tire forces are separated from the axle weigh signal. The results of simulation and field experiments prove the effectiveness of the proposed method.
Development of Reactive Power Optimization Software of Distribution Network%配电网无功优化软件的设计
Institute of Scientific and Technical Information of China (English)
何子昂; 张波; 王学梅; 丘东元
2012-01-01
Nowaday, reactive compensation of distribution network cannot fulfill the demand and a sound reactive power planning is still absent, causing low voltage and more electric circuit loss, therefor, the status of optimizing reactive power compensation is in serious need of change. To enhance the efficiency of var compensation devices, improve the voltage level and reduce electric circuit loss, this paper carried on research on calculating power flow for radial distribution network using back/forward sweep method and placing reactive compensation devices with proper capacity based on the power flow solutions, and the task have to be repeated many times until the best scheme has been found. The author used Microsoft Visual Basic 6.0 as the development platform to establish the topological model of distribution network, calculate and make out excel report and diagram. The software has been applied in Shaoguan City. The practical tests prove that the development is successful.%关于优化配电网的质量问题,针对目前配电网无功补偿普遍缺乏合理的无功规划,导致运行电压较低及较大的线损的问题,迫切要求改善现有配电网无功优化的现状,为有效地提高现有无功补偿装置的效率,提升配电网运行电压以及降低线损.结合配电网绝大部分线路是放射状的实际情况,以辐射型网络潮流的分层前推回代算法分析计算配电网的潮流,在潮流结果的基础上根据无功精确矩确定无功补偿点及补偿容量,通过重复多次计算得到最优方案.通过vb6.0软件建立电网拓扑模型,结合理论分析,并进行仿真.仿真结果证明,补偿效果较好,软件已在韶关市配电系统中得到试用,并具有良好的实用性,无功优化效果良好.
PARTICLE SWARM OPTIMIZATION BASED OF THE MAXIMUM ...
African Journals Online (AJOL)
2010-06-30
Jun 30, 2010 ... This latter change instantaneously with changing radiation and temperature, ... dealing accurately with these optimization problems and to ... Shunt resistance Rsh, in parallel with the diode, this corresponds to the leakage.
Neuro-estimator based GMC control of a batch reactive distillation.
Prakash, K J Jithin; Patle, Dipesh S; Jana, Amiya K
2011-07-01
In this paper, an artificial neural network (ANN)-based nonlinear control algorithm is proposed for a simulated batch reactive distillation (RD) column. In the homogeneously catalyzed reactive process, an esterification reaction takes place for the production of ethyl acetate. The fundamental model has been derived incorporating the reaction term in the model structure of the nonreactive distillation process. The process operation is simulated at the startup phase under total reflux conditions. The open-loop process dynamics is also addressed running the batch process at the production phase under partial reflux conditions. In this study, a neuro-estimator based generic model controller (GMC), which consists of an ANN-based state predictor and the GMC law, has been synthesized. Finally, this proposed control law has been tested on the representative batch reactive distillation comparing with a gain-scheduled proportional integral (GSPI) controller and with its ideal performance (ideal GMC). Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
Veselinović, Aleksandar M; Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M
2014-11-26
For three random splits, one-variable models of oximes reactivation of sarin inhibited acetylcholinesterase (logarithm of the AChE reactivation percentage by oximes with concentration of 0.001 M) have been calculated with CORAL software. The total number of considered oximes was 42. Simplified molecular input line entry system (SMILES) and hydrogen-suppressed graph (HSG) are used to represent the molecular structure. Using CORAL software by means of the calculation with Monte Carlo optimization of the so called correlation weights for the molecular fragments, optimal SMILES-based descriptors were defined, which are correlated with an endpoint for the training set. The predictability of these descriptors for an external test are estimated. In this study hybrid representation HSG together with SMILES was used. The "classic" scheme (i.e. split data into the training set and test set) of building up quantitative structure-activity relationships was employed. Computational experiments indicated that this approach can satisfactorily predict the desired endpoint. Best model had following statistical characteristics n=32, r2= 0.6012, s= 0.279, F= 45 for training and n=10, r2= 0.9301, s= 0.076, Rm2=0.9206 for test set.
GPP-Based Soft Base Station Designing and Optimization
Institute of Scientific and Technical Information of China (English)
Xiao-Feng Tao; Yan-Zhao Hou; Kai-Dong Wang; Hai-Yang He; Y.Jay Guo
2013-01-01
It is generally acknowledged that mobile communication base stations are composed of hardware components such as Field Programming Gate Array (FPGA),Digital Signal Processor (DSP),which promise reliable and fluent services for the mobile users.However,with the increasing demand for energy-efficiency,approaches of low power-consumption and high-flexibility are needed urgently.In this circumstance,General Purpose Processor (GPP) attracts people's attention for its low-cost and flexibility.Benefited from the development of modern GPP in multi-core,Single Instruction Multiple Data (SIMD) instructions,larger cache,etc.,GPPs are capable of performing high-density digital processing.In this paper,we compare several software-defined radio (SDR) prototypes and propose the general architecture of GPP-based soft base stations.Then,the schematic design of resource allocation and algorithm optimization in soft base station implementation are studied.As an application example,a prototype of GPP-based soft base station referring to the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) is realized and evaluated.To the best of our knowledge,it is the first Soft-LTE prototype ever reported.In the end,we evaluate the timing performance of the LTE soft base station and a packet loss ratio of less than 0.003 is obtained.
First field-based atmospheric observation of the reduction of reactive mercury driven by sunlight
de Foy, Benjamin; Tong, Yindong; Yin, Xiufeng; Zhang, Wei; Kang, Shichang; Zhang, Qianggong; Zhang, Guoshuai; Wang, Xuejun; Schauer, James J.
2016-06-01
Hourly speciated measurements of atmospheric mercury made in a remote, high-altitude site in the Tibetan Plateau revealed the first field observations of the reduction of reactive mercury in the presence of sunlight in the atmosphere. Measurements were collected over four winter months on the shore of Nam Co Lake in the inland Tibetan Plateau. The data was analyzed to identify sources and atmospheric transformations of the speciated mercury compounds. The absence of local anthropogenic sources provided a unique opportunity to examine chemical transformations of mercury. An optimization algorithm was used to determine the parameters of a chemical box model that would match the measured reactive mercury concentrations. This required the presence of a photolytic reduction reaction previously observed in laboratory studies and in power plant plumes. In addition, the model estimated the role of vertical mixing in diluting reactive gaseous mercury during the day, and the role of bromine chemistry in oxidizing gaseous elemental mercury to produce reactive gaseous mercury. This work provides further evidence of the need to add the photolytic reduction reaction of oxidized mercury into atmospheric transport models in order to better simulate mercury deposition.
Institute of Scientific and Technical Information of China (English)
刘晓伟; 朱岩
2013-01-01
在探讨无功电压综合优化控制研究现状的基础上，从传统研究方法和人工智能研究方法2方面，介绍国内外无功电压综合优化控制方法的原理、发展历程、优势及存在的问题，为提高电力系统无功电压综合优化控制水平提供参考。%Based on the study of the control method of integrated optimization of reactive voltage this article introduces the principle, de-velopment process, advantages and existing problems of the control methods of the comprehensive optimization of reactive voltage at home and abroad, from 2 aspects, namely, traditional research methods and artificial intelligence methods, in order to provide reference for improving the comprehensive optimization of reactive voltage for the power system.
Reliability Based Optimization of Composite Laminates for Frequency Constraint
Institute of Scientific and Technical Information of China (English)
Wu Hao; Yan Ying; Liu Yujia
2008-01-01
The reliability based optimization (RBO) issue of composite laminates under fundamental frequency constraint is studied. Considering the uncertainties of material properties, the frequency constraint reliability of the structure is evaluated by the combination of response surface method (RSM) and finite element method. An optimization algorithm is developed based on the mechanism of laminate frequency characteristics, to optimize the laminate in terms of the ply amount and orientation angles. Numerical examples of composite laminates and cylindrical shell illustrate the advantages of the present optimization algorithm on the efficiency and applicability respects.The optimal solutions of RBO are obviously different from the deterministic optimization results, and the necessity of considering material property uncertainties in the composite srtuctural frequency constraint optimization is revealed.
Research on particle swarm optimization algorithm based on optimal movement probability
Ma, Jianhong; Zhang, Han; He, Baofeng
2017-01-01
The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.
Multi-objective reactive power optimization incorporating UPFC%计及UPFC的电力系统多目标无功优化
Institute of Scientific and Technical Information of China (English)
王韶; 刘光时; 邹青林
2012-01-01
The unified power flow controller (UPFC) can control the power flow flexibly, which gives full play to the potential of the power system. In order to improve safety and economy of power system, this paper introduces a kind of model for multi-objective reactive power optimization with UPFC based on the power injection model of UPFC. NSGA-II algorithm is used to solve the model. By improving the fast nondominated sorting approach, NSGA-II algorithm can deal with the divergence solution of power flow calculation effectively. After obtaining the Pareto optimal solutions, the analytic hierarchy process (AHP) is adopted to set each objective function's weight and rank these solutions to determine the best solution of reactive power optimization. The simulation result of the IEEE30 bus system demonstrates the proposed model and algorithm is corrective and efficient.%统一潮流控制器( UPFC)可以实现对电力系统潮流的灵活控制,从而充分发挥电力系统的潜力.基于UPFC的等效注入功率模型,以实现电力系统运行安全性和经济性为目标,建立了计及UPFC的多目标无功优化模型.求解方法为带精英策略的快速非支配排序遗传算法( NSGA- II),通过改进算法的快速非支配排序方法,使之能有效处理潮流计算不收敛的解；应用层次分析法( AHP)确定模型中各个目标的相对权重,并以此对Pareto最优解集进行排序,得出无功优化的最佳方案.最后对IEEE30节点系统进行仿真计算,结果表明了该模型和算法的有效性和正确性.
Lim, Steven; Lee, Keat Teong
2013-08-01
In this study, optimization of supercritical reactive extraction directly from Jatropha seeds in a high pressure batch reactor using Response Surface Methodology (RSM) coupled with Central Composite Rotatable Design (CCRD) was performed. Four primary variables (methanol to solid ratio (SSR), reaction temperature, time and CO2 initial pressure) were investigated under the proposed constraints. It was found that all variables had significant effects towards fatty acid methyl esters (FAME) yield. Moreover, three interaction effects between the variables also played a major role in influencing the final FAME yield. Optimum FAME yield at 92.0 wt.% was achieved under the following conditions: 5.9 SSR, 300°C, 12.3 min and 20 bar CO2. Final FAME product was discovered to fulfil existing international standard. Preliminary characterization analysis proved that the solid residue can be burnt as solid fuel in the form of biochar while the liquid product can be separated as specialty chemicals or burned as bio-oil for energy production. Copyright © 2013 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Wenjie Zhang
2016-12-01
Full Text Available Reactive oxygen species (ROS play important roles in cell signaling and homeostasis. However, an abnormally high level of ROS is toxic, and is implicated in a number of diseases. Positron emission tomography (PET imaging of ROS can assist in the detection of these diseases. For the purpose of clinical translation of [18F]6-(4-((1-(2-fluoroethyl-1H-1,2,3-triazol-4-ylmethoxyphenyl-5-methyl-5,6-dihydrophenanthridine-3,8-diamine ([18F]DHMT, a promising ROS PET radiotracer, we first manually optimized the large-scale radiosynthesis conditions and then implemented them in an automated synthesis module. Our manual synthesis procedure afforded [18F]DHMT in 120 min with overall radiochemical yield (RCY of 31.6% ± 9.3% (n = 2, decay-uncorrected and specific activity of 426 ± 272 GBq/µmol (n = 2. Fully automated radiosynthesis of [18F]DHMT was achieved within 77 min with overall isolated RCY of 6.9% ± 2.8% (n = 7, decay-uncorrected and specific activity of 155 ± 153 GBq/µmol (n = 7 at the end of synthesis. This study is the first demonstration of producing 2-[18F]fluoroethyl azide by an automated module, which can be used for a variety of PET tracers through click chemistry. It is also the first time that [18F]DHMT was successfully tested for PET imaging in a healthy beagle dog.
Ong, Wee-Jun; Tan, Lling-Lling; Chai, Siang-Piao; Yong, Siek-Ting; Mohamed, Abdul Rahman
2014-02-21
Titanium dioxide (TiO2) is one of the most widely investigated metal oxides due to its extraordinary surface, electronic and catalytic properties. However, the large band gap of TiO2 and massive recombination of photogenerated electron-hole pairs limit its photocatalytic and photovoltaic efficiency. Therefore, increasing research attention is now being directed towards engineering the surface structure of TiO2 at the most fundamental and atomic level namely morphological control of {001} facets in the range of microscale and nanoscale to fine-tune its physicochemical properties, which could ultimately lead to the optimization of its selectivity and reactivity. The synthesis of {001}-faceted TiO2 is currently one of the most active interdisciplinary research areas and demonstrations of catalytic enhancement are abundant. Modifications such as metal and non-metal doping have also been extensively studied to extend its band gap to the visible light region. This steady progress has demonstrated that TiO2-based composites with {001} facets are playing and will continue to play an indispensable role in the environmental remediation and in the search for clean and renewable energy technologies. This review encompasses the state-of-the-art research activities and latest advancements in the design of highly reactive {001} facet-dominated TiO2via various strategies, including hydrothermal/solvothermal, high temperature gas phase reactions and non-hydrolytic alcoholysis methods. The stabilization of {001} facets using fluorine-containing species and fluorine-free capping agents is also critically discussed in this review. To overcome the large band gap of TiO2 and rapid recombination of photogenerated charge carriers, modifications are carried out to manipulate its electronic band structure, including transition metal doping, noble metal doping, non-metal doping and incorporating graphene as a two-dimensional (2D) catalyst support. The advancements made in these aspects are
一种实用的配电网无功优化方法%A Practical Method of Reactive Power Optimization for Distribution Network
Institute of Scientific and Technical Information of China (English)
曹媛; 张帅辉; 马进
2011-01-01
电力系统无功优化一直是电力系统经济运行研究的重要组成部分.本文针对配电网无功优化的需求,提出了一种实用的无功优化方法.这种方法以配电网常用的电力系统分析综合程序(PSASP)输出的电网数据为基础,以全网有功功率损耗最小为目标,应用MATLAB遗传算法优化工具箱完成优化.最后,结合某地区配电网的实际数据进行无功优化,结果表明,该方法切实有效降低了网损,改善了电网的运行条件,有实际应用价值.%Reactive power optimization for electric power system always plays an important role of researching on security operation of power system.As to the demand for reactive power optimization in distribution network, this paper puts forward a practical method of reactive power optimization.By using of this method, the data exported by Power System Analysis Software Package (PSASP) is used, the minimization of losses of active power for entire network is the objective, and optimization is realized by genetic algorithm optimization toolbox in MATLAB.In the end, the reactive power optimization of certain distribution network according to the actual data is implemented by this method.The results show that the method can effectively reduce the network losses and can improve its operating conditions, which verifies its validity.
Energy Technology Data Exchange (ETDEWEB)
Du, Dan; Wang, Jun; Smith, Jordan N.; Timchalk, Charles; Lin, Yuehe
2009-11-15
A portable, rapid, and sensitive assessment of sub-clinical organophosphorus (OPs) agent exposure based on reactivation of cholinesterase (ChE) from OP-inhibited ChE using rat saliva (in vitro) was developed using an electrochemical sensor coupled with a microflow-injection system. The sensor was based on a carbon nanotube (CNT)-modified screen printed carbon electrode (SPE), which was integrated into a flow cell. Due to the extent of inter-individual ChE activity variability, ChE biomonitoring often requires an initial base-line determination (non-inhibited) of enzyme activity which is then directly compared with activity after OP exposure. This manuscript described an alternative strategy where reactivation of the phosphorylated enzyme was exploited to enable measurement of both inhibited and baseline ChE activity (i.e. after reactivation) in the same sample. The use of CNT makes the electrochemical detection of the products from enzymatic reactions more feasible with extremely high sensitivity and at low potentials. Paraoxon was selected as a model OP compound for in vitro inhibition studies. Some experiment parameters, (e.g. inhibition and reactivation times), have been optimized such that, 92 - 95% ChE reactivation can be achieved over a broad range of ChE inhibition (5 - 94 %) with paraoxon. The extent of enzyme inhibition using this electrochemical sensor correlates well with conventional enzyme activity measurements.
Decomposition Techniques and Effective Algorithms in Reliability-Based Optimization
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1995-01-01
The common problem of an extensive number of limit state function calculations in the various formulations and applications of reliability-based optimization is treated. It is suggested to use a formulation based on decomposition techniques so the nested two-level optimization problem can be solved...
Solution of optimal power flow using evolutionary-based algorithms
African Journals Online (AJOL)
This paper applies two reliable and efficient evolutionary-based methods named Shuffled Frog Leaping Algorithm ... Grey Wolf Optimizer (GWO) to solve Optimal Power Flow (OPF) problem. OPF is ..... The wolves search for the prey based on the alpha, beta, and delta positions. ..... Energy Conversion and Management, Vol.
Hierarchical control based on Hopfield network for nonseparable optimization problems
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The nonseparable optimization control problem is considered, where the overall objective function is not of an additive form with respect to subsystems. Since there exists the problem that computation is very slow when using iterative algorithms in multiobjective optimization, Hopfield optimization hierarchical network based on IPM is presented to overcome such slow computation difficulty. Asymptotic stability of this Hopfield network is proved and its equilibrium point is the optimal point of the original problem. The simulation shows that the net is effective to deal with the optimization control problem for large-scale nonseparable steady state systems.
Optimization based automated curation of metabolic reconstructions
Directory of Open Access Journals (Sweden)
Maranas Costas D
2007-06-01
Full Text Available Abstract Background Currently, there exists tens of different microbial and eukaryotic metabolic reconstructions (e.g., Escherichia coli, Saccharomyces cerevisiae, Bacillus subtilis with many more under development. All of these reconstructions are inherently incomplete with some functionalities missing due to the lack of experimental and/or homology information. A key challenge in the automated generation of genome-scale reconstructions is the elucidation of these gaps and the subsequent generation of hypotheses to bridge them. Results In this work, an optimization based procedure is proposed to identify and eliminate network gaps in these reconstructions. First we identify the metabolites in the metabolic network reconstruction which cannot be produced under any uptake conditions and subsequently we identify the reactions from a customized multi-organism database that restores the connectivity of these metabolites to the parent network using four mechanisms. This connectivity restoration is hypothesized to take place through four mechanisms: a reversing the directionality of one or more reactions in the existing model, b adding reaction from another organism to provide functionality absent in the existing model, c adding external transport mechanisms to allow for importation of metabolites in the existing model and d restore flow by adding intracellular transport reactions in multi-compartment models. We demonstrate this procedure for the genome- scale reconstruction of Escherichia coli and also Saccharomyces cerevisiae wherein compartmentalization of intra-cellular reactions results in a more complex topology of the metabolic network. We determine that about 10% of metabolites in E. coli and 30% of metabolites in S. cerevisiae cannot carry any flux. Interestingly, the dominant flow restoration mechanism is directionality reversals of existing reactions in the respective models. Conclusion We have proposed systematic methods to identify and
Reliability-Based Optimization and Optimal Reliability Level of Offshore Wind Turbines
DEFF Research Database (Denmark)
Tarp-Johansen, N.J.; Sørensen, John Dalsgaard
2006-01-01
Different formulations relevant for the reliability-based optimization of offshore wind turbines are presented, including different reconstruction policies in case of failure. Illustrative examples are presented and, as a part of the results, optimal reliability levels for the different failure m...
Reliability-Based Optimization and Optimal Reliability Level of Offshore Wind Turbines
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Tarp-Johansen, N.J.
2005-01-01
Different formulations relevant for the reliability-based optimization of offshore wind turbines are presented, including different reconstruction policies in case of failure. Illustrative examples are presented and, as a part of the results, optimal reliability levels for the different failure...
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...
DYNAMIC LABELING BASED FPGA DELAY OPTIMIZATION ALGORITHM
Institute of Scientific and Technical Information of China (English)
吕宗伟; 林争辉; 张镭
2001-01-01
DAG-MAP is an FPGA technology mapping algorithm for delay optimization and the labeling phase is the algorithm's kernel. This paper studied the labeling phase and presented an improved labeling method. It is shown through the experimental results on MCNC benchmarks that the improved method is more effective than the original method while the computation time is almost the same.
An approximation based global optimization strategy for structural synthesis
Sepulveda, A. E.; Schmit, L. A.
1991-01-01
A global optimization strategy for structural synthesis based on approximation concepts is presented. The methodology involves the solution of a sequence of highly accurate approximate problems using a global optimization algorithm. The global optimization algorithm implemented consists of a branch and bound strategy based on the interval evaluation of the objective function and constraint functions, combined with a local feasible directions algorithm. The approximate design optimization problems are constructed using first order approximations of selected intermediate response quantities in terms of intermediate design variables. Some numerical results for example problems are presented to illustrate the efficacy of the design procedure setforth.
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.
Directory of Open Access Journals (Sweden)
J. Fang
1998-01-01
Full Text Available An approach to the optimum design of structures, in which uncertainties with a fuzzy nature in the magnitude of the loads are considered, is proposed in this study. The optimization process under fuzzy loads is transformed into a fuzzy optimization problem based on the notion of Werners' maximizing set by defining membership functions of the objective function and constraints. In this paper, Werner's maximizing set is defined using the results obtained by first conducting an optimization through anti-optimization modeling of the uncertain loads. An example of a ten-bar truss is used to illustrate the present optimization process. The results are compared with those yielded by other optimization methods.
Synthesis and Reactivity of Tripodal Complexes Containing Pendant Bases
Energy Technology Data Exchange (ETDEWEB)
Blacquiere, Johanna M.; Pegis, Michael L.; Raugei, Simone; Kaminsky, Werner; Forget, Amelie; Cook, Sarah; Taguchi, Taketo; Borovik, Andrew S.; Mayer, James M.
2014-09-02
The synthesis of a new tripodal ligand family is reported, with tertiary-amine groups in the second-coordination sphere. The ligands are tris(amido)amine derivatives, with the pendant amines attached via a peptide coupling strategy. They were designed to be used in new catalysts for the oxygen reduction reaction (ORR), in which the pendant acid/base group could improve catalyst performance. Two members of the new ligand family were each metallated with Co(II) and Zn(II) to afford trigonal monopyramidal complexes. Reaction of the cobalt complexes, [Co(L)]-, with dioxygen reversibly generates a small amount of a Co(III)-superoxo species, which was characterized by EPR. Protonation of the zinc complex Zn[N{CH2CH2NC(O)CH2N(CH2Ph)2}3)-– ([Zn(TNBn)]-) with one equivalent of acid occurs with displacement and dissociation of an amide ligand. Addition of excess acid to the any of the complexes [M(L)]- results in complete proteolysis and formation of the ligands H3L. This decomposition limits the use of these complexes as catalysts for the ORR. An alternative ligand with two pyridyl arms was also prepared but could not be metallated. These studies highlight the importance of stability of the primary-coordination sphere of ORR electrocatalysts to both oxidative and acidic conditions. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences.
PERFORMANCE EVALUATION OF A CARBON-BASED REACTIVE BARRIER FOR NITRATE REMEDIATION
Nitrate (NO3-) is a common ground water contaminant related to agricultural activity, waste water disposal, leachate from landfills, septic systems, and industrial processes. This study reports on the performance of a carbon-based permeable reactive barrier (PRB) that was constr...
CARBON-BASED REACTIVE BARRIER FOR NITRATE REMEDIATION AT A FORMER SWINE CAFO
Nitrate (NO3-) is a common ground water contaminant related to agricultural activity, waste water disposal, leachate from landfills, septic systems, and industrial processes. This study reports on the performance of a carbon-based permeable reactive barrier (PRB) that was constr...
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 well
DEFF Research Database (Denmark)
Baohua, Zhang; Hu, Weihao; Chen, Zhe
2014-01-01
The paper deals with control techniques for minimizing the operating loss of doubly fed induction generator based wind generation systems when providing reactive power. The proposed method achieves its goal through controlling the rotor side q-axis current in the synchronous reference frame....... The formula for the control reference is explicitly deduced in this paper considering the losses of the generator, the power electronic devices and the filter. Three control strategies are compared with the proposed method under different wind speeds and different reactive power references. The simulation...
Function Optimization Based on Quantum Genetic Algorithm
Ying Sun; Hegen Xiong
2014-01-01
Optimization method is important in engineering design and application. Quantum genetic algorithm has the characteristics of good population diversity, rapid convergence and good global search capability and so on. It combines quantum algorithm with genetic algorithm. A novel quantum genetic algorithm is proposed, which is called Variable-boundary-coded Quantum Genetic Algorithm (vbQGA) in which qubit chromosomes are collapsed into variable-boundary-coded chromosomes instead of binary-coded c...
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.
Directory of Open Access Journals (Sweden)
Karolina Żukowska
2015-08-01
Full Text Available 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.
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.
Pump, Eva; Pazio, Aleksandra E; Woźniak, Krzysztof; Cavallo, Luigi
2015-01-01
Summary 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. PMID:26425202
Optimal Design of DC Electromagnets Based on Imposed Dynamic Characteristics
Directory of Open Access Journals (Sweden)
Sergiu Ivas
2016-10-01
Full Text Available In this paper is proposed a method for computing of optimal geometric dimensions of a DC electromagnet, based on the imposed dynamical characteristics. For obtaining the optimal design, it is built the criterion function in an analytic form that may be optimized in the order to find the constructive solution. Numerical simulations performed in Matlab software confirm the proposed work. The presented method can be extended to other electromagnetic devices which frequently operate in dynamic regime.
Support vector machines optimization based theory, algorithms, and extensions
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
Fuzzy controller based on chaos optimal design and its application
Institute of Scientific and Technical Information of China (English)
邹恩; 李祥飞; 张泰山
2004-01-01
In order to overcome difficulty of tuning parameters of fuzzy controller, a chaos optimal design method based on annealing strategy is proposed. First, apply the chaotic variables to search for parameters of fuzzy controller, and transform the optimal variables into chaotic variables by carrier-wave method. Making use of the intrinsic stochastic property and ergodicity of chaos movement to escape from the local minimum and direct optimization searching within global range, an approximate global optimal solution is obtained. Then, the chaos local searching and optimization based on annealing strategy are cited, the parameters are optimized again within the limits of the approximate global optimal solution, the optimization is realized by means of combination of global and partial chaos searching, which can converge quickly to global optimal value. Finally, the third order system and discrete nonlinear system are simulated and compared with traditional method of fuzzy control. The results show that the new chaos optimal design method is superior to fuzzy control method, and that the control results are of high precision, with no overshoot and fast response.
Nanosized iron based permeable reactive barriers for nitrate removal - Systematic review
Araújo, Rui; Castro, Ana C. Meira; Santos Baptista, João; Fiúza, António
2016-08-01
It is unquestionable that an effective decision concerning the usage of a certain environmental clean-up technology should be conveniently supported. Significant amount of scientific work focussing on the reduction of nitrate concentration in drinking water by both metallic iron and nanomaterials and their usage in permeable reactive barriers has been worldwide published over the last two decades. This work aims to present in a systematic review of the most relevant research done on the removal of nitrate from groundwater using nanosized iron based permeable reactive barriers. The research was based on scientific papers published between 2004 and June 2014. It was performed using 16 combinations of keywords in 34 databases, according to PRISMA statement guidelines. Independent reviewers validated the selection criteria. From the 4161 records filtered, 45 met the selection criteria and were selected to be included in this review. This study's outcomes show that the permeable reactive barriers are, indeed, a suitable technology for denitrification and with good performance record but the long-term impact of the use of nanosized zero valent iron in this remediation process, in both on the environment and on the human health, is far to be conveniently known. As a consequence, further work is required on this matter, so that nanosized iron based permeable reactive barriers for the removal of nitrate from drinking water can be genuinely considered an eco-efficient technology.
Cai, Lanlan; Li, Peng; Luo, Qi; Zhai, Pengcheng; Zhang, Qingjie
2017-03-01
As no single thermoelectric material has presented a high figure-of-merit (ZT) over a very wide temperature range, segmented thermoelectric generators (STEGs), where the p- and n-legs are formed of different thermoelectric material segments joined in series, have been developed to improve the performance of thermoelectric generators. A crucial but difficult problem in a STEG design is to determine the optimal values of the geometrical parameters, like the relative lengths of each segment and the cross-sectional area ratio of the n- and p-legs. Herein, a multi-parameter and nonlinear optimization method, based on the Improved Powell Algorithm in conjunction with the discrete numerical model, was implemented to solve the STEG's geometrical optimization problem. The multi-parameter optimal results were validated by comparison with the optimal outcomes obtained from the single-parameter optimization method. Finally, the effect of the hot- and cold-junction temperatures on the geometry optimization was investigated. Results show that the optimal geometry parameters for maximizing the specific output power of a STEG are different from those for maximizing the conversion efficiency. Data also suggest that the optimal geometry parameters and the interfacial temperatures of the adjacent segments optimized for maximum specific output power or conversion efficiency vary with changing hot- and cold-junction temperatures. Through the geometry optimization, the CoSb3/Bi2Te3-based STEG can obtain a maximum specific output power up to 1725.3 W/kg and a maximum efficiency of 13.4% when operating at a hot-junction temperature of 823 K and a cold-junction temperature of 298 K.
Performance investigation of multigrid optimization for DNS-based optimal control problems
Nita, Cornelia; Vandewalle, Stefan; Meyers, Johan
2016-11-01
Optimal control theory in Direct Numerical Simulation (DNS) or Large-Eddy Simulation (LES) of turbulent flow involves large computational cost and memory overhead for the optimization of the controls. In this context, the minimization of the cost functional is typically achieved by employing gradient-based iterative methods such as quasi-Newton, truncated Newton or non-linear conjugate gradient. In the current work, we investigate the multigrid optimization strategy (MGOpt) in order to speed up the convergence of the damped L-BFGS algorithm for DNS-based optimal control problems. The method consists in a hierarchy of optimization problems defined on different representation levels aiming to reduce the computational resources associated with the cost functional improvement on the finest level. We examine the MGOpt efficiency for the optimization of an internal volume force distribution with the goal of reducing the turbulent kinetic energy or increasing the energy extraction in a turbulent wall-bounded flow; problems that are respectively related to drag reduction in boundary layers, or energy extraction in large wind farms. Results indicate that in some cases the multigrid optimization method requires up to a factor two less DNS and adjoint DNS than single-grid damped L-BFGS. The authors acknowledge support from OPTEC (OPTimization in Engineering Center of Excellence, KU Leuven, Grant No PFV/10/002).
Optimal Reliability-Based Planning of Experiments for POD Curves
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Faber, M. H.; Kroon, I. B.
Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First O...... Order Reliability Methods in combination with life-cycle cost-optimal inspection and maintenance planning. The methodology is based on preposterior analyses from Bayesian decision theory. An illustrative example is shown.......Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First...
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.
Gradient-Based Cuckoo Search for Global Optimization
Directory of Open Access Journals (Sweden)
Seif-Eddeen K. Fateen
2014-01-01
Full Text Available One of the major advantages of stochastic global optimization methods is the lack of the need of the gradient of the objective function. However, in some cases, this gradient is readily available and can be used to improve the numerical performance of stochastic optimization methods specially the quality and precision of global optimal solution. In this study, we proposed a gradient-based modification to the cuckoo search algorithm, which is a nature-inspired swarm-based stochastic global optimization method. We introduced the gradient-based cuckoo search (GBCS and evaluated its performance vis-à-vis the original algorithm in solving twenty-four benchmark functions. The use of GBCS improved reliability and effectiveness of the algorithm in all but four of the tested benchmark problems. GBCS proved to be a strong candidate for solving difficult optimization problems, for which the gradient of the objective function is readily available.
Nanoengineered Carbon-Based Materials For Reactive Adsorption of Toxic Industrial Compounds
2015-01-13
ChemSusChem, (03 2011): 0. doi: 10.1002/cssc.201000296 Camille Petit, Teresa J. Bandosz. Synthesis , Characterization, and Ammonia Adsorption...Bandosz. The synthesis and characterization of copper-based metal organic framework/graphene composites, Carbon, (9 2010): . doi: C. Petit, B...Mendoza, T.J. Bandosz. Reactive adsorption of ammonia on Cu-based MOF /graphene composites , Langmuir, (7 2010): . doi: Kavindra Singh, Nikolina A
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.
Reliability-Based Optimization for Maintenance Management in Bridge Networks
Hu, Xiaofei
2014-01-01
This dissertation addresses the problem of optimizing maintenance, repair and reconstruction decisions for bridge networks. Incorporating network topologies into bridge management problems is computationally difficult. Because of the interdependencies among networked bridges, they have to be analyzed together. Simulation-based numerical optimization techniques adopted in past research are limited to networks of moderate sizes. In this dissertation, novel approaches are developed to dete...
Optimal Reliability-Based Planning of Experiments for POD Curves
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Faber, M. H.; Kroon, I. B.
Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First...
Cross-layer utility-based system optimization
Ditzel, M.; Kester, L.J.H.M.; Broek, S.P. van den; Rijn, M. van
2013-01-01
Multilevel fusion systems need provisions to optimally schedule scarce processing and communication resources. To this end, we explore the idea of using utility-based metrics to optimize the run-time operation of a computation and communication constrained multilevel system, including automatic deci
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...... problems are described. Numerical tests indicate that a sequential technique called the bounds iteration method (BIM) is particularly fast and stable....
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....
portfolio optimization based on nonparametric estimation methods
Directory of Open Access Journals (Sweden)
mahsa ghandehari
2017-03-01
Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.
Optimization of FPGA-based Moore FSM
Barkalov, Aleksander; Titarenko, Larysa; Chmielewski, Sławomir
2014-10-01
A metod is proposed for hardware reduction in FPGA-based Moore FSM. It is based on using two sources of codes. It reduces the number of LUTs in the FSM circuit. The results of investigations are shown.
Optimal Heating in Heat-Treatment Process Based on Grey Asynchronous Particle Swarm Optimization
Institute of Scientific and Technical Information of China (English)
2012-01-01
To ensure plate heating quality and reduce energy consumption in heat-treatment process, optimal heating for plates in a roller hearth furnace was investigated and a new strategy for heating procedure optimization was developed. During solving process, plate temperature forecast model based on heat transfer mechanics was established to calculate plate temperature with the assumed heating procedure. In addition, multi-objective feature of optimal heating was analyzed. And the method, which is composed of asynchronous particle swarm optimization and grey relational analysis, was adopted for solving the multi-objective problem. The developed strategy for optimizing heating has been applied to the mass production. The result indicates that the absolute plate discharging temperature deviation between measured value and target value does not exceed ± 8 ℃, and the relative deviation is less than ± 0.77%.
Optimization of Land Use Structure Based on Ecological GREEN Equivalent
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Optimization of land use structure consists of economic and social and ecological optimization.Applying the minds of system engineering and principles of ecology,this paper presents such thoughts:the optimal forest-coverage rate calculated according to the reality of a district is set as main standard of ecological rationality in the district;through considering the value of ecosystem services of the land with GREEN equivalent (mainly cultivated land and grassland)and based on the rule,GREEN equivalent,this paper introduces the area conversion between woodland and cultivated land,also between woodland and grassland;this paper establishes a multi-dimension controlling model of optimization of land use structure.In addition,a multi-objective linear programming model for optimization of land use structure is designed.In the end,this paper tests and verifies this theory of ecological optimization,taking Qionghai city in Hainan Province as an example.
Optimization of transmission system design based on genetic algorithm
Directory of Open Access Journals (Sweden)
Xianbing Chen
2016-05-01
Full Text Available Transmission system is a crucial precision mechanism for twin-screw chemi-mechanical pulping equipment. The structure of the system designed by traditional method is not optimal because the structure designed by the traditional methods is easy to fall into the local optimum. To achieve the global optimum, this article applies the genetic algorithm which has grown in recent years in the field of structure optimization. The article uses the volume of transmission system as the objective function to optimize the structure designed by traditional method. Compared to the simulation results, the original structure is not optimal, and the optimized structure is tighter and more reasonable. Based on the optimized results, the transmission shafts in the transmission system are designed and checked, and the parameters of the twin screw are selected and calculated. The article provided an effective method to design the structure of transmission system.
Reliability-based design optimization with progressive surrogate models
Kanakasabai, Pugazhendhi; Dhingra, Anoop K.
2014-12-01
Reliability-based design optimization (RBDO) has traditionally been solved as a nested (bilevel) optimization problem, which is a computationally expensive approach. Unilevel and decoupled approaches for solving the RBDO problem have also been suggested in the past to improve the computational efficiency. However, these approaches also require a large number of response evaluations during optimization. To alleviate the computational burden, surrogate models have been used for reliability evaluation. These approaches involve construction of surrogate models for the reliability computation at each point visited by the optimizer in the design variable space. In this article, a novel approach to solving the RBDO problem is proposed based on a progressive sensitivity surrogate model. The sensitivity surrogate models are built in the design variable space outside the optimization loop using the kriging method or the moving least squares (MLS) method based on sample points generated from low-discrepancy sampling (LDS) to estimate the most probable point of failure (MPP). During the iterative deterministic optimization, the MPP is estimated from the surrogate model for each design point visited by the optimizer. The surrogate sensitivity model is also progressively updated for each new iteration of deterministic optimization by adding new points and their responses. Four example problems are presented showing the relative merits of the kriging and MLS approaches and the overall accuracy and improved efficiency of the proposed approach.
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.
Performance optimization of web-based medical simulation.
Halic, Tansel; Ahn, Woojin; De, Suvranu
2013-01-01
This paper presents a technique for performance optimization of multimodal interactive web-based medical simulation. A web-based simulation framework is promising for easy access and wide dissemination of medical simulation. However, the real-time performance of the simulation highly depends on hardware capability on the client side. Providing consistent simulation in different hardware is critical for reliable medical simulation. This paper proposes a non-linear mixed integer programming model to optimize the performance of visualization and physics computation while considering hardware capability and application specific constraints. The optimization model identifies and parameterizes the rendering and computing capabilities of the client hardware using an exploratory proxy code. The parameters are utilized to determine the optimized simulation conditions including texture sizes, mesh sizes and canvas resolution. The test results show that the optimization model not only achieves a desired frame per second but also resolves visual artifacts due to low performance hardware.
Hybrid and adaptive meta-model-based global optimization
Gu, J.; Li, G. Y.; Dong, Z.
2012-01-01
As an efficient and robust technique for global optimization, meta-model-based search methods have been increasingly used in solving complex and computation intensive design optimization problems. In this work, a hybrid and adaptive meta-model-based global optimization method that can automatically select appropriate meta-modelling techniques during the search process to improve search efficiency is introduced. The search initially applies three representative meta-models concurrently. Progress towards a better performing model is then introduced by selecting sample data points adaptively according to the calculated values of the three meta-models to improve modelling accuracy and search efficiency. To demonstrate the superior performance of the new algorithm over existing search methods, the new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization example involving vehicle crash simulation. The method is particularly suitable for design problems involving computation intensive, black-box analyses and simulations.
Energy Technology Data Exchange (ETDEWEB)
Bergren, Adam Johan [Iowa State Univ., Ames, IA (United States)
2006-01-01
Electroanalytical chemistry is often utilized in chemical analysis and Fundamental studies. Important advances have been made in these areas since the advent of chemically modified electrodes: the coating of an electrode with a chemical film in order to impart desirable, and ideally, predictable properties. These procedures enable the exploitation of unique reactivity patterns. This dissertation presents studies that investigate novel reaction mechanisms at self-assembled monolayers on gold. In particular, a unique electrochemical current amplification scheme is detailed that relies on a selective electrode to enable a reactivity pattern that results in regeneration of the analyte (redox recycling). This regenerating reaction can occur up to 250 times for each analyte molecule, leading to a notable enhancement in the observed current. The requirements of electrode selectivity and the resulting amplification and detection limit improvements are described with respect to the heterogeneous and homogeneous electron transfer rates that characterize the system. These studies revealed that the heterogeneous electrolysis of the analyte should ideally be electrochemically reversible, while that for the regenerating agent should be held to a low level. Moreover, the homogeneous reaction that recycles the analyte should occur at a rapid rate. The physical selectivity mechanism is also detailed with respect to the properties of the electrode and redox probes utilized. It is shown that partitioning of the analyte into/onto the adlayer leads to the extraordinary selectivity of the alkanethiolate monolayer modified electrode. Collectively, these studies enable a thorough understanding of the complex electrode mechanism required for successful redox recycling amplification systems, Finally, in a separate (but related) study, the effect of the akyl chain length on the heterogeneous electron transfer behavior of solution-based redox probes is reported, where an odd-even oscillation
Stochastic learning and optimization a sensitivity-based approach
Cao, Xi-Ren
2007-01-01
Performance optimization is vital in the design and operation of modern engineering systems. This book provides a unified framework based on a sensitivity point of view. It introduces new approaches and proposes new research topics.
Design of Optimal Attack-Angle for RLV Reentry Based on Quantum Particle Swarm Optimization
Directory of Open Access Journals (Sweden)
Qingzhen Zhang
2014-04-01
Full Text Available The attack-angle optimization is a key problem for reentry trajectory design of a gliding type reusable launch vehicle (RLV. In order to solve such a problem, the equations of motion are derived first. A physical programming (PP method is briefly presented and the preference function is reflected in mathematical representation. The attack-angle optimization problem with four criteria (i.e., downrange, total heat, heat rate, and trajectory oscillation is converted into a single-objective optimization problem based on the PP method. A winged gliding reentry RLV is chosen as a simulation example and the transformed single-objective problem is solved by the quantum-behaved particle swarm optimization (QPSO algorithm based on two types of preference structures, longer range preference and smaller total heat preference. The constraints of maximizing heating rate, normal load factor, and dynamic pressure and minimizing terminal velocity are handled by a penalty function method. The simulation results demonstrate the efficiency of these methods. The physical causation of the optimal solution and the typical profiles are presented, which reflect the designer's preference. At last, the feasibility and advantages of QPSO are revealed by comparison with the results of genetic algorithm (GA and standard particle swarm optimization (PSO algorithm on this optimization problem.
Institute of Scientific and Technical Information of China (English)
WANG Shu-fang; ZHANG Li; JIANG Jian-guo; WANG Ru-lin
2004-01-01
Inevitably, the question of reactive power compensation was aroused by applied of power electronics. Based on the study of the instantaneous reactive power theory, the designs of TCR(thyristor control reactor) thyristor control reactor reactive power compensation system and TCR single closed loop strategy was proposed. In addition, as digital simulation software, Arene was applied to simulate the Jining coal mine No.2 system. The simulation results validate that the design is effective to improve power factor and stabilization of the system.
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...
Torpedo Overall Multidisciplinary Design Based on Collaborative Optimization
Institute of Scientific and Technical Information of China (English)
YU De-hai; SONG Bao-wei; LI Jia-wang; YANG Shi-xing; GAO Zhi-yong
2008-01-01
A torpedo multidisciplinary design optimization (MDO) based on the collaborative optimization is proposed. Through decomposition and coordination, some problems in torpedo design such as multidisciplinary coupling, large data volume and complex data relationships can be solved. Taking aim at some complex problems in the torpedo design, such as computation in multidisciplinary design, organization, modeling and information exchange, the collaborative optimization methods based on approximate technology are presented. An example to increase the torpedo range is also given. It demonstrates that the method can converge quickly, has higher reliability and smaller data throughput, and is a very effective MDO method.
Adaptive Central Force Optimization Algorithm Based on the Stability Analysis
Directory of Open Access Journals (Sweden)
Weiyi Qian
2015-01-01
Full Text Available In order to enhance the convergence capability of the central force optimization (CFO algorithm, an adaptive central force optimization (ACFO algorithm is presented by introducing an adaptive weight and defining an adaptive gravitational constant. The adaptive weight and gravitational constant are selected based on the stability theory of discrete time-varying dynamic systems. The convergence capability of ACFO algorithm is compared with the other improved CFO algorithm and evolutionary-based algorithm using 23 unimodal and multimodal benchmark functions. Experiments results show that ACFO substantially enhances the performance of CFO in terms of global optimality and solution accuracy.
Optimization Research of Urban Space Configuration Based on Space Syntax
Institute of Scientific and Technical Information of China (English)
Zhu Qing; Wang Jingwen
2005-01-01
In this paper, a new method based on the space syntax is presented to optimize the urban space configuration. Space syntax theory is used to detect systematically whether one urban space configuration is optimal or not from four aspects including traffic space, cognition space, land use space and culture space. After introducing the computational and cognitive aspects of space syntax for the research of urban space, a framework of urban space optimization based on space syntax is proposed, then the integration with GIS and the extension to third dimension are discussed. Finally, a case study for Kanmen town of Zhejiang province of P.R.China is illustrated by using Axwoman tool.
Emission of reactive compounds and secondary products from wood-based furniture coatings
Salthammer, T.; Schwarz, A.; Fuhrmann, F.
Emissions of organic fragmentation products, so-called "secondary emission products" and reactive species from wood-based furniture coatings have been studied in 1 m 3 test chambers. the climatic conditions were representative of indoor environments. Relevant compounds and compound groups were the wetting agent 2,4,7,9-tetramethyl-5-dicyne-4,7-diol (T4MDD), the plasticiser di-2-ethyl-hexyl-phthalate (DEHP), aliphatic aldehydes, monoterpenes, photoinitiator fragments, acrylic monomers/reactive solvents and diisocyanate monomers. Such substances may affect human health in several ways. Aliphatic aldehydes and some photoinitiator fragments are of strong odour, while acrylates and diisocyanates cause irritation of skin, eyes and upper airways. Terpenes and reactive solvents like styrene undergo indoor chemistry in the presence of ozone, nitrogen oxides or hydroxy radicals. Secondary emission products and reactive species can achieve significant indoor concentrations. On the other hand, it has been reported that even small quantities can cause health effects. In the cases of indoor studies with special regard to emissions from furniture, chemical analysis should always include these compounds.
AN OPTIMIZATION ALGORITHM BASED ON BACTERIA BEHAVIOR
Directory of Open Access Journals (Sweden)
Ricardo Contreras
2014-09-01
Full Text Available Paradigms based on competition have shown to be useful for solving difficult problems. In this paper we present a new approach for solving hard problems using a collaborative philosophy. A collaborative philosophy can produce paradigms as interesting as the ones found in algorithms based on a competitive philosophy. Furthermore, we show that the performance - in problems associated to explosive combinatorial - is comparable to the performance obtained using a classic evolutive approach.
Reactive Power Compensation Method Considering Minimum Effective Reactive Power Reserve
Gong, Yiyu; Zhang, Kai; Pu, Zhang; Li, Xuenan; Zuo, Xianghong; Zhen, Jiao; Sudan, Teng
2017-05-01
According to the calculation model of minimum generator reactive power reserve of power system voltage stability under the premise of the guarantee, the reactive power management system with reactive power compensation combined generator, the formation of a multi-objective optimization problem, propose a reactive power reserve is considered the minimum generator reactive power compensation optimization method. This method through the improvement of the objective function and constraint conditions, when the system load growth, relying solely on reactive power generation system can not meet the requirement of safe operation, increase the reactive power reserve to solve the problem of minimum generator reactive power compensation in the case of load node.
Concentric Circular Antenna Array Synthesis Using Biogeography Based Optimization
Directory of Open Access Journals (Sweden)
Urvinder Singh
2012-03-01
Full Text Available Biogeography based optimization (BBO is a new stochastic force based on the science of biogeography. Biogeography is the schoolwork of geographical allotment of biological organisms. BBO utilizes migration operator to share information between the problem solutions. The problem solutions are known as habitats and sharing of features is called migration. In this paper, BBO algorithm is developed to optimize the current excitations of concentric circular antenna arrays (CCAA. Concentric Circular Antenna Array (CCAA has numerous attractive features that make it essential in mobile and communication applications. The goal of the optimization is to reduce the side lobe levels and the primary lobe beam width as much as possible. To confirm the capabilities of BBO, three different CCAA antennas of different sizes are taken. The results obtained by BBO are compared with the Real coded Genetic Algorithm (RGA, Craziness based Particle Swarm Optimization (CRPSO and Hybrid Evolutionary Programming (HEP.
Modeling of the jack rabbit series of experiments with a temperature based reactive burn model
Desbiens, Nicolas
2017-01-01
The Jack Rabbit experiments, performed by Lawrence Livermore National Laboratory, focus on detonation wave corner turning and shock desensitization. Indeed, while important for safety or charge design, the behaviour of explosives in these regimes is poorly understood. In this paper, our temperature based reactive burn model is calibrated for LX-17 and compared to the Jack Rabbit data. It is shown that our model can reproduce the corner turning and shock desensitization behaviour of four out of the five experiments.
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.
Directory of Open Access Journals (Sweden)
Heng-Yi Su
2016-01-01
Full Text Available This paper proposes an optimal control scheme based on a synchronized phasor (synchrophasor for power system secondary voltage control. The framework covers voltage stability monitoring and control. Specifically, a voltage stability margin estimation algorithm is developed and built in the newly designed adaptive secondary voltage control (ASVC method to achieve more reliable and efficient voltage regulation in power systems. This new approach is applied to improve voltage profile across the entire power grid by an optimized plan for VAR (reactive power sources allocation; therefore, voltage stability margin of a power system can be increased to reduce the risk of voltage collapse. An extensive simulation study on the IEEE 30-bus test system is carried out to demonstrate the feasibility and effectiveness of the proposed scheme.
Optimal Sensor Decision Based on Particle Filter
Institute of Scientific and Technical Information of China (English)
XU Meng; WANG Hong-wei; HU Shi-qiang
2006-01-01
A novel infrared and radar synergistic tracking algorithm, which is based on the idea of closed loop control, and target's motion model identification and particle filter approach, was put forward. In order to improve the observability and filtering divergence of infrared search and tracking, the unscented Kalman filter algorithm that has stronger ability of non-linear approximation was adopted. The polynomial and least square method based on radar and IRST measurements to identify the parameters of the model was proposed, and a "pseudo sensor" was suggested to estimate the target position according to the identified model even if the radar is turned off. At last,the average Kullback-Leibler discrimination distance based on particle filter was used to measure the tracking performance, based on tracking performance and fuzzy stochastic decision, the idea of closed loop was used to retrieve the module parameter of "pseudo sensor". The experimental result indicates that the algorithm can not only limit the radar activity effectively but also keep the tracking accuracy of active/passive system well.
GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE
Directory of Open Access Journals (Sweden)
Ashish Jain
2012-07-01
Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.
AGENT based structural static and dynamic collaborative optimization
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A static and dynamic collaborative optimization mode for complex machine system and itsontology project relationship are put forward, on which an agent-based structural static and dynamiccollaborative optimization system is constructed as two agent colonies: optimization agent colony andfinite element analysis colony. And a two-level solving strategy as well as the necessity and possibilityfor handing with finite element analysis model in multi-level mode is discussed. Furthermore, the coop-eration of all FEA agents for optimal design of complicated structural is studied in detail. Structural stat-ic and dynamic collaborative optimization of hydraulic excavator working equimpent is taken as an ex-ample to show that the system is reliable.
Earth Observation Satellites Scheduling Based on Decomposition Optimization Algorithm
Directory of Open Access Journals (Sweden)
Feng Yao
2010-11-01
Full Text Available A decomposition-based optimization algorithm was proposed for solving Earth Observation Satellites scheduling problem. The problem was decomposed into task assignment main problem and single satellite scheduling sub-problem. In task assignment phase, the tasks were allocated to the satellites, and each satellite would schedule the task respectively in single satellite scheduling phase. We adopted an adaptive ant colony optimization algorithm to search the optimal task assignment scheme. Adaptive parameter adjusting strategy and pheromone trail smoothing strategy were introduced to balance the exploration and the exploitation of search process. A heuristic algorithm and a very fast simulated annealing algorithm were proposed to solve the single satellite scheduling problem. The task assignment scheme was valued by integrating the observation scheduling result of multiple satellites. The result was responded to the ant colony optimization algorithm, which can guide the search process of ant colony optimization. Computation results showed that the approach was effective to the satellites observation scheduling problem.
Study on Ice Regime Forecast Based on SVR Optimized by Particle Swarm Optimization Algorithm
Institute of Scientific and Technical Information of China (English)
WANG; Fu-qiang; RONG; Fei
2012-01-01
[Objective] The research aimed to study forecast models for frozen and melted dates of the river water in Ningxia-Inner Mongolia section of the Yellow River based on SVR optimized by particle swarm optimization algorithm. [Method] Correlation analysis and cause analysis were used to select suitable forecast factor combination of the ice regime. Particle swarm optimization algorithm was used to determine the optimal parameter to construct forecast model. The model was used to forecast frozen and melted dates of the river water in Ningxia-Inner Mongolia section of the Yellow River. [Result] The model had high prediction accuracy and short running time. Average forecast error was 3.51 d, and average running time was 10.464 s. Its forecast effect was better than that of the support vector regression optimized by genetic algorithm (GA) and back propagation type neural network (BPNN). It could accurately forecast frozen and melted dates of the river water. [Conclusion] SVR based on particle swarm optimization algorithm could be used for ice regime forecast.
Energy Technology Data Exchange (ETDEWEB)
Cho, Tae Min; Lee, Byung Chai [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)
2010-01-15
In this study, an effective method for reliability-based design optimization (RBDO) is proposed enhancing sequential optimization and reliability assessment (SORA) method by convex approximations. In SORA, reliability estimation and deterministic optimization are performed sequentially. The sensitivity and function value of probabilistic constraint at the most probable point (MPP) are obtained in the reliability analysis loop. In this study, the convex approximations for probabilistic constraint are constructed by utilizing the sensitivity and function value of the probabilistic constraint at the MPP. Hence, the proposed method requires much less function evaluations of probabilistic constraints in the deterministic optimization than the original SORA method. The efficiency and accuracy of the proposed method were verified through numerical examples
A new efficient optimal path planner for mobile robot based on Invasive Weed Optimization algorithm
Mohanty, Prases K.; Parhi, Dayal R.
2014-12-01
Planning of the shortest/optimal route is essential for efficient operation of autonomous mobile robot or vehicle. In this paper Invasive Weed Optimization (IWO), a new meta-heuristic algorithm, has been implemented for solving the path planning problem of mobile robot in partially or totally unknown environments. This meta-heuristic optimization is based on the colonizing property of weeds. First we have framed an objective function that satisfied the conditions of obstacle avoidance and target seeking behavior of robot in partially or completely unknown environments. Depending upon the value of objective function of each weed in colony, the robot avoids obstacles and proceeds towards destination. The optimal trajectory is generated with this navigational algorithm when robot reaches its destination. The effectiveness, feasibility, and robustness of the proposed algorithm has been demonstrated through series of simulation and experimental results. Finally, it has been found that the developed path planning algorithm can be effectively applied to any kinds of complex situation.
一种电力系统无功优化的新型混合优化算法%A novel hybrid algorithm for reactive-power optimization of power system
Institute of Scientific and Technical Information of China (English)
宋永超; 张勇军; 蔡泽祥; 杨银国; 朱鹰屏
2011-01-01
提出了一种适合于求解电力系统无功优化问题的新型混合优化算法,该算法结合基于邻域搜索的群搜索优化算法和改进灾变遗传算法.综合考虑两种算法的特点,将无功优化问题分步进行交替求解,第一步采用改进灾变遗传算法迭代两次更新解群体,第二步在此基础上采用基于邻域搜索的群搜索优化算法使群体中各解向当前最优解靠拢,交替进行,最终达到全局最优解.在IEEE118节点系统试验计算结果表明,与其他算法相比,该混合算法具有较好的全局收敛性且不容易陷入局部最优,在优化效果以及算法稳定度上都具有明显的优势.在某实际290节点电网计算结果表明,该混合算法能够适应实际电力系统无功优化问题的求解.%Based on the group search optimizer with neighborhood search (NGSO) and the improved catastrophic genetic algorithm(ICGA), this paper proposes a novel hybrid algorithm for solving reactive-power optimization of power system. Considering the characteristics of the two kinds of algorithms, the reactive power optimization will be solved by improved sequential method, which adopts ICGA twice to update the solutions first and then NGSO is used to make the solutions closer to the current optimal solution, and then alternates to get the global optimal solution. When it is tested in IEEE118-bus system, the hybrid algorithm has competitive superiority to other algorithms in terms of global performance and local optimum search, especially on the optimization effect and stability. The hybrid algorithm is also applied to the actual 290-bus grid. The promising results illustrate the applicability of hybrid algorithm for solving reactive-power optimization of the actual power system.This work is supported by National Natural Science Foundation of China (No. 51077055).
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.
Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm
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P. Sabarinath
2015-01-01
Full Text Available The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms.
Energy Technology Data Exchange (ETDEWEB)
Fingerhut, Benjamin Philipp
2011-02-08
One of the main challenges in photochemical energy conversion is the design of charge separating units which are able to generate a long lived charge separated state, and to couple efficiently to an energy storage state. In part I of this work the energy conversion efficiency of a photochemical unit inspired by bacterial photosynthesis is investigated. The developed model is based on non-adiabatic multi step electron transfer to generate a trans-membrane potential gradient. Upon optimization with multi objective genetic algorithms, the biological strategies for high quantum efficiency in photosynthetic reaction centers are derived, which have to suppress loss channels such as charge recombination. The concepts of bacterial photosynthesis are extended to the design of artificial photochemical devices. The unified model consists of a charge separation unit and an energy storing system whereby the coupling between both units is assured by thermal repopulation according to the principle of detailed balance. The complete photosynthetic unit is characterized by the respective current-voltage relation and an upper limit for the overall energy efficiency is derived under AM1.5 global conditions. Such a realistic chemical solar energy conversion system can reach efficiencies, which are comparable to the limits of an ideal single-junction solar cell. In Part II of this work the reactive dynamics of two surrounding controlled photoreactions is investigated on a microscopic scale. In general the effect of the surrounding can be classified into intramolecular contributions, like steric or electronic effects, and intermolecular contributions like the solvent or the embedding in an enzyme. Both limiting cases are examined on the basis of two generic photoreactions. The Dewar DNA lesion follows quantitatively from the 6-4 lesion by UV-A/B irradiation and constitutes the stable end product of continuous solar irradiation. Here the detailed mechanism of the formally 4{pi
Rajkumar, K.; Muthukumar, M.
2015-03-01
In this study, central composite design at five levels (-β, -1, 0, +1, +β) combined with response surface methodology has been applied to optimize C.I. Reactive Yellow 186 using electro-oxidation process with graphite electrodes in a batch reactor. The variables considered were the pH (X 1), NaCl concentration (M) (X 2), and electrolysis time (min) (X 3) on C.I. Reactive Yellow 186 were studied. A second-order empirical relationship between the response and independent variables was derived. Analysis of variance showed a high coefficient of determination value (R 2 = 0.9556 and 0.9416 for color and COD, respectively). The optimized condition of the electro-oxidation of Reactive Yellow 186 is as follows: pH 3.9; NaCl concentration 0.11 M; and electrolysis time 18 min. Under this condition, the maximal decolorization efficiency of 99 % and COD removal 73 % was achieved. Detailed physico-chemical analysis of electrode and residues of the electro-oxidation process has also been carried out UV-Visible and Fourier transform infrared spectroscopy. The intermediate compounds formed during the oxidation were identified using a gas chromatography coupled with mass spectrometry. According to these results, response surface methodology could be useful for reducing the time to treat effluent wastewater.
Rajkumar, K.; Muthukumar, M.
2017-05-01
In this study, central composite design at five levels (- β, -1, 0, +1, + β) combined with response surface methodology has been applied to optimize C.I. Reactive Yellow 186 using electro-oxidation process with graphite electrodes in a batch reactor. The variables considered were the pH ( X 1), NaCl concentration (M) ( X 2), and electrolysis time (min) ( X 3) on C.I. Reactive Yellow 186 were studied. A second-order empirical relationship between the response and independent variables was derived. Analysis of variance showed a high coefficient of determination value ( R 2 = 0.9556 and 0.9416 for color and COD, respectively). The optimized condition of the electro-oxidation of Reactive Yellow 186 is as follows: pH 3.9; NaCl concentration 0.11 M; and electrolysis time 18 min. Under this condition, the maximal decolorization efficiency of 99 % and COD removal 73 % was achieved. Detailed physico-chemical analysis of electrode and residues of the electro-oxidation process has also been carried out UV-Visible and Fourier transform infrared spectroscopy. The intermediate compounds formed during the oxidation were identified using a gas chromatography coupled with mass spectrometry. According to these results, response surface methodology could be useful for reducing the time to treat effluent wastewater.
煤矿低压系统动态无功补偿优化%Optimization of Reactive-load Compensation of Low Voltage System in Coal Mine
Institute of Scientific and Technical Information of China (English)
刘天野
2014-01-01
针对煤矿低压供电系统中功率因数低、电能质量不稳等问题，对煤矿低压系统无功功率补偿应用情况进行了研究。在分析了无功功率补偿方式和原理的基础上，提出了煤矿低压系统无功补偿优化算法，使线损在矿区低压系统无功平衡条件下达到最小。%Aiming at low power factor and instable electric energy quality of low voltage power supply system in coal mine ,this paper studied reactive-load compensation in low voltage system .On the basis of analysis of the reactive-load compensation principle and method ,the algorithm for optimization of reactive-load compensation in low voltage system was proposed ,achieving minimum line loss in the condition of balanced reactive component .
Particle swarm optimization based space debris surveillance network scheduling
Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao
2017-02-01
The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.
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.
Cooperative Game Study of Airlines Based on Flight Frequency Optimization
Directory of Open Access Journals (Sweden)
Wanming Liu
2014-01-01
Full Text Available By applying the game theory, the relationship between airline ticket price and optimal flight frequency is analyzed. The paper establishes the payoff matrix of the flight frequency in noncooperation scenario and flight frequency optimization model in cooperation scenario. The airline alliance profit distribution is converted into profit distribution game based on the cooperation game theory. The profit distribution game is proved to be convex, and there exists an optimal distribution strategy. The results show that joining the airline alliance can increase airline whole profit, the change of negotiated prices and cost is beneficial to profit distribution of large airlines, and the distribution result is in accordance with aviation development.
Genetic-evolution-based optimization methods for engineering design
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.
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...
Genetic-evolution-based optimization methods for engineering design
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.
Optimizing Combination of Units Commitment Based on Improved Genetic Algorithms
Institute of Scientific and Technical Information of China (English)
LAI Yifei; ZHANG Qianhua; JIA Junping
2007-01-01
GAs are general purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms, such as natural selection, genetic recombination and survival of the fittest. By use of coding betterment, the dynamic changes of the mutation rate and the crossover probability, the dynamic choice of subsistence, the reservation of the optimal fitness value, a modified genetic algorithm for optimizing combination of units in thermal power plants is proposed.And through taking examples, test result are analyzed and compared with results of some different algorithms. Numerical results show available value for the unit commitment problem with examples.
GOBF-ARMA based model predictive control for an ideal reactive distillation column.
Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K
2015-11-01
This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC.
Furfural resin-based bio-nanocomposites reinforced by reactive nanocrystalline cellulose
Wang, C.; Sun, S.; Zhao, G.; He, B.; Xiao, H.
2009-07-01
The work presented herein has been focused on reinforcing the furfural resins (FA) by reactive-modified nanocrystalline cellulose (NCC) in an attempt to create a bio-nanocomposite completely based on natural resources. FA prepolymers were synthesized with an acid catalyst, and NCC was rendered reactive via the grafting of maleic anhydride (MAH). The resulting NCC and nanocomposites were characterized using TEM, SEM and FT-IR. It was found that NCC appeared to be spherical in shape with diameters under 100 nm. FT-IR confirmed that there were hydrogen and esterification bonding between MAH and NCC or FA prepolymer. After solidified with paratoluenesulfonic acid, NCC-reinforced FA resin composites showed granular cross-section while FA resin with layered structures. Mechanical property tests indicated that NCC-reinforced FA resin composites possessed the improved tensile and flexural strengths, in comparison with FA resin.
Indian Academy of Sciences (India)
Francisco Méndez; María De L Romero; José L Gazquez
2005-09-01
The silicon atom may increase its coordination number to values greater than four, to form pentacoordinated compounds. It has been observed experimentally that, in general, pentacoordinated compounds show greater reactivity than tetracoordinated compounds. In this work, density functional theory is used to calculate the global softness and the condensed softness of the silicon atom for SiHF4- and SiHF$^{1-}_{5-n}$. The values obtained show that the global and condensed softness are greater in the pentacoordinated compounds than in the tetracoordinated compounds, a result that explains the enhanced reactivity. If the results are analysed through a local version of the hard and soft acids and bases principle, it is possible to suggest that in nucleophilic substitution reactions, soft nucleophiles preferably react with SiHF$^{1-}_{5-n}$, and hard nucleophiles with SiHF4-.
CADLIVE optimizer: web-based parameter estimation for dynamic models
Directory of Open Access Journals (Sweden)
Inoue Kentaro
2012-08-01
Full Text Available Abstract Computer simulation has been an important technique to capture the dynamics of biochemical networks. In most networks, however, few kinetic parameters have been measured in vivo because of experimental complexity. We develop a kinetic parameter estimation system, named the CADLIVE Optimizer, which comprises genetic algorithms-based solvers with a graphical user interface. This optimizer is integrated into the CADLIVE Dynamic Simulator to attain efficient simulation for dynamic models.
Optimal Design of Mountain Bicycle Based on Biomechanics
Institute of Scientific and Technical Information of China (English)
卜研; 黄田; 项忠霞; 吴小凡; 陈春
2010-01-01
To achieve better cycling performance and vibration comfort of mountain bicycle, the optimization of frame structural parameters and rear suspension scale parameters is investigated based on biomechanics.Firstly, the quadratic sum of rider lower limb muscles stresses is presented as the evaluation criterion of muscle fatigue.By taking the criterion as the objective function, the relative positions of three pivot points of frame are optimized to ensure that the frame structural parameters match the stature o...
Reliability-based design optimization with Cross-Entropy method
Ghidey, Hiruy
2015-01-01
Implementation of the Cross-entropy (CE) method to solve reliability-based design optimization (RBDO) problems was investigated. The emphasis of this implementation method was to solve independently both the reliability and optimization sub-problems within the RBDO problem; therefore, the main aim of this study was to evaluate the performance of the Cross-entropy method in terms of efficiency and accuracy to solve RBDO problems. A numerical approach was followed in which the implementatio...
Perspective texture synthesis based on improved energy optimization.
Directory of Open Access Journals (Sweden)
Syed Muhammad Arsalan Bashir
Full Text Available Perspective texture synthesis has great significance in many fields like video editing, scene capturing etc., due to its ability to read and control global feature information. In this paper, we present a novel example-based, specifically energy optimization-based algorithm, to synthesize perspective textures. Energy optimization technique is a pixel-based approach, so it's time-consuming. We improve it from two aspects with the purpose of achieving faster synthesis and high quality. Firstly, we change this pixel-based technique by replacing the pixel computation with a little patch. Secondly, we present a novel technique to accelerate searching nearest neighborhoods in energy optimization. Using k- means clustering technique to build a search tree to accelerate the search. Hence, we make use of principal component analysis (PCA technique to reduce dimensions of input vectors. The high quality results prove that our approach is feasible. Besides, our proposed algorithm needs shorter time relative to other similar methods.
Algebra-Based Optimization of XML-Extended OLAP Queries
DEFF Research Database (Denmark)
Yin, Xuepeng; Pedersen, Torben Bach
is desirable. This report presents a complete foundation for such OLAP-XML federations. This includes a prototypical query engine, a simplified query semantics based on previous work, and a complete physical algebra which enables precise modeling of the execution tasks of an OLAP-XML query. Effective algebra......-based and cost-based query optimization and implementation are also proposed, as well as the execution techniques. Finally, experiments with the prototypical query engine w.r.t. federation performance, optimization effectiveness, and feasibility suggest that our approach, unlike the physical integration...
Applying BAT Evolutionary Optimization to Image-Based Visual Servoing
Directory of Open Access Journals (Sweden)
Marco Perez-Cisneros
2015-01-01
Full Text Available This paper presents a predictive control strategy for an image-based visual servoing scheme that employs evolutionary optimization. The visual control task is approached as a nonlinear optimization problem that naturally handles relevant visual servoing constraints such as workspace limitations and visibility restrictions. As the predictive scheme requires a reliable model, this paper uses a local model that is based on the visual interaction matrix and a global model that employs 3D trajectory data extracted from a quaternion-based interpolator. The work assumes a free-flying camera with 6-DOF simulation whose results support the discussion on the constraint handling and the image prediction scheme.
A Model-Based Methodology for Integrated Design and Operation of Reactive Distillation Processes
DEFF Research Database (Denmark)
Mansouri, Seyed Soheil; Sales-Cruz, Mauricio; Huusom, Jakob Kjøbsted
2015-01-01
and resolved. A new approach isto tackle process intensification and controllability issues in an integrated manner, in the early stages of process design. This integrated and simultaneous synthesis approach provides optimal operation and moreefficient control of complex intensified systems that suffice...... bubble point algorithm is used to compute the reactive vapor-liquid equilibrium data set.The operation of the RDC at the highest driving force and other candidate points is compared through openloop and closed-loop analysis. By application of this methodology it is shown that designing the process atthe......Process intensification is a new approach that has the potential to improve existing processes as well as new designs of processes to achieve more profitable and sustainable production. However, many issues with respect to their implementation and operation is not clear; for example, the question...
Optimization of wireless sensor networks based on chicken swarm optimization algorithm
Wang, Qingxi; Zhu, Lihua
2017-05-01
In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.
Energy Technology Data Exchange (ETDEWEB)
Li, Jixin; Song, Xiaohui; Feng, Ying [School of Petrochemical Engineering, Shenyang University of Technology, 30 Guanghua Street, Liaoyang 111003 (China); Wang, Zhiming, E-mail: wangzm2011@yahoo.com.cn [School of Petrochemical Engineering, Shenyang University of Technology, 30 Guanghua Street, Liaoyang 111003 (China); State Key Laboratory of Supramolecular Structure and Materials, Jilin University, 2699 Qianjin Avenue, Changchun 130012 (China); Zhang, Xiaojuan [School of Petrochemical Engineering, Shenyang University of Technology, 30 Guanghua Street, Liaoyang 111003 (China); Shen, Fangzhong; Lu, Ping [State Key Laboratory of Supramolecular Structure and Materials, Jilin University, 2699 Qianjin Avenue, Changchun 130012 (China)
2013-10-31
In this work, we prepared three fluorene-based copolymers with different conjugate degreed quinoxaline segments from one reactive polymer by microwave assisted method. The obtained quinoxaline-based copolymers exhibited different bright color emissions, high photoluminescence quantum, low electron affinity and electron injection barrier. This approach not only simplified the steps of similar-structure polymers, but also avoided the monomer solubility problem. - Highlights: • Quinoxaline-based copolymers were prepared in microwave-assisted synthesis. • Polymer-synthesis containing different acceptors was simplified from reactive polymer. • Multi-functions were tuned by controlling reactive monomer structures.
Maqbool, Zahid; Hussain, Sabir; Ahmad, Tanvir; Nadeem, Habibullah; Imran, Muhammad; Khalid, Azeem; Abid, Muhammad; Martin-Laurent, Fabrice
2016-06-01
Remediation of colored wastewater loaded with dyes and metal ions is a matter of interest nowadays. In this study, 220 bacteria isolated from textile wastewater were tested for their potential to decolorize each of the four reactive dyes (reactive red-120, reactive black-5, reactive yellow-2, and reactive orange-16) in the presence of a mixture of four different heavy metals (Cr, Zn, Pb, Cd) commonly found in textile effluents. Among the tested bacteria, the isolate ZM130 was found to be the most efficient in decolorizing reactive dyes in the presence of the mixture of heavy metals and was identified as Pseudomonas aeruginosa strain ZM130 by 16S rRNA gene analysis. The strain ZM130 was highly effective in simultaneously removing hexavalent chromium (25 mg L(-1)) and the azo dyes (100 mg L(-1)) from the simulated wastewater even in the presence of other three heavy metals (Zn, Pb, Cd). Simultaneous removal of chromium and azo dyes ranged as 76.6-98.7 % and 51.9-91.1 %, respectively, after 180 h incubation. On the basis of quadratic polynomial equation and response surfaces given by the response surface methodology (RSM), optimal salt content, pH, carbon co-substrate content, and level of multi-metal mixtures for decolorization of reactive red-120 in a simulated textile wastewater by the strain ZM130 were predicted to be 19.8, 7.8, and 6.33 g L(-1) and a multi-metal mixture (Cr 13.10 mg L(-1), Pb 26.21 mg L(-1), Cd 13.10 mg L(-1), Zn 26.21 mg L(-1)), respectively. Moreover, the strain ZM130 also exhibited laccase and nicotinamide adenine dinucleotide (reduced)-dichlorophenolindophenol reductase (NADH-DCIP reductase) activity during the decolorization of reactive red-120. However, the laccase activity was found to be maximum in the presence of 300 mg L(-1) of the dye as compared to other concentrations. Hence, the isolation of this strain might serve as a potential bio-resource required for developing the strategies aiming at bioremediation of the
Institute of Scientific and Technical Information of China (English)
白恺; 李泽滔
2016-01-01
The operation of the wind power plant has two major characteristics :the randomness of the active power output and its demand for absorption of massive reactive power .Large scale wind power grid connected operation would have adverse effects on the power system .Thus ,it is necessary to optimally plan for reactive power of the access system of the wind power plant .In view of the randomness of the wind power plant ,the probability analysis based scenario method is used to study optimization of reactive power of the access system of the wind power plant and the genetic algorithm is used to find the optimal solution .Simulation calculation is carried out for the IEEE14 node system of the wind power plant .The result show s that the above model is correct and valid .%风电场运行时有两个显著特点：有功出力具有随机性和需要吸收大量无功功率。大规模风电并网运行会对电力系统产生不利影响，需要对风电场接入系统进行无功优化规划。针对风电场有功出力随机性的特点，利用基于概率的场景方法研究风电场接入系统的无功优化问题，采用遗传算法求取最优解。利用风电场接入IEEE14节点系统进行仿真计算，得到的结果显示上述模型的正确性和有效性。
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.
Cover crop-based ecological weed management: exploration and optimization
Kruidhof, H.M.
2008-01-01
Keywords: organic farming, ecologically-based weed management, cover crops, green manure, allelopathy, Secale cereale, Brassica napus, Medicago sativa Cover crop-based ecological weed management: exploration and optimization. In organic farming systems, weed control is recognized as one of the mai
Cover crop-based ecological weed management: exploration and optimization
Kruidhof, H.M.
2008-01-01
Keywords: organic farming, ecologically-based weed management, cover crops, green manure, allelopathy, Secale cereale, Brassica napus, Medicago sativa Cover crop-based ecological weed management: exploration and optimization. In organic farming systems, weed control is recognized as one of the
Gradient-based methods for production optimization of oil reservoirs
Energy Technology Data Exchange (ETDEWEB)
Suwartadi, Eka
2012-07-01
Production optimization for water flooding in the secondary phase of oil recovery is the main topic in this thesis. The emphasis has been on numerical optimization algorithms, tested on case examples using simple hypothetical oil reservoirs. Gradientbased optimization, which utilizes adjoint-based gradient computation, is used to solve the optimization problems. The first contribution of this thesis is to address output constraint problems. These kinds of constraints are natural in production optimization. Limiting total water production and water cut at producer wells are examples of such constraints. To maintain the feasibility of an optimization solution, a Lagrangian barrier method is proposed to handle the output constraints. This method incorporates the output constraints into the objective function, thus avoiding additional computations for the constraints gradient (Jacobian) which may be detrimental to the efficiency of the adjoint method. The second contribution is the study of the use of second-order adjoint-gradient information for production optimization. In order to speedup convergence rate in the optimization, one usually uses quasi-Newton approaches such as BFGS and SR1 methods. These methods compute an approximation of the inverse of the Hessian matrix given the first-order gradient from the adjoint method. The methods may not give significant speedup if the Hessian is ill-conditioned. We have developed and implemented the Hessian matrix computation using the adjoint method. Due to high computational cost of the Newton method itself, we instead compute the Hessian-timesvector product which is used in a conjugate gradient algorithm. Finally, the last contribution of this thesis is on surrogate optimization for water flooding in the presence of the output constraints. Two kinds of model order reduction techniques are applied to build surrogate models. These are proper orthogonal decomposition (POD) and the discrete empirical interpolation method (DEIM
DEFF Research Database (Denmark)
Sousa, Tiago; Morais, Hugo; Vale, Zita
2015-01-01
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...... the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive...... scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives....
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
SAR Image Segmentation Based On Hybrid PSOGSA Optimization Algorithm
Directory of Open Access Journals (Sweden)
Amandeep Kaur
2014-09-01
Full Text Available Image segmentation is useful in many applications. It can identify the regions of interest in a scene or annotate the data. It categorizes the existing segmentation algorithm into region-based segmentation, data clustering, and edge-base segmentation. Region-based segmentation includes the seeded and unseeded region growing algorithms, the JSEG, and the fast scanning algorithm. Due to the presence of speckle noise, segmentation of Synthetic Aperture Radar (SAR images is still a challenging problem. We proposed a fast SAR image segmentation method based on Particle Swarm Optimization-Gravitational Search Algorithm (PSO-GSA. In this method, threshold estimation is regarded as a search procedure that examinations for an appropriate value in a continuous grayscale interval. Hence, PSO-GSA algorithm is familiarized to search for the optimal threshold. Experimental results indicate that our method is superior to GA based, AFS based and ABC based methods in terms of segmentation accuracy, segmentation time, and Thresholding.
Segment-Based Predominant Learning Swarm Optimizer for Large-Scale Optimization.
Yang, Qiang; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Deng, Jeremiah D; Li, Yun; Zhang, Jun
2016-10-24
Large-scale optimization has become a significant yet challenging area in evolutionary computation. To solve this problem, this paper proposes a novel segment-based predominant learning swarm optimizer (SPLSO) swarm optimizer through letting several predominant particles guide the learning of a particle. First, a segment-based learning strategy is proposed to randomly divide the whole dimensions into segments. During update, variables in different segments are evolved by learning from different exemplars while the ones in the same segment are evolved by the same exemplar. Second, to accelerate search speed and enhance search diversity, a predominant learning strategy is also proposed, which lets several predominant particles guide the update of a particle with each predominant particle responsible for one segment of dimensions. By combining these two learning strategies together, SPLSO evolves all dimensions simultaneously and possesses competitive exploration and exploitation abilities. Extensive experiments are conducted on two large-scale benchmark function sets to investigate the influence of each algorithmic component and comparisons with several state-of-the-art meta-heuristic algorithms dealing with large-scale problems demonstrate the competitive efficiency and effectiveness of the proposed optimizer. Further the scalability of the optimizer to solve problems with dimensionality up to 2000 is also verified.
Bettonvil, B.W.M.; Del Castillo, E.; Kleijnen, J.P.C.
2007-01-01
This paper studies simulation-based optimization with multiple outputs. It assumes that the simulation model has one random objective function and must satisfy given constraints on the other random outputs. It presents a statistical procedure for test- ing whether a specific input combination
Bettonvil, B.W.M.; Del Castillo, E.; Kleijnen, J.P.C.
2007-01-01
This paper studies simulation-based optimization with multiple outputs. It assumes that the simulation model has one random objective function and must satisfy given constraints on the other random outputs. It presents a statistical procedure for test- ing whether a specific input combination (propo
Structural Optimization of Slender Robot Arm Based on Sensitivity Analysis
Directory of Open Access Journals (Sweden)
Zhong Luo
2012-01-01
Full Text Available An effective structural optimization method based on a sensitivity analysis is proposed to optimize the variable section of a slender robot arm. The structure mechanism and the operating principle of a polishing robot are introduced firstly, and its stiffness model is established. Then, a design of sensitivity analysis method and a sequential linear programming (SLP strategy are developed. At the beginning of the optimization, the design sensitivity analysis method is applied to select the sensitive design variables which can make the optimized results more efficient and accurate. In addition, it can also be used to determine the scale of moving step which will improve the convergency during the optimization process. The design sensitivities are calculated using the finite difference method. The search for the final optimal structure is performed using the SLP method. Simulation results show that the proposed structure optimization method is effective in enhancing the stiffness of the robot arm regardless of the robot arm suffering either a constant force or variable forces.
Optimal image-fusion method based on nonsubsampled contourlet transform
Dou, Jianfang; Li, Jianxun
2012-10-01
The optimization of image fusion is researched. Based on the properties of nonsubsampled contourlet transform (NSCT), shift invariance, multiscale and multidirectional expansion, the fusion parameters of the multiscale decompostion scheme is optimized. In order to meet the requirement of feedback optimization, a new image fusion quality metric of image quality index normalized edge association (IQI-NEA) is built. A polynomial model is adopted to establish the relationship between the IQI_NEA metric and several decomposition levels. The optimal fusion includes four steps. First, the source images are decomposed in NSCT domain for several given levels. Second, principal component analysis is adopted to fuse the low frequency coefficients and the maximum fusion rule is utilized to fuse the high frequency coefficients to obtain the fused coefficients and the fused result is reconstructed from the obtained fused coefficients. Third, calculate the fusion quality metric IQI_NEA for the source images and fused images. Finally, the optimal fused image and optimal level are obtained through extremum properties of polynomials function. The visual and statistical results show that the proposed method has optimized the fusion performance compared to the existing fusion schemes, in terms of the visual effects and quantitative fusion evaluation indexes.
Zhang, Yong-Feng; Chiang, Hsiao-Dong
2016-06-20
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.
A Smartphone-Based Colorimetric Reader for Human C-Reactive Protein Immunoassay.
Venkatesh, A G; van Oordt, Thomas; Schneider, E Marion; Zengerle, Roland; von Stetten, Felix; Luong, John H T; Vashist, Sandeep Kumar
2017-01-01
A smartphone-based colorimetric reader (SBCR), comprising a Samsung Galaxy SIII mini, a gadget (iPAD mini, iPAD4, or iPhone 5s) and a custom-made dark hood and base holder assembly, is used for human C-reactive protein (CRP) immunoassay. A 96-well microtiter plate (MTP) is positioned on the gadget's screensaver to provide white light-based bottom illumination only in the specific regions corresponding to the well's bottom. The images captured by the smartphone's back camera are analyzed by a novel image processing algorithm. Based on one-step kinetics-based human C-reactive protein immunoassay (IA), SBCR is evaluated and compared with a commercial MTP reader (MTPR). For analysis of CRP spiked in diluted human whole blood and plasma as well as CRP in clinical plasma samples, SBCR exhibits the same precision, dynamic range, detection limit, and sensitivity as MTPR for the developed IA (DIA). Considering its compactness, low cost, advanced features and a remarkable computing power, SBCR is an ideal point-of-care (POC) colorimetric detection device for the next-generation of cost-effective POC testing (POCT).
Trust regions in Kriging-based optimization with expected improvement
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.
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.
Mode-Tracking Based Stationary-Point Optimization
Bergeler, Maike; Reiher, Markus
2014-01-01
In this work, we present a transition-state optimization protocol based on the Mode-Tracking algorithm [J. Chem. Phys. 118 (2003) 1634]. By calculating only the eigenvector of interest instead of diagonalizing the full Hessian matrix and performing an eigenvector following search based on the selectively calculated vector, we can efficiently optimize transition-state structures. The initial guess structures and eigenvectors are either chosen from a linear interpolation between the reactant and product structures, from a nudged-elastic band search, from a constrained-optimization scan, or from the minimum-energy structures. Alternatively, initial guess vectors based on chemical intuition may be defined. We then iteratively refine the selected vectors by the Davidson subspace iteration technique. This procedure accelerates finding transition states for large molecules of a few hundred atoms. It is also beneficial in cases where the starting structure is very different from the transition-state structure or wher...
Optimizing medical data quality based on multiagent web service framework.
Wu, Ching-Seh; Khoury, Ibrahim; Shah, Hemant
2012-07-01
One of the most important issues in e-healthcare information systems is to optimize the medical data quality extracted from distributed and heterogeneous environments, which can extremely improve diagnostic and treatment decision making. This paper proposes a multiagent web service framework based on service-oriented architecture for the optimization of medical data quality in the e-healthcare information system. Based on the design of the multiagent web service framework, an evolutionary algorithm (EA) for the dynamic optimization of the medical data quality is proposed. The framework consists of two main components; first, an EA will be used to dynamically optimize the composition of medical processes into optimal task sequence according to specific quality attributes. Second, a multiagent framework will be proposed to discover, monitor, and report any inconstancy between the optimized task sequence and the actual medical records. To demonstrate the proposed framework, experimental results for a breast cancer case study are provided. Furthermore, to show the unique performance of our algorithm, a comparison with other works in the literature review will be presented.
Prediction of RNA Secondary Structure Based on Particle Swarm Optimization
Institute of Scientific and Technical Information of China (English)
LIU Yuan-ning; DONG Hao; ZHANG Hao; WANG Gang; LI Zhi; CHEN Hui-ling
2011-01-01
A novel method for the prediction of RNA secondary structure was proposed based on the particle swarm optimization(PSO). PSO is known to be effective in solving many different types of optimization problems and known for being able to approximate the global optimal results in the solution space. We designed an efficient objective function according to the minimum free energy, the number of selected stems and the average length of selected stems. We calculated how many legal stems there were in the sequence, and selected some of them to obtain an optimal result using PSO in the right of the objective function. A method based on the improved particle swarm optimization(IPSO) was proposed to predict RNA secondary structure, which consisted of three stages. The first stage was applied to e ncoding the source sequences, and to exploring all the legal stems. Then, a set of encoded stems were created in order to prepare input data for the second stage. In the second stage, IPSO was responsible for structure selection. At last, the optimal result was obtained from the secondary structures selected via IPSO. Nine sequences from the comparative RNA website were selected for the evaluation of the proposed method. Compared with other six methods, the proposed method decreased the complexity and enhanced the sensitivity and specificity on the basis of the experiment results.
Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization
Directory of Open Access Journals (Sweden)
Mohammed Hasan Abdulameer
2014-01-01
Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.
Energy Technology Data Exchange (ETDEWEB)
Mahdad, Belkacem, E-mail: bemahdad@yahoo.f [University of Biskra, Department of Electrical Engineering, Biskra 07000 (Algeria); Bouktir, T. [Oum El Bouaghi, Department of Electrical Engineering, Oum El Bouaghi 04000 (Algeria); Srairi, K. [University of Biskra, Department of Electrical Engineering, Biskra 07000 (Algeria); EL Benbouzid, M. [Laboratoire Brestois de Mecanique et des Systemes, University of Brest (France)
2010-07-15
Under critical situation the main preoccupation of expert engineers is to assure power system security and to deliver power to the consumer within the desired index power quality. The total generation cost taken as a secondary strategy. This paper presents an efficient decomposed GA to enhance the solution of the optimal power flow (OPF) with non-smooth cost function and under severe loading conditions. At the decomposed stage the length of the original chromosome is reduced successively and adapted to the topology of the new partition. Two sub problems are proposed to coordinate the OPF problem under different loading conditions: the first sub problem related to the active power planning under different loading factor to minimize the total fuel cost, and the second sub problem is a reactive power planning designed based in practical rules to make fine corrections to the voltage deviation and reactive power violation using a specified number of shunt dynamic compensators named Static Var Compensators (SVC). To validate the robustness of the proposed approach, the proposed algorithm tested on IEEE 30-Bus, 26-Bus and IEEE 118-Bus under different loading conditions and compared with global optimization methods (GA, EGA, FGA, PSO, MTS, MDE and ACO) and with two robust simulation packages: PSAT and MATPOWER. The results show that the proposed approach can converge to the near solution and obtain a competitive solution at critical situation and with a reasonable time.
Inversion method based on stochastic optimization for particle sizing.
Sánchez-Escobar, Juan Jaime; Barbosa-Santillán, Liliana Ibeth; Vargas-Ubera, Javier; Aguilar-Valdés, Félix
2016-08-01
A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46≤α≤150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem.
Engineering Design Optimization Based on Intelligent Response Surface Methodology
Institute of Scientific and Technical Information of China (English)
SONG Guo-hui; WU Yu; LI Cong-xin
2008-01-01
An intelligent response surface methodology (IRSM) was proposed to achieve the most competitivemetal forming products, in which artificial intelligence technologies are introduced into the optimization process.It is used as simple and inexpensive replacement for computationally expensive simulation model. In IRSM,the optimal design space can be reduced greatly without any prior information about function distribution.Also, by identifying the approximation error region, new design points can be supplemented correspondingly toimprove the response surface model effectively. The procedure is iterated until the accuracy reaches the desiredthreshold value. Thus, the global optimization can be performed based on this substitute model. Finally, wepresent an optimization design example about roll forming of a "U" channel product.
Planar straightness error evaluation based on particle swarm optimization
Mao, Jian; Zheng, Huawen; Cao, Yanlong; Yang, Jiangxin
2006-11-01
The straightness error generally refers to the deviation between an actual line and an ideal line. According to the characteristics of planar straightness error evaluation, a novel method to evaluate planar straightness errors based on the particle swarm optimization (PSO) is proposed. The planar straightness error evaluation problem is formulated as a nonlinear optimization problem. According to minimum zone condition the mathematical model of planar straightness together with the optimal objective function and fitness function is developed. Compared with the genetic algorithm (GA), the PSO algorithm has some advantages. It is not only implemented without crossover and mutation but also has fast congruence speed. Moreover fewer parameters are needed to set up. The results show that the PSO method is very suitable for nonlinear optimization problems and provides a promising new method for straightness error evaluation. It can be applied to deal with the measured data of planar straightness obtained by the three-coordinates measuring machines.
Optimization and Design of Wideband Antenna Based on Q Factor
Directory of Open Access Journals (Sweden)
Han Liu
2015-01-01
Full Text Available A wideband antenna is designed based on Q factor in this paper. Firstly, the volume-surface integral equations (VSIEs and self-adaptive differential evolution algorithm (DEA are introduced as the basic theories to optimize antennas. Secondly, we study the computation of Q of arbitrary shaped structures, aiming at designing an antenna with maximum bandwidth by minimizing the Q of the antenna. This method is much more efficient for only Q values at specific frequency points that are computed, which avoids optimizing bandwidth directly. Thirdly, an integrated method combining the above method with VSIEs and self-adaptive DEA is employed to optimize the wideband antenna, extending its bandwidth from 11.5~16.5 GHz to 7~20 GHz. Lastly, the optimized antenna is fabricated and measured. The measured results are consistent with the simulated results, demonstrating the feasibility and effectiveness of the proposed method.
Routing Optimization Based on Taboo Search Algorithm for Logistic Distribution
Directory of Open Access Journals (Sweden)
Hongxue Yang
2014-04-01
Full Text Available Along with the widespread application of the electronic commerce in the modern business, the logistic distribution has become increasingly important. More and more enterprises recognize that the logistic distribution plays an important role in the process of production and sales. A good routing for logistic distribution can cut down transport cost and improve efficiency. In order to cut down transport cost and improve efficiency, a routing optimization based on taboo search for logistic distribution is proposed in this paper. Taboo search is a metaheuristic search method to perform local search used for logistic optimization. The taboo search is employed to accelerate convergence and the aspiration criterion is combined with the heuristics algorithm to solve routing optimization. Simulation experimental results demonstrate that the optimal routing in the logistic distribution can be quickly obtained by the taboo search algorithm
Application of Teaching Learning Based Optimization in antenna designing
Directory of Open Access Journals (Sweden)
S. Dwivedi
2015-07-01
Full Text Available Numerous optimization techniques are studied and applied on antenna designs to optimize various performance parameters. Authors used many Multiple Attributes Decision Making (MADM methods, which include, Weighted Sum Method (WSM, Weighted Product Method (WPM, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS, Analytic Hierarchy Process (AHP, ELECTRE, etc. Of these many MADM methods, TOPSIS and AHP are more widely used decision making methods. Both TOPSIS and AHP are logical decision making approaches and deal with the problem of choosing an alternative from a set of alternatives which are characterized in terms of some attributes. Analytic Hierarchy Process (AHP is explained in detail and compared with WSM and WPM. Authors ﬁ- nally used Teaching-Learning-Based Optimization (TLBO technique; which is a novel method for constrained antenna design optimization problems.
Optimization-based topology identification of complex networks
Institute of Scientific and Technical Information of China (English)
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 synchronizationbased 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.
Teaching learning based optimization algorithm and its engineering applications
Rao, R Venkata
2016-01-01
Describing a new optimization algorithm, the “Teaching-Learning-Based Optimization (TLBO),” in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners’ results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.
Optimal weight based on energy imbalance and utility maximization
Sun, Ruoyan
2016-01-01
This paper investigates the optimal weight for both male and female using energy imbalance and utility maximization. Based on the difference of energy intake and expenditure, we develop a state equation that reveals the weight gain from this energy gap. We construct an objective function considering food consumption, eating habits and survival rate to measure utility. Through applying mathematical tools from optimal control methods and qualitative theory of differential equations, we obtain some results. For both male and female, the optimal weight is larger than the physiologically optimal weight calculated by the Body Mass Index (BMI). We also study the corresponding trajectories to steady state weight respectively. Depending on the value of a few parameters, the steady state can either be a saddle point with a monotonic trajectory or a focus with dampened oscillations.
EUD-based biological optimization for carbon ion therapy
Energy Technology Data Exchange (ETDEWEB)
Brüningk, Sarah C., E-mail: sarah.brueningk@icr.ac.uk; Kamp, Florian; Wilkens, Jan J. [Department of Radiation Oncology, Technische Universität München, Klinikum rechts der Isar, Ismaninger Str. 22, München 81675, Germany and Physik-Department, Technische Universität München, James-Franck-Str. 1, Garching 85748 (Germany)
2015-11-15
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
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.
Directory of Open Access Journals (Sweden)
R. Mageshvaran
2015-03-01
Full Text Available Load shedding is considered as a last alternative to avoid the cascaded tripping and blackout in power systems during generation contingencies. It is essential to optimize the amount of load to be shed in order to prevent excessive load shedding. To minimize load shedding, this paper proposes the implementation of nature inspired optimization algorithm known as glowworm swarm optimization (GSO algorithm. The optimal solution of steady state load shedding is carried out by squaring the difference between the connected and supplied power (active and reactive. The proposed algorithm is tested on IEEE 14, 30, 57, 118 and Northern Regional Power Grid (NRPG-(India 246 bus test systems. The viability of the proposed method in terms of solution quality and convergence properties is compared with the conventional methods, namely, projected augmented Lagrangian method (PALM, gradient technique based on Kuhn–Tucker theorem (GTBKTT and second order gradient technique (SOGT.
Directory of Open Access Journals (Sweden)
R. Venkata Rao
2016-03-01
Full Text Available The performance of rapid prototyping (RP processes is often measured in terms of build time, product quality, dimensional accuracy, cost of production, mechanical and tribological properties of the models and energy consumed in the process. The success of any RP process in terms of these performance measures entails selection of the optimum combination of the influential process parameters. Thus, in this work the single-objective and multi-objective optimization problems of a widely used RP process, namely, fused deposition modeling (FDM, are formulated, and the same are solved using the teaching-learning-based optimization (TLBO algorithm and non-dominated Sorting TLBO (NSTLBO algorithm, respectively. The results of the TLBO algorithm are compared with those obtained using genetic algorithm (GA, and quantum behaved particle swarm optimization (QPSO algorithm. The TLBO algorithm showed better performance as compared to GA and QPSO algorithms. The NSTLBO algorithm proposed to solve the multi-objective optimization problems of the FDM process in this work is a posteriori version of the TLBO algorithm. The NSTLBO algorithm is incorporated with non-dominated sorting concept and crowding distance assignment mechanism to obtain a dense set of Pareto optimal solutions in a single simulation run. The results of the NSTLBO algorithm are compared with those obtained using non-dominated sorting genetic algorithm (NSGA-II and the desirability function approach. The Pareto-optimal set of solutions for each problem is obtained and reported. These Pareto-optimal set of solutions will help the decision maker in volatile scenarios and are useful for the FDM process.
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.
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.
A single loop reliability-based design optimization using EPM and MPP-based PSO
Liao, Kuo-Wei; Ivan,Gautama
2014-01-01
A reliability-based design optimization (RBDO) incorporates a probabilistic analysis with an optimization technique to find a best design within a reliable design space. However, the computational cost of an RBDO task is often expensive compared to a deterministic optimization, which is mainly due to the reliability analysis performed inside the optimization loop. Theoretically, the reliability of a given design point can be obtained through a multidimensional integration. Integration with mu...
Reliability-based design optimization strategies based on FORM: a review
Lopez, Rafael Holdorf; BECK, André Teófilo
2012-01-01
In deterministic optimization, the uncertainties of the structural system (i.e. dimension, model, material, loads, etc) are not explicitly taken into account. Hence, resulting optimal solutions may lead to reduced reliability levels. The objective of reliability based design optimization (RBDO) is to optimize structures guaranteeing that a minimum level of reliability, chosen a priori by the designer, is maintained. Since reliability analysis using the First Order Reliability Method (FORM) is...
Natsch, Andreas; Gfeller, Hans; Haupt, Tina; Brunner, Gerhard
2012-10-15
Skin sensitizers chemically modify skin proteins rendering them immunogenic. Sensitizing chemicals have been divided into applicability domains according to their suspected reaction mechanism. The widely accepted Schiff base applicability domain covers aldehydes and ketones, and detailed structure-activity-modeling for this chemical group was presented. While Schiff base formation is the obvious reaction pathway for these chemicals, the in silico work was followed up by limited experimental work. It remains unclear whether hydrolytically labile Schiff bases can form sufficiently stable epitopes to trigger an immune response in the living organism with an excess of water being present. Here, we performed experimental studies on benzaldehydes of highly differing skin sensitization potential. Schiff base formation toward butylamine was evaluated in acetonitrile, and a detailed SAR study is presented. o-Hydroxybenzaldehydes such as salicylaldehyde and the oakmoss allergens atranol and chloratranol have a high propensity to form Schiff bases. The reactivity is highly reduced in p-hydroxy benzaldehydes such as the nonsensitizing vanillin with an intermediate reactivity for p-alkyl and p-methoxy-benzaldehydes. The work was followed up under more physiological conditions in the peptide reactivity assay with a lysine-containing heptapeptide. Under these conditions, Schiff base formation was only observable for the strong sensitizers atranol and chloratranol and for salicylaldehyde. Trapping experiments with NaBH₃CN showed that Schiff base formation occurred under these conditions also for some less sensitizing aldehydes, but the reaction is not favored in the absence of in situ reduction. Surprisingly, the Schiff bases of some weaker sensitizers apparently may react further to form stable peptide adducts. These were identified as the amides between the lysine residues and the corresponding acids. Adduct formation was paralleled by oxidative deamination of the parent
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.
Kekulé-based Valence Bond Model.Ⅱ. Diels-Alder Reactivity of Polycyclic Aromatic Hydrocarbons
Institute of Scientific and Technical Information of China (English)
MA,Jing(马晶); LI,Shu-Hua(黎书华); JIANG,Yuan-Sheng(江元生)
2002-01-01
The Kekule-based valence bond ( VB ) method was employed to study the ground state properties of 52 polycyclic aromatic hydrocarbons. The reactivity indices defined upon our VB calculations were demonstrated to be capable of quantitatively interpreting the secnd order rate constants of the Diels-Alder reactions. The qualitative trends of the reactivities of many homologous series can be also explained based on the local aromaticity index defined in this work.
Indian Academy of Sciences (India)
Bhakti S Kulkarni; Deepti Mishra; Sourav Pal
2013-09-01
In this paper, we study the reactivity of diimines like 2, 2'-bipyridine, 1, l0-phenanthroline and 1, 2, 4-triazines using density-based reactivity descriptors. We discuss the enhancement or diminution in the reactivity of these ligands as a function of two substituent groups, namely methyl (-CH3) group and phenyl (-C6H5) group. The global reactivity descriptors explain the global affinity and philicity of these ligands, whereas the local softness depicts the particular site selectivity. The inter-molecular reactivity trends for the same systems are analysed through the philicity and group philicity indices. The -donor character of these ligands is quantified with the help of electron density profile. In addition, the possible strength of interaction of these ligands with metal ions is supported with actual reaction energies of Ru-L complexes.
Optimization of Component Based Software Engineering Model Using Neural Network
Directory of Open Access Journals (Sweden)
Gaurav Kumar
2014-10-01
Full Text Available The goal of Component Based Software Engineering (CBSE is to deliver high quality, more reliable and more maintainable software systems in a shorter time and within limited budget by reusing and combining existing quality components. A high quality system can be achieved by using quality components, framework and integration process that plays a significant role. So, techniques and methods used for quality assurance and assessment of a component based system is different from those of the traditional software engineering methodology. In this paper, we are presenting a model for optimizing Chidamber and Kemerer (CK metric values of component-based software. A deep analysis of a series of CK metrics of the software components design patterns is done and metric values are drawn from them. By using unsupervised neural network- Self Organizing Map, we have proposed a model that provides an optimized model for Software Component engineering model based on reusability that depends on CK metric values. Average, standard deviated and optimized values for the CK metric are compared and evaluated to show the optimized reusability of component based model.
ODVBA: optimally-discriminative voxel-based analysis.
Zhang, Tianhao; Davatzikos, Christos
2011-08-01
Gaussian smoothing of images prior to applying voxel-based statistics is an important step in voxel-based analysis and statistical parametric mapping (VBA-SPM) and is used to account for registration errors, to Gaussianize the data and to integrate imaging signals from a region around each voxel. However, it has also become a limitation of VBA-SPM based methods, since it is often chosen empirically and lacks spatial adaptivity to the shape and spatial extent of the region of interest, such as a region of atrophy or functional activity. In this paper, we propose a new framework, named optimally-discriminative voxel-based analysis (ODVBA), for determining the optimal spatially adaptive smoothing of images, followed by applying voxel-based group analysis. In ODVBA, nonnegative discriminative projection is applied regionally to get the direction that best discriminates between two groups, e.g., patients and controls; this direction is equivalent to local filtering by an optimal kernel whose coefficients define the optimally discriminative direction. By considering all the neighborhoods that contain a given voxel, we then compose this information to produce the statistic for each voxel. Finally, permutation tests are used to obtain a statistical parametric map of group differences. ODVBA has been evaluated using simulated data in which the ground truth is known and with data from an Alzheimer's disease (AD) study. The experimental results have shown that the proposed ODVBA can precisely describe the shape and location of structural abnormality.
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.
DEFF Research Database (Denmark)
Tjell, Simon; Lassen, Kristian Bisgaard
2008-01-01
In this paper, we describe a formal foundation for a specialized approach to automatically checking traces against real-time requirements. The traces are obtained from simulation of Coloured Petri Net (CPN) models of reactive systems. The real-time requirements are expressed in terms...... of a derivative of UML 2.0 high-level Sequence Diagrams. The automated requirement checking is part of a bigger tool framework in which VDM++ is applied to automatically generate initial CPN models based on Problem Diagrams. These models are manually enhanced to provide behavioral descriptions of the environment...
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 c......, well-defined designs with robust performances. The overview discusses the limitations, the advantages and the associated computational costs. The review is completed with optimized designs for minimum compliance, mechanism design and heat transfer.......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...
Structural eigenfrequency optimization based on local sub-domain "frequencies"
DEFF Research Database (Denmark)
Pedersen, Pauli; Pedersen, Niels Leergaard
2013-01-01
The engineering approach of fully stressed design is a practical tool with a theoretical foundation. The analog approach to structural eigenfrequency optimization is presented here with its theoretical foundation. A numerical redesign procedure is proposed and illustrated with examples.......For the ideal case, an optimality criterion is fulfilled if the design have the same sub-domain ”frequency” (local Rayleigh quotient). Sensitivity analysis shows an important relation between squared system eigenfrequency and squared local sub-domain frequency for a given eigenmode. Higher order...... eigenfrequencies may also be controlled in this manner.The presented examples are based on 2D finite element models with the use of subspace iteration for analysis and a recursive design procedure based on the derived optimality condition. The design that maximize a frequency depend on the total amount...
ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS
Directory of Open Access Journals (Sweden)
T. SHANKAR
2014-04-01
Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.
Robust Collaborative Optimization Method Based on Dual-response Surface
Institute of Scientific and Technical Information of China (English)
WANG Wei; FAN Wenhui; CHANG Tianqing; YUAN Yuming
2009-01-01
A novel method for robust collaborative design of complex products based on dual-response surface (DRS-RCO) is proposed to solve multidisciplinary design optimization (MDO) problems under uncertainty. Collaborative optimization (CO) which decomposes the whole system into a double-level nonlinear optimization problem is widely Accepted as an efficient method to solve MDO problems. In order to improve the quality of complex product in design process, robust collaborative optimization (RCO) is developed to solve those problems under uncertain conditions. RCO does opfmiTation on the linear sum of mean and standard deviation of objective function and gets an optimal solution with high robustnmess. Response surfaces method is an important way to do approximation in robust design. DRS-RCO is an improved RCO method in which dual-response surface replaces system uncertainty analysis module of CO. The dual-response surface is the approximate model of mean and standard deviation of objective function respectively. In DRS-RCO, All the information of subsystems is included in dual-response surfaces. As an additional item, the standard deviation of objective function is added to the subsystem optimization. This item guarantee both the mean and standard deviation of this subsystem is reaching the minima at the same time. Finally, a test problem with two coupled subsystems is conducted to verify the feasibility and effectiveness of DRS-RCO.
Statistical model for combustion of high-metal magnesium-based hydro-reactive fuel
Institute of Scientific and Technical Information of China (English)
Hu Jian-Xin; Han Chao; Xia Zhi-Xun; Huang Li-Ya; Huang Xu
2012-01-01
We investigate experimentally and analytically the combustion behavior of a high-metal magnesium-based hydro-reactive fuel under high temperature gaseous atmosphere.The fuel studied in this paper contains 73％ magnesium powders.An experimental system is designed and experimeuts are carried out in both argon and water vapor atmospheres.It is found that the burning surface temperature of the fuel is higher in water vapor than that in argon and both of them are higher than the melting point of magnesium,which indicates the molten state of magnesium particles in the burning surface of the fuel.Based on physical considerations and experimental results,a mathematical one-dimensional model is formulated to describe the combustion behavior of the high-metal magnesium-based hydro-reactive fuel.The model enables the evaluation of the burning surface temperature,the burning rate and the flame standoff distance each as a function of chamber pressure and water vapor concentration.The results predicted by the model show that the burning rate and the surface temperature increase when the chamber pressure and the water vapor concentration increase,which are in agreement with the observed experimental trends.
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
In this work, integrated design and control of reactive distillation processes is presented. Simple graphical design methods that are similar in concept to non-reactive distillation processes are used, such as reactive McCabe-Thiele method and driving force approach. The methods are based...... 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...
Electrochemical model based charge optimization for lithium-ion batteries
Pramanik, Sourav; Anwar, Sohel
2016-05-01
In this paper, we propose the design of a novel optimal strategy for charging the lithium-ion battery based on electrochemical battery model that is aimed at improved performance. A performance index that aims at minimizing the charging effort along with a minimum deviation from the rated maximum thresholds for cell temperature and charging current has been defined. The method proposed in this paper aims at achieving a faster charging rate while maintaining safe limits for various battery parameters. Safe operation of the battery is achieved by including the battery bulk temperature as a control component in the performance index which is of critical importance for electric vehicles. Another important aspect of the performance objective proposed here is the efficiency of the algorithm that would allow higher charging rates without compromising the internal electrochemical kinetics of the battery which would prevent abusive conditions, thereby improving the long term durability. A more realistic model, based on battery electro-chemistry has been used for the design of the optimal algorithm as opposed to the conventional equivalent circuit models. To solve the optimization problem, Pontryagins principle has been used which is very effective for constrained optimization problems with both state and input constraints. Simulation results show that the proposed optimal charging algorithm is capable of shortening the charging time of a lithium ion cell while maintaining the temperature constraint when compared with the standard constant current charging. The designed method also maintains the internal states within limits that can avoid abusive operating conditions.
Adjoint-based optimization of a foam EOR process
Namdar Zanganeh, M.; Kraaijevanger, J.F.B.M.; Buurman, H.W.; Jansen, J.D.; Rossen, W.R.
2012-01-01
We apply adjoint-based optimization to a Surfactant-Alternating-Gas foam process using a linear foam model introducing gradual changes in gas mobility and a nonlinear foam model giving abrupt changes in gas mobility as function of oil and water saturations and surfactant concentration. For the
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 secti...
Reliability-Based Shape Optimization using Stochastic Finite Element Methods
DEFF Research Database (Denmark)
Enevoldsen, Ib; Sørensen, John Dalsgaard; Sigurdsson, G.
1991-01-01
Application of first-order reliability methods FORM (see Madsen, Krenk & Lind [8)) in structural design problems has attracted growing interest in recent years, see e.g. Frangopol [4), Murotsu, Kishi, Okada, Yonezawa & Taguchi [9) and Sørensen [14). In probabilistically based optimal design...
MVMO-based approach for optimal placement and tuning of ...
African Journals Online (AJOL)
DR OKE
This paper introduces an approach based on the Swarm Variant of the ... comprehensive learning particle swarm optimization (CLPSO), genetic ... DOI: http://dx.doi.org/10.4314/ijest.v7i3.12S ..... machine power systems: a comparative study.
Runtime Optimizations for Tree-Based Machine Learning Models
N. Asadi; J.J.P. Lin (Jimmy); A.P. de Vries (Arjen)
2014-01-01
htmlabstractTree-based models have proven to be an effective solution for web ranking as well as other machine learning problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, specifically using gradient-boosted regression
Reality based optimization of steel monopod offshore-towers
Vrouwenvelder, A.C.W.M.
2008-01-01
In this work, the implementation of reliability-based optimization (RBO) of a circular steel monopod-offshore-tower with constant and variable diameters (represented by segmentations) and thicknesses is presented. The tower is subjected to the extreme wave loading. For this purpose, the deterministi
Reliability-Based Optimization of Series Systems of Parallel Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1993-01-01
) a sequential formulation based on optimality criteria; and (4) a sequential formulation including a new so-called bounds iteration method (BIM). Numerical tests indicate that the sequential technique including the BIM is particularly fast and stable. The B1M is not only effective in reliabilitybased...
Optimal Model-Based Control in HVAC Systems
DEFF Research Database (Denmark)
Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik;
2008-01-01
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...
Cooperation in Carrier Sense Based Wireless Ad Hoc Networks - Part I: Reactive Schemes
Munari, Andrea; Zorzi, Michele
2012-01-01
Cooperative techniques have been shown to significantly improve the performance of wireless systems. Despite being a mature technology in single communication link scenarios, their implementation in wider, and practical, networks poses several challenges which have not been fully identified and understood so far. In this two-part paper, the implementation of cooperative communications in non-centralized ad hoc networks with sensing-based channel access is extensively discussed. Both analysis and simulation are employed to provide a clear understanding of the mutual influence between the link layer contention mechanism and collaborative protocols. Part I of this work focuses on reactive cooperation, in which relaying is triggered by packet delivery failure events, while Part II addresses proactive approaches, preemptively initiated by the source based on channel state information. Results show that sensing-based channel access significantly hampers the effectiveness of cooperation by biasing the spatial distri...
Directory of Open Access Journals (Sweden)
Mostafa Lotfi Forushani
2012-04-01
Full Text Available This paper presents an optimized controller around the longitudinal axis of multivariable system in one of the aircraft flight conditions. The controller is introduced in order to control the angle of attack from the pitch attitude angle independently (that is required for designing a set of direct force-modes for the longitudinal axis based on particle swarm optimization (PSO algorithm. The autopilot system for military or civil aircraft is an essential component and in this paper, the autopilot system via 6 degree of freedom model for the control and guidance of aircraft in which the autopilot design will perform based on defining the longitudinal and the lateral-directional axes are supposed. The effectiveness of the proposed controller is illustrated by considering HIMAT aircraft. The simulation results verify merits of the proposed controller.
QOS-BASED MULTICAST ROUTING OPTIMIZATION ALGORITHMS FOR INTERNET
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Most of the multimedia applications require strict Quality-of-Service (QoS) guarantee during the communication between a single source and multiple destinations. The paper mainly presents a QoS Multicast Routing algorithms based on Genetic Algorithm (QMRGA). Simulation results demonstrate that the algorithm is capable of discovering a set of QoS-based near optimized, non-dominated multicast routes within a few iterations, even for the networks environment with uncertain parameters.
Arc Based Ant Colony Optimization Algorithm for optimal design of gravitational sewer networks
Directory of Open Access Journals (Sweden)
R. Moeini
2017-06-01
Full Text Available In this paper, constrained and unconstrained versions of a new formulation of Ant Colony Optimization Algorithm (ACOA named Arc Based Ant Colony Optimization Algorithm (ABACOA are augmented with the Tree Growing Algorithm (TGA and used for the optimal layout and pipe size design of gravitational sewer networks. The main advantages offered by the proposed ABACOA formulation are proper definition of heuristic information, a useful component of the ant-based algorithms, and proper trade-off between the two conflicting search attributes of exploration and exploitation. In both the formulations, the TGA is used to incrementally construct feasible tree-like layouts out of the base layout. In the first formulation, unconstrained version of ABACOA is used to determine the nodal cover depths of sewer pipes while in the second formulation, a constrained version of ABACOA is used to determine the nodal cover depths of sewer pipes which satisfy the pipe slopes constraint. Three different methods of cut determination are also proposed to complete the construction of a tree-like network containing all base layout pipes, here. The proposed formulations are used to solve three test examples of different scales and the results are presented and compared with other available results in the literature. Comparison of the results shows that best results are obtained using the third cutting method in both the formulations. In addition, the results indicate the ability of the proposed methods and in particular the constrained version of ABACOA equipped with TGA to solve sewer networks design optimization problem. To be specific, the constrained version of ABACOA has been able to produce results 0.1%, 1% and 2.1% cheaper than those obtained by the unconstrained version of ABACOA for the first, second and the third test examples, respectively.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Based on entransy dissipation, the mean temperature difference of solenoid (electromagnet) with high thermal conductivity material inserted is deduced, which can be taken as the fundament for heat transfer optimization using the extremum principle of entransy dissipation. Then, the electromagnet working at steady state (constant magnetic field, constant heat generating rate per unit volume) is optimized for entransy dissipation minimization (i.e. mean temperature difference minimization) with and without volume constraint. Besides, the effect of high thermal conductivity material on the magnetic field is analyzed, and the minimum mean temperature versus volume and magnetic induction characteristic are also studied.
Method of Fire Image Identification Based on Optimization Theory
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In view of some distinctive characteristics of the early-stage flame image, a corresponding method of characteristic extraction is presented. Also introduced is the application of the improved BP algorithm based on the optimization theory to identifying fire image characteristics. First the optimization of BP neural network adopting Levenberg-Marquardt algorithm with the property of quadratic convergence is discussed, and then a new system of fire image identification is devised. Plenty of experiments and field tests have proved that this system can detect the early-stage fire flame quickly and reliably.
Optimal Route Selection Method Based on Vague Sets
Institute of Scientific and Technical Information of China (English)
GUO Rui; DU Li min; WANG Chun
2015-01-01
Optimal route selection is an important function of vehicle trac flow guidance system. Its core is to determine the index weight for measuring the route merits and to determine the evaluation method for selecting route. In this paper, subjective weighting method which relies on driver preference is used to determine the weight and the paper proposes the multi-criteria weighted decision method based on vague sets for selecting the optimal route. Examples show that, the usage of vague sets to describe route index value can provide more decision-making information for route selection.
Parallel Harmony Search Based Distributed Energy Resource Optimization
Energy Technology Data Exchange (ETDEWEB)
Ceylan, Oguzhan [ORNL; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)
2015-01-01
This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.
SECURE STEGANOGRAPHY BASED ON BINARY PARTICLE SWARM OPTIMIZATION
Institute of Scientific and Technical Information of China (English)
Guo Yanqing; Kong Xiangwei; You Xingang
2009-01-01
The objective of steganography is to hide message securely in cover objects for secret communication. How to design a secure steganographic algorithm is still major challenge in this research field. In this letter, developing secure steganography is formulated as solving a constrained IP (Integer Programming) problem, which takes the relative entropy of cover and stego distributions as the objective function. Furthermore, a novel method is introduced based on BPSO (Binary Particle Swarm Optimization) for achieving the optimal solution of this programming problem. Experimental results show that the proposed method can achieve excellent performance on preserving neighboring co-occurrence features for JPEG steganography.
Optimization based tuning approach for offset free MPC
DEFF Research Database (Denmark)
Olesen, Daniel Haugård; Huusom, Jakob Kjøbsted; Jørgensen, John Bagterp
2012-01-01
We present an optimization based tuning procedure with certain robustness properties for an offset free Model Predictive Controller (MPC). The MPC is designed for multivariate processes that can be represented by an ARX model. The advantage of ARX model representations is that standard system...... identifiation techniques using convex optimization can be used for identification of such models from input-output data. The stochastic model of the ARX model identified from input-output data is modified with an ARMA model designed as part of the MPC-design procedure to ensure offset-free control. The ARMAX...
Investment Strategies Optimization based on a SAX-GA Methodology
Canelas, António M L; Horta, Nuno C G
2013-01-01
This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
Optimal high speed CMOS inverter design using craziness based Particle Swarm Optimization Algorithm
De, Bishnu P.; Kar, Rajib; Mandal, Durbadal; Ghoshal, Sakti P.
2015-07-01
The inverter is the most fundamental logic gate that performs a Boolean operation on a single input variable. In this paper, an optimal design of CMOS inverter using an improved version of particle swarm optimization technique called Craziness based Particle Swarm Optimization (CRPSO) is proposed. CRPSO is very simple in concept, easy to implement and computationally efficient algorithm with two main advantages: it has fast, nearglobal convergence, and it uses nearly robust control parameters. The performance of PSO depends on its control parameters and may be influenced by premature convergence and stagnation problems. To overcome these problems the PSO algorithm has been modiffed to CRPSO in this paper and is used for CMOS inverter design. In birds' flocking or ffsh schooling, a bird or a ffsh often changes direction suddenly. In the proposed technique, the sudden change of velocity is modelled by a direction reversal factor associated with the previous velocity and a "craziness" velocity factor associated with another direction reversal factor. The second condition is introduced depending on a predeffned craziness probability to maintain the diversity of particles. The performance of CRPSO is compared with real code.gnetic algorithm (RGA), and conventional PSO reported in the recent literature. CRPSO based design results are also compared with the PSPICE based results. The simulation results show that the CRPSO is superior to the other algorithms for the examples considered and can be efficiently used for the CMOS inverter design.
Institute of Scientific and Technical Information of China (English)
蒋健; 汪隆君
2015-01-01
Aiming at problems such as concentrated compensation points and overlapping compensation range of reactive power matrix method in reactive power compensation optimization of power distribution network,a kind of improved pre-cise matrix method was studied. According to several times of load flow results ,compensation points were selected and com-pensation capacities were confirmed. Meanwhile,deficiencies of original optimization method by using only once load flow result were changed,concept of virtual root node was discussed and reactive power compensation points and capacities were determined based on modified precise matrix concept. Example results indicate that it is not only able to overcome problems of concentrated compensation points and overlapping compensation range,but also reflect strong practicability and effective-ness by using the improved precise matrix method for reactive power optimization in the power distribution network.%针对无功精确矩法在配电网无功补偿优化中存在的补偿点集中、补偿范围重叠等问题，研究了一种改进精确矩法。根据多次的潮流结果选择补偿点并确定其补偿容量，改变了原来仅利用一次潮流计算结果进行优化的不足，并探讨“虚根节点”的概念，利用修正的无功精确矩定义确定无功补偿地点和补偿容量。算例结果表明，采用改进的无功精确矩法进行配电网无功优化，不仅克服了原来补偿点集中、补偿范围重叠的问题，而且具有很强的实用性和有效性。
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.
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.
Optimal diabatic dynamics of Majorana-based quantum gates
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.
Directory of Open Access Journals (Sweden)
Hongjin Wang
2015-09-01
Full Text Available To efficiently recover the waste heat from a diesel engine exhaust, a regenerative organic Rankine cycle (RORC system was employed, and butane, R124, R416A, and R134a were used as the working fluids. The resulting diesel engine-RORC combined system was defined and the relevant evaluation indexes were proposed. First, the variation tendency of the exhaust energy rate under various diesel engine operating conditions was analyzed using experimental data. The thermodynamic model of the RORC system was established based on the first and second laws of thermodynamics, and the net power output and exergy destruction rate of the RORC system were selected as the objective functions. A particle swarm optimization (PSO algorithm was used to optimize the operating parameters of the RORC system, including evaporating pressure, intermediate pressure, and degree of superheat. The operating performances of the RORC system and diesel engine-RORC combined system were studied for the four selected working fluids under various operating conditions of the diesel engine. The results show that the operating performances of the RORC system and the combined system using butane are optimal on the basis of optimizing the operating parameters; when the engine speed is 2200 r/min and engine torque is 1215 N·m, the net power output of the RORC system using butane is 36.57 kW, and the power output increasing ratio (POIR of the combined system using butane is 11.56%.
Silvicultural decisions based on simulation-optimization systems
Energy Technology Data Exchange (ETDEWEB)
Cao, Tianjian
2010-05-15
Forest management is facing new challenges under climate change. By adjusting thinning regimes, conventional forest management can be adapted to various objectives of utilization of forest resources, such as wood quality, forest bioenergy, and carbon sequestration. This thesis aims to develop and apply a simulation-optimization system as a tool for an interdisciplinary understanding of the interactions between wood science, forest ecology, and forest economics. In this thesis, the OptiFor software was developed for forest resources management. The OptiFor simulation-optimization system integrated the process-based growth model PipeQual, wood quality models, biomass production and carbon emission models, as well as energy wood and commercial logging models into a single optimization model. Osyczka s direct and random search algorithm was employed to identify optimal values for a set of decision variables. The numerical studies in this thesis broadened our current knowledge and understanding of the relationships between wood science, forest ecology, and forest economics. The results for timber production show that optimal thinning regimes depend on site quality and initial stand characteristics. Taking wood properties into account, our results show that increasing the intensity of thinning resulted in lower wood density and shorter fibers. The addition of nutrients accelerated volume growth, but lowered wood quality for Norway spruce. Integrating energy wood harvesting into conventional forest management showed that conventional forest management without energy wood harvesting was still superior in sparse stands of Scots pine. Energy wood from pre-commercial thinning turned out to be optimal for dense stands. When carbon balance is taken into account, our results show that changing carbon assessment methods leads to very different optimal thinning regimes and average carbon stocks. Raising the carbon price resulted in longer rotations and a higher mean annual
Optimal Analysis of Irreversible Carnot Cycle Based on Entransy Dissipation
Energy Technology Data Exchange (ETDEWEB)
Kim, Kyoung Hoon [Kumoh Nat’l Institute of Technology, Gumi (Korea, Republic of)
2017-02-15
The concept of entransy has been proposed recently as a potential heat transfer mechanism and could be useful in analyzing and optimizing the heat-work conversion systems. This work presents an entransy analysis for the irreversible Carnot cycle by systematic balance formulations of the entransy loss, work entransy, and entransy dissipations, which are consistent with exergy balances. Additionally, several forms of system efficiency are introduced based on entransy for the appreciation of the optimal system performance. The effects of the source temperature and irreversible efficiencies on the optimal conditions for system efficiencies are systematically investigated for both dumping and non-dumping cases of used source fluid. The results show different trends in entransy efficiencies when compared to the conventional efficiencies of energy and exergy, and represent another method to assess the effective use of heat source in power generation systems.
A danger-theory-based immune network optimization algorithm.
Zhang, Ruirui; Li, Tao; Xiao, Xin; Shi, Yuanquan
2013-01-01
Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times.
Electronic Commerce Logistics Network Optimization Based on Swarm Intelligent Algorithm
Directory of Open Access Journals (Sweden)
Yabing Jiao
2013-09-01
Full Text Available This article establish an efficient electronic commerce logistics operation system to reduce distribution costs and build a logistics network operation model based on around the B2C electronic commerce enterprise logistics network operation system. B2C electronic commerce transactions features in the enterprise network platform. To solve the NP-hard problem this article use hybrid ant colony algorithm, particle swarm algorithm and group swarm intelligence algorithm to get a best solution. According to the intelligent algorithm, design of electronic commerce logistics network optimization system, enter the national 22 electronic commerce logistics network for validation. Through the experiment to verify the optimized logistics cost greatly decreased. This research can help B2C electronic commerce enterprise logistics network to optimize decision-making under the premise of ensuring the interests of consumers and service levels also can be an effective way for enterprises to improve the efficiency of logistics services and reduce operation costs
PCNN document segmentation method based on bacterial foraging optimization algorithm
Liao, Yanping; Zhang, Peng; Guo, Qiang; Wan, Jian
2014-04-01
Pulse Coupled Neural Network(PCNN) is widely used in the field of image processing, but it is a difficult task to define the relative parameters properly in the research of the applications of PCNN. So far the determination of parameters of its model needs a lot of experiments. To deal with the above problem, a document segmentation based on the improved PCNN is proposed. It uses the maximum entropy function as the fitness function of bacterial foraging optimization algorithm, adopts bacterial foraging optimization algorithm to search the optimal parameters, and eliminates the trouble of manually set the experiment parameters. Experimental results show that the proposed algorithm can effectively complete document segmentation. And result of the segmentation is better than the contrast algorithms.
A correlation consistency based multivariate alarm thresholds optimization approach.
Gao, Huihui; Liu, Feifei; Zhu, Qunxiong
2016-11-01
Different alarm thresholds could generate different alarm data, resulting in different correlations. A new multivariate alarm thresholds optimization methodology based on the correlation consistency between process data and alarm data is proposed in this paper. The interpretative structural modeling is adopted to select the key variables. For the key variables, the correlation coefficients of process data are calculated by the Pearson correlation analysis, while the correlation coefficients of alarm data are calculated by kernel density estimation. To ensure the correlation consistency, the objective function is established as the sum of the absolute differences between these two types of correlations. The optimal thresholds are obtained using particle swarm optimization algorithm. Case study of Tennessee Eastman process is given to demonstrate the effectiveness of proposed method.
An optimal scheduling algorithm based on task duplication
Institute of Scientific and Technical Information of China (English)
Ruan Youlin; Liu Gan; Zhu Guangxi; Lu Xiaofeng
2005-01-01
When the communication time is relatively shorter than the computation time for every task, the task duplication based scheduling (TDS) algorithm proposed by Darbha and Agrawal generates an optimal schedule. Park and Choe also proposed an extended TDS algorithm whose optimality condition is less restricted than that of TDS algorithm, but the condition is very complex and is difficult to satisfy when the number of tasks is large. An efficient algorithm is proposed whose optimality condition is less restricted and simpler than both of the algorithms, and the schedule length is also shorter than both of the algorithms. The time complexity of the proposed algorithm is O ( v2 ), where v represents the number of tasks.
Analog Circuit Design Optimization Based on Evolutionary Algorithms
Directory of Open Access Journals (Sweden)
Mansour Barari
2014-01-01
Full Text Available This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs. Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met. Comparisons with available methods like genetic algorithms show that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.
Study of Coal Mine Ventilation System Optimization based on Ventsim
Directory of Open Access Journals (Sweden)
Zhang Jing Gang
2016-01-01
Full Text Available This article is based on the situation of too large coal mine ventilation resistance in the Majiagou coal mine. According to Majiagou coal mine late production plans, it measures resistance comprehensively, analyses the resistance distributions and the problems exist in the ventilation systems and comes up with targeted optimization programs. By studying the ventilation system model, as well as adjusting the system parameters, Ventsim software is applied to study ventilation system in Majiagou coal mine. Design of mine ventilation is proved practical in the mine ventilation system optimizations, thus Ventsim software can not only be used in the ventilation network calculation and merry-demand simulation and dynamic of wind flow, but also can be used to assist in the short-term and long-term planning for ventilation system, it is of a certain significance of guidance to find the problems in the mine management and optimizations of the ventilation network.
Extended Range Guided Munition Parameter Optimization Based on Genetic Algorithms
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Many factors influencing range of extended range guided munition (ERGM) are analyzed. The definition domain of the most important three parameters are ascertained by preparatory mathematical simulation, the optimized mathematical model of ERGM maximum range with boundary conditions is created, and parameter optimization based on genetic algorithm (GA) is adopted. In the GA design, three-point crossover is used and the best chromosome is kept so that the convergence speed becomes rapid. Simulation result shows that GA is feasible, the result is good and it can be easy to attain global optimization solution, especially when the objective function is not the convex one for independent variables and it is a multi-parameter problem.
Optimization of Classical Hydraulic Engine Mounts Based on RMS Method
Directory of Open Access Journals (Sweden)
J. Christopherson
2005-01-01
Full Text Available Based on RMS averaging of the frequency response functions of the absolute acceleration and relative displacement transmissibility, optimal parameters describing the hydraulic engine mount are determined to explain the internal mount geometry. More specifically, it is shown that a line of minima exists to define a relationship between the absolute acceleration and relative displacement transmissibility of a sprung mass using a hydraulic mount as a means of suspension. This line of minima is used to determine several optimal systems developed on the basis of different clearance requirements, hence different relative displacement requirements, and compare them by means of their respective acceleration and displacement transmissibility functions. In addition, the transient response of the mount to a step input is also investigated to show the effects of the optimization upon the time domain response of the hydraulic mount.
GPU-based ultra fast IMRT plan optimization
Men, Chunhua; Choi, Dongju; Majumdar, Amitava; Zheng, Ziyi; Mueller, Klaus; Jiang, Steve B
2009-01-01
The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real-time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evalu...
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.
Visibility-based optimal path and motion planning
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...
Energy Technology Data Exchange (ETDEWEB)
BOWLES NA
2010-10-06
The objective of this field test instruction is to provide technical guidance for aqueous injection emplacement of an extension apatite permeable reactive barrier (PRE) for the sequestration of strontium-90 (Sr-90) using a high concentration amendment formulation. These field activities will be conducted according to the guidelines established in DOE/RL-2010-29, 100-NR-2 Design Optimization Study, hereafter referred to as the DOS. The DOS supports the Federal Facility Agreement Consent Order (EPA et al., 1989), Milestone M-16-06-01, and 'Complete Construction of a Permeable Reactive Barrier at 100-N.' Injections of apatite precursor chemicals will occur at an equal distance intervals on each end of the existing PRE to extend the PRB from the existing 91 m (300 ft) to at least 274 m (900 ft). Field testing at the 100-N Area Apatite Treatability Test Site, as depicted on Figure 1, shows that the barrier is categorized by two general hydrologic conceptual models based on overall well capacity and contrast between the Hanford and Ringold hydraulic conductivities. The upstream portion of the original barrier, shown on Figure 1, is characterized by relatively low overall well specific capacity. This is estimated from well development data and a lower contrast in hydraulic conductivity between the Hanford formation and Ringold Formations. Comparison of test results from these two locations indicate that permeability contrast between the Hanford formation and Ringold Formation is significantly less over the upstream one-third of the barrier. The estimated hydraulic conductivity for the Hanford formation and Ringold Formation over the upstream portion of the barrier based on observations during emplacement of the existing 91 m (300 ft) PRB is approximately 12 and 10 m/day (39 and 32 ft/day), respectively (PNNL-17429). However, these estimates should be used as a rough guideline only, as significant variability in hydraulic conductivity is likely to be observed in
Component-based integration of chemistry and optimization software.
Kenny, Joseph P; Benson, Steven J; Alexeev, Yuri; Sarich, Jason; Janssen, Curtis L; McInnes, Lois Curfman; Krishnan, Manojkumar; Nieplocha, Jarek; Jurrus, Elizabeth; Fahlstrom, Carl; Windus, Theresa L
2004-11-15
Typical scientific software designs make rigid assumptions regarding programming language and data structures, frustrating software interoperability and scientific collaboration. Component-based software engineering is an emerging approach to managing the increasing complexity of scientific software. Component technology facilitates code interoperability and reuse. Through the adoption of methodology and tools developed by the Common Component Architecture Forum, we have developed a component architecture for molecular structure optimization. Using the NWChem and Massively Parallel Quantum Chemistry packages, we have produced chemistry components that provide capacity for energy and energy derivative evaluation. We have constructed geometry optimization applications by integrating the Toolkit for Advanced Optimization, Portable Extensible Toolkit for Scientific Computation, and Global Arrays packages, which provide optimization and linear algebra capabilities. We present a brief overview of the component development process and a description of abstract interfaces for chemical optimizations. The components conforming to these abstract interfaces allow the construction of applications using different chemistry and mathematics packages interchangeably. Initial numerical results for the component software demonstrate good performance, and highlight potential research enabled by this platform.
Nozzle Mounting Method Optimization Based on Robot Kinematic Analysis
Chen, Chaoyue; Liao, Hanlin; Montavon, Ghislain; Deng, Sihao
2016-08-01
Nowadays, the application of industrial robots in thermal spray is gaining more and more importance. A desired coating quality depends on factors such as a balanced robot performance, a uniform scanning trajectory and stable parameters (e.g. nozzle speed, scanning step, spray angle, standoff distance). These factors also affect the mass and heat transfer as well as the coating formation. Thus, the kinematic optimization of all these aspects plays a key role in order to obtain an optimal coating quality. In this study, the robot performance was optimized from the aspect of nozzle mounting on the robot. An optimized nozzle mounting for a type F4 nozzle was designed, based on the conventional mounting method from the point of view of robot kinematics validated on a virtual robot. Robot kinematic parameters were obtained from the simulation by offline programming software and analyzed by statistical methods. The energy consumptions of different nozzle mounting methods were also compared. The results showed that it was possible to reasonably assign the amount of robot motion to each axis during the process, so achieving a constant nozzle speed. Thus, it is possible optimize robot performance and to economize robot energy.
An efficient approach for reliability-based topology optimization
Kanakasabai, Pugazhendhi; Dhingra, Anoop K.
2016-01-01
This article presents an efficient approach for reliability-based topology optimization (RBTO) in which the computational effort involved in solving the RBTO problem is equivalent to that of solving a deterministic topology optimization (DTO) problem. The methodology presented is built upon the bidirectional evolutionary structural optimization (BESO) method used for solving the deterministic optimization problem. The proposed method is suitable for linear elastic problems with independent and normally distributed loads, subjected to deflection and reliability constraints. The linear relationship between the deflection and stiffness matrices along with the principle of superposition are exploited to handle reliability constraints to develop an efficient algorithm for solving RBTO problems. Four example problems with various random variables and single or multiple applied loads are presented to demonstrate the applicability of the proposed approach in solving RBTO problems. The major contribution of this article comes from the improved efficiency of the proposed algorithm when measured in terms of the computational effort involved in the finite element analysis runs required to compute the optimum solution. For the examples presented with a single applied load, it is shown that the CPU time required in computing the optimum solution for the RBTO problem is 15-30% less than the time required to solve the DTO problems. The improved computational efficiency allows for incorporation of reliability considerations in topology optimization without an increase in the computational time needed to solve the DTO problem.
Directory of Open Access Journals (Sweden)
Giovanni Fiorilli, Enzo Iuliano, Michalis Mitrotasios, Eugenio M. Pistone, Giovanna Aquino, Giuseppe Calcagno, Alessandra di Cagno
2017-06-01
Full Text Available Change Of Direction Speed (CODS and Reactive Agility (RA are two determining factors in the ability of young soccer players. We aimed to verify if CODS and RA could be useful in order to establish the best young soccer player field position. Ninety-two elite soccer players (15.18 ± 1.21 years, weight 59.18 ± 9.93, height 1.72 ± 0.08, BMI 19.76 ± 2.22, belonging to two youth categories from the Italian First and Second Divisions, volunteered in this study. The participants included 32 defenders (15.06 ± 0.80 years, 37 midfielders (15.11 ± 0.84 years and 23 forwards (15.48 ± 1.16 years, and they underwent two tests, each one performed in two different ways: the Y-Agility Test, carried out in a planned and reactive mode (Y-PLAN and Y-REAC, and the Illinois for Change of Direction Test (ICODT performed with and without the ball. REAC-INDEX, which represents the index of reactivity, was calculated as Y-REAC minus Y-PLAN. The difference between the two scores of ICODT (ICODT with the ball minus ICODT without the ball represents the TECHN-INDEX. Multivariate Analysis of Variances (MANOVA was used to evaluate significant differences among all position groups, for all the test scores. MANOVA showed no significant differences in test scores or in TECHN-INDEX among the groups, except for the forwards, who were significantly more reactive than the defenders (p < 0.05. The strong and significant Pearson’s Correlation between ICODT with and without the ball (p < 0.01 demonstrated that physical and technical preparations have the same relevance in all positions. No significant differences were found among players in different field positions for CODS and RA performances, both with and without the ball. This study does not recommend to use RA and CODS as indicators to assign the players roles in youth soccer.
Directory of Open Access Journals (Sweden)
Zhang PF
2015-09-01
Full Text Available Pengfei Zhang,1,* Yan Bao,1,* Mohamed Shehata Draz,2,3,* Huiqi Lu,1 Chang Liu,1 Huanxing Han11Center for Translational Medicine, Changzheng Hospital, Second Military Medical University, Shanghai, People’s Republic of China; 2Zhejiang-California International Nanosystems Institute, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 3Faculty of Science, Tanta University, Tanta, Egypt*These authors contributed equally to this workAbstract: Convenient and rapid immunofiltration assays (IFAs enable on-site “yes” or “no” determination of disease markers. However, traditional IFAs are commonly qualitative or semi-quantitative and are very limited for the efficient testing of samples in field diagnostics. Here, we overcome these limitations by developing a quantum dots (QDs-based fluorescent IFA for the quantitative detection of C-reactive proteins (CRP. CRP, the well-known diagnostic marker for acute viral and bacterial infections, was used as a model analyte to demonstrate performance and sensitivity of our developed QDs-based IFA. QDs capped with both polyethylene glycol (PEG and glutathione were used as fluorescent labels for our IFAs. The presence of the surface PEG layer, which reduced the non-specific protein interactions, in conjunction with the inherent optical properties of QDs, resulted in lower background signal, increased sensitivity, and ability to detect CRP down to 0.79 mg/L with only 5 µL serum sample. In addition, the developed assay is simple, fast and can quantitatively detect CRP with a detection limit up to 200 mg/L. Clinical test results of our QD-based IFA are well correlated with the traditional latex enhance immune-agglutination aggregation. The proposed QD-based fluorescent IFA is very promising, and potentially will be adopted for multiplexed immunoassay and in field point-of-care test.Keywords: C-reactive proteins, point-of-care test, Glutathione capped QDs, PEGylation
CFSO3: A New Supervised Swarm-Based Optimization Algorithm
Directory of Open Access Journals (Sweden)
Antonino Laudani
2013-01-01
Full Text Available We present CFSO3, an optimization heuristic within the class of the swarm intelligence, based on a synergy among three different features of the Continuous Flock-of-Starlings Optimization. One of the main novelties is that this optimizer is no more a classical numerical algorithm since it now can be seen as a continuous dynamic system, which can be treated by using all the mathematical instruments available for managing state equations. In addition, CFSO3 allows passing from stochastic approaches to supervised deterministic ones since the random updating of parameters, a typical feature for numerical swam-based optimization algorithms, is now fully substituted by a supervised strategy: in CFSO3 the tuning of parameters is a priori designed for obtaining both exploration and exploitation. Indeed the exploration, that is, the escaping from a local minimum, as well as the convergence and the refinement to a solution can be designed simply by managing the eigenvalues of the CFSO state equations. Virtually in CFSO3, just the initial values of positions and velocities of the swarm members have to be randomly assigned. Both standard and parallel versions of CFSO3 together with validations on classical benchmarks are presented.
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.
Mars Mission Optimization Based on Collocation of Resources
Chamitoff, G. E.; James, G. H.; Barker, D. C.; Dershowitz, A. L.
2003-01-01
This paper presents a powerful approach for analyzing Martian data and for optimizing mission site selection based on resource collocation. This approach is implemented in a program called PROMT (Planetary Resource Optimization and Mapping Tool), which provides a wide range of analysis and display functions that can be applied to raw data or imagery. Thresholds, contours, custom algorithms, and graphical editing are some of the various methods that can be used to process data. Output maps can be created to identify surface regions on Mars that meet any specific criteria. The use of this tool for analyzing data, generating maps, and collocating features is demonstrated using data from the Mars Global Surveyor and the Odyssey spacecraft. The overall mission design objective is to maximize a combination of scientific return and self-sufficiency based on utilization of local materials. Landing site optimization involves maximizing accessibility to collocated science and resource features within a given mission radius. Mission types are categorized according to duration, energy resources, and in-situ resource utilization. Optimization results are shown for a number of mission scenarios.
Computer Based Porosity Design by Multi Phase Topology Optimization
Burblies, Andreas; Busse, Matthias
2008-02-01
A numerical simulation technique called Multi Phase Topology Optimization (MPTO) based on finite element method has been developed and refined by Fraunhofer IFAM during the last five years. MPTO is able to determine the optimum distribution of two or more different materials in components under thermal and mechanical loads. The objective of optimization is to minimize the component's elastic energy. Conventional topology optimization methods which simulate adaptive bone mineralization have got the disadvantage that there is a continuous change of mass by growth processes. MPTO keeps all initial material concentrations and uses methods adapted from molecular dynamics to find energy minimum. Applying MPTO to mechanically loaded components with a high number of different material densities, the optimization results show graded and sometimes anisotropic porosity distributions which are very similar to natural bone structures. Now it is possible to design the macro- and microstructure of a mechanical component in one step. Computer based porosity design structures can be manufactured by new Rapid Prototyping technologies. Fraunhofer IFAM has applied successfully 3D-Printing and Selective Laser Sintering methods in order to produce very stiff light weight components with graded porosities calculated by MPTO.
Group Elevator Peak Scheduling Based on Robust Optimization Model
Directory of Open Access Journals (Sweden)
ZHANG, J.
2013-08-01
Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.
Directory of Open Access Journals (Sweden)
Petrović Milica M.
2014-01-01
Full Text Available The Bi2O3 films-based anodes were synthesized by electrodeposition of Bi on stainless steel substrate at constant current density and during different deposition times, fallowed by calcination, forming Bi2O3. The thickness of the films was determined by two methods: the observation under the microscope and by calculation from mass difference. Electrochemical proceses at the anodes were ivestigated by linear sweep voltammetry. At the anodes obtained within 2, 5, 10 and 15 minutes of deposition, two dyes, namely: Reactive Blue 19 and Crystal Violet, were decolorized by oxidation with •OH radical, generated from H2O2 decomposition at the anodes. Decoloration times of the anodes varied, and the shortest one was achieved with the anode obtained during 5 minutes of deposition, with the film thickness of 2.5±0.3 μm. The optimal H2O2 concentration for the dyes degradation was found to be 10 mmol dm-3. [Projekat Ministarstva nauke Republike Srbije, br. ТR 34008
Rubio-Godoy, Verena; Ayyoub, Maha; Dutoit, Valerie; Servis, Catherine; Schink, Amy; Rimoldi, Donata; Romero, Pedro; Cerottini, Jean-Charles; Simon, Richard; Zhao, Yindong; Houghten, Richard A; Pinilla, Clemencia; Valmori, Danila
2002-08-01
A novel approach for the identification of tumor antigen-derived sequences recognized by CD8(+) cytolytic T lymphocytes (CTL) consists in using synthetic combinatorial peptide libraries. Here we have screened a library composed of 3.1 x 10(11) nonapeptides arranged in a positional scanning format, in a cytotoxicity assay, to search the antigen recognized by melanoma-reactive CTL of unknown specificity. The results of this analysis enabled the identification of several optimal peptide ligands, as most of the individual nonapeptides deduced from the primary screening were efficiently recognized by the CTL. The results of the library screening were also analyzed with a mathematical approach based on a model of independent and additive contribution of individual amino acids to antigen recognition. This biometrical data analysis enabled the retrieval, in public databases, of the native antigenic peptide SSX-2(41-49), whose sequence is highly homologous to the ones deduced from the library screening, among the ones with the highest stimulatory score. These results underline the high predictive value of positional scanning synthetic combinatorial peptide library analysis and encourage its use for the identification of CTL ligands.
Khalik, Wan Fadhilah; Ho, Li-Ngee; Ong, Soon-An; Voon, Chun-Hong; Wong, Yee-Shian; Yusoff, NikAthirah; Lee, Sin-Li; Yusuf, Sara Yasina
2017-10-01
The photocatalytic fuel cell (PFC) system was developed in order to study the effect of several operating parameters in degradation of Reactive Black 5 (RB5) and its electricity generation. Light irradiation, initial dye concentration, aeration, pH and cathode electrode are the operating parameters that might give contribution in the efficiency of PFC system. The degradation of RB5 depends on the presence of light irradiation and solar light gives better performance to degrade the azo dye. The azo dye with low initial concentration decolorizes faster compared to higher initial concentration and presence of aeration in PFC system would enhance its performance. Reactive Black 5 rapidly decreased at higher pH due to the higher amount of OH generated at higher pH and Pt-loaded carbon (Pt/C) was more suitable to be used as cathode in PFC system compared to Cu foil and Fe foil. The rapid decolorization of RB5 would increase their voltage output and in addition, it would also increase their Voc, Jsc and Pmax. The breakage of azo bond and aromatic rings was confirmed through UV-Vis spectrum and COD analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bechtle, M; Butté, A; Storti, G; Morbidelli, M
2010-07-09
Polymeric monoliths are a relatively new separation medium for chromatographic applications. The innovative approach to produce such monoliths, the Reactive Gelation Process, presented by Marti et al. [1] for polystyrene macroporous materials is applied to a methacrylate-based material. It is shown that it is possible to create a macroporous structure by Reactive Gelation also with this polymer even if the properties of the material are different. Besides the analysis of the material by SEM and BET, several chromatographic methods are used to analyze the material properties. The ISEC experiments showed a much smaller size exclusion effect than in conventional packed beds. The permeability of the material is comparable to a packed bed with 4.13 μm particles. The column efficiency is not changing for increasing flow rates. Because of the high efficiency of the material, shorter columns are needed and therefore the comparatively low permeability is compensated. The monolith also exhibits a significant adsorption capacity for hydrophobic interaction, which makes it suitable for chromatographic purification processes.
Institute of Scientific and Technical Information of China (English)
Gurmanik KAUR‡; Ajat Shatru ARORA; Vijender Kumar JAIN
2015-01-01
Accurate blood pressure (BP) measurement is essential in epidemiological studies, screening programmes, and re-search studies as well as in clinical practice for the early detection and prevention of high BP-related risks such as coronary heart disease, stroke, and kidney failure. Posture of the participant plays a vital role in accurate measurement of BP. Guidelines on measurement of BP contain recommendations on the position of the back of the participants by advising that they should sit with supported back to avoid spuriously high readings. In this work, principal component analysis (PCA) is fused with forward stepwise regression (SWR), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and the least squares support vector machine (LS-SVM) model for the prediction of BP reactivity to an unsupported back in normotensive and hypertensive participants. PCA is used to remove multi-collinearity among anthropometric predictor variables and to select a subset of com-ponents, termed‘principal components’ (PCs), from the original dataset. The selected PCs are fed into the proposed models for modeling and testing. The evaluation of the performance of the constructed models, using appropriate statistical indices, shows clearly that a PCA-based LS-SVM (PCA-LS-SVM) model is a promising approach for the prediction of BP reactivity in com-parison to others. This assessment demonstrates the importance and advantages posed by hybrid models for the prediction of variables in biomedical research studies.
An Improved Particle Swarm Optimization Algorithm Based on Ensemble Technique
Institute of Scientific and Technical Information of China (English)
SHI Yan; HUANG Cong-ming
2006-01-01
An improved particle swarm optimization (PSO) algorithm based on ensemble technique is presented. The algorithm combines some previous best positions (pbest) of the particles to get an ensemble position (Epbest), which is used to replace the global best position (gbest). It is compared with the standard PSO algorithm invented by Kennedy and Eberhart and some improved PSO algorithms based on three different benchmark functions. The simulation results show that the improved PSO based on ensemble technique can get better solutions than the standard PSO and some other improved algorithms under all test cases.
Aron, Allegra T; Ramos-Torres, Karla M; Cotruvo, Joseph A; Chang, Christopher J
2015-08-18
Metals are essential for life, playing critical roles in all aspects of the central dogma of biology (e.g., the transcription and translation of nucleic acids and synthesis of proteins). Redox-inactive alkali, alkaline earth, and transition metals such as sodium, potassium, calcium, and zinc are widely recognized as dynamic signals, whereas redox-active transition metals such as copper and iron are traditionally thought of as sequestered by protein ligands, including as static enzyme cofactors, in part because of their potential to trigger oxidative stress and damage via Fenton chemistry. Metals in biology can be broadly categorized into two pools: static and labile. In the former, proteins and other macromolecules tightly bind metals; in the latter, metals are bound relatively weakly to cellular ligands, including proteins and low molecular weight ligands. Fluorescent probes can be useful tools for studying the roles of transition metals in their labile forms. Probes for imaging transition metal dynamics in living systems must meet several stringent criteria. In addition to exhibiting desirable photophysical properties and biocompatibility, they must be selective and show a fluorescence turn-on response to the metal of interest. To meet this challenge, we have pursued two general strategies for metal detection, termed "recognition" and "reactivity". Our design of transition metal probes makes use of a recognition-based approach for copper and nickel and a reactivity-based approach for cobalt and iron. This Account summarizes progress in our laboratory on both the development and application of fluorescent probes to identify and study the signaling roles of transition metals in biology. In conjunction with complementary methods for direct metal detection and genetic and/or pharmacological manipulations, fluorescent probes for transition metals have helped reveal a number of principles underlying transition metal dynamics. In this Account, we give three recent
Removal of Selenium and Nitrate in Groundwater Using Organic Carbon-Based Reactive Mixtures
An, Hyeonsil; Jeen, Sung-Wook
2016-04-01
Treatment of selenium and nitrate in groundwater was evaluated through column experiments. Four columns consisting of reactive mixtures, either organic carbon-limestone (OC-LS) or organic carbon-zero valent iron (OC-ZVI), were used to determine the removal efficiency of selenium with different concentrations of nitrate. The source waters were collected from a mine site in Korea or were prepared artificially based on the mine drainage water or deionized water, followed by spiking of elevated concentrations of Se (40 mg/L) and nitrate (100 or 10 mg/L as NO3-N). The results for the aqueous chemistry showed that selenium and nitrate were effectively removed both in the mine drainage water and deionized water-based artificial input solution. However, the removal of selenium was delayed when selenium and nitrate coexisted in the OC-LS columns. The removal of selenium was not significant when the influent nitrate concentration was 100 mg/L as NO3-N, while most of nitrate was gradually removed within the columns. In contrast, 94% of selenium was removed when the influent nitrate concentration was reduced to 10 mg/L as NO3-N. In the OC-ZVI column, selenium and nitrate was removed almost simultaneously and completely even with the high nitrate concentration; however, a high concentration of ammonia was produced as a by-product of abiotic reaction between ZVI and nitrate. The elemental analysis for the solid samples after the termination of the experiments showed that selenium was accumulated in the reactive materials where removal of aqueous-phase selenium mostly occurred. The X-ray absorption near-edge structure (XANES) study indicated that selenium existed in the forms of SeS2 and Se(0) in the OC-LS column, while selenium was present in the forms of FeSe, SeS2 and absorbed Se(IV) in the OC-ZVI column. This study shows that OC-based reactive mixtures have an ability to remove selenium and nitrate in groundwater. However, the removal of selenium was influenced by the high
DEFF Research Database (Denmark)
Vlachogiannis, Ioannis (John); Lee, K Y
2009-01-01
In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem...... of steady-state of power systems. Specifically, reactive power control is formulated as a multi-objective optimization problem and solved using the parallel VEPSO algorithm. The results on the IEEE 30-bus test system are compared with those given by another multi-objective evolutionary technique...... demonstrating the advantage of parallel VEPSO. The parallel VEPSO is also tested on a larger power system this with 136 busses. (C) 2009 Elsevier Ltd. All rights reserved....
Multicast Routing Problem Using Tree-Based Cuckoo Optimization Algorithm
Directory of Open Access Journals (Sweden)
Mahmood Sardarpour
2016-06-01
Full Text Available The problem of QoS multicast routing is to find a multicast tree with the least expense/cost which would meet the limitations such as band width, delay and loss rate. This is a NP-Complete problem. To solve the problem of multicast routing, the entire routes from the source node to every destination node are often recognized. Then the routes are integrated and changed into a single multicast tree. But they are slow and complicated methods. The present paper introduces a new tree-based optimization method to overcome such weaknesses. The recommended method directly optimizes the multicast tree. Therefore a tree-based typology including several spanning trees is created which combines the trees two by two. For this purpose, the Cuckoo Algorithm is used which is proved to be well converged and makes quick calculations. The simulation conducted on different types of network typologies proved that it is a practical and influential algorithm.
FEM Optimal Design of Wind Energy-based Heater
Directory of Open Access Journals (Sweden)
Tiberiu Tudorache
2009-07-01
Full Text Available This paper deals with the finite element based optimal design of a wind energybased heater. The proposed device ensures the conversion of the wind kinetic energy intoheat by means of Joule effect of eddy currents induced in the wall of a tubular stator due tothe rotating magnetic field produced by rotor permanent magnets. The transientelectromagnetic field problem associated to the operation of the device is solved using a2D finite element approach based on vector potential formulation. A simplified method forthe 2D heat transfer analysis of the device is also proposed. The influence of stator wallmaterial and thickness, number of poles, the airgap thickness and the geometricalparameters of the permanent magnets is analyzed in the aim of optimizing the studiedheater.
On combining Laplacian and optimization-based mesh smoothing techniques
Energy Technology Data Exchange (ETDEWEB)
Freitag, L.A.
1997-07-01
Local mesh smoothing algorithms have been shown to be effective in repairing distorted elements in automatically generated meshes. The simplest such algorithm is Laplacian smoothing, which moves grid points to the geometric center of incident vertices. Unfortunately, this method operates heuristically and can create invalid meshes or elements of worse quality than those contained in the original mesh. In contrast, optimization-based methods are designed to maximize some measure of mesh quality and are very effective at eliminating extremal angles in the mesh. These improvements come at a higher computational cost, however. In this article the author proposes three smoothing techniques that combine a smart variant of Laplacian smoothing with an optimization-based approach. Several numerical experiments are performed that compare the mesh quality and computational cost for each of the methods in two and three dimensions. The author finds that the combined approaches are very cost effective and yield high-quality meshes.
Optimal reliability-based design of offshore wind turbine parks
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2006-01-01
that wind turbines are parked for wind speeds larger than 25 m/s resulting in reduced wind loads. Basic relationships are described for the mean wind velocity and turbulence intensity in wind turbine parks with emphasis on the spatial correlation. The expected total failure costs for the wind turbine park......A basic formulation for optimal reliability-based design of wind turbine parks is presented. Based on this model a probabilistic model and representative limit state equations for structural failure of wind turbine towers are formulated. The probability of failure is determined taking into account...... are estimated and normalised with a situation with only one wind turbine taking into account the spatial correlation. A sensitivity analysis is made with respect to parameters modelling the spatial correlation. Further, an optimization problem is formulated where a design parameter is the distance between...
Parameter optimization in differential geometry based solvation models.
Wang, Bao; Wei, G W
2015-10-01
Differential geometry (DG) based solvation models are a new class of variational implicit solvent approaches that are able to avoid unphysical solvent-solute boundary definitions and associated geometric singularities, and dynamically couple polar and non-polar interactions in a self-consistent framework. Our earlier study indicates that DG based non-polar solvation model outperforms other methods in non-polar solvation energy predictions. However, the DG based full solvation model has not shown its superiority in solvation analysis, due to its difficulty in parametrization, which must ensure the stability of the solution of strongly coupled nonlinear Laplace-Beltrami and Poisson-Boltzmann equations. In this work, we introduce new parameter learning algorithms based on perturbation and convex optimization theories to stabilize the numerical solution and thus achieve an optimal parametrization of the DG based solvation models. An interesting feature of the present DG based solvation model is that it provides accurate solvation free energy predictions for both polar and non-polar molecules in a unified formulation. Extensive numerical experiment demonstrates that the present DG based solvation model delivers some of the most accurate predictions of the solvation free energies for a large number of molecules.
Magalhães, Luís M; Lúcio, Marlene; Segundo, Marcela A; Reis, Salette; Lima, José L F C
2009-06-15
Redox reactions are the heart of numerous biochemical pathways found in cellular chemistry, generating reactive oxygen species (ROS) and reactive nitrogen species (RNS), that includes superoxide anion radical (O2-), hydrogen peroxide (H2O2), hydroxyl radical (HO), singlet oxygen ((1)O2), hypochlorite anion (OCl-), peroxynitrite anion (ONOO-) and nitric oxide radical (NO). The measurement of scavenging capacity against these reactive species presents new challenges, which can be met by flow injection analysis (FIA). In the present review several methods based on FIA and also on its predecessors computer-controlled techniques (sequential injection analysis, multisyringe flow injection analysis, multicommutated and multipumping flow systems) are critically discussed. The selectivity and applicability of the methodology, the generation and detection of the target reactive species, the benefits and limitations of automation when compared to batch methods are some of the issues addressed.
LTE/MVNO NETWORKS STRUCTURE OPTIMIZATION BASED ON TENSOR DECOMPOSITION
Strelkovskaya, Iryna; Solovskaya, Iryna
2015-01-01
The usage of tensor methods on the decomposition basis is offered for the tasks solution of structure optimization for LTE/MVNO networks mobile communication. The choice problem of optimum topology of e-Node B base stations connectionsin the radio access of E-UTRAN/LTE network was solved. The assessment problem of QoS quality characteristics of complex LTE/MVNO network architecture was solved.
Information fusion based optimal control for large civil aircraft system.
Zhen, Ziyang; Jiang, Ju; Wang, Xinhua; Gao, Chen
2015-03-01
Wind disturbance has a great influence on landing security of Large Civil Aircraft. Through simulation research and engineering experience, it can be found that PID control is not good enough to solve the problem of restraining the wind disturbance. This paper focuses on anti-wind attitude control for Large Civil Aircraft in landing phase. In order to improve the riding comfort and the flight security, an information fusion based optimal control strategy is presented to restrain the wind in landing phase for maintaining attitudes and airspeed. Data of Boeing707 is used to establish a nonlinear mode with total variables of Large Civil Aircraft, and then two linear models are obtained which are divided into longitudinal and lateral equations. Based on engineering experience, the longitudinal channel adopts PID control and C inner control to keep longitudinal attitude constant, and applies autothrottle system for keeping airspeed constant, while an information fusion based optimal regulator in the lateral control channel is designed to achieve lateral attitude holding. According to information fusion estimation, by fusing hard constraint information of system dynamic equations and the soft constraint information of performance index function, optimal estimation of the control sequence is derived. Based on this, an information fusion state regulator is deduced for discrete time linear system with disturbance. The simulation results of nonlinear model of aircraft indicate that the information fusion optimal control is better than traditional PID control, LQR control and LQR control with integral action, in anti-wind disturbance performance in the landing phase. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Methods for reliability based design optimization of structural components
Dersjö, Tomas
2012-01-01
Cost and quality are key properties of a product, possibly even the two most important. Onedefinition of quality is fitness for purpose. Load-bearing products, i.e. structural components,loose their fitness for purpose if they fail. Thus, the ability to withstand failure is a fundamentalmeasure of quality for structural components. Reliability based design optimization(RBDO) is an approach for development of structural components which aims to minimizethe cost while constraining the probabili...
Routing Optimization Based on Taboo Search Algorithm for Logistic Distribution
Hongxue Yang; Lingling Xuan
2014-01-01
Along with the widespread application of the electronic commerce in the modern business, the logistic distribution has become increasingly important. More and more enterprises recognize that the logistic distribution plays an important role in the process of production and sales. A good routing for logistic distribution can cut down transport cost and improve efficiency. In order to cut down transport cost and improve efficiency, a routing optimization based on taboo search for logistic distr...
Parameter optimization for tandemregenerative system based on critical path
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
For a tandem queue system, the regenerative path is constructed. In an inter-regeneration cycle, the sensitivity value of performance measure with respect to the adjustable parameter θ can be acquired based on a fixed length of observation. Furthermore, a new algorithm of parameter optimization for the tandem queue system is given,which requires less simulation and no analysis for the perturbation transmission and makes a better estimation for the sen sitivity.
Optimal design of SAW-based gyroscope to improve sensitivity
Oh, Haekwan; Yang, Sangsik; Lee, Keekeun
2010-02-01
A surface acoustic wave (SAW)-based gyroscope was developed on a piezoelectric substrate. The developed gyroscope consists of two SAW oscillators, metallic dots, and absorber. Coupling of mode (COM) modeling was conducted to determine the optimal device parameters prior to fabrication. Depending on the angular velocity, the difference of the oscillation frequency was modulated. The obtained sensitivity was approximately 52.35 Hz/deg.s at an angular rate range of 0~1000 deg/s.
Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.
2011-01-01
Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with
Martorell, María M; Pajot, Hipólito F; Rovati, José I; Figueroa, Lucía I C
2012-03-01
Decolourization and degradation of the diazo dye Reactive Black 5 was carried out by the yeast Trichosporon akiyoshidainum. A nine-factor Plackett-Burman design was employed for the study and optimization of the decolourization process and production of manganese peroxidase (MnP) and tyrosinase activities. In the present study, 26 individual experiments were conducted and three responses were evaluated. Raising yeast extract concentration significantly enhanced decolourization and MnP production. Carbon and nitrogen sources, glucose and (NH4)2 SO4, showed no significant effect on any response over the concentration range tested. Other culture medium components, such as CaCl2 or MgSO4, could be excluded from the medium formula, as they had no effect on the evaluated responses. Metal ions (Fe, Cu and Mn) showed different effects on decolourization and enzymatic activities. Addition of copper significantly enhanced MnP activity and decreased dye decolourization. On the contrary, iron had a positive effect on decolourization and no effect on enzyme production. Oddly, increasing manganese concentration had a positive effect on tyrosinase production without affecting decolourization or MnP activity. These results strongly suggest that dye decolourization should be regarded as a complex multi-enzymatic process, where optimal medium composition should arise as a compromise between those optimal for each implied enzyme production. Copyright © 2012 John Wiley & Sons, Ltd.
Model-based dynamic control and optimization of gas networks
Energy Technology Data Exchange (ETDEWEB)
Hofsten, Kai
2001-07-01
by a structured sequential quadratic programming algorithm of Newton type. Each open loop problem is specified using a nonlinear prediction model. For each iteration of the quadratic programming procedure, a linear time variant prediction model is formulated. The suggested controller also handles time varying source capacity. Potential problems such as infeasibility and the security of the supply when facing a change in the status of the infrastructure of the transmission system under a transient customer load are treated. Comments on the infeasibility due to errors such as load forecast error, model error and state estimation error are also discussed. A simplified nonlinear model called the creep flow model is used to describe the fluid dynamics inside a natural gas transmission line. Different assumptions and reformulations of this model yield the different control, simulation and optimization models used in this thesis. The control of a single gas transmission line is investigated using linear model predictive control based on instant linearization of the nonlinear model. Model predictive control using a bi quadratic optimization model formulated from the creep flow model is also investigated. A distributed parameter control model of the gas dynamics for a transmission line is formulated. An analytic solution of this model is given with both Neuman boundary conditions and distributed supplies and loads. A transfer function model is developed expressing the dynamics between the defined output and the control and disturbance inputs of the transmission line. Based on the qualitative behaviour observed from the step responses of the solutions of the distributed parameter model formulated in this thesis, simplified transfer function models were developed. These control models expresses the dynamics of a natural gas transmission line with Neuman boundary control and load. Further, these models were used to design a control law, which is a combination of a Smith
Bulgakov, V. K.; Strigunov, V. V.
2009-05-01
The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.
DEFF Research Database (Denmark)
Stöhr, Frederik; Wright, Jonathan; Simons, Hugh
2015-01-01
. The remaining sacrificial material inside the lens cavities was removed by etching through the silicon wafer. Since the wafers become fragile after through-etching, they were then adhesively bonded to a carrier wafer. Individual chips were separated using laser micro machining and the 3D shape of fabricated......Line-focusing compound silicon x-ray lenses with structure heights exceeding 300 μm were fabricated using deep reactive ion etching. To ensure profile uniformity over the full height, a new strategy was developed in which the perimeter of the structures was defined by trenches of constant width...... the resolution and capabilities of modern x-ray techniques such as x-ray microscopy and 3D x-ray diffraction....
Yang, Wandian; Li, Pingli; Bo, Dechen; Chang, Heying; Wang, Xiaowei; Zhu, Tao
2013-04-01
Furfural is one of the most promising platform chemicals derived from biomass. In this study, response surface methodology (RSM) was utilized to determine four important parameters including reaction temperature (170-210°C), formic acid concentration (5-25 g/L), o-nitrotoluene volume percentage (20-80 vt.%), and residence time (40-200 min). The maximum furfural yield of 74% and selectivity of 86% were achieved at 190°C for 20 g/L formic acid concentration and 75 vt.% o-nitrotoluene by 75 min. The high boiling solvent, o-nitrotoluene, was recommended as extraction solvent in a reactive extraction system to obtain high furfural yield and reduce furfural-solvent separation costs. Although the addition of halides to the xylose solutions enhanced the furfural yield and selectivity, the concentration of halides was not an important factor on the furfural yield and selectivity.
Tour Route Multiobjective Optimization Design Based on the Tourist Satisfaction
Directory of Open Access Journals (Sweden)
Yan Han
2014-01-01
Full Text Available The question prompted is how to design the tour route to make the tourists get the maximum satisfactions considering the tourists’ demand. The influence factors of the tour route choices of tourists were analyzed and tourists’ behavior characteristics and psychological preferences were regarded as the important influence factors based on the tourist behavioral theories. A questionnaire of tourists’ tour route information and satisfaction degree was carried out. Some information about the scene spot and tourists demand and tour behaviors characteristic such as visit frequency, number of attractions visited was obtained and analyzed. Based on the convey datum, tour routes multiobjective optimization functions were prompted for the tour route design regarding the maximum satisfaction and the minimum tour distance as the optimal objective. The available routes are listed and categorized. Based on the particle swarm optimization model, the priorities of the tour route are calculated and finally the suggestion depth tour route and quick route tour routes are given considering the different tour demands of tourists. The results can offer constructive suggestions on how to design tour routes on the part of tourism enterprises and how to choose a proper tour route on the part of tourists.
Modeling the crop transpiration using an optimality-based approach
Institute of Scientific and Technical Information of China (English)
Stanislaus; J.Schymanski; Murugesu; Sivapalan
2008-01-01
Evapotranspiration constitutes more than 80% of the long-term water balance in Northern China.In this area,crop transpiration due to large areas of agriculture and irrigation is responsible for the majority of evapotranspiration.A model for crop transpiration is therefore essential for estimating the agricultural water consumption and understanding its feedback to the environment.However,most existing hydrological models usually calculate transpiration by relying on parameter calibration against local observations,and do not take into account crop feedback to the ambient environment.This study presents an optimality-based ecohydrology model that couples an ecological hypothesis,the photosynthetic process,stomatal movement,water balance,root water uptake and crop senescence,with the aim of predicting crop characteristics,CO2 assimilation and water balance based only on given meteorological data.Field experiments were conducted in the Weishan Irrigation District of Northern China to evaluate performance of the model.Agreement between simulation and measurement was achieved for CO2 assimilation,evapotranspiration and soil moisture content.The vegetation optimality was proven valid for crops and the model was applicable for both C3 and C4 plants.Due to the simple scheme of the optimality-based approach as well as its capability for modeling dynamic interactions between crops and the water cycle without prior vegetation information,this methodology is potentially useful to couple with the distributed hydrological model for application at the watershed scale.
Genetic based optimization for multicast routing algorithm for MANET
Indian Academy of Sciences (India)
C Rajan; N Shanthi
2015-12-01
Mobile Ad hoc Network (MANET) is established for a limited period, for special extemporaneous services related to mobile applications. This ad hoc network is set up for a limited period, in environments that change with the application. While in Internet the TCP/IP protocol suite supports a wide range of application, in MANETs protocols are tuned to specific customer/application. Multicasting is emerging as a popular communication format where the same packet is sent to multiple nodes in a network. Routing in multicasting involves maintaining routes and finding new node locations in a group and is NP-complete due to the dynamic nature of the network. In this paper, a Hybrid Genetic Based Optimization for Multicast Routing algorithm is proposed. The proposed algorithm uses the best features of Genetic Algorithm (GA) and particle swarm optimization (PSO) to improve the solution. Simulations were conducted by varying number of mobile nodes and results compared with Multicast AODV (MAODV) protocol, PSO based and GA based solution. The proposed optimization improves jitter, end to end delay and Packet Delivery Ratio (PDR) with faster convergence.
Energy Technology Data Exchange (ETDEWEB)
Fingerhut, Benjamin Philipp
2011-02-08
One of the main challenges in photochemical energy conversion is the design of charge separating units which are able to generate a long lived charge separated state, and to couple efficiently to an energy storage state. In part I of this work the energy conversion efficiency of a photochemical unit inspired by bacterial photosynthesis is investigated. The developed model is based on non-adiabatic multi step electron transfer to generate a trans-membrane potential gradient. Upon optimization with multi objective genetic algorithms, the biological strategies for high quantum efficiency in photosynthetic reaction centers are derived, which have to suppress loss channels such as charge recombination. The concepts of bacterial photosynthesis are extended to the design of artificial photochemical devices. The unified model consists of a charge separation unit and an energy storing system whereby the coupling between both units is assured by thermal repopulation according to the principle of detailed balance. The complete photosynthetic unit is characterized by the respective current-voltage relation and an upper limit for the overall energy efficiency is derived under AM1.5 global conditions. Such a realistic chemical solar energy conversion system can reach efficiencies, which are comparable to the limits of an ideal single-junction solar cell. In Part II of this work the reactive dynamics of two surrounding controlled photoreactions is investigated on a microscopic scale. In general the effect of the surrounding can be classified into intramolecular contributions, like steric or electronic effects, and intermolecular contributions like the solvent or the embedding in an enzyme. Both limiting cases are examined on the basis of two generic photoreactions. The Dewar DNA lesion follows quantitatively from the 6-4 lesion by UV-A/B irradiation and constitutes the stable end product of continuous solar irradiation. Here the detailed mechanism of the formally 4{pi
DEFF Research Database (Denmark)
Qin, Nan; Bak, Claus Leth; Abildgaard, Hans
2017-01-01
cost and the generator reactive power output cost. The problem is formulated in a multi-stage optimal reactive power flow (MORPF) framework, solved by the nonlinear programming techniques via a rolling process. The voltage uncertainty caused by wind power forecasting errors is considered in the optimal......This paper proposes an automatic voltage control (AVC) system for power systems with limited continuous voltage control capability. The objective is to minimize the operational cost over a period, which consists of the power loss in the grid, the shunt switching cost, the transformer tap change...
Development and reactivity tests of Ce-Zr-based Claus catalysts for coal gas cleanup
Energy Technology Data Exchange (ETDEWEB)
No-Kuk Park; Dong Cheul Han; Gi Bo Han; Si Ok Ryu; Tae Jin Lee; Ki Jun Yoon [Yeungnam University, Gyeongbuk (Republic of Korea). National Research Laboratory, School of Chemical Engineering and Technology
2007-09-15
Claus reaction (2H{sub 2}S + SO{sub 2} {leftrightarrow} 3/nS{sub n} + 2H{sub 2}O) was used to clean the gasified coal gas and the reactivity of several metal oxide-based catalysts on Claus reaction was investigated at various operating conditions. In order to convert H{sub 2}S contained in the gasified coal gas to elemental sulfur during Claus reaction, the catalysts having the high activity under the highly reducing condition with the moisture should be developed. CeO{sub 2}, ZrO{sub 2}, and Ce{sub 1-x}Zr{sub x}O{sub 2} catalysts were prepared for Claus reaction and their reactivity changes due to the existence of the reducing gases and H{sub 2}O in the fuel gas was investigated in this study. The Ce-based catalysts shows that their activity was deteriorated by the reduction of the catalyst due to the reducing gases at higher than 220{sup o}C. Meanwhile, the effect of the reducing gases on the catalytic activity was not considerable at low temperature. The activities of all three catalysts were degraded on the condition that the moisture existed in the test gas. Specifically, the Ce-based catalysts were remarkably deactivated by their sulfation. The Ce-Zr-based catalyst had a high catalytic activity when the reducing gases and the moisture co-existed in the simulated fuel gas. The deactivation of the Ce-Zr-based catalyst was not observed in this study. The lattice oxygen of the Ce-based catalyst was used for the oxidation of H{sub 2}S and the lattice oxygen vacancy on the catalyst was contributed to the reduction of SO{sub 2}. ZrO{sub 2} added to the Ce-Zr-based catalyst improved the redox properties of the catalyst in Claus reaction by increasing the mobility of the lattice oxygen of CeO{sub 2}. 21 refs., 14 figs.
Survey on Power Optimization for Disk Based Systems
Directory of Open Access Journals (Sweden)
G. Ravikumar
2011-09-01
Full Text Available Energy optimization has become a growing concern in the present world. Energy optimization can influence the overall system design and reliability. Power can greatly influence the performance of the disk, as power dissipation generates heat that affects stability and reliability of the component, particularly for large server systems. Hence, developers concentrate on the configuration of disk arrays which can deliver extremely high performance. Though, there are several significant techniques for tackling disk power for laptops and workstations, using them in a server environment are a considerable challenge, especially under stringent performance needs. Excessive power consumption is a major barrier to the market acceptance of hard disks in mobile electronic devices. Studying and reducing power consumption, however, often comprises running time intensive disk traces on real hardware with specialized power-monitoring equipment. Most of the conventional energy optimization techniques are based on architectural level techniques and is found to be effective only in certain scenarios. This paper proposes a survey on the disk energy optimization techniques. This paper analyses the functionalities, advantages and the disadvantages of the various techniques for the disk power consumption.
Motion Structural Optimization Strategy for Rhombic Element Based Foldable Structure
Directory of Open Access Journals (Sweden)
Seung Hyun Jeong
2015-02-01
Full Text Available This research presents a new systematical design approach of foldable structure composed of several rhombic elements by applying genetic algorithm. As structural shapes represented by a foldable structure can be easily and dramatically morphed by manipulating rotational directions and angle of joints, the foldable structure has been used for various elementary structural members and engineering mechanisms. However a systematic design approach determining detail rotational angle and directions of unit cells for arbitrary shaped target areas has not been proposed yet. This research contributes to it by developing a new structural optimization method determining optimal angle and rotation directions to cover arbitrary shaped target areas of interest with aggregated rhombic elements. To achieve this purpose, we present an optimization formulation minimizing the sum of distances between each reference joint of an arbitrary shaped target area and its closest outer joints of foldable structure. To find out the outer joint set of a given foldable structure, an efficient geometric analysis method based on Delaunay triangulation is also developed and implemented. To show the validity and limitations of the present approach, several foldable structure design problems for two-dimensional arbitrary shaped target areas are solved with the present optimization procedure.
An Optimized Analogy-Based Project Effort Estimation
Directory of Open Access Journals (Sweden)
Mohammad Azzeh
2014-05-01
Full Text Available despite the predictive performance of Analogy-Based Estimation (ABE in generating better effort estimates, there is no consensus on: (1 how to predetermine the appropriate number of analogies, (2 which adjustment technique produces better estimates. Yet, there is no prior works attempted to optimize both number of analogies and feature distance weights for each test project. Perhaps rather than using fixed number, it is better to optimize this value for each project individually and then adjust the retrieved analogies by optimizing and approximating complex relationships between features and reflects that approximation on the final estimate. The Artificial Bees Algorithm is utilized to find, for each test project, the appropriate number of closest projects and features distance weights that is used to adjust those analogies’ efforts. The proposed technique has been applied and validated to 8 publically datasets from PROMISE repository. Results obtained show that: (1 the predictive performance of ABE has noticeably been improved, (2 the number of analogies was remarkably variable for each test project. While there are many techniques to adjust ABE, Using optimization algorithm provides two solutions in one technique and appeared useful for datasets with complex structure.
Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
LI Jimin; SHANG Chaoxuan; ZOU Minghu
2007-01-01
The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach.
Genetic Algorithm (GA)-Based Inclinometer Layout Optimization.
Liang, Weijie; Zhang, Ping; Chen, Xianping; Cai, Miao; Yang, Daoguo
2015-04-17
This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors.
Simulated Annealing-Based Krill Herd Algorithm for Global Optimization
Directory of Open Access Journals (Sweden)
Gai-Ge Wang
2013-01-01
Full Text Available Recently, Gandomi and Alavi proposed a novel swarm intelligent method, called krill herd (KH, for global optimization. To enhance the performance of the KH method, in this paper, a new improved meta-heuristic simulated annealing-based krill herd (SKH method is proposed for optimization tasks. A new krill selecting (KS operator is used to refine krill behavior when updating krill’s position so as to enhance its reliability and robustness dealing with optimization problems. The introduced KS operator involves greedy strategy and accepting few not-so-good solutions with a low probability originally used in simulated annealing (SA. In addition, a kind of elitism scheme is used to save the best individuals in the population in the process of the krill updating. The merits of these improvements are verified by fourteen standard benchmarking functions and experimental results show that, in most cases, the performance of this improved meta-heuristic SKH method is superior to, or at least highly competitive with, the standard KH and other optimization methods.
Cytochromes c': Structure, Reactivity and Relevance to Haem-Based Gas Sensing.
Hough, Michael A; Andrew, Colin R
2015-01-01
Cytochromes c' are a group of class IIa cytochromes with pentacoordinate haem centres and are found in photosynthetic, denitrifying and methanotrophic bacteria. Their function remains unclear, although roles in nitric oxide (NO) trafficking during denitrification or in cellular defence against nitrosoative stress have been proposed. Cytochromes c' are typically dimeric with each c-type haem-containing monomer folding as a four-α-helix bundle. Their hydrophobic and crowded distal sites impose severe restrictions on the binding of distal ligands, including diatomic gases. By contrast, NO binds to the proximal haem face in a similar manner to that of the eukaryotic NO sensor, soluble guanylate cyclase and bacterial analogues. In this review, we focus on how structural features of cytochromes c' influence haem spectroscopy and reactivity with NO, CO and O2. We also discuss the relevance of cytochrome c' to understanding the mechanisms of gas binding to haem-based sensor proteins.
Low-Loss Silica-Based Optical Film Waveguides Deposited by Helicon-Activated Reactive Evaporation
Bulla, Douglas A. P.; Li, Wei-Tang; Charles, Christine; Boswell, Rod; Ankiewicz, Adrian; Love, John D.
2005-03-01
Planar silica-based optical waveguides have been deposited by a plasma helicon-activated reactive evaporation system, at a low temperature and with reduced hydrogen contamination, on thermally oxidized silicon wafers. The transmission loss of the rib waveguides, formed on the deposited films by etching with hydrofluoric acid, is determined to be lower than 0.1 and 0.7 dB/cm at wavelengths of 1310 and 1510 nm, respectively, for TE polarization. The influence of substrate leakage on propagation loss is determined numerically and compared with experimental results for TE and TM polarizations. The presence of the OH vibrational overtone band in the fabricated waveguides, at a wavelength of around 1385 nm, is discussed in terms of the waveguide structure.
Cat swarm optimization based evolutionary framework for multi document summarization
Rautray, Rasmita; Balabantaray, Rakesh Chandra
2017-07-01
Today, World Wide Web has brought us enormous quantity of on-line information. As a result, extracting relevant information from massive data has become a challenging issue. In recent past text summarization is recognized as one of the solution to extract useful information from vast amount documents. Based on number of documents considered for summarization, it is categorized as single document or multi document summarization. Rather than single document, multi document summarization is more challenging for the researchers to find accurate summary from multiple documents. Hence in this study, a novel Cat Swarm Optimization (CSO) based multi document summarizer is proposed to address the problem of multi document summarization. The proposed CSO based model is also compared with two other nature inspired based summarizer such as Harmony Search (HS) based summarizer and Particle Swarm Optimization (PSO) based summarizer. With respect to the benchmark Document Understanding Conference (DUC) datasets, the performance of all algorithms are compared in terms of different evaluation metrics such as ROUGE score, F score, sensitivity, positive predicate value, summary accuracy, inter sentence similarity and readability metric to validate non-redundancy, cohesiveness and readability of the summary respectively. The experimental analysis clearly reveals that the proposed approach outperforms the other summarizers included in the study.
Directory of Open Access Journals (Sweden)
N. K. Khalid
2008-01-01
Full Text Available Problem statement: In DNA based computation and DNA nanotechnology, the design of good DNA sequences has turned out to be an essential problem and one of the most practical and important research topics. Basically, the DNA sequence design problem is a multi-objective problem and it can be evaluated using four objective functions, namely, Hmeasure, similarity, continuity and hairpin. Approach: There are several ways to solve multi-objective problem, however, in order to evaluate the correctness of PSO algorithm in DNA sequence design, this problem is converted into single objective problem. Particle Swarm Optimization (PSO is proposed to minimize the objective in the problem, subjected to two constraints: melting temperature and GCcontent. A model is developed to present the DNA sequence design based on PSO computation. Results: Based on experiments and researches done, 20 particles are used in the implementation of the optimization process, where the average values and the standard deviation for 100 runs are shown along with comparison to other existing methods. Conclusion: The results achieve verified that PSO can suitably solves the DNA sequence design problem using the proposed method and model, comparatively better than other approaches.
Directory of Open Access Journals (Sweden)
Firat Evirgen
2016-04-01
Full Text Available In this paper, a class of Nonlinear Programming problem is modeled with gradient based system of fractional order differential equations in Caputo's sense. To see the overlap between the equilibrium point of the fractional order dynamic system and theoptimal solution of the NLP problem in a longer timespan the Multistage Variational İteration Method isapplied. The comparisons among the multistage variational iteration method, the variationaliteration method and the fourth order Runge-Kutta method in fractional and integer order showthat fractional order model and techniques can be seen as an effective and reliable tool for finding optimal solutions of Nonlinear Programming problems.
Chaotic Teaching-Learning-Based Optimization with Lévy Flight for Global Numerical Optimization
Directory of Open Access Journals (Sweden)
Xiangzhu He
2016-01-01
Full Text Available Recently, teaching-learning-based optimization (TLBO, as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a novel metaheuristic has been developed in this paper, where particular characteristics of the chaos mechanism and Lévy flight are introduced to the basic framework of TLBO. The new algorithm is tested on several large-scale nonlinear benchmark functions with different characteristics and compared with other methods. Experimental results show that the proposed algorithm outperforms other algorithms and achieves a satisfactory improvement over TLBO.
Chaotic Teaching-Learning-Based Optimization with Lévy Flight for Global Numerical Optimization.
He, Xiangzhu; Huang, Jida; Rao, Yunqing; Gao, Liang
2016-01-01
Recently, teaching-learning-based optimization (TLBO), as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a novel metaheuristic has been developed in this paper, where particular characteristics of the chaos mechanism and Lévy flight are introduced to the basic framework of TLBO. The new algorithm is tested on several large-scale nonlinear benchmark functions with different characteristics and compared with other methods. Experimental results show that the proposed algorithm outperforms other algorithms and achieves a satisfactory improvement over TLBO.
Effects of reactive filters based on modified zeolite in dairy industry wastewater treatment process
Directory of Open Access Journals (Sweden)
Kolaković Srđan
2013-01-01
Full Text Available Application of adsorbents based on organo-zeolites has certain advantages over conventional methods applied in food industry wastewater treatment process. The case study presented in this paper examines the possibilities and effects of treatment of dairy industry wastewater by using adsorbents based on organo-zeolites. The obtained results indicate favorable filtration properties of organo-zeolite, their high level of adsorption of organic matter and nitrate nitrogen in the analyzed wastewater. This paper concludes with recommendations of optimal technical and technological parameters for the application of these filters in practice.
An Optimal Rubrics-Based Approach to Real Estate Appraisal
Directory of Open Access Journals (Sweden)
Zhangcheng Chen
2017-05-01
Full Text Available Traditional real estate appraisal methods obtain estimates of real estate by using mathematical modeling to analyze the existing sample data. However, the information of sample data sometimes cannot fully reflect the real-time quotes. For example, in a thin real estate market, the correlated sample data for estimated object is lacking, which limits the estimates of these traditional methods. In this paper, an optimal rubrics-based approach to real estate appraisal is proposed, which brings in crowdsourcing. The valuation estimate can serve as a market indication for the potential real estate buyers or sellers. It is not only based on the information of the existing sample data (just like these traditional methods, but also on the extra real-time market information from online crowdsourcing feedback, which makes the estimated result close to that of the market. The proposed method constructs the rubrics model from sample data. Based on this, the cosine similarity function is used to calculate the similarity between each rubric for selecting the optimal rubrics. The selected optimal rubrics and the estimated point are posted on a crowdsourcing platform. After comparing the information of the estimated point with the optimal rubrics on the crowdsourcing platform, those users who are connected with the estimated object complete the appraisal with their knowledge of the real estate market. The experiment results show that the average accuracy of the proposed approach is over 70%; the maximum accuracy is 90%. This supports that the proposed method can easily provide a valuable market reference for the potential real estate buyers or sellers, and is an attempt to use the human-computer interaction in the real estate appraisal field.
Attitude Optimal Backstepping Controller Based Quaternion for a UAV
Directory of Open Access Journals (Sweden)
Kaddouri Djamel
2016-01-01
Full Text Available A hierarchical controller design based on nonlinear H∞ theory and backstepping technique is developed for a nonlinear and coupled dynamic attitude system using conventional quaternion based method. The derived controller combines the attractive features of H∞ optimal controller and the advantages of the backstepping technique leading to a control law which avoids winding phenomena. Performance issues of the controller are illustrated in a simulation study made for a four-rotor vertical take-off and landing (VTOL aerial robot prototype known as the quadrotor aircraft.
Directory of Open Access Journals (Sweden)
N. Okada
2017-06-01
Full Text Available We focused on inductively coupled plasma and reactive ion etching (ICP–RIE for etching GaN and tried to fabricate distinctive GaN structures under optimized chemical etching conditions. To determine the optimum chemical etching conditions, the flow rates of Ar and Cl2, ICP power, and chamber pressure were varied in the etching of c-plane GaN layers with stripe patterns. It was determined that the combination of Ar and Cl2 flow rates of 100 sccm, chamber pressure of 7 Pa, and ICP power of 800 W resulted in the most enhanced reaction, yielding distinctive GaN structures such as pillars with inverted mesa structures for c-plane GaN and a semipolar GaN layer with asymmetric inclined sidewalls. The selectivity and etching rate were also investigated.
Okada, N.; Nojima, K.; Ishibashi, N.; Nagatoshi, K.; Itagaki, N.; Inomoto, R.; Motoyama, S.; Kobayashi, T.; Tadatomo, K.
2017-06-01
We focused on inductively coupled plasma and reactive ion etching (ICP-RIE) for etching GaN and tried to fabricate distinctive GaN structures under optimized chemical etching conditions. To determine the optimum chemical etching conditions, the flow rates of Ar and Cl2, ICP power, and chamber pressure were varied in the etching of c-plane GaN layers with stripe patterns. It was determined that the combination of Ar and Cl2 flow rates of 100 sccm, chamber pressure of 7 Pa, and ICP power of 800 W resulted in the most enhanced reaction, yielding distinctive GaN structures such as pillars with inverted mesa structures for c-plane GaN and a semipolar GaN layer with asymmetric inclined sidewalls. The selectivity and etching rate were also investigated.
农村变电站无功优化的控制策略%Optimal reactive power control strategies for rural substation
Institute of Scientific and Technical Information of China (English)
朴在林; 王慧
2013-01-01
农网改造以来农村变电站的无功电源合理补偿一直是被关注的热门课题。结合当前农村配电网无功潮流现状，提出变电站二次侧采样折合到一次侧功率因数，由二次侧控制电容器投切方式。基于主变压器二次侧功率因数和无功缺额，同时考虑主变的有功、无功损耗的基础上，采用最优补偿容量的方法在二次侧动态补偿，实现了最大负荷时主变压器一次侧功率因数达到0.95以上的考核标准，研究对农村配网无功电源的充分利用具有现实意义。%Reasonable reactive power sources compensation of rural substations has been becoming a hot issue since Chinese rural electric network alteration. The principal reactive power compensation mode of rural substations is still using fixed compensation capacitor to control voltage and reactive power at present in China. This compensation mode has some problems such as capacity adjustment requires manual intervention under power outage, the phenomenon of over and under compensation may always happen, the rate of putting into operation of reactive power compensation is relatively low, and so on. At the same time, there is no sampling function at the primary side of the main transformer because of the special devices in rural substations. In order to realize the objectives that the power factor is not less than 0.95 at primary side and not less than 0.9 at secondary side at the highest load, in this paper, some optimal reactive power control strategies for rural substation were proposed. In accordance with the reactive power flow conditions of the rural distribution network, the pros and cons of two control strategies were analyzed. One of the strategies was sampling at the primary side of the main transformer, the other was sampling at the secondary side and switching control by power factor of secondary side. After comparison of such analysis, an optimal control strategy was proposed. The
Energy Technology Data Exchange (ETDEWEB)
Cockeram, B.V.
1999-11-01
Hardfacing alloys are weld deposited on a base material to provide a wear resistant surface. Commercially available iron-base hardfacing alloys are being evaluated for replacement of cobalt-base alloys to reduce nuclear plant activation levels. Corrosion testing was used to evaluate the corrosion resistance of several iron-base hardfacing alloys in highly oxygenated environments. The corrosion test results indicate that iron-base hardfacing alloys in the as-deposited condition have acceptable corrosion resistance when the chromium to carbon ratio is greater than 4. Tristelle 5183, with a high niobium (stabilizer) content, did not follow this trend due to precipitation of niobium-rich carbides instead of chromium-rich carbides. This result indicates that iron-base hardfacing alloys containing high stabilizer contents may possess good corrosion resistance with Cr:C < 4. NOREM 02, NOREM 01, and NoCo-M2 hardfacing alloys had acceptable corrosion resistance in the as-deposited and 885 C/4 hour heat treated condition, but rusting from sensitization was observed in the 621 C/6 hour heat treated condition. The feasibility of using an Electrochemical Potentiokinetic Reactivation (EPR) test method, such as used for stainless steel, to detect sensitization in iron-base hardfacing alloys was evaluated. A single loop-EPR method was found to provide a more consistent measurement of sensitization than a double loop-EPR method. The high carbon content that is needed for a wear resistant hardfacing alloy produces a high volume fraction of chromium-rich carbides that are attacked during EPR testing. This results in inherently lower sensitivity for detection of a sensitized iron-base hardfacing alloy than stainless steel using conventional EPR test methods.
Van der Gucht, Katleen; Takano, Keisuke; Raes, Filip; Kuppens, Peter
2017-03-31
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.
Image-based modeling of flow and reactive transport in porous media
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
Stochastically optimized monocular vision-based navigation and guidance
Watanabe, Yoko
-effort guidance (MEG) law for multiple target tracking is applied for a guidance design to achieve the mission. Through simulations, it is shown that the control effort can be reduced by using the MEG-based guidance design instead of a conventional proportional navigation-based one. The navigation and guidance designs are implemented and evaluated in a 6 DoF UAV flight simulation. Furthermore, the vision-based obstacle avoidance system is also tested in a flight test using a balloon as an obstacle. For monocular vision-based control problems, it is well-known that the separation principle between estimation and control does not hold. In other words, that vision-based estimation performance highly depends on the relative motion of the vehicle with respect to the target. Therefore, this thesis aims to derive an optimal guidance law to achieve a given mission under the condition of using the EKF-based relative navigation. Unlike many other works on observer trajectory optimization, this thesis suggests a stochastically optimized guidance design that minimizes the expected value of a cost function of the guidance error and the control effort subject to the EKF prediction and update procedures. A suboptimal guidance law is derived based on an idea of the one-step-ahead (OSA) optimization, in which the optimization is performed under the assumption that there will be only one more final measurement at the one time step ahead. The OSA suboptimal guidance law is applied to problems of vision-based rendezvous and vision-based obstacle avoidance. Simulation results are presented to show that the suggested guidance law significantly improves the guidance performance. The OSA suboptimal optimization approach is generalized as the n-step-ahead (nSA) optimization for an arbitrary number of n. Furthermore, the nSA suboptimal guidance law is extended to the p %-ahead suboptimal guidance by changing the value of n at each time step depending on the current time. The nSA (including the OSA) and
RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE
Directory of Open Access Journals (Sweden)
Ming-Chang LEE
2015-07-01
Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets. The risk analysis and asset allocation are the key technology of banking and risk management. The aim of this paper, build a loan portfolio optimization model based on risk analysis. Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank. In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm. This paper solves the highly difficult problem by matrix operation method. Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space. It is easy calculation in proposed method.
Evaluating the Usability of Optimizing Text-based CAPTCHA Generation
Directory of Open Access Journals (Sweden)
Suliman A. Alsuhibany
2016-08-01
Full Text Available A CAPTCHA is a test that can, automatically, tell human and computer programs apart. It is a mechanism widely used nowadays for protecting web applications, interfaces, and services from malicious users and automated spammers. Usability and robustness are two fundamental aspects with CAPTCHA, where the usability aspect is the ease with which humans pass its challenges, while the robustness is the strength of its segmentation-resistance mechanism. The collapsing mechanism, which is removing the space between characters to prevent segmentation, has been shown to be reasonably resistant to known attacks. On the other hand, this mechanism drops considerably the human-solvability of text-based CAPTCHAs. Accordingly, an optimizer has previously been proposed that automatically enhances the usability of a CAPTCHA generation without sacrificing its robustness level. However, this optimizer has not yet been evaluated in terms of improving the usability. This paper, therefore, evaluates the usability of this optimizer by conducting an experimental study. The results of this evaluation showed that a statistically significant enhancement is found in the usability of text-based CAPTCHA generation.
Optimizing legacy molecular dynamics software with directive-based offload
Michael Brown, W.; Carrillo, Jan-Michael Y.; Gavhane, Nitin; Thakkar, Foram M.; Plimpton, Steven J.
2015-10-01
Directive-based programming models are one solution for exploiting many-core coprocessors to increase simulation rates in molecular dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In this paper, we describe modifications to the LAMMPS molecular dynamics code to enable concurrent calculations on a CPU and coprocessor. We demonstrate that standard molecular dynamics algorithms can run efficiently on both the CPU and an x86-based coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also result in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMPS benchmarks and for production molecular dynamics simulations using the Stampede hybrid supercomputer with both Intel® Xeon Phi™ coprocessors and NVIDIA GPUs. The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS.
Variance optimal sampling based estimation of subset sums
Cohen, Edith; Kaplan, Haim; Lund, Carsten; Thorup, Mikkel
2008-01-01
From a high volume stream of weighted items, we want to maintain a generic sample of a certain limited size $k$ that we can later use to estimate the total weight of arbitrary subsets. This is the classic context of on-line reservoir sampling, thinking of the generic sample as a reservoir. We present a reservoir sampling scheme providing variance optimal estimation of subset sums. More precisely, if we have seen $n$ items of the stream, then for any subset size $m$, our scheme based on $k$ samples minimizes the average variance over all subsets of size $m$. In fact, the optimality is against any off-line sampling scheme tailored for the concrete set of items seen: no off-line scheme based on $k$ samples can perform better than our on-line scheme when it comes to average variance over any subset size. Our scheme has no positive covariances between any pair of item estimates. Also, our scheme can handle each new item of the stream in $O(\\log k)$ time, which is optimal even on the word RAM.