Optimal load allocation of complex ship power plants

International Nuclear Information System (INIS)

Baldi, Francesco; Ahlgren, Fredrik; Melino, Francesco; Gabrielii, Cecilia; Andersson, Karin

2016-01-01

Highlights: • The optimal operation of the prime movers of hybrid ship power plants is addressed. • Both mechanical, electric and thermal power demand are considered. • The problem is modelled as a mixed integer-nonlinear programming problem. • Up to 3% savings can be achieved with hybrid power plants. • Including the thermal power demand improves the solution by up to 4%. - Abstract: In a world with increased pressure on reducing fuel consumption and carbon dioxide emissions, the cruise industry is growing in size and impact. In this context, further effort is required for improving the energy efficiency of cruise ship energy systems. In this paper, we propose a generic method for modelling the power plant of an isolated system with mechanical, electric and thermal power demands and for the optimal load allocation of the different components that are able to fulfil the demand. The optimisation problem is presented in the form of a mixed integer linear programming (MINLP) problem, where the number of engines and/or boilers running is represented by the integer variables, while their respective load is represented by the non-integer variables. The individual components are modelled using a combination of first-principle models and polynomial regressions, thus making the system nonlinear. The proposed method is applied to the load-allocation problem of a cruise ship sailing in the Baltic Sea, and used to compare the existing power plant with a hybrid propulsion plant. The results show the benefits brought by using the proposing method, which allow estimating the performance of the hybrid system (for which the load allocation is a non-trivial problem) while also including the contribution of the heat demand. This allows showing that, based on a reference round voyage, up to 3% savings could be achieved by installing the proposed system, compared to the existing one, and that a NPV of 11 kUSD could be achieved already 5 years after the installation of the

Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium

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Xiao Han

2017-12-01

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

GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

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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.

Simultaneous optimization of the cavity heat load and trip rates in linacs using a genetic algorithm

Directory of Open Access Journals (Sweden)

Balša Terzić

2014-10-01

Full Text Available In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab’s Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.

Solution quality improvement in chiller loading optimization

International Nuclear Information System (INIS)

Geem, Zong Woo

2011-01-01

In order to reduce greenhouse gas emission, we can energy-efficiently operate a multiple chiller system using optimization techniques. So far, various optimization techniques have been proposed to the optimal chiller loading problem. Most of those techniques are meta-heuristic algorithms such as genetic algorithm, simulated annealing, and particle swarm optimization. However, this study applied a gradient-based method, named generalized reduced gradient, and then obtains better results when compared with other approaches. When two additional approaches (hybridization between meta-heuristic algorithm and gradient-based algorithm; and reformulation of optimization structure by adding a binary variable which denotes chiller's operating status) were introduced, generalized reduced gradient found even better solutions. - Highlights: → Chiller loading problem is optimized by generalized reduced gradient (GRG) method. → Results are compared with meta-heuristic algorithms such as genetic algorithm. → Results are even enhanced by hybridizing meta-heuristic and gradient techniques. → Results are even enhanced by modifying the optimization formulation.

Study of load change control in PWRs using the methods of linear optimal control

International Nuclear Information System (INIS)

Yang, T.

1983-01-01

This thesis investigates the application of modern control theory to the problem of controlling load changes in PWR power plants. A linear optimal state feedback scheme resulting from linear optimal control theory with a quadratic cost function is reduced to a partially decentralized control system using mode preservation techniques. Minimum information transfer among major components of the plant is investigated to provide an adequate coordination, simple implementation, and a reliable control system. Two control approaches are proposed: servo and model following. Each design considers several information structures for performance comparison. Integrated output error has been included in the control systems to accommodate external and plant parameter disturbances. In addition, the cross limit feature, specific to certain modern reactor control systems, is considered in the study to prevent low pressure reactor trip conditions. An 11th order nonlinear model for the reactor and boiler is derived based on theoretical principles, and simulation tests are performed for 10% load change as an illustration of system performance

The effect of implementing cognitive load theory-based design principles in virtual reality simulation training of surgical skills: a randomized controlled trial.

Science.gov (United States)

Andersen, Steven Arild Wuyts; Mikkelsen, Peter Trier; Konge, Lars; Cayé-Thomasen, Per; Sørensen, Mads Sølvsten

2016-01-01

Cognitive overload can inhibit learning, and cognitive load theory-based instructional design principles can be used to optimize learning situations. This study aims to investigate the effect of implementing cognitive load theory-based design principles in virtual reality simulation training of mastoidectomy. Eighteen novice medical students received 1 h of self-directed virtual reality simulation training of the mastoidectomy procedure randomized for standard instructions (control) or cognitive load theory-based instructions with a worked example followed by a problem completion exercise (intervention). Participants then completed two post-training virtual procedures for assessment and comparison. Cognitive load during the post-training procedures was estimated by reaction time testing on an integrated secondary task. Final-product analysis by two blinded expert raters was used to assess the virtual mastoidectomy performances. Participants in the intervention group had a significantly increased cognitive load during the post-training procedures compared with the control group (52 vs. 41 %, p  = 0.02). This was also reflected in the final-product performance: the intervention group had a significantly lower final-product score than the control group (13.0 vs. 15.4, p  virtual reality surgical simulation training of novices.

Numerical optimization of composite hip endoprostheses under different loading conditions

Science.gov (United States)

Blake, T. A.; Davy, D. T.; Saravanos, D. A.; Hopkins, D. A.

1992-01-01

The optimization of composite hip implants was investigated. Emphasis was placed on the effect of shape and material tailoring of the implant to improve the implant-bone interaction. A variety of loading conditions were investigated to better understand the relationship between loading and optimization outcome. Comparisons of the initial and optimal models with more complex 3D finite element models were performed. The results indicate that design improvements made using this method result in similar improvements in the 3D models. Although the optimization outcomes were significantly affected by the choice of loading conditions, certain trends were observed that were independent of the applied loading.

A novel approach for optimal chiller loading using particle swarm optimization

Energy Technology Data Exchange (ETDEWEB)

Ardakani, A. Jahanbani; Ardakani, F. Fattahi; Hosseinian, S.H. [Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Avenue, Tehran 15875-4413 (Iran, Islamic Republic of)

2008-07-01

This study employs two new methods to solve optimal chiller loading (OCL) problem. These methods are continuous genetic algorithm (GA) and particle swarm optimization (PSO). Because of continuous nature of variables in OCL problem, continuous GA and PSO easily overcome deficiencies in other conventional optimization methods. Partial load ratio (PLR) of the chiller is chosen as the variable to be optimized and consumption power of the chiller is considered as fitness function. Both of these methods find the optimal solution while the equality constraint is exactly satisfied. Some of the major advantages of proposed approaches over other conventional methods can be mentioned as fast convergence, escaping from getting into local optima, simple implementation as well as independency of the solution from the problem. Abilities of proposed methods are examined with reference to an example system. To demonstrate these abilities, results are compared with binary genetic algorithm method. The proposed approaches can be perfectly applied to air-conditioning systems. (author)

First-principle optimal local pseudopotentials construction via optimized effective potential method

International Nuclear Information System (INIS)

Mi, Wenhui; Zhang, Shoutao; Wang, Yanchao; Ma, Yanming; Miao, Maosheng

2016-01-01

The local pseudopotential (LPP) is an important component of orbital-free density functional theory, a promising large-scale simulation method that can maintain information on a material’s electron state. The LPP is usually extracted from solid-state density functional theory calculations, thereby it is difficult to assess its transferability to cases involving very different chemical environments. Here, we reveal a fundamental relation between the first-principles norm-conserving pseudopotential (NCPP) and the LPP. On the basis of this relationship, we demonstrate that the LPP can be constructed optimally from the NCPP for a large number of elements using the optimized effective potential method. Specially, our method provides a unified scheme for constructing and assessing the LPP within the framework of first-principles pseudopotentials. Our practice reveals that the existence of a valid LPP with high transferability may strongly depend on the element.

An implementation of particle swarm optimization to evaluate optimal under-voltage load shedding in competitive electricity markets

Science.gov (United States)

Hosseini-Bioki, M. M.; Rashidinejad, M.; Abdollahi, A.

2013-11-01

Load shedding is a crucial issue in power systems especially under restructured electricity environment. Market-driven load shedding in reregulated power systems associated with security as well as reliability is investigated in this paper. A technoeconomic multi-objective function is introduced to reveal an optimal load shedding scheme considering maximum social welfare. The proposed optimization problem includes maximum GENCOs and loads' profits as well as maximum loadability limit under normal and contingency conditions. Particle swarm optimization (PSO) as a heuristic optimization technique, is utilized to find an optimal load shedding scheme. In a market-driven structure, generators offer their bidding blocks while the dispatchable loads will bid their price-responsive demands. An independent system operator (ISO) derives a market clearing price (MCP) while rescheduling the amount of generating power in both pre-contingency and post-contingency conditions. The proposed methodology is developed on a 3-bus system and then is applied to a modified IEEE 30-bus test system. The obtained results show the effectiveness of the proposed methodology in implementing the optimal load shedding satisfying social welfare by maintaining voltage stability margin (VSM) through technoeconomic analyses.

Loading pattern optimization using ant colony algorithm

International Nuclear Information System (INIS)

Hoareau, Fabrice

2008-01-01

Electricite de France (EDF) operates 58 nuclear power plants (NPP), of the Pressurized Water Reactor type. The loading pattern optimization of these NPP is currently done by EDF expert engineers. Within this framework, EDF R and D has developed automatic optimization tools that assist the experts. LOOP is an industrial tool, developed by EDF R and D and based on a simulated annealing algorithm. In order to improve the results of such automatic tools, new optimization methods have to be tested. Ant Colony Optimization (ACO) algorithms are recent methods that have given very good results on combinatorial optimization problems. In order to evaluate the performance of such methods on loading pattern optimization, direct comparisons between LOOP and a mock-up based on the Max-Min Ant System algorithm (a particular variant of ACO algorithms) were made on realistic test-cases. It is shown that the results obtained by the ACO mock-up are very similar to those of LOOP. Future research will consist in improving these encouraging results by using parallelization and by hybridizing the ACO algorithm with local search procedures. (author)

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

Science.gov (United States)

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

2009-05-01

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

Application of the distributed genetic algorithm for loading pattern optimization problems

International Nuclear Information System (INIS)

Hashimoto, Hiroshi; Yamamoto, Akio

2000-01-01

The distributed genetic algorithm (DGA) is applied for loading pattern optimization problems of the pressurized water reactors (PWR). Due to stiff nature of the loading pattern optimizations (e.g. multi-modality and non-linearity), stochastic methods like the simulated annealing or the genetic algorithm (GA) are widely applied for these problems. A basic concept of DGA is based on that of GA. However, DGA equally distributes candidates of solutions (i.e. loading patterns) to several independent 'islands' and evolves them in each island. Migrations of some candidates are performed among islands with a certain period. Since candidates of solutions independently evolve in each island with accepting different genes of migrants from other islands, premature convergence in the traditional GA can be prevented. Because many candidate loading patterns should be evaluated in one generation of GA or DGA, the parallelization in these calculations works efficiently. Parallel efficiency was measured using our optimization code and good load balance was attained even in a heterogeneous cluster environment due to dynamic distribution of the calculation load. The optimization code is based on the client/server architecture with the TCP/IP native socket and a client (optimization module) and calculation server modules communicate the objects of loading patterns each other. Throughout the sensitivity study on optimization parameters of DGA, a suitable set of the parameters for a test problem was identified. Finally, optimization capability of DGA and the traditional GA was compared in the test problem and DGA provided better optimization results than the traditional GA. (author)

Optimization of cryoprotectant loading into murine and human oocytes.

Science.gov (United States)

Karlsson, Jens O M; Szurek, Edyta A; Higgins, Adam Z; Lee, Sang R; Eroglu, Ali

2014-02-01

Loading of cryoprotectants into oocytes is an important step of the cryopreservation process, in which the cells are exposed to potentially damaging osmotic stresses and chemical toxicity. Thus, we investigated the use of physics-based mathematical optimization to guide design of cryoprotectant loading methods for mouse and human oocytes. We first examined loading of 1.5 M dimethyl sulfoxide (Me(2)SO) into mouse oocytes at 23°C. Conventional one-step loading resulted in rates of fertilization (34%) and embryonic development (60%) that were significantly lower than those of untreated controls (95% and 94%, respectively). In contrast, the mathematically optimized two-step method yielded much higher rates of fertilization (85%) and development (87%). To examine the causes for oocyte damage, we performed experiments to separate the effects of cell shrinkage and Me(2)SO exposure time, revealing that neither shrinkage nor Me(2)SO exposure single-handedly impairs the fertilization and development rates. Thus, damage during one-step Me(2)SO addition appears to result from interactions between the effects of Me(2)SO toxicity and osmotic stress. We also investigated Me(2)SO loading into mouse oocytes at 30°C. At this temperature, fertilization rates were again lower after one-step loading (8%) in comparison to mathematically optimized two-step loading (86%) and untreated controls (96%). Furthermore, our computer algorithm generated an effective strategy for reducing Me(2)SO exposure time, using hypotonic diluents for cryoprotectant solutions. With this technique, 1.5 M Me(2)SO was successfully loaded in only 2.5 min, with 92% fertilizability. Based on these promising results, we propose new methods to load cryoprotectants into human oocytes, designed using our mathematical optimization approach. Copyright © 2013 Elsevier Inc. All rights reserved.

Integrated resource planning-concepts and principles

Energy Technology Data Exchange (ETDEWEB)

Atkinson, S.

1994-12-31

The concepts and principles of integrated resource planning (IRP) are outlined. The following topics are discussed: utility opportunities and methodologies, application considerations, ambitious energy-efficient programs, the future of IRP, three methods to study resource alternatives, the load adjustment method, simultaneous optimization, static analysis, utility profile data, load forecasts and shapes, load data, conversion, variable costs, external analysis, internal analysis, DSM objectives, supply-side prescreening, DSM screening analysis, DSM evaluation, the IRP process, risk analysis, collaborative planning process, and load shape objectives.

Research on the parallel load sharing principle of a novel self-decoupled piezoelectric six-dimensional force sensor.

Science.gov (United States)

Li, Ying-Jun; Yang, Cong; Wang, Gui-Cong; Zhang, Hui; Cui, Huan-Yong; Zhang, Yong-Liang

2017-09-01

This paper presents a novel integrated piezoelectric six-dimensional force sensor which can realize dynamic measurement of multi-dimensional space load. Firstly, the composition of the sensor, the spatial layout of force-sensitive components, and measurement principle are analyzed and designed. There is no interference of piezoelectric six-dimensional force sensor in theoretical analysis. Based on the principle of actual work and deformation compatibility coherence, this paper deduces the parallel load sharing principle of the piezoelectric six-dimensional force sensor. The main effect factors which affect the load sharing ratio are obtained. The finite element model of the piezoelectric six-dimensional force sensor is established. In order to verify the load sharing principle of the sensor, a load sharing test device of piezoelectric force sensor is designed and fabricated. The load sharing experimental platform is set up. The experimental results are in accordance with the theoretical analysis and simulation results. The experiments show that the multi-dimensional and heavy force measurement can be realized by the parallel arrangement of the load sharing ring and the force sensitive element in the novel integrated piezoelectric six-dimensional force sensor. The ideal load sharing effect of the sensor can be achieved by appropriate size parameters. This paper has an important guide for the design of the force measuring device according to the load sharing mode. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal decisions principles of programming

CERN Document Server

Lange, Oskar

1971-01-01

Optimal Decisions: Principles of Programming deals with all important problems related to programming.This book provides a general interpretation of the theory of programming based on the application of the Lagrange multipliers, followed by a presentation of the marginal and linear programming as special cases of this general theory. The praxeological interpretation of the method of Lagrange multipliers is also discussed.This text covers the Koopmans' model of transportation, geometric interpretation of the programming problem, and nature of activity analysis. The solution of t

Loading pattern optimization by multi-objective simulated annealing with screening technique

International Nuclear Information System (INIS)

Tong, K. P.; Hyun, C. L.; Hyung, K. J.; Chang, H. K.

2006-01-01

This paper presents a new multi-objective function which is made up of the main objective term as well as penalty terms related to the constraints. All the terms are represented in the same functional form and the coefficient of each term is normalized so that each term has equal weighting in the subsequent simulated annealing optimization calculations. The screening technique introduced in the previous work is also adopted in order to save computer time in 3-D neutronics evaluation of trial loading patterns. For numerical test of the new multi-objective function in the loading pattern optimization, the optimum loading patterns for the initial and the cycle 7 reload PWR core of Yonggwang Unit 4 are calculated by the simulated annealing algorithm with screening technique. A total of 10 optimum loading patterns are obtained for the initial core through 10 independent simulated annealing optimization runs. For the cycle 7 reload core one optimum loading pattern has been obtained from a single simulated annealing optimization run. More SA optimization runs will be conducted to optimum loading patterns for the cycle 7 reload core and results will be presented in the further work. (authors)

Optimal quantum state estimation with use of the no-signaling principle

International Nuclear Information System (INIS)

Han, Yeong-Deok; Bae, Joonwoo; Wang Xiangbin; Hwang, Won-Young

2010-01-01

A simple derivation of the optimal state estimation of a quantum bit was obtained by using the no-signaling principle. In particular, the no-signaling principle determines a unique form of the guessing probability independent of figures of merit, such as the fidelity or information gain. This proves that the optimal estimation for a quantum bit can be achieved by the same measurement for almost all figures of merit.

Optimal Load Control via Frequency Measurement and Neighborhood Area Communication

Energy Technology Data Exchange (ETDEWEB)

Zhao, CH; Topcu, U; Low, SH

2013-11-01

We propose a decentralized optimal load control scheme that provides contingency reserve in the presence of sudden generation drop. The scheme takes advantage of flexibility of frequency responsive loads and neighborhood area communication to solve an optimal load control problem that balances load and generation while minimizing end-use disutility of participating in load control. Local frequency measurements enable individual loads to estimate the total mismatch between load and generation. Neighborhood area communication helps mitigate effects of inconsistencies in the local estimates due to frequency measurement noise. Case studies show that the proposed scheme can balance load with generation and restore the frequency within seconds of time after a generation drop, even when the loads use a highly simplified power system model in their algorithms. We also investigate tradeoffs between the amount of communication and the performance of the proposed scheme through simulation-based experiments.

Load Sharing Multiobjective Optimization Design of a Split Torque Helicopter Transmission

Directory of Open Access Journals (Sweden)

Chenxi Fu

2015-01-01

Full Text Available Split torque designs can offer significant advantages over the traditional planetary designs for helicopter transmissions. However, it has two unique properties, gap and phase differences, which result in the risk of unequal load sharing. Various methods have been proposed to eliminate the effect of gap and promote load sharing to a certain extent. In this paper, system design parameters will be optimized to change the phase difference, thereby further improving load sharing. A nonlinear dynamic model is established to measure the load sharing with dynamic mesh forces quantitatively. Afterwards, a multiobjective optimization of a reference split torque design is conducted with the promoting of load sharing property, lightweight, and safety considered as the objectives. The load sharing property, which is measured by load sharing coefficient, is evaluated under multiple operating conditions with dynamic analysis method. To solve the multiobjective model with NSGA-II, an improvement is done to overcome the problem of time consuming. Finally, a satisfied optimal solution is picked up as the final design from the Pareto optimal front, which achieves improvements in all the three objectives compared with the reference design.

Genetic algorithms in loading pattern optimization

International Nuclear Information System (INIS)

Yilmazbayhan, A.; Tombakoglu, M.; Bekar, K. B.; Erdemli, A. Oe

2001-01-01

Genetic Algorithm (GA) based systems are used for the loading pattern optimization. The use of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection of initial population size for PWRs are discussed. Antithetic variates are used to generate the initial population. The performance of GA with antithetic variates is compared to traditional GA. The results of multi-cycle optimization are discussed for objective function taking into account cycle burn-up and discharge burn-up

An overview of optimization of structures subjected to transient loads

International Nuclear Information System (INIS)

Kang, Byung Soo; Park, Gyung Jin

2005-01-01

Various aspects of structural optimization techniques under transient loads are extensively reviewed. The main themes of the paper are treatment of time dependent constraints, calculation of design sensitivity, and approximation. Each subject is reviewed with the corresponding papers that have been published since 1970s. The treatment of time dependent constraints in both the direct method and the transformation method is discussed. Two ways of calculating design sensitivity of a structure under transient loads are discussed-direct differentiation method and adjoint variable method. The approximation concept mainly focuses on response surface method in crashworthiness and local approximation with the intermediate variable. Especially, as an approximated optimization technique, equivalent static load method which takes advantage of the well-established static response optimization technique is introduced. And as an application area of dynamic response optimization technique, the structural optimization in flexible multibody dynamic system is reviewed in the viewpoint of the above three themes

Performance evaluation of Genetic Algorithms on loading pattern optimization of PWRs

International Nuclear Information System (INIS)

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

2001-01-01

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

Characteristic statistic algorithm (CSA) for in-core loading pattern optimization

International Nuclear Information System (INIS)

Liu Zhihong; Hu Yongming; Shi Gong

2007-01-01

To solve the problem of PWR in-core loading pattern optimization, a more suitable global optimization algorithm, i.e., Characteristic statistic algorithm (CSA), is used. The searching process of this algorithm and how to apply it to this problem are presented. Loading pattern optimization code SCYCLE is developed. Two different problems on real PWR models are calculated and the results are compared with other algorithms. It is shown that SCYCLE has high efficiency and good global performance on this problem. (authors)

Fuzzy Simulation-Optimization Model for Waste Load Allocation

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Motahhare Saadatpour

2006-01-01

Full Text Available This paper present simulation-optimization models for waste load allocation from multiple point sources which include uncertainty due to vagueness of the parameters and goals. This model employs fuzzy sets with appropriate membership functions to deal with uncertainties due to vagueness. The fuzzy waste load allocation model (FWLAM incorporate QUAL2E as a water quality simulation model and Genetic Algorithm (GA as an optimization tool to find the optimal combination of the fraction removal level to the dischargers and pollution control agency (PCA. Penalty functions are employed to control the violations in the system.  The results demonstrate that the goal of PCA to achieve the best water quality and the goal of the dischargers to use the full assimilative capacity of the river have not been satisfied completely and a compromise solution between these goals is provided. This fuzzy optimization model with genetic algorithm has been used for a hypothetical problem. Results demonstrate a very suitable convergence of proposed optimization algorithm to the global optima.

Role of optimization criterion in static asymmetric analysis of lumbar spine load.

Science.gov (United States)

Daniel, Matej

2011-10-01

A common method for load estimation in biomechanics is the inverse dynamics optimization, where the muscle activation pattern is found by minimizing or maximizing the optimization criterion. It has been shown that various optimization criteria predict remarkably similar muscle activation pattern and intra-articular contact forces during leg motion. The aim of this paper is to study the effect of the choice of optimization criterion on L4/L5 loading during static asymmetric loading. Upright standing with weight in one stretched arm was taken as a representative position. Musculoskeletal model of lumbar spine model was created from CT images of Visible Human Project. Several criteria were tested based on the minimization of muscle forces, muscle stresses, and spinal load. All criteria provide the same level of lumbar spine loading (difference is below 25%), except the criterion of minimum lumbar shear force which predicts unrealistically high spinal load and should not be considered further. Estimated spinal load and predicted muscle force activation pattern are in accordance with the intradiscal pressure measurements and EMG measurements. The L4/L5 spine loads 1312 N, 1674 N, and 1993 N were predicted for mass of weight in hand 2, 5, and 8 kg, respectively using criterion of mininum muscle stress cubed. As the optimization criteria do not considerably affect the spinal load, their choice is not critical in further clinical or ergonomic studies and computationally simpler criterion can be used.

Design principles and operating principles: the yin and yang of optimal functioning.

Science.gov (United States)

Voit, Eberhard O

2003-03-01

Metabolic engineering has as a goal the improvement of yield of desired products from microorganisms and cell lines. This goal has traditionally been approached with experimental biotechnological methods, but it is becoming increasingly popular to precede the experimental phase by a mathematical modeling step that allows objective pre-screening of possible improvement strategies. The models are either linear and represent the stoichiometry and flux distribution in pathways or they are non-linear and account for the full kinetic behavior of the pathway, which is often significantly effected by regulatory signals. Linear flux analysis is simpler and requires less input information than a full kinetic analysis, and the question arises whether the consideration of non-linearities is really necessary for devising optimal strategies for yield improvements. The article analyzes this question with a generic, representative pathway. It shows that flux split ratios, which are the key criterion for linear flux analysis, are essentially sufficient for unregulated, but not for regulated branch points. The interrelationships between regulatory design on one hand and optimal patterns of operation on the other suggest the investigation of operating principles that complement design principles, like a user's manual complements the hardwiring of electronic equipment.

Optimization of structures subjected to dynamic load: deterministic and probabilistic methods

Directory of Open Access Journals (Sweden)

Élcio Cassimiro Alves

Full Text Available Abstract This paper deals with the deterministic and probabilistic optimization of structures against bending when submitted to dynamic loads. The deterministic optimization problem considers the plate submitted to a time varying load while the probabilistic one takes into account a random loading defined by a power spectral density function. The correlation between the two problems is made by one Fourier Transformed. The finite element method is used to model the structures. The sensitivity analysis is performed through the analytical method and the optimization problem is dealt with by the method of interior points. A comparison between the deterministic optimisation and the probabilistic one with a power spectral density function compatible with the time varying load shows very good results.

An Optimization Framework for Load and Power Distribution in Wind Farms

DEFF Research Database (Denmark)

Soleimanzadeh, Maryam; Wisniewski, Rafal; Kanev, Stoyan

2012-01-01

The aim of this paper is to develop a controller for wind farms to optimize the load and power distribution. In this regard, the farm controller calculates the power reference signals for individual wind turbine controllers such that the sum of the power references tracks the power demanded...... by a system operator. Moreover, the reference signals are determined to reduce the load acting on wind turbines at low frequencies. Therefore, a trade-off is made for load and power control, which is formulated as an optimization problem. Afterwards, the optimization problem for the wind farm modeled...

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Experiment Development

Science.gov (United States)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads. The subject of this paper is the design of the optimal control architecture, and provides the reader with some techniques for tailoring the architecture, along with detailed simulation results.

Multi-objective optimization of an arch dam shape under static loads using an evolutionary game method

Science.gov (United States)

Meng, Rui; Cheong, Kang Hao; Bao, Wei; Wong, Kelvin Kian Loong; Wang, Lu; Xie, Neng-gang

2018-06-01

This article attempts to evaluate the safety and economic performance of an arch dam under the action of static loads. The geometric description of a crown cantilever section and the horizontal arch ring is presented. A three-objective optimization model of arch dam shape is established based on the arch dam volume, maximum principal tensile stress and total strain energy. The evolutionary game method is then applied to obtain the optimal solution. In the evolutionary game technique, a novel and more efficient exploration method of the game players' strategy space, named the 'sorting partition method under the threshold limit', is presented, with the game profit functions constructed according to both competitive and cooperative behaviour. By way of example, three optimization goals have all shown improvements over the initial solutions. In particular, the evolutionary game method has potentially faster convergence. This demonstrates the preliminary proof of principle of the evolutionary game method.

Optimal loading and protection of multi-state systems considering performance sharing mechanism

International Nuclear Information System (INIS)

Xiao, Hui; Shi, Daimin; Ding, Yi; Peng, Rui

2016-01-01

Engineering systems are designed to carry the load. The performance of the system largely depends on how much load it carries. On the other hand, the failure rate of the system is strongly affected by its load. Besides internal failures, such as fatigue and aging process, systems may also fail due to external impacts such as nature disasters and terrorism. In this paper, we integrate the effect of loading and protection of external impacts on multi-state systems with performance sharing mechanism. The objective of this research is to determine how to balance the load and protection on system elements. An availability evaluation algorithm of the proposed system is suggested and the corresponding optimization problem is solved utilizing genetic algorithms. - Highlights: • Performance sharing of multi-state systems is considered. • The effect of load on system elements is analyzed. • Joint optimization model of element loading and protection is formulated. • Genetic Algorithms are adapted to solve the reliability optimization problem.

Deterministic methods for multi-control fuel loading optimization

Science.gov (United States)

Rahman, Fariz B. Abdul

We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.

On the equivalent static loads approach for dynamic response structural optimization

DEFF Research Database (Denmark)

Stolpe, Mathias

2014-01-01

The equivalent static loads algorithm is an increasingly popular approach to solve dynamic response structural optimization problems. The algorithm is based on solving a sequence of related static response structural optimization problems with the same objective and constraint functions...... as the original problem. The optimization theoretical foundation of the algorithm is mainly developed in Park and Kang (J Optim Theory Appl 118(1):191–200, 2003). In that article it is shown, for a certain class of problems, that if the equivalent static loads algorithm terminates then the KKT conditions...

Loaded Gelled Bipropellants for Optimized Performance, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The focus of this program is the development and validation of formulations, and development methodologies, for optimizing high-performance particulate-loaded...

Comparison of optimization of loading patterns on the basis of SA and PMA algorithms

International Nuclear Information System (INIS)

Beliczai, Botond

2007-01-01

Optimization of loading patterns is a very important task from economical point of view in a nuclear power plant. The optimization algorithms used for this purpose can be categorized basically into two categories: deterministic ones and stochastic ones. In the Paks nuclear power plant a deterministic optimization procedure is used to optimize the loading pattern at BOC, so that the core would have maximal reactivity reserve. To the group of stochastic optimization procedures belong mainly simulated annealing (SA) procedures and genetic algorithms (GA). There are new procedures as well, which try to combine the advantages of SAs and GAs. One of them is called population mutation annealing algorithm (PMA). In the Paks NPP we would like to introduce fuel assemblies including burnable poison (Gd) in the near future. In order to be able to find the optimal loading pattern (or near-optimal loading patterns) in that case, we have to optimize our core not only for objective functions defined at BOC, but at EOC as well. For this purpose I used stochastic algorithms (SA and PMA) to investigate loading pattern optimization results for different objective functions at BOC. (author)

Wind load modeling for topology optimization of continuum structures

NARCIS (Netherlands)

Zakhama, R.; Abdalla, M.M.; Gürdal, Z.; Smaoui, H.

2010-01-01

Topology optimization of two and three dimensional structures subject to dead and wind loading is considered. The wind loading is introduced into the formulation by using standard expressions for the drag force, and a strategy is devised so that wind pressure is ignored where there is no surface

Optimal control of load-following operations in a pressurized water reactor

International Nuclear Information System (INIS)

Zhao Fuyu; Zhou Dawei

2000-01-01

According to the optimal control theory, the problem of load-following operation in a pressurized water reactor is formulated as a nonlinear-quadratic optimal control problem. One-dimensional core model is adopted. A successful optimization algorithm DDPSR is proposed to solving the obtained problem. The research results show that the DDPSR can converge with a long time interval and needs very small iteration number and computing time, and the practical reactor can be fairly operated in an optimal load-following manner and axial offset satisfies the required value from beginning to end. Control characters of boron concentration are discussed specially

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

International Nuclear Information System (INIS)

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

2003-01-01

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

Loading pattern optimization in hexagonal geometry using PANTHER

International Nuclear Information System (INIS)

Parks, G.T.; Knight, M.P.

1996-01-01

The extension of the loading pattern optimization capability of Nuclear Electric's reactor physics code PANTHER to hexagonal geometry cores is described. The variety of search methods available and the code's performance are illustrated by an example in which three search different methods are used in turn in order to find an optimal reload design for a sample hexagonal geometry problem. (author)

Optimization Formulations for the Maximum Nonlinear Buckling Load of Composite Structures

DEFF Research Database (Denmark)

Lindgaard, Esben; Lund, Erik

2011-01-01

This paper focuses on criterion functions for gradient based optimization of the buckling load of laminated composite structures considering different types of buckling behaviour. A local criterion is developed, and is, together with a range of local and global criterion functions from literature......, benchmarked on a number of numerical examples of laminated composite structures for the maximization of the buckling load considering fiber angle design variables. The optimization formulations are based on either linear or geometrically nonlinear analysis and formulated as mathematical programming problems...... solved using gradient based techniques. The developed local criterion is formulated such it captures nonlinear effects upon loading and proves useful for both analysis purposes and as a criterion for use in nonlinear buckling optimization. © 2010 Springer-Verlag....

An Optimized Control for LLC Resonant Converter with Wide Load Range

Science.gov (United States)

Xi, Xia; Qian, Qinsong

2017-05-01

This paper presents an optimized control which makes LLC resonant converters operate with a wider load range and provides good closed-loop performance. The proposed control employs two paralleled digital compensations to guarantee the good closed-loop performance in a wide load range during the steady state, an optimized trajectory control will take over to change the gate-driving signals immediately at the load transients. Finally, the proposed control has been implemented and tested on a 150W 200kHz 400V/24V LLC resonant converter and the result validates the proposed method.

Optimization at different loads by minimization of irreversibilities

International Nuclear Information System (INIS)

Wong, K.F.V.; Niu, Z.

1991-01-01

This paper reports that the irreversibility of the power cycle was chosen as the objective function as this function can successfully measure both the quality and quantity of energy flow in the cycle. Minimization of the irreversibility ensures that the power cycle will operate more efficiently. One feature of the present work is that the boiler, turbine, condenser and heaters are treated as one system for the purpose of optimization. In the optimization model, nine regression formulae are used, which are obtained from the measured test data. From the results of the present work, it can be seen that the optimization model developed can represent the effect of operational parameters on the power plant first and second law efficiency. Some of the results can be used to provide guidance for the optimal operation of the power plant. When the power cycle works at full load, the main steam temperature and pressure should be at the upper limit for minimal irreversibility of the system. If the load is less than 65% of its design capacity, the steam temperature and pressure should be decreased for a lower irreversibility of the system

Improving the Quality of Online Discussion: The Effects of Strategies Designed Based on Cognitive Load Theory Principles

Science.gov (United States)

Darabi, Aubteen; Jin, Li

2013-01-01

This article focuses on heavy cognitive load as the reason for the lack of quality associated with conventional online discussion. Using the principles of cognitive load theory, four online discussion strategies were designed specifically aiming at reducing the discussants' cognitive load and thus enhancing the quality of their online discussion.…

Optimal Control of Polymer Flooding Based on Maximum Principle

Directory of Open Access Journals (Sweden)

Yang Lei

2012-01-01

Full Text Available Polymer flooding is one of the most important technologies for enhanced oil recovery (EOR. In this paper, an optimal control model of distributed parameter systems (DPSs for polymer injection strategies is established, which involves the performance index as maximum of the profit, the governing equations as the fluid flow equations of polymer flooding, and the inequality constraint as the polymer concentration limitation. To cope with the optimal control problem (OCP of this DPS, the necessary conditions for optimality are obtained through application of the calculus of variations and Pontryagin’s weak maximum principle. A gradient method is proposed for the computation of optimal injection strategies. The numerical results of an example illustrate the effectiveness of the proposed method.

Reduced design load basis for ultimate blade loads estimation in multidisciplinary design optimization frameworks

DEFF Research Database (Denmark)

Pavese, Christian; Tibaldi, Carlo; Larsen, Torben J.

2016-01-01

The aim is to provide a fast and reliable approach to estimate ultimate blade loads for a multidisciplinary design optimization (MDO) framework. For blade design purposes, the standards require a large amount of computationally expensive simulations, which cannot be efficiently run each cost...... function evaluation of an MDO process. This work describes a method that allows integrating the calculation of the blade load envelopes inside an MDO loop. Ultimate blade load envelopes are calculated for a baseline design and a design obtained after an iteration of an MDO. These envelopes are computed...... for a full standard design load basis (DLB) and a deterministic reduced DLB. Ultimate loads extracted from the two DLBs with the two blade designs each are compared and analyzed. Although the reduced DLB supplies ultimate loads of different magnitude, the shape of the estimated envelopes are similar...

Optimization of refueling loading pattern of uranium zirconium hydride research reactor

International Nuclear Information System (INIS)

Chen Wei; Xie Zhongsheng; Chen Da

1999-01-01

The orthogonal design method is used in the optimization of in-core fuel management. A code package of in-core fuel management in hexagonal geometry HEX-ORTH is developed. The loading pattern after the end of 3 cycle of Xi'an Pulsed Reactor is optimized using the HEX-ORTH. The optimistic loading pattern of the core are obtained as the objective function is Max(k eff BOC )

Robust Topology Optimization Based on Stochastic Collocation Methods under Loading Uncertainties

Directory of Open Access Journals (Sweden)

Qinghai Zhao

2015-01-01

Full Text Available A robust topology optimization (RTO approach with consideration of loading uncertainties is developed in this paper. The stochastic collocation method combined with full tensor product grid and Smolyak sparse grid transforms the robust formulation into a weighted multiple loading deterministic problem at the collocation points. The proposed approach is amenable to implementation in existing commercial topology optimization software package and thus feasible to practical engineering problems. Numerical examples of two- and three-dimensional topology optimization problems are provided to demonstrate the proposed RTO approach and its applications. The optimal topologies obtained from deterministic and robust topology optimization designs under tensor product grid and sparse grid with different levels are compared with one another to investigate the pros and cons of optimization algorithm on final topologies, and an extensive Monte Carlo simulation is also performed to verify the proposed approach.

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems: Preprint

Energy Technology Data Exchange (ETDEWEB)

Yang, Rui; Zhang, Yingchen

2016-08-01

Distributed energy resources (DERs) and smart loads have the potential to provide flexibility to the distribution system operation. A coordinated optimization approach is proposed in this paper to actively manage DERs and smart loads in distribution systems to achieve the optimal operation status. A three-phase unbalanced Optimal Power Flow (OPF) problem is developed to determine the output from DERs and smart loads with respect to the system operator's control objective. This paper focuses on coordinating PV systems and smart loads to improve the overall voltage profile in distribution systems. Simulations have been carried out in a 12-bus distribution feeder and results illustrate the superior control performance of the proposed approach.

A Wind Farm Controller for Load and Power Optimization in a Farm

DEFF Research Database (Denmark)

Soleimanzadeh, Maryam; Brand, Arno; Wisniewski, Rafal

2011-01-01

This paper describes the design procedure of an optimal wind farm controller. The controller optimizes the structural load and power production simultaneously, on the basis of an analytical wind farm model. The farm model delivers maps of wind, loads and energy in the wind farm. Moreover, the model...... computes the wind speed at the turbines, turbine bending moments and aerodynamic power and torque. The optimal control problem is formulated based on the model for two different wind directions. The controller determines the reference signals for each individual wind turbine controller in two scenarios...... based on low and high wind speed. In low wind speed, the reference signals for rotor speed are adjusted, taking the trade-off between power maximization and load minimization into account. In high wind speed, the power and pitch angle reference signals are determined while structural loads are minimized....

Optimal Load Response to Time-of-Use Power Price for Demand Side Management in Denmark

DEFF Research Database (Denmark)

Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

2010-01-01

-of-use power price for demand side management in order to save the energy costs as much as possible. 3 typical different kinds of loads (industrial load, residential load and commercial load) in Denmark are chosen as study cases. The energy costs decrease up to 9.6% with optimal load response to time......-of-use power price for different loads. Simulation results show that the optimal load response to time-of-use power price for demand side management generates different load profiles and reduces the load peaks. This kind of load patterns may also have significant effects on the power system normal operation.......Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift their loads from high price periods to the low price periods in order to save their energy costs. This paper presents a load optimization method to time...

Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling

DEFF Research Database (Denmark)

Tan, Kang Miao; Ramachandaramurthy, Vigna K.; Yong, Jia Ying

2017-01-01

-to-grid optimization algorithm is implemented and tested in MATLAB software (R2013a, MathWorks, Natick, MA, USA). The performance of the optimization algorithm depends heavily on the setting of the target load, power grid load and capability of the grid-connected electric vehicles. Hence, the performance...... of the proposed algorithm under various target load and electric vehicles’ state of charge selections were analysed. The effectiveness of the vehicle-to-grid scheduling to implement the appropriate peak load shaving and load levelling services for the grid load variance minimization is verified under various...

Finding Multiple Optimal Solutions to Optimal Load Distribution Problem in Hydropower Plant

Directory of Open Access Journals (Sweden)

Xinhao Jiang

2012-05-01

Full Text Available Optimal load distribution (OLD among generator units of a hydropower plant is a vital task for hydropower generation scheduling and management. Traditional optimization methods for solving this problem focus on finding a single optimal solution. However, many practical constraints on hydropower plant operation are very difficult, if not impossible, to be modeled, and the optimal solution found by those models might be of limited practical uses. This motivates us to find multiple optimal solutions to the OLD problem, which can provide more flexible choices for decision-making. Based on a special dynamic programming model, we use a modified shortest path algorithm to produce multiple solutions to the problem. It is shown that multiple optimal solutions exist for the case study of China’s Geheyan hydropower plant, and they are valuable for assessing the stability of generator units, showing the potential of reducing occurrence times of units across vibration areas.

Fuzzy Adaptive Particle Swarm Optimization for Power Loss Minimisation in Distribution Systems Using Optimal Load Response

DEFF Research Database (Denmark)

Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

2014-01-01

Consumers may decide to modify the profile of their demand from high price periods to low price periods in order to reduce their electricity costs. This optimal load response to electricity prices for demand side management generates different load profiles and provides an opportunity to achieve...... power loss minimization in distribution systems. In this paper, a new method to achieve power loss minimization in distribution systems by using a price signal to guide the demand side management is proposed. A fuzzy adaptive particle swarm optimization (FAPSO) is used as a tool for the power loss...

Optimization of fuel core loading pattern design in a VVER nuclear power reactors using Particle Swarm Optimization (PSO)

International Nuclear Information System (INIS)

Babazadeh, Davood; Boroushaki, Mehrdad; Lucas, Caro

2009-01-01

The two main goals in core fuel loading pattern design optimization are maximizing the core effective multiplication factor (K eff ) in order to extract the maximum energy, and keeping the local power peaking factor (P q ) lower than a predetermined value to maintain fuel integrity. In this research, a new strategy based on Particle Swarm Optimization (PSO) algorithm has been developed to optimize the fuel core loading pattern in a typical VVER. The PSO algorithm presents a simple social model by inspiration from bird collective behavior in finding food. A modified version of PSO algorithm for discrete variables has been developed and implemented successfully for the multi-objective optimization of fuel loading pattern design with constraints of keeping P q lower than a predetermined value and maximizing K eff . This strategy has been accomplished using WIMSD and CITATION calculation codes. Simulation results show that this algorithm can help in the acquisition of a new pattern without contravention of the constraints.

Determining the optimal load for jump squats: a review of methods and calculations.

Science.gov (United States)

Dugan, Eric L; Doyle, Tim L A; Humphries, Brendan; Hasson, Christopher J; Newton, Robert U

2004-08-01

There has been an increasing volume of research focused on the load that elicits maximum power output during jump squats. Because of a lack of standardization for data collection and analysis protocols, results of much of this research are contradictory. The purpose of this paper is to examine why differing methods of data collection and analysis can lead to conflicting results for maximum power and associated optimal load. Six topics relevant to measurement and reporting of maximum power and optimal load are addressed: (a) data collection equipment, (b) inclusion or exclusion of body weight force in calculations of power, (c) free weight versus Smith machine jump squats, (d) reporting of average versus peak power, (e) reporting of load intensity, and (f) instructions given to athletes/ participants. Based on this information, a standardized protocol for data collection and reporting of jump squat power and optimal load is presented.

First principles molecular dynamics without self-consistent field optimization

International Nuclear Information System (INIS)

Souvatzis, Petros; Niklasson, Anders M. N.

2014-01-01

We present a first principles molecular dynamics approach that is based on time-reversible extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The optimization-free dynamics keeps the computational cost to a minimum and typically provides molecular trajectories that closely follow the exact Born-Oppenheimer potential energy surface. Only one single diagonalization and Hamiltonian (or Fockian) construction are required in each integration time step. The proposed dynamics is derived for a general free-energy potential surface valid at finite electronic temperatures within hybrid density functional theory. Even in the event of irregular functional behavior that may cause a dynamical instability, the optimization-free limit represents a natural starting guess for force calculations that may require a more elaborate iterative electronic ground state optimization. Our optimization-free dynamics thus represents a flexible theoretical framework for a broad and general class of ab initio molecular dynamics simulations

Topology optimization considering design-dependent Stokes flow loads

NARCIS (Netherlands)

Picelli, R.; Vicente, W.M.; Pavanello, R.; van Keulen, A.; Li, Qing; Steven, Grant P.; Zhang, Zhongpu

2015-01-01

This article presents an evolutionary topology optimization method for mean compliance minimization of structures under design-dependent viscous fluid flow loads. The structural domain is governed by the elasticity equation and the fluid by the incompressible Stokes flow equations. When the

Real-Time Vehicle Energy Management System Based on Optimized Distribution of Electrical Load Power

Directory of Open Access Journals (Sweden)

Yuefei Wang

2016-10-01

Full Text Available As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as a global optimal control problem which aims to minimize fuel consumption. Pontryagin’s minimum principle is applied to solve the optimal control problem to realize a real-time control strategy for electrical energy management in vehicles. The control strategy can change the output of the intelligent alternator and the battery with the changes of electrical load and driving conditions in real-time. Experimental results demonstrate that, compared to the traditional open-loop control strategy, the proposed control strategy for vehicle energy management can effectively reduce fuel consumption and the fuel consumption per 100 km is decreased by approximately 1.7%.

Assessment of Optimal Flexibility in Ensemble of Frequency Responsive Loads

Energy Technology Data Exchange (ETDEWEB)

Kundu, Soumya; Hansen, Jacob; Lian, Jianming; Kalsi, Karanjit

2018-04-19

Potential of electrical loads in providing grid ancillary services is often limited due to the uncertainties associated with the load behavior. A knowledge of the expected uncertainties with a load control program would invariably yield to better informed control policies, opening up the possibility of extracting the maximal load control potential without affecting grid operations. In the context of frequency responsive load control, a probabilistic uncertainty analysis framework is presented to quantify the expected error between the target and actual load response, under uncertainties in the load dynamics. A closed-form expression of an optimal demand flexibility, minimizing the expected error in actual and committed flexibility, is provided. Analytical results are validated through Monte Carlo simulations of ensembles of electric water heaters.

Optimization between heating load and entropy-production rate for endoreversible absorption heat-transformers

International Nuclear Information System (INIS)

Sun Fengrui; Qin Xiaoyong; Chen Lingen; Wu Chih

2005-01-01

For an endoreversible four-heat-reservoir absorption heat-transformer cycle, for which a linear (Newtonian) heat-transfer law applies, an ecological optimization criterion is proposed for the best mode of operation of the cycle. This involves maximizing a function representing the compromise between the heating load and the entropy-production rate. The optimal relation between the ecological criterion and the COP (coefficient of performance), the maximum ecological criterion and the corresponding COP, heating load and entropy production rate, as well as the ecological criterion and entropy-production rate at the maximum heating load are derived using finite-time thermodynamics. Moreover, compared with the heating-load criterion, the effects of the cycle parameters on the ecological performance are studied by numerical examples. These show that achieving the maximum ecological criterion makes the entropy-production rate decrease by 77.0% and the COP increase by 55.4% with only 27.3% heating-load losses compared with the maximum heating-load objective. The results reflect that the ecological criterion has long-term significance for optimal design of absorption heat-transformers

Space and time optimization of nuclear reactors by means of the Pontryagin principle

International Nuclear Information System (INIS)

Anton, V.

1979-01-01

A numerical method is being presented for solving space dependent optimization problems concerning a functional for one dimensional geometries in the few group diffusion approximation. General dimensional analysis was applied to derive relations for the maximum of a functional and the limiting values of the constraints. Two procedures were given for calculating the anisotropic diffusion coefficients in order to improve the results of the diffusion approximation. In this work two procedures were presented for collapsing the microscopic multigroup cross sections, one general and another specific to the space dependent optimization problems solved by means of the Pontryagin maximum principle. Neutron spectrum optimization is performed to ensure the burnup of Pu 239 isotope produced in a thermal nuclear reactor. A procedure is also given for the minimization of finite functional set by means of the Pontryagin maximum principle. A method for determining the characteristics of fission Pseudo products is formulated in one group and multigroup cases. This method is applied in the optimization of the burnup in nuclear reactors with fuel electric cells. A procedure to mjnimze the number of the fuel burnup equations is described. The optimization problems presented and solved in this work point to the efficiency of the maximum principle. Each problem on method presented in the various chapters is accompanied by considerations concerning dual problems and possibilities of further research development. (author)

[Optimization of trehalose loading in red blood cells before freeze-drying].

Science.gov (United States)

Zhuang, Yuan; Liu, Jing-Han; Ouyang, Xi-Lin; Chen, Lin-Feng; Che, Ji

2007-04-01

The key points for better protection of trehalose in freeze-drying red blood cells (RBCs) are to resolve non-osmosis of trehalose to red blood cells and to make cytoplasmic trehalose to reach effective concentration. This study was aimed to investigate the regularity of loading RBCs with trehalose, screen out optimal loading condition and evaluate the effect of trehalose on physico-chemical parameters of RBCs during the period of loading. The cytoplasmic trehalose concentration in red blood cells, free hemoglobin and ATP level were determined at different incubation temperatures (4, 22 and 37 degrees C), different trehaolse concentrations (0, 200, 400, 600, 800 and 1000 mmol/L) and different incubation times (2, 4, 6, 8 and 10 hours), the cytoplasmic trehalose, free hemoglobin (FHb), hemoglobin (Hb) and mean corpuscular volume (MCV) in fresh RBCs and RBCs stored for 72 hours at 4 degrees C were compared, when loading condition was ensured. The results showed that with increase of incubation temperature, time and extracellular trehalose concentration, the loading of trehalose in RBCs also increased. Under the optimal loading condition, cytoplasmic trehalose concentration and free hemoglobin level of fresh RBCs and RBCs stored for 72 hours at 4 degrees C were 65.505 +/- 6.314 mmol/L, 66.2 +/- 5.002 mmol/L and 6.567 +/- 2.568 g/L, 16.168 +/- 3.922 g/L respectively. It is concluded that the most optimal condition of loading trehalose is that fresh RBCs incubate in 800 mmol/L trehalose solution for 8 hours at 37 degrees C. This condition can result in a efficient cytoplasmic trehalose concentration. The study provides an important basis for long-term preservation of RBCs.

An automatic procedure for optimizing fuel loading in consideration of the effect of burnup nonuniformity in assembly

International Nuclear Information System (INIS)

Wang Guoli.

1988-01-01

The effect of burnup nonuniformity across the assembly on optimizing fuel loading in core is investigated. Some new rules which can be used for optimizing fuel loading in the core are proposed. New automatic procedure for optimizing fuel loading in the core is described

Optimization of drug loading to improve physical stability of paclitaxel-loaded long-circulating liposomes.

Science.gov (United States)

Kannan, Vinayagam; Balabathula, Pavan; Divi, Murali K; Thoma, Laura A; Wood, George C

2015-01-01

The effect of formulation and process parameters on drug loading and physical stability of paclitaxel-loaded long-circulating liposomes was evaluated. The liposomes were prepared by hydration-extrusion method. The formulation parameters such as total lipid content, cholesterol content, saturated-unsaturated lipid ratio, drug-lipid ratio and process parameters such as extrusion pressure and number of extrusion cycles were studied and their impact on drug loading and physical stability was evaluated. A proportionate increase in drug loading was observed with increase in the total phospholipid content. Cholesterol content and saturated lipid content in the bilayer showed a negative influence on drug loading. The short-term stability evaluation of liposomes prepared with different drug-lipid ratios demonstrated that 1:60 as the optimum drug-lipid ratio to achieve a loading of 1-1.3 mg/mL without the risk of physical instability. The vesicle size decreased with an increase in the extrusion pressure and number of extrusion cycles, but no significant trends were observed for drug loading with changes in process pressure or number of cycles. The optimization of formulation and process parameters led to a physically stable formulation of paclitaxel-loaded long-circulating liposomes that maintain size, charge and integrity during storage.

Simultaneous loading patterns optimization for two successive cycles of pressurized water reactors

International Nuclear Information System (INIS)

Yamamoto, Akio; Sugimura, Erina; Kitamura, Yasunori; Yamane, Yoshihiro

2004-01-01

In this paper, simultaneous optimization is carried out for successive two cycles of pressurized water reactors. At first, a simplified problem of the simultaneous optimization was studied by assuming the batch-wise power sharing as independent variable, i.e., batch-wise power sharing was optimized without considering corresponding loading patterns. The optimization of the batch-wise power sharing was carried out for the conventional single cycle, the equilibrium cycle and the two successive (tandem) cycles. The analysis indicated that the tandem cycle optimization well reproduce that of the equilibrium cycle optimization, which is considered as a typical case of the true multicycle optimization. Next, simultaneous optimization of loading patterns for tandem cycles is carried out using the simulated annealing method. Since the design space of the tandem cycles optimization is much larger than that of the conventional single cycle optimization, the optimization condition (i.e., number of calculated patterns) are established through sensitivity study. The optimization results are compared with those obtained by the successive single cycle optimizations and it is clarified that the successive single cycle optimization well reproduces the optimization results obtained by the simultaneous optimization if objective functions are appropriately chosen. The above result will be encouraging for the current in-core optimization method since single cycle optimization is utilized due to limitation of computation time. (author)

Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units

Directory of Open Access Journals (Sweden)

Ghulam Hafeez

2018-03-01

Full Text Available With the rapid advancement in technology, electrical energy consumption is increasing rapidly. Especially, in the residential sector, more than 80% of electrical energy is being consumed because of consumer negligence. This brings the challenging task of maintaining the balance between the demand and supply of electric power. In this paper, we focus on the problem of load balancing via load scheduling under utility and rooftop photovoltaic (PV units to reduce electricity cost and peak to average ratio (PAR in demand-side management. For this purpose, we adopted genetic algorithm (GA, binary particle swarm optimization (BPSO, wind-driven optimization (WDO, and our proposed genetic WDO (GWDO algorithm, which is a hybrid of GA and WDO, to schedule the household load. For energy cost estimation, combined real-time pricing (RTP and inclined block rate (IBR were used. The proposed algorithm shifts load from peak consumption hours to off-peak hours based on combined pricing scheme and generation from rooftop PV units. Simulation results validate our proposed GWDO algorithm in terms of electricity cost and PAR reduction while considering all three scenarios which we have considered in this work: (1 load scheduling without renewable energy sources (RESs and energy storage system (ESS, (2 load scheduling with RESs, and (3 load scheduling with RESs and ESS. Furthermore, our proposed scheme reduced electricity cost and PAR by 22.5% and 29.1% in scenario 1, 47.7% and 30% in scenario 2, and 49.2% and 35.4% in scenario 3, respectively, as compared to unscheduled electricity consumption.

Adaptive Beam Loading Compensation in Room Temperature Bunching Cavities

Energy Technology Data Exchange (ETDEWEB)

Edelen, J. P. [Fermilab; Chase, B. E. [Fermilab; Cullerton, E. [Fermilab; Varghese, P. [Fermilab

2017-10-01

In this paper we present the design, simulation, and proof of principle results of an optimization based adaptive feedforward algorithm for beam-loading compensation in a high impedance room temperature cavity. We begin with an overview of prior developments in beam loading compensation. Then we discuss different techniques for adaptive beam loading compensation and why the use of Newton?s Method is of interest for this application. This is followed by simulation and initial experimental results of this method.

Optimization of Boiler Heat Load in Water-Heating Boiler-House

Directory of Open Access Journals (Sweden)

B. A. Bayrashevsky

2009-01-01

Full Text Available An analytical method for optimization of water-heating boiler loads has been developed on the basis of approximated semi-empirical dependences pertaining to changes of boiler gross efficiency due to its load. A complex (∂tух/∂ξΔξ is determined on the basis of a systematic analysis (monitoring of experimental data and the Y. P. Pecker’s formula for calculation of balance losses q2. This complex makes it possible to set a corresponding correction to a standard value of the boiler gross efficiency due to contamination of heating surfaces.Software means for optimization of water-heating boilers has been developed and it is recommended to be applied under operational conditions.

Study on ant colony optimization for fuel loading pattern problem

International Nuclear Information System (INIS)

Kishi, Hironori; Kitada, Takanori

2013-01-01

Modified ant colony optimization (ACO) was applied to the in-core fuel loading pattern (LP) optimization problem to minimize the power peaking factor (PPF) in the modeled 1/4 symmetry PWR core. Loading order was found to be important in ACO. Three different loading orders with and without the adjacent effect between fuel assemblies (FAs) were compared, and it was found that the loading order from the central core is preferable because many selections of FAs to be inserted are available in the core center region. LPs were determined from pheromone trail and heuristic information, which is a priori knowledge based on the feature of the problem. Three types of heuristic information were compared to obtain the desirable performance of searching LPs with low PPF. Moreover, mutation operation, such as the genetic algorithm (GA), was introduced into the ACO algorithm to avoid searching similar LPs because heuristic information used in ACO tends to localize the searching space in the LP problem. The performance of ACO with some improvement was compared with those of simulated annealing and GA. In conclusion, good performance can be achieved by setting proper heuristic information and mutation operation parameter in ACO. (author)

Geometry and Topology Optimization of Statically Determinate Beams under Fixed and Most Unfavorably Distributed Load

Directory of Open Access Journals (Sweden)

Agata Kozikowska

Full Text Available Abstract The paper concerns topology and geometry optimization of statically determinate beams with an arbitrary number of pin supports. The beams are simultaneously exposed to uniform dead load and arbitrarily distributed live load and optimized for the absolute maximum bending moment. First, all the beams with fixed topology are subjected to geometrical optimization by genetic algorithm. Strict mathematical formulas for calculation of optimal geometrical parameters are found for all topologies and any ratio of dead to live load. Then beams with the same minimal values of the objective function and different topologies are classified into groups called topological classes. The detailed characteristics of these classes are described.

Optimal fuel loading pattern design using artificial intelligence techniques

International Nuclear Information System (INIS)

Kim, Han Gon; Chang, Soon Heung; Lee, Byung Ho

1993-01-01

The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (Author)

Optimization and modeling of the remote loading of luciferin into liposomes.

Science.gov (United States)

Hansen, Anders Højgaard; Lomholt, Michael A; Hansen, Per Lyngs; Mouritsen, Ole G; Arouri, Ahmad

2016-07-11

We carried out a mechanistic study to characterize and optimize the remote loading of luciferin into preformed liposomes of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine/1,2-dipalmitoyl-sn-glycero-3-phosphoglycerol (DPPC/DPPG) 7:3 mixtures. The influence of the loading agent (acetate, propionate, butyrate), the metal counterion (Na(+), K(+), Ca(+2), Mg(+2)), and the initial extra-liposomal amount of luciferin (nL(add)) on the luciferin Loading Efficiency (LE%) and luciferin-to-lipid weight ratio, i.e., Loading Capacity (LC), in the final formulation was determined. In addition, the effect of the loading process on the colloidal stability and phase behavior of the liposomes was monitored. Based on our experimental results, a theoretical model was developed to describe the course of luciferin remote loading. It was found that the highest luciferin loading was obtained with magnesium acetate. The use of longer aliphatic carboxylates or inorganic proton donors pronouncedly reduced luciferin loading, whereas the effect of the counterion was modest. The remote-loading process barely affected the colloidal stability and drug retention of the liposomes, albeit with moderate luciferin-induced membrane perturbations. The correlation between luciferin loading, expressed as LE% and LC, and nL(add) was established, and under our conditions the maximum LC was attained using an nL(add) of around 2.6μmol. Higher amounts of luciferin tend to pronouncedly perturb the liposome stability and luciferin retention. Our theoretical model furnishes a fair quantitative description of the correlation between nL(add) and luciferin loading, and a membrane permeability coefficient for uncharged luciferin of 1×10(-8)cm/s could be determined. We believe that our study will prove very useful to optimize the remote-loading strategies of moderately polar carboxylic acid drugs in general. Copyright © 2016 Elsevier B.V. All rights reserved.

Daily Peak Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm

Directory of Open Access Journals (Sweden)

Shuyu Dai

2018-01-01

Full Text Available Daily peak load forecasting is an important part of power load forecasting. The accuracy of its prediction has great influence on the formulation of power generation plan, power grid dispatching, power grid operation and power supply reliability of power system. Therefore, it is of great significance to construct a suitable model to realize the accurate prediction of the daily peak load. A novel daily peak load forecasting model, CEEMDAN-MGWO-SVM (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, is proposed in this paper. Firstly, the model uses the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN algorithm to decompose the daily peak load sequence into multiple sub sequences. Then, the model of modified grey wolf optimization and support vector machine (MGWO-SVM is adopted to forecast the sub sequences. Finally, the forecasting sequence is reconstructed and the forecasting result is obtained. Using CEEMDAN can realize noise reduction for non-stationary daily peak load sequence, which makes the daily peak load sequence more regular. The model adopts the grey wolf optimization algorithm improved by introducing the population dynamic evolution operator and the nonlinear convergence factor to enhance the global search ability and avoid falling into the local optimum, which can better optimize the parameters of the SVM algorithm for improving the forecasting accuracy of daily peak load. In this paper, three cases are used to test the forecasting accuracy of the CEEMDAN-MGWO-SVM model. We choose the models EEMD-MGWO-SVM (Ensemble Empirical Mode Decomposition and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, MGWO-SVM (Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, GWO-SVM (Support Vector Machine Optimized by Grey Wolf Optimization Algorithm, SVM (Support Vector

Comparison of DVH parameters and loading patterns of standard loading, manual and inverse optimization for intracavitary brachytherapy on a subset of tandem/ovoid cases

International Nuclear Information System (INIS)

Jamema, Swamidas V.; Kirisits, Christian; Mahantshetty, Umesh; Trnkova, Petra; Deshpande, Deepak D.; Shrivastava, Shyam K.; Poetter, Richard

2010-01-01

Purpose: Comparison of inverse planning with the standard clinical plan and with the manually optimized plan based on dose-volume parameters and loading patterns. Materials and methods: Twenty-eight patients who underwent MRI based HDR brachytherapy for cervix cancer were selected for this study. Three plans were calculated for each patient: (1) standard loading, (2) manual optimized, and (3) inverse optimized. Dosimetric outcomes from these plans were compared based on dose-volume parameters. The ratio of Total Reference Air Kerma of ovoid to tandem (TRAK O/T ) was used to compare the loading patterns. Results: The volume of HR CTV ranged from 9-68 cc with a mean of 41(±16.2)cc. Mean V100 for standard, manual optimized and inverse plans was found to be not significant (p = 0.35, 0.38, 0.4). Dose to bladder (7.8 ± 1.6 Gy) and sigmoid (5.6 ± 1.4 Gy) was high for standard plans; Manual optimization reduced the dose to bladder (7.1 ± 1.7 Gy p = 0.006) and sigmoid (4.5 ± 1.0 Gy p = 0.005) without compromising the HR CTV coverage. The inverse plan resulted in a significant reduction to bladder dose (6.5 ± 1.4 Gy, p = 0.002). TRAK was found to be 0.49(±0.02), 0.44(±0.04) and 0.40(±0.04)cGy m -2 for the standard loading, manual optimized and inverse plans, respectively. It was observed that TRAK O/T was 0.82(±0.05), 1.7(±1.04) and 1.41(±0.93) for standard loading, manual optimized and inverse plans, respectively, while this ratio was 1 for the traditional loading pattern. Conclusions: Inverse planning offers good sparing of critical structures without compromising the target coverage. The average loading pattern of the whole patient cohort deviates from the standard Fletcher loading pattern.

Comparison of DVH parameters and loading patterns of standard loading, manual and inverse optimization for intracavitary brachytherapy on a subset of tandem/ovoid cases.

Science.gov (United States)

Jamema, Swamidas V; Kirisits, Christian; Mahantshetty, Umesh; Trnkova, Petra; Deshpande, Deepak D; Shrivastava, Shyam K; Pötter, Richard

2010-12-01

Comparison of inverse planning with the standard clinical plan and with the manually optimized plan based on dose-volume parameters and loading patterns. Twenty-eight patients who underwent MRI based HDR brachytherapy for cervix cancer were selected for this study. Three plans were calculated for each patient: (1) standard loading, (2) manual optimized, and (3) inverse optimized. Dosimetric outcomes from these plans were compared based on dose-volume parameters. The ratio of Total Reference Air Kerma of ovoid to tandem (TRAK(O/T)) was used to compare the loading patterns. The volume of HR CTV ranged from 9-68 cc with a mean of 41(±16.2) cc. Mean V100 for standard, manual optimized and inverse plans was found to be not significant (p=0.35, 0.38, 0.4). Dose to bladder (7.8±1.6 Gy) and sigmoid (5.6±1.4 Gy) was high for standard plans; Manual optimization reduced the dose to bladder (7.1±1.7 Gy p=0.006) and sigmoid (4.5±1.0 Gy p=0.005) without compromising the HR CTV coverage. The inverse plan resulted in a significant reduction to bladder dose (6.5±1.4 Gy, p=0.002). TRAK was found to be 0.49(±0.02), 0.44(±0.04) and 0.40(±0.04) cGy m(-2) for the standard loading, manual optimized and inverse plans, respectively. It was observed that TRAK(O/T) was 0.82(±0.05), 1.7(±1.04) and 1.41(±0.93) for standard loading, manual optimized and inverse plans, respectively, while this ratio was 1 for the traditional loading pattern. Inverse planning offers good sparing of critical structures without compromising the target coverage. The average loading pattern of the whole patient cohort deviates from the standard Fletcher loading pattern. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

[Optimization on trehalose loading technique as protective conditioning for lyophilization of human platelets].

Science.gov (United States)

Liu, Jing-Han; Zhou, Jun; Ouyang, Xi-Lin; Li, Xi-Jin; Lu, Fa-Qiang

2005-08-01

This study was aimed to further optimize trehalose loading technique including loading temperature, loading time, loading solution and loading concentration of trehalose, based on the established parameters. Loading efficiency in plasma was compared with that in buffer at 37 degrees C; the curves of intracellular trehalose concentration versus loading time at 37 degrees C and 16 degrees C were measured; curves of mean platelet volume (MPV) versus loading time and loading concentration were investigated and compared. According to results obtained, the loaing time, loading temperature, loading solution and trehalose concentration were ascertained for high loading efficiency of trehalose into human platelet. The results showed that the loading efficiency in plasma was markedly higher than that in buffer at 37 degrees C, the loading efficiency in plasma at 37 degrees C was significantly higher than that at 16 degrees C and reached 19.51% after loading for 4 hours, but 6.16% at 16 degrees C. MPV at 16 degrees C was increased by 43.2% than that at 37 degrees C, but had no distinct changes with loading time and loading concentration. In loading at 37 degrees C, MPV increased with loading time and loading concentration positively. Loading time and loading concentration displayed synergetic effect on MPV. MPV increased with loading time and concentration while trehalose loading concentration was above 50 mmol/L. It is concluded that the optimization parameters of trehalose loading technique are 37 degrees C (temperature), 4 hours (leading time), plasma (loading solution), 50 mmol/L (feasible trehalose concentration). The trehalose concentration can be adjusted to meet the requirement of lyophilization.

Optimization programs for reactor core fuel loading exhibiting reduced neutron leakage

International Nuclear Information System (INIS)

Darilek, P.

1991-01-01

The program MAXIM was developed for the optimization of the fuel loading of WWER-440 reactors. It enables the reactor core reactivity to be maximized by modifying the arrangement of the fuel assemblies. The procedure is divided into three steps. The first step includes the passage from the three-dimensional model of the reactor core to the two-dimensional model. In the second step, the solution to the problem is sought assuming that the multiplying properties, or the reactivity in the zones of the core, vary continuously. In the third step, parameters of actual fuel assemblies are inserted in the ''continuous'' solution obtained. Combined with the program PROPAL for a detailed refinement of the loading, the program MAXIM forms a basis for the development of programs for the optimization of fuel loading with burnable poisons. (Z.M.). 16 refs

Optimal design of high-speed loading spindle based on ABAQUS

Science.gov (United States)

Yang, Xudong; Dong, Yu; Ge, Qingkuan; Yang, Hai

2017-12-01

The three-dimensional model of high-speed loading spindle is established by using ABAQUS’s modeling module. A finite element analysis model of high-speed loading spindle was established by using spring element to simulate bearing boundary condition. The static and dynamic performance of the spindle structure with different specifications of the rectangular spline and the different diameter neck of axle are studied in depth, and the influence of different spindle span on the static and dynamic performance of the high-speed loading spindle is studied. Finally, the optimal structure of the high-speed loading spindle is obtained. The results provide a theoretical basis for improving the overall performance of the test-bed

Optimality principle for the coupled chemical reactions of ATP synthesis and its molecular interpretation

Science.gov (United States)

Nath, Sunil

2018-05-01

Metabolic energy obtained from the coupled chemical reactions of oxidative phosphorylation (OX PHOS) is harnessed in the form of ATP by cells. We experimentally measured thermodynamic forces and fluxes during ATP synthesis, and calculated the thermodynamic efficiency, η and the rate of free energy dissipation, Φ. We show that the OX PHOS system is tuned such that the coupled nonequilibrium processes operate at optimal η. This state does not coincide with the state of minimum Φ but is compatible with maximum Φ under the imposed constraints. Conditions that must hold for species concentration in order to satisfy the principle of optimal efficiency are derived analytically and a molecular explanation based on Nath's torsional mechanism of energy transduction and ATP synthesis is suggested. Differences of the proposed principle with Prigogine's principle are discussed.

Optimal control problems with delay, the maximum principle and necessary conditions

NARCIS (Netherlands)

Frankena, J.F.

1975-01-01

In this paper we consider a rather general optimal control problem involving ordinary differential equations with delayed arguments and a set of equality and inequality restrictions on state- and control variables. For this problem a maximum principle is given in pointwise form, using variational

Development of a VVER-1000 core loading pattern optimization program based on perturbation theory

International Nuclear Information System (INIS)

Hosseini, Mohammad; Vosoughi, Naser

2012-01-01

Highlights: ► We use perturbation theory to find an optimum fuel loading pattern in a VVER-1000. ► We provide a software for in-core fuel management optimization. ► We consider two objectives for our method (perturbation theory). ► We show that perturbation theory method is very fast and accurate for optimization. - Abstract: In-core nuclear fuel management is one of the most important concerns in the design of nuclear reactors. Two main goals in core fuel loading pattern design optimization are maximizing the core effective multiplication factor in order to extract the maximum energy, and keeping the local power peaking factor lower than a predetermined value to maintain the fuel integrity. Because of the numerous possible patterns of fuel assemblies in the reactor core, finding the best configuration is so important and challenging. Different techniques for optimization of fuel loading pattern in the reactor core have been introduced by now. In this study, a software is programmed in C language to find an order of the fuel loading pattern of a VVER-1000 reactor core using the perturbation theory. Our optimization method is based on minimizing the radial power peaking factor. The optimization process launches by considering an initial loading pattern and the specifications of the fuel assemblies which are given as the input of the software. The results on a typical VVER-1000 reactor reveal that the method could reach to a pattern with an allowed radial power peaking factor and increases the cycle length 1.1 days, as well.

Evolutionary multimodal optimization using the principle of locality

KAUST Repository

Wong, Kachun; Wu, Chunho; Mok, Ricky; Peng, Chengbin; Zhang, Zhaolei

2012-01-01

The principle of locality is one of the most widely used concepts in designing computing systems. To explore the principle in evolutionary computation, crowding differential evolution is incorporated with locality for multimodal optimization. Instead of generating trial vectors randomly, the first method proposed takes advantage of spatial locality to generate trial vectors. Temporal locality is also adopted to help generate offspring in the second method proposed. Temporal and spatial locality are then applied together in the third method proposed. Numerical experiments are conducted to compare the proposed methods with the state-of-the-art methods on benchmark functions. Experimental analysis is undertaken to observe the effect of locality and the synergy between temporal locality and spatial locality. Further experiments are also conducted on two application problems. One is the varied-line-spacing holographic grating design problem, while the other is the protein structure prediction problem. The numerical results demonstrate the effectiveness of the methods proposed. © 2012 Elsevier Inc. All rights reserved.

Evolutionary multimodal optimization using the principle of locality

KAUST Repository

Wong, Kachun

2012-07-01

The principle of locality is one of the most widely used concepts in designing computing systems. To explore the principle in evolutionary computation, crowding differential evolution is incorporated with locality for multimodal optimization. Instead of generating trial vectors randomly, the first method proposed takes advantage of spatial locality to generate trial vectors. Temporal locality is also adopted to help generate offspring in the second method proposed. Temporal and spatial locality are then applied together in the third method proposed. Numerical experiments are conducted to compare the proposed methods with the state-of-the-art methods on benchmark functions. Experimental analysis is undertaken to observe the effect of locality and the synergy between temporal locality and spatial locality. Further experiments are also conducted on two application problems. One is the varied-line-spacing holographic grating design problem, while the other is the protein structure prediction problem. The numerical results demonstrate the effectiveness of the methods proposed. © 2012 Elsevier Inc. All rights reserved.

Stress-strain state analysis and optimization of rod system under periodic pulse load

Directory of Open Access Journals (Sweden)

Grebenyuk Grigory

2018-01-01

Full Text Available The paper considers the problem of analysis and optimization of rod systems subjected to combined static and periodic pulse load. As a result of the study the analysis method was developed based on traditional approach to solving homogeneous matrix equations of state and a special algorithm for developing a particular solution. The influence of pulse parameters variations on stress-strain state of a rod system was analyzed. Algorithms for rod systems optimization were developed basing on strength recalculation and statement and solution of optimization problem as a problem of nonlinear mathematical programming. Recommendations are developed for efficient organization of process for optimization of rod systems under static and periodic pulse load.

An ant colony optimization algorithm for phylogenetic estimation under the minimum evolution principle

Directory of Open Access Journals (Sweden)

Milinkovitch Michel C

2007-11-01

Full Text Available Abstract Background Distance matrix methods constitute a major family of phylogenetic estimation methods, and the minimum evolution (ME principle (aiming at recovering the phylogeny with shortest length is one of the most commonly used optimality criteria for estimating phylogenetic trees. The major difficulty for its application is that the number of possible phylogenies grows exponentially with the number of taxa analyzed and the minimum evolution principle is known to belong to the NP MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaWenfgDOvwBHrxAJfwnHbqeg0uy0HwzTfgDPnwy1aaceaGae8xdX7Kaeeiuaafaaa@3888@-hard class of problems. Results In this paper, we introduce an Ant Colony Optimization (ACO algorithm to estimate phylogenies under the minimum evolution principle. ACO is an optimization technique inspired from the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems. Conclusion We show that the ACO algorithm is potentially competitive in comparison with state-of-the-art algorithms for the minimum evolution principle. This is the first application of an ACO algorithm to the phylogenetic estimation problem.

A loading pattern optimization method for nuclear fuel management

International Nuclear Information System (INIS)

Argaud, J.P.

1997-01-01

Nuclear fuel reload of PWR core leads to the search of an optimal nuclear fuel assemblies distribution, namely of loading pattern. This large discrete optimization problem is here expressed as a cost function minimization. To deal with this problem, an approach based on gradient information is used to direct the search in the patterns discrete space. A method using an adjoint state formulation is then developed, and final results of complete patterns search tests by this method are presented. (author)

An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics

Science.gov (United States)

Turkington, Bruce

2013-08-01

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.

Analytic model for ultrasound energy receivers and their optimal electric loads

Science.gov (United States)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-08-01

In this paper, we present an analytic model for thickness resonating plate ultrasound energy receivers, which we have derived from the piezoelectric and the wave equations and, in which we have included dielectric, viscosity and acoustic attenuation losses. Afterwards, we explore the optimal electric load predictions by the zero reflection and power maximization approaches present in the literature with different acoustic boundary conditions, and discuss their limitations. To validate our model, we compared our expressions with the KLM model solved numerically with very good agreement. Finally, we discuss the differences between the zero reflection and power maximization optimal electric loads, which start to differ as losses in the receiver increase.

Optimal control of a double integrator a primer on maximum principle

CERN Document Server

Locatelli, Arturo

2017-01-01

This book provides an introductory yet rigorous treatment of Pontryagin’s Maximum Principle and its application to optimal control problems when simple and complex constraints act on state and control variables, the two classes of variable in such problems. The achievements resulting from first-order variational methods are illustrated with reference to a large number of problems that, almost universally, relate to a particular second-order, linear and time-invariant dynamical system, referred to as the double integrator. The book is ideal for students who have some knowledge of the basics of system and control theory and possess the calculus background typically taught in undergraduate curricula in engineering. Optimal control theory, of which the Maximum Principle must be considered a cornerstone, has been very popular ever since the late 1950s. However, the possibly excessive initial enthusiasm engendered by its perceived capability to solve any kind of problem gave way to its equally unjustified rejecti...

Differential harmony search algorithm to optimize PWRs loading pattern

Energy Technology Data Exchange (ETDEWEB)

Poursalehi, N., E-mail: npsalehi@yahoo.com [Engineering Department, Shahid Beheshti University, G.C, P.O.Box: 1983963113, Tehran (Iran, Islamic Republic of); Zolfaghari, A.; Minuchehr, A. [Engineering Department, Shahid Beheshti University, G.C, P.O.Box: 1983963113, Tehran (Iran, Islamic Republic of)

2013-04-15

Highlights: ► Exploit of DHS algorithm in LP optimization reveals its flexibility, robustness and reliability. ► Upshot of our experiments with DHS shows that the search approach to optimal LP is quickly. ► On the average, the final band width of DHS fitness values is narrow relative to HS and GHS. -- Abstract: The objective of this work is to develop a core loading optimization technique using differential harmony search algorithm in the context of obtaining an optimal configuration of fuel assemblies in pressurized water reactors. To implement and evaluate the proposed technique, differential harmony search nodal expansion package for 2-D geometry, DHSNEP-2D, is developed. The package includes two modules; in the first modules differential harmony search (DHS) is implemented and nodal expansion code which solves two dimensional-multi group neutron diffusion equations using fourth degree flux expansion with one node per a fuel assembly is in the second module. For evaluation of DHS algorithm, classical harmony search (HS) and global-best harmony search (GHS) algorithms are also included in DHSNEP-2D in order to compare the outcome of techniques together. For this purpose, two PWR test cases have been investigated to demonstrate the DHS algorithm capability in obtaining near optimal loading pattern. Results show that the convergence rate of DHS and execution times are quite promising and also is reliable for the fuel management operation. Moreover, numerical results show the good performance of DHS relative to other competitive algorithms such as genetic algorithm (GA), classical harmony search (HS) and global-best harmony search (GHS) algorithms.

Differential harmony search algorithm to optimize PWRs loading pattern

International Nuclear Information System (INIS)

Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.

2013-01-01

Highlights: ► Exploit of DHS algorithm in LP optimization reveals its flexibility, robustness and reliability. ► Upshot of our experiments with DHS shows that the search approach to optimal LP is quickly. ► On the average, the final band width of DHS fitness values is narrow relative to HS and GHS. -- Abstract: The objective of this work is to develop a core loading optimization technique using differential harmony search algorithm in the context of obtaining an optimal configuration of fuel assemblies in pressurized water reactors. To implement and evaluate the proposed technique, differential harmony search nodal expansion package for 2-D geometry, DHSNEP-2D, is developed. The package includes two modules; in the first modules differential harmony search (DHS) is implemented and nodal expansion code which solves two dimensional-multi group neutron diffusion equations using fourth degree flux expansion with one node per a fuel assembly is in the second module. For evaluation of DHS algorithm, classical harmony search (HS) and global-best harmony search (GHS) algorithms are also included in DHSNEP-2D in order to compare the outcome of techniques together. For this purpose, two PWR test cases have been investigated to demonstrate the DHS algorithm capability in obtaining near optimal loading pattern. Results show that the convergence rate of DHS and execution times are quite promising and also is reliable for the fuel management operation. Moreover, numerical results show the good performance of DHS relative to other competitive algorithms such as genetic algorithm (GA), classical harmony search (HS) and global-best harmony search (GHS) algorithms

Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling

Directory of Open Access Journals (Sweden)

Kang Miao Tan

2017-11-01

Full Text Available The introduction of electric vehicles into the transportation sector helps reduce global warming and carbon emissions. The interaction between electric vehicles and the power grid has spurred the emergence of a smart grid technology, denoted as vehicle-to grid-technology. Vehicle-to-grid technology manages the energy exchange between a large fleet of electric vehicles and the power grid to accomplish shared advantages for the vehicle owners and the power utility. This paper presents an optimal scheduling of vehicle-to-grid using the genetic algorithm to minimize the power grid load variance. This is achieved by allowing electric vehicles charging (grid-to-vehicle whenever the actual power grid loading is lower than the target loading, while conducting electric vehicle discharging (vehicle-to-grid whenever the actual power grid loading is higher than the target loading. The vehicle-to-grid optimization algorithm is implemented and tested in MATLAB software (R2013a, MathWorks, Natick, MA, USA. The performance of the optimization algorithm depends heavily on the setting of the target load, power grid load and capability of the grid-connected electric vehicles. Hence, the performance of the proposed algorithm under various target load and electric vehicles’ state of charge selections were analysed. The effectiveness of the vehicle-to-grid scheduling to implement the appropriate peak load shaving and load levelling services for the grid load variance minimization is verified under various simulation investigations. This research proposal also recommends an appropriate setting for the power utility in terms of the selection of the target load based on the electric vehicle historical data.

Small Signal Stability Improvement of Power Systems Using Optimal Load Responses in Competitive Electricity Markets

DEFF Research Database (Denmark)

Hu, Weihao; Su, Chi; Chen, Zhe

2011-01-01

Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift some of their loads from high price periods to the low price periods in order to save their energy costs. The optimal load response to an electricity price...... price is proposed. A 17-bus power system with high wind power penetrations, which resembles the Eastern Danish power system, is chosen as the study case. Simulation results show that the optimal load response to electricity prices is an effective measure to improve the small signal stability of power...... for demand side management generates different load profiles and may provide an opportunity to improve the small signal stability of power systems with high wind power penetrations. In this paper, the idea of power system small signal stability improvement by using optimal load response to the electricity...

Robust Optimization for Household Load Scheduling with Uncertain Parameters

Directory of Open Access Journals (Sweden)

Jidong Wang

2018-04-01

Full Text Available Home energy management systems (HEMS face many challenges of uncertainty, which have a great impact on the scheduling of home appliances. To handle the uncertain parameters in the household load scheduling problem, this paper uses a robust optimization method to rebuild the household load scheduling model for home energy management. The model proposed in this paper can provide the complete robust schedules for customers while considering the disturbance of uncertain parameters. The complete robust schedules can not only guarantee the customers’ comfort constraints but also cooperatively schedule the electric devices for cost minimization and load shifting. Moreover, it is available for customers to obtain multiple schedules through setting different robust levels while considering the trade-off between the comfort and economy.

Tackling optimization challenges in industrial load control and full-duplex radios

Science.gov (United States)

Gholian, Armen

In price-based demand response programs in smart grid, utilities set the price in accordance with the grid operating conditions and consumers respond to price signals by conducting optimal load control to minimize their energy expenditure while satisfying their energy needs. Industrial sector consumes a large portion of world electricity and addressing optimal load control of energy-intensive industrial complexes, such as steel industry and oil-refinery, is of practical importance. Formulating a general industrial complex and addressing issues in optimal industrial load control in smart grid is the focus of the second part of this dissertation. Several industrial load details are considered in the proposed formulation, including those that do not appear in residential or commercial load control problems. Operation under different smart pricing scenarios, namely, day-ahead pricing, time-of-use pricing, peak pricing, inclining block rates, and critical peak pricing are considered. The use of behind-the-meter renewable generation and energy storage is also considered. The formulated optimization problem is originally nonlinear and nonconvex and thus hard to solve. However, it is then reformulated into a tractable linear mixed-integer program. The performance of the design is assessed through various simulations for an oil refinery and a steel mini-mill. In the third part of this dissertation, a novel all-analog RF interference canceler is proposed. Radio self-interference cancellation (SIC) is the fundamental enabler for full-duplex radios. While SIC methods based on baseband digital signal processing and/or beamforming are inadequate, an all-analog method is useful to drastically reduce the self-interference as the first stage of SIC. It is shown that a uniform architecture with uniformly distributed RF attenuators has a performance highly dependent on the carrier frequency. It is also shown that a new architecture with the attenuators distributed in a clustered

Principles of optimizing animal production from rangeland

International Nuclear Information System (INIS)

Stubbendieck, J.; Waller, S.S.

1983-01-01

Increasing world population is one of the dominant factors escalating demands for the world's natural resources. Range and forage resources, which are used primarily for food and fibre, could be more efficiently used if management techniques were improved. The principles of managing forage resources are directly associated with both the growth and development of plants and the actions and needs of the grazing animal. An understanding of the effects of environmental factors and herbage removal (frequency, intensity and season of defoliation) on growth and regrowth of plants is the first step towards optimizing animal productivity from rangelands. Most potential changes will fit into three categories: (1) increase the quantity of forage, (2) improve the quality of forage, and (3) improve use of forage. The principles of grazing management can be separated into four intricately related categories: (1) proper degree of grazing, (2) proper season of grazing, (3) proper kind of livestock, and (4) proper distribution of grazing. Grazing management is affected by the manner in which both improvements and manipulation of vegetation affect forage yield and quality. The adaptation and application of existing knowledge to individual locations will be one step towards optimizing animal production from rangeland. Some of the problems may be solved through better dissemination of present knowledge through existing educational programmes, while others will require expanded programmes of information dissemination. A third group of problems may also be solved with present technology, but the solutions are not currently economical. Some of the problems will be solved only through expanded research. These research efforts need to be directed towards grazing or browsing animals, plant resources and the interaction between plants and animals. Application of nuclear techniques will be an integral part of this research. (author)

A new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting

International Nuclear Information System (INIS)

Wang, Bo; Tai, Neng-ling; Zhai, Hai-qing; Ye, Jian; Zhu, Jia-dong; Qi, Liang-bo

2008-01-01

In this paper, a new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting is proposed. Auto-regressive (AR) and moving average (MA) with exogenous variables (ARMAX) has been widely applied in the load forecasting area. Because of the nonlinear characteristics of the power system loads, the forecasting function has many local optimal points. The traditional method based on gradient searching may be trapped in local optimal points and lead to high error. While, the hybrid method based on evolutionary algorithm and particle swarm optimization can solve this problem more efficiently than the traditional ways. It takes advantage of evolutionary strategy to speed up the convergence of particle swarm optimization (PSO), and applies the crossover operation of genetic algorithm to enhance the global search ability. The new ARMAX model for short-term load forecasting has been tested based on the load data of Eastern China location market, and the results indicate that the proposed approach has achieved good accuracy. (author)

An optimal control model for load shifting - With application in the energy management of a colliery

International Nuclear Information System (INIS)

Middelberg, Arno; Zhang Jiangfeng; Xia Xiaohua

2009-01-01

This paper presents an optimal control model for the load shifting problem in energy management and its application in a South African colliery. It is illustrated in the colliery scenario that how the optimal control model can be applied to optimize load shifting and improve energy efficiency through the control of conveyor belts. The time-of-use electricity tariff is used as an input to the objective function in order to obtain a solution that minimizes electricity costs and thus maximizes load shifting. The case study yields promising results that show the potential of applying this optimal control model to other industrial Demand Side Management initiatives

Performance of Estimation of distribution algorithm for initial core loading optimization of AHWR-LEU

International Nuclear Information System (INIS)

Thakur, Amit; Singh, Baltej; Gupta, Anurag; Duggal, Vibhuti; Bhatt, Kislay; Krishnani, P.D.

2016-01-01

Highlights: • EDA has been applied to optimize initial core of AHWR-LEU. • Suitable value of weighing factor ‘α’ and population size in EDA was estimated. • The effect of varying initial distribution function on optimized solution was studied. • For comparison, Genetic algorithm was also applied. - Abstract: Population based evolutionary algorithms now form an integral part of fuel management in nuclear reactors and are frequently being used for fuel loading pattern optimization (LPO) problems. In this paper we have applied Estimation of distribution algorithm (EDA) to optimize initial core loading pattern (LP) of AHWR-LEU. In EDA, new solutions are generated by sampling the probability distribution model estimated from the selected best candidate solutions. The weighing factor ‘α’ decides the fraction of current best solution for updating the probability distribution function after each generation. A wider use of EDA warrants a comprehensive study on parameters like population size, weighing factor ‘α’ and initial probability distribution function. In the present study, we have done an extensive analysis on these parameters (population size, weighing factor ‘α’ and initial probability distribution function) in EDA. It is observed that choosing a very small value of ‘α’ may limit the search of optimized solutions in the near vicinity of initial probability distribution function and better loading patterns which are away from initial distribution function may not be considered with due weightage. It is also observed that increasing the population size improves the optimized loading pattern, however the algorithm still fails if the initial distribution function is not close to the expected optimized solution. We have tried to find out the suitable values for ‘α’ and population size to be considered for AHWR-LEU initial core loading pattern optimization problem. For sake of comparison and completeness, we have also addressed the

Structure Optimal Design of Electromagnetic Levitation Load Reduction Device for Hydroturbine Generator Set

Directory of Open Access Journals (Sweden)

Qingyan Wang

2015-01-01

Full Text Available Thrust bearing is one part with the highest failure rate in hydroturbine generator set, which is primarily due to heavy axial load. Such heavy load often makes oil film destruction, bearing friction, and even burning. It is necessary to study the load and the reduction method. The dynamic thrust is an important factor to influence the axial load and reduction design of electromagnetic device. Therefore, in the paper, combined with the structure features of vertical turbine, the hydraulic thrust is analyzed accurately. Then, take the turbine model HL-220-LT-550, for instance; the electromagnetic levitation load reduction device is designed, and its mathematical model is built, whose purpose is to minimize excitation loss and total quality under the constraints of installation space, connection layout, and heat dissipation. Particle swarm optimization (PSO is employed to search for the optimum solution; finally, the result is verified by finite element method (FEM, which demonstrates that the optimized structure is more effective.

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

Science.gov (United States)

Morelli, Eugene A.; Klein, Vladislav

1990-01-01

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Optimal Topology of Aircraft Rib and Spar Structures under Aeroelastic Loads

Science.gov (United States)

Stanford, Bret K.; Dunning, Peter D.

2014-01-01

Several topology optimization problems are conducted within the ribs and spars of a wing box. It is desired to locate the best position of lightening holes, truss/cross-bracing, etc. A variety of aeroelastic metrics are isolated for each of these problems: elastic wing compliance under trim loads and taxi loads, stress distribution, and crushing loads. Aileron effectiveness under a constant roll rate is considered, as are dynamic metrics: natural vibration frequency and flutter. This approach helps uncover the relationship between topology and aeroelasticity in subsonic transport wings, and can therefore aid in understanding the complex aircraft design process which must eventually consider all these metrics and load cases simultaneously.

Shape optimization and sensitivity of compliant beams for prescribed load-displacement response

NARCIS (Netherlands)

Radaelli, G.; Herder, J.L.

2016-01-01

This paper presents the shape optimization of a compliant beam for prescribed load-displacements response. The analysis of the design is based on the isogeometric analysis framework for an enhanced fidelity between designed and analysed shape. The sensitivities used for an improved optimization

Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework

Science.gov (United States)

Best management practices (BMPs) are perceived as being effective in reducing nutrient loads transported from non-point sources (NPS) to receiving water bodies. The objective of this study was to develop a modeling-optimization framework that can be used by watershed management p...

On quasistability radius of a vector trajectorial problem with a principle of optimality generalizing Pareto and lexicographic principles

Directory of Open Access Journals (Sweden)

Sergey E. Bukhtoyarov

2005-05-01

Full Text Available A multicriterion linear combinatorial problem with a parametric principle of optimality is considered. This principle is defined by a partitioning of partial criteria onto Pareto preference relation groups within each group and the lexicographic preference relation between them. Quasistability of the problem is investigated. This type of stability is a discrete analog of Hausdorff lower semi-continuity of the multiple-valued mapping that defines the choice function. A formula of quasistability radius is derived for the case of the metric l∞. Some known results are stated as corollaries. Mathematics Subject Classification 2000: 90C05, 90C10, 90C29, 90C31.

Fatigue Load Sensitivity Based Optimal Active Power Dispatch For Wind Farms

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun

2017-01-01

This paper proposes an optimal active power dispatch algorithm for wind farms based on Wind Turbine (WT) load sensitivity. The control objectives include tracking power references from the system operator and minimizing fatigue loads experienced by WTs. The sensitivity of WT fatigue loads to power...... sensitivity are derived, which significantly improves the computation efficiency of the local WT controller. The proposed algorithm can be implemented in different active power control schemes. Case studies were conducted with a wind farm under balance control for both low and high wind conditions...

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

International Nuclear Information System (INIS)

Dong, Feifei; Liu, Yong; Su, Han; Zou, Rui; Guo, Huaicheng

2015-01-01

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

Reliability-oriented multi-objective optimal decision-making approach for uncertainty-based watershed load reduction

Energy Technology Data Exchange (ETDEWEB)

Dong, Feifei [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Liu, Yong, E-mail: yongliu@pku.edu.cn [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Institute of Water Sciences, Peking University, Beijing 100871 (China); Su, Han [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China); Zou, Rui [Tetra Tech, Inc., 10306 Eaton Place, Ste 340, Fairfax, VA 22030 (United States); Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming 650034 (China); Guo, Huaicheng [College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing 100871 (China)

2015-05-15

Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely “optimal” solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multi-objective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. - Highlights: • Reliability-oriented multi-objective (ROMO) optimal decision approach was proposed. • The approach can avoid specifying reliability levels prior to optimization modeling. • Multiple reliability objectives can be systematically balanced using Pareto fronts. • Neural network model was used to

Polyurethane foam loaded with SDS for the adsorption of cationic dyes from aqueous medium: Multivariate optimization of the loading process.

Science.gov (United States)

Robaina, Nicolle F; Soriano, Silvio; Cassella, Ricardo J

2009-08-15

This paper reports the development of a new procedure for the adsorption of four cationic dyes (Rhodamine B, Methylene Blue, Crystal Violet and Malachite Green) from aqueous medium employing polyurethane foam (PUF) loaded with sodium dodecylsulfate (SDS) as solid phase. PUF loading process was based on the stirring of 200mg PUF cylinders with acidic solutions containing SDS. The conditions for loading were optimized by response surface methodology (RSM) using a Doehlert design with three variables that were SDS and HCl concentrations and stirring time. Results obtained in the optimization process showed that the stirring time is not a relevant parameter in the PUF loading, evidencing that the transport of SDS from solution to PUF surface is fast. On the other hand, both SDS and HCl concentrations were important parameters causing significant variation in the efficiency of the resulting solid phase for the removal of dyes from solution. At optimized conditions, SDS and HCl concentrations were 4.0 x 10(-4) and 0.90 mol L(-1), respectively. The influence of stirring time was evaluated by univariate methodology. A 20 min stirring time was established in order to make the PUF loading process fast and robust without losing efficiency. The procedure was tested for the removal of the four cationic dyes from aqueous solutions and removal efficiencies always better than 90% were achieved for the two concentrations tested (2.0 x 10(-5) and 1.0 x 10(-4)mol L(-1)).

Use and optimization of a dual-flowrate loading strategy to maximize throughput in protein-a affinity chromatography.

Science.gov (United States)

Ghose, Sanchayita; Nagrath, Deepak; Hubbard, Brian; Brooks, Clayton; Cramer, Steven M

2004-01-01

The effect of an alternate strategy employing two different flowrates during loading was explored as a means of increasing system productivity in Protein-A chromatography. The effect of such a loading strategy was evaluated using a chromatographic model that was able to accurately predict experimental breakthrough curves for this Protein-A system. A gradient-based optimization routine is carried out to establish the optimal loading conditions (initial and final flowrates and switching time). The two-step loading strategy (using a higher flowrate during the initial stages followed by a lower flowrate) was evaluated for an Fc-fusion protein and was found to result in significant improvements in process throughput. In an extension of this optimization routine, dynamic loading capacity and productivity were simultaneously optimized using a weighted objective function, and this result was compared to that obtained with the single flowrate. Again, the dual-flowrate strategy was found to be superior.

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

International Nuclear Information System (INIS)

Gong Zhaohu; Wang Kan; Yao Dong

2011-01-01

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

Optimal allocation of industrial PV-storage micro-grid considering important load

Science.gov (United States)

He, Shaohua; Ju, Rong; Yang, Yang; Xu, Shuai; Liang, Lei

2018-03-01

At present, the industrial PV-storage micro-grid has been widely used. This paper presents an optimal allocation model of PV-storage micro-grid capacity considering the important load of industrial users. A multi-objective optimization model is established to promote the local extinction of PV power generation and the maximum investment income of the enterprise as the objective function. Particle swarm optimization (PSO) is used to solve the case of a city in Jiangsu Province, the results are analyzed economically.

Microprocessor control unit of thyristor regulator of microhydroelectric power station ballast load

International Nuclear Information System (INIS)

Nomokonova, Yu; Bogdanov, E

2014-01-01

The operational principle of microhydroelectric power station ballast load is presented. The comparative overview of the mathematical modeling methods is performed. The ranges of thyristors optimal work are shown as a result of the regulator regimes analysis. Shows the necessity of regulation the ballast load in microhydroelectric power station with help of developed algorithm of the program for microprocessor control

Impact of optimal load response to real-time electricity price on power system constraints in Denmark

DEFF Research Database (Denmark)

Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

2010-01-01

Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift their loads from high price periods to the low price periods in order to save their energy costs. The optimal load response to a real-time electricity price...... and may represent the future of electricity markets in some ways, is chosen as the studied power system in this paper. A distribution system where wind power capacity is 126% of maximum loads is chosen as the study case. This paper presents a nonlinear load optimization method to real-time power price...... for demand side management in order to save the energy costs as much as possible. Simulation results show that the optimal load response to a real-time electricity price has some good impacts on power system constraints in a distribution system with high wind power penetrations....

SN-38 loading capacity of hydrophobic polymer blend nanoparticles: formulation, optimization and efficacy evaluation.

Science.gov (United States)

Dimchevska, Simona; Geskovski, Nikola; Petruševski, Gjorgji; Chacorovska, Marina; Popeski-Dimovski, Riste; Ugarkovic, Sonja; Goracinova, Katerina

2017-03-01

One of the most important problems in nanoencapsulation of extremely hydrophobic drugs is poor drug loading due to rapid drug crystallization outside the polymer core. The effort to use nanoprecipitation, as a simple one-step procedure with good reproducibility and FDA approved polymers like Poly(lactic-co-glycolic acid) (PLGA) and Polycaprolactone (PCL), will only potentiate this issue. Considering that drug loading is one of the key defining characteristics, in this study we attempted to examine whether the nanoparticle (NP) core composed of two hydrophobic polymers will provide increased drug loading for 7-Ethyl-10-hydroxy-camptothecin (SN-38), relative to NPs prepared using individual polymers. D-optimal design was applied to optimize PLGA/PCL ratio in the polymer blend and the mode of addition of the amphiphilic copolymer Lutrol ® F127 in order to maximize SN-38 loading and obtain NPs with acceptable size for passive tumor targeting. Drug/polymer and polymer/polymer interaction analysis pointed to high degree of compatibility and miscibility among both hydrophobic polymers, providing core configuration with higher drug loading capacity. Toxicity studies outlined the biocompatibility of the blank NPs. Increased in vitro efficacy of drug-loaded NPs compared to the free drug was confirmed by growth inhibition studies using SW-480 cell line. Additionally, the optimized NP formulation showed very promising blood circulation profile with elimination half-time of 7.4 h.

Optimizing load transfer in multiwall nanotubes through interwall coupling: Theory and simulation

International Nuclear Information System (INIS)

Byrne, E.M.; Letertre, A.; McCarthy, M.A.; Curtin, W.A.; Xia, Z.

2010-01-01

An analytical model is developed to determine the length scales over which load is transferred from outer to inner walls of multiwall carbon nanotubes (MWCNTs) as a function of the amount of bonding between walls. The model predicts that the characteristic length for load transfer scales as l∼t√(E/μ-bar), where t is the CNT wall spacing, E is the effective wall Young's modulus, and μ-bar is the average interwall shear modulus due to interwall coupling. Molecular dynamics simulations for MWCNTs with up to six walls, and with interwall coupling achieved by interwall sp 3 bonding at various densities, provide data against which the model is tested. For interwall bonding having a uniform axial distribution, the analytic and simulation models agree well, showing that continuum mechanics concepts apply down to the atomic scale in this problem. The simulation models show, however, that load transfer is sensitive to natural statistical fluctuations in the spatial distribution of the interwall bonding between pairs of walls, and such fluctuations generally increase the net load transfer length needed to fully load an MWCNT. Optimal load transfer is achieved when bonding is uniformly distributed axially, and all interwall regions have the same shear stiffness, implying a linear decrease in the number of interwall bonds with distance from the outer wall. Optimal load transfer into an n-wall MWCNT is shown to occur over a length of ∼1.5nl. The model can be used to design MWCNTs for structural materials, and to interpret load transfer characteristics deduced from experiments on individual MWCNTs.

Normalization of doxorubicin release from graphene oxide: New approach for optimization of effective parameters on drug loading.

Science.gov (United States)

Hashemi, Mohadeseh; Yadegari, Amir; Yazdanpanah, Ghasem; Omidi, Meisam; Jabbehdari, Sayena; Haghiralsadat, Fatemeh; Yazdian, Fatemeh; Tayebi, Lobat

2017-05-01

Graphene oxide (GO) has been recently introduced as a suitable anticancer drug carrier, which could be loaded with doxorubicin (DOX) as a general chemotherapy agent. Herein, the attempts were made to optimize the effective parameters on both loading and release of DOX on GO. GO and GO-DOX were characterized using transition electron microscopy , zeta potential, Raman spectroscopy, UV-visible spectroscopy, and Fourier transform infrared spectroscopy. In addition, loading and releasing behaviors of DOX on GO were studied in terms of different temperature and pH values. The primary optimized values of pH and temperature for best-loaded amount of DOX were 8.9 and 309 K, respectively. Moreover, we found that the smallest amount of released DOX, in pH of cancer microenvironment (5.4), occurs when DOX had been previously loaded in pH 7.8 and 310 K. Although the highest amount of loaded DOX was in basic pH, the results of efficient release of DOX from the GO-DOX complex and also cellular toxicity assay revealed that the best pH for loading of DOX on GO was 7.8. Therefore, in addition to optimization of parameters for efficient loading of DOX on GO, this study suggested that normalization of a released drug compared with the amount of a loaded drug could be a new approach for optimization of drug loading on nanocarriers. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

Active load sharing technique for on-line efficiency optimization in DC microgrids

DEFF Research Database (Denmark)

Sanseverino, E. Riva; Zizzo, G.; Boscaino, V.

2017-01-01

Recently, DC power distribution is gaining more and more importance over its AC counterpart achieving increased efficiency, greater flexibility, reduced volumes and capital cost. In this paper, a 24-120-325V two-level DC distribution system for home appliances, each including three parallel DC......-DC converters, is modeled. An active load sharing technique is proposed for the on-line optimization of the global efficiency of the DC distribution network. The algorithm aims at the instantaneous efficiency optimization of the whole DC network, based on the on-line load current sampling. A Look Up Table......, is created to store the real efficiencies of the converters taking into account components tolerances. A MATLAB/Simulink model of the DC distribution network has been set up and a Genetic Algorithm has been employed for the global efficiency optimization. Simulation results are shown to validate the proposed...

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-25

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

Engineering to Control Noise, Loading, and Optimal Operating Points

International Nuclear Information System (INIS)

Mitchell R. Swartz

2000-01-01

Successful engineering of low-energy nuclear systems requires control of noise, loading, and optimum operating point (OOP) manifolds. The latter result from the biphasic system response of low-energy nuclear reaction (LENR)/cold fusion systems, and their ash production rate, to input electrical power. Knowledge of the optimal operating point manifold can improve the reproducibility and efficacy of these systems in several ways. Improved control of noise, loading, and peak production rates is available through the study, and use, of OOP manifolds. Engineering of systems toward the OOP-manifold drive-point peak may, with inclusion of geometric factors, permit more accurate uniform determinations of the calibrated activity of these materials/systems

Optimizing electrical load pattern in Kuwait using grid connected photovoltaic systems

International Nuclear Information System (INIS)

Al-Hasan, A.Y.; Ghoneim, A.A.; Abdullah, A.H.

2004-01-01

Grid connected photovoltaic systems is one of the most promising applications of photovoltaic systems. These systems are employed in applications where utility service is already available. In this case, there is no need for battery storage because grid power may be used to supplement photovoltaic systems (PV) when the load exceeds available PV generation. The load receives electricity from both the photovoltaic array and the utility grid. In this system, the load is the total electrical energy consumption. The main objective of the present work is to optimize the electrical load pattern in Kuwait using grid connected PV systems. In this situation, the electric load demand can be satisfied from both the photovoltaic array and the utility grid. The performance of grid connected photovoltaic systems in the Kuwait climate has been evaluated. It was found that the peak load matches the maximum incident solar radiation in Kuwait, which would emphasize the role of using the PV station to minimize the electrical load demand. In addition, a significant reduction in peak load can be achieved with grid connected PV systems

A fast and optimized dynamic economic load dispatch for large scale power systems

International Nuclear Information System (INIS)

Musse Mohamud Ahmed; Mohd Ruddin Ab Ghani; Ismail Hassan

2000-01-01

This paper presents Lagrangian Multipliers (LM) and Linear Programming (LP) based dynamic economic load dispatch (DELD) solution for large-scale power system operations. It is to minimize the operation cost of power generation. units subject to the considered constraints. After individual generator units are economically loaded and periodically dispatched, fast and optimized DELD has been achieved. DELD with period intervals has been taken into consideration The results found from the algorithm based on LM and LP techniques appear to be modest in both optimizing the operation cost and achieving fast computation. (author)

Analytic model for ultrasound energy receivers and their optimal electric loads II: Experimental validation

Science.gov (United States)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-10-01

In this paper, we verify the two optimal electric load concepts based on the zero reflection condition and on the power maximization approach for ultrasound energy receivers. We test a high loss 1-3 composite transducer, and find that the measurements agree very well with the predictions of the analytic model for plate transducers that we have developed previously. Additionally, we also confirm that the power maximization and zero reflection loads are very different when the losses in the receiver are high. Finally, we compare the optimal load predictions by the KLM and the analytic models with frequency dependent attenuation to evaluate the influence of the viscosity.

Advanced and flexible genetic algorithms for BWR fuel loading pattern optimization

International Nuclear Information System (INIS)

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

2009-01-01

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

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Wei Sun

2015-01-01

Full Text Available Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM which is optimized by fruit fly algorithm (FOA for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.

Generalized perturbation theory error control within PWR core-loading pattern optimization

International Nuclear Information System (INIS)

Imbriani, J.S.; Turinsky, P.J.; Kropaczek, D.J.

1995-01-01

The fuel management optimization code FORMOSA-P has been developed to determine the family of near-optimum loading patterns for PWR reactors. The code couples the optimization technique of simulated annealing (SA) with a generalized perturbation theory (GPT) model for evaluating core physics characteristics. To ensure the accuracy of the GPT predictions, as well as to maximize the efficient of the SA search, a GPT error control method has been developed

Application of chaotic ant swarm optimization in electric load forecasting

International Nuclear Information System (INIS)

Hong, W.-C.

2010-01-01

Support vector regression (SVR) had revealed strong potential in accurate electric load forecasting, particularly by employing effective evolutionary algorithms to determine suitable values of its three parameters. Based on previous research results, however, these employed evolutionary algorithms themselves have several drawbacks, such as converging prematurely, reaching slowly the global optimal solution, and trapping into a local optimum. This investigation presents an SVR-based electric load forecasting model that applied a novel algorithm, namely chaotic ant swarm optimization (CAS), to improve the forecasting performance by searching its suitable parameters combination. The proposed CAS combines with the chaotic behavior of single ant and self-organization behavior of ant colony in the foraging process to overcome premature local optimum. The empirical results indicate that the SVR model with CAS (SVRCAS) results in better forecasting performance than the other alternative methods, namely SVRCPSO (SVR with chaotic PSO), SVRCGA (SVR with chaotic GA), regression model, and ANN model.

Design And Modeling An Automated Digsilent Power System For Optimal New Load Locations

Directory of Open Access Journals (Sweden)

Mohamed Saad

2015-08-01

Full Text Available Abstract The electric power utilities seek to take advantage of novel approaches to meet growing energy demand. Utilities are under pressure to evolve their classical topologies to increase the usage of distributed generation. Currently the electrical power engineers in many regions of the world are implementing manual methods to measure power consumption for farther assessment of voltage violation. Such process proved to be time consuming costly and inaccurate. Also demand response is a grid management technique where retail or wholesale customers are requested either electronically or manually to reduce their load. Therefore this paper aims to design and model an automated power system for optimal new load locations using DPL DIgSILENT Programming Language. This study is a diagnostic approach that assists system operator about any voltage violation cases that would happen during adding new load to the grid. The process of identifying the optimal bus bar location involves a complicated calculation of the power consumptions at each load bus As a result the DPL program would consider all the IEEE 30 bus internal networks data then a load flow simulation will be executed. To add the new load to the first bus in the network. Therefore the developed model will simulate the new load at each available bus bar in the network and generate three analytical reports for each case that captures the overunder voltage and the loading elements among the grid.

Optimization, formulation, and characterization of multiflavonoids-loaded flavanosome by bulk or sequential technique.

Science.gov (United States)

Karthivashan, Govindarajan; Masarudin, Mas Jaffri; Kura, Aminu Umar; Abas, Faridah; Fakurazi, Sharida

2016-01-01

This study involves adaptation of bulk or sequential technique to load multiple flavonoids in a single phytosome, which can be termed as "flavonosome". Three widely established and therapeutically valuable flavonoids, such as quercetin (Q), kaempferol (K), and apigenin (A), were quantified in the ethyl acetate fraction of Moringa oleifera leaves extract and were commercially obtained and incorporated in a single flavonosome (QKA-phosphatidylcholine) through four different methods of synthesis - bulk (M1) and serialized (M2) co-sonication and bulk (M3) and sequential (M4) co-loading. The study also established an optimal formulation method based on screening the synthesized flavonosomes with respect to their size, charge, polydispersity index, morphology, drug-carrier interaction, antioxidant potential through in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics, and cytotoxicity evaluation against human hepatoma cell line (HepaRG). Furthermore, entrapment and loading efficiency of flavonoids in the optimal flavonosome have been identified. Among the four synthesis methods, sequential loading technique has been optimized as the best method for the synthesis of QKA-phosphatidylcholine flavonosome, which revealed an average diameter of 375.93±33.61 nm, with a zeta potential of -39.07±3.55 mV, and the entrapment efficiency was >98% for all the flavonoids, whereas the drug-loading capacity of Q, K, and A was 31.63%±0.17%, 34.51%±2.07%, and 31.79%±0.01%, respectively. The in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics of the flavonoids indirectly depicts the release kinetic behavior of the flavonoids from the carrier. The QKA-loaded flavonosome had no indication of toxicity toward human hepatoma cell line as shown by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide result, wherein even at the higher concentration of 200 µg/mL, the flavonosomes exert >85% of cell viability. These results suggest that sequential loading technique may be a promising

On a variational principle for shape optimization and elliptic free boundary problems

Directory of Open Access Journals (Sweden)

Raúl B. González De Paz

2009-02-01

Full Text Available A variational principle for several free boundary value problems using a relaxation approach is presented. The relaxed Energy functional is concave and it is defined on a convex set, so that the minimizing points are characteristic functions of sets. As a consequence of the first order optimality conditions, it is shown that the corresponding sets are domains bounded by free boundaries, so that the equivalence of the solution of the relaxed problem with the solution of several free boundary value problem is proved. Keywords: Calculus of variations, optimization, free boundary problems.

Rigorous force field optimization principles based on statistical distance minimization

Energy Technology Data Exchange (ETDEWEB)

Vlcek, Lukas, E-mail: vlcekl1@ornl.gov [Chemical Sciences Division, Geochemistry & Interfacial Sciences Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6110 (United States); Joint Institute for Computational Sciences, University of Tennessee, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6173 (United States); Chialvo, Ariel A. [Chemical Sciences Division, Geochemistry & Interfacial Sciences Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6110 (United States)

2015-10-14

We use the concept of statistical distance to define a measure of distinguishability between a pair of statistical mechanical systems, i.e., a model and its target, and show that its minimization leads to general convergence of the model’s static measurable properties to those of the target. We exploit this feature to define a rigorous basis for the development of accurate and robust effective molecular force fields that are inherently compatible with coarse-grained experimental data. The new model optimization principles and their efficient implementation are illustrated through selected examples, whose outcome demonstrates the higher robustness and predictive accuracy of the approach compared to other currently used methods, such as force matching and relative entropy minimization. We also discuss relations between the newly developed principles and established thermodynamic concepts, which include the Gibbs-Bogoliubov inequality and the thermodynamic length.

Optimal load suitability based RAT selection for HSDPA and IEEE 802.11e

DEFF Research Database (Denmark)

Prasad, Ramjee; Cabral, O.; Felez, F.J.

2009-01-01

are a premium. This paper investigates cooperation between networks based Radio Access Technology (RAT) selection algorithm that uses suitability to optimize the choice between WiFi and High Speed Downlink Packet Access (HSDPA). It has been shown that this approach has the potential to provide gain...... by allocating a user terminal to the most preferred network based on traffic type and network load. Optimal load threshold values that maximise the total QoS throughput for the given interworking scenario are 0.6 and 0.53 for HSDPA and WiFi, respectively. This corresponds to a CRRM gain on throughput of 80...

Using spatial principles to optimize distributed computing for enabling the physical science discoveries.

Science.gov (United States)

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-04-05

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century.

PWR loading pattern optimization using Harmony Search algorithm

International Nuclear Information System (INIS)

Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.

2013-01-01

Highlights: ► Numerical results reveal that the HS method is reliable. ► The great advantage of HS is significant gain in computational cost. ► On the average, the final band width of search fitness values is narrow. ► Our experiments show that the search approaches the optimal value fast. - Abstract: In this paper a core reloading technique using Harmony Search, HS, is presented in the context of finding an optimal configuration of fuel assemblies, FA, in pressurized water reactors. To implement and evaluate the proposed technique a Harmony Search along Nodal Expansion Code for 2-D geometry, HSNEC2D, is developed to obtain nearly optimal arrangement of fuel assemblies in PWR cores. This code consists of two sections including Harmony Search algorithm and Nodal Expansion modules using fourth degree flux expansion which solves two dimensional-multi group diffusion equations with one node per fuel assembly. Two optimization test problems are investigated to demonstrate the HS algorithm capability in converging to near optimal loading pattern in the fuel management field and other subjects. Results, convergence rate and reliability of the method are quite promising and show the HS algorithm performs very well and is comparable to other competitive algorithms such as Genetic Algorithm and Particle Swarm Intelligence. Furthermore, implementation of nodal expansion technique along HS causes considerable reduction of computational time to process and analysis optimization in the core fuel management problems

The Dutch premium principle

NARCIS (Netherlands)

van Heerwaarden, A.E.; Kaas, R.

1992-01-01

A premium principle is derived, in which the loading for a risk is the reinsurance loading for an excess-of-loss cover. It is shown that the principle is well-behaved in the sense that it results in larger premiums for risks that are larger in stop-loss order or in stochastic dominance.

Optimizing Cognitive Load for Learning from Computer-Based Science Simulations

Science.gov (United States)

Lee, Hyunjeong; Plass, Jan L.; Homer, Bruce D.

2006-01-01

How can cognitive load in visual displays of computer simulations be optimized? Middle-school chemistry students (N = 257) learned with a simulation of the ideal gas law. Visual complexity was manipulated by separating the display of the simulations in two screens (low complexity) or presenting all information on one screen (high complexity). The…

Optimal task partition and state-dependent loading in heterogeneous two-element work sharing system

International Nuclear Information System (INIS)

Levitin, Gregory; Xing, Liudong; Ben-Haim, Hanoch; Dai, Yuanshun

2016-01-01

Many real-world systems such as multi-channel data communication, multi-path flow transmission and multi-processor computing systems have work sharing attributes where system elements perform different portions of the same task simultaneously. Motivated by these applications, this paper models a heterogeneous work-sharing system with two non-repairable elements. When one element fails, the other element takes over the uncompleted task of the failed element upon finishing its own part; the load level of the remaining operating element can change at the time of the failure, which further affects its performance, failure behavior and operation cost. Considering these dynamics, mission success probability (MSP), expected mission completion time (EMCT) and expected cost of successful mission (ECSM) are first derived. Further, optimization problems are formulated and solved, which find optimal task partition and element load levels maximizing MSP, minimizing EMCT or minimizing ECSM. Effects of element reliability, performance, operation cost on the optimal solutions are also investigated through examples. Results of this work can facilitate a tradeoff analysis of different mission performance indices for heterogeneous work-sharing systems. - Highlights: • A heterogeneous work-sharing system with two non-repairable elements is considered. • The optimal work distribution and element loading problem is formulated and solved. • Effects of element reliability, performance, operation cost on the optimal solutions are investigated.

An application of Pontrjagin's principle to the study of the optimal growth of population

International Nuclear Information System (INIS)

Spinadel, V. de

1976-01-01

This paper examines the consequences of an optimal control of population growth and allows to derive criteria referring to the economic basis of expenditure on population control and to obtain optimal paths for a model in which such a control is possible. By means of very simple assumptions one can reduce the problem to a two-state variable control problem and, in consequence, apply Pontrjagin's maximum principle to solve it. (author)

Basic Principles of Electrical Network Reliability Optimization in Liberalised Electricity Market

Science.gov (United States)

Oleinikova, I.; Krishans, Z.; Mutule, A.

2008-01-01

The authors propose to select long-term solutions to the reliability problems of electrical networks in the stage of development planning. The guide lines or basic principles of such optimization are: 1) its dynamical nature; 2) development sustainability; 3) integrated solution of the problems of network development and electricity supply reliability; 4) consideration of information uncertainty; 5) concurrent consideration of the network and generation development problems; 6) application of specialized information technologies; 7) definition of requirements for independent electricity producers. In the article, the major aspects of liberalized electricity market, its functions and tasks are reviewed, with emphasis placed on the optimization of electrical network development as a significant component of sustainable management of power systems.

Dynamic Optimization of a Polymer Flooding Process Based on Implicit Discrete Maximum Principle

Directory of Open Access Journals (Sweden)

Yang Lei

2012-01-01

Full Text Available Polymer flooding is one of the most important technologies for enhanced oil recovery (EOR. In this paper, an optimal control model of distributed parameter systems (DPSs for polymer injection strategies is established, which involves the performance index as maximum of the profit, the governing equations as the fluid flow equations of polymer flooding, and some inequality constraints as polymer concentration and injection amount limitation. The optimal control model is discretized by full implicit finite-difference method. To cope with the discrete optimal control problem (OCP, the necessary conditions for optimality are obtained through application of the calculus of variations and Pontryagin’s discrete maximum principle. A modified gradient method with new adjoint construction is proposed for the computation of optimal injection strategies. The numerical results of an example illustrate the effectiveness of the proposed method.

The Analysis of process optimization during the loading distribution test for steam turbine

International Nuclear Information System (INIS)

Li Jiangwei; Cao Yuhua; Li Dawei

2014-01-01

The loading distribution of steam turbine needs six times to complete in total, the first time is completed when the turbine cylinder buckles, the rest must be completed orderly in the process of installing GVP pipe. To complete 5 tests of loading distribution and installation of GVP pipe, it usually takes around 90 days for most nuclear plants while the unit l of Fuqing Nuclear Power Station compress it into about 45 days by optimizing the installation process. this article describes the successful experience of how the Unit l of Fuqing Nuclear Power Station finished 5 tests of loading distribution and installation of GVP pipe in 45 days by optimizing the process, Meanwhile they analysis the advantages and disadvantages through comparing it with the process provide by suppliers, which brings up some rationalization proposals for installation work to the follow-up units of our plant. (authors)

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Flight-Test Performance

Science.gov (United States)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads to specified values. This technique has been implemented and flown on the National Aeronautics and Space Administration Full-scale Advanced Systems Testbed aircraft. The flight tests illustrate that the approach achieves the desired performance and show promising potential benefits. The flights also uncovered some important issues that will need to be addressed for production application.

Identifying the optimal resistive load for complex training in male rugby players.

Science.gov (United States)

Comyns, Thomas M; Harrison, Andrew J; Hennessy, Liam; Jensen, Randall L

2007-01-01

Alternating a resistance exercise with a plyometric exercise is referred to as "complex training". In this study, we examined the effect of various resistive loads on the biomechanics of performance of a fast stretch-shortening cycle activity to determine if an optimal resistive load exists for complex training. Twelve elite rugby players performed three drop jumps before and after three back squat resistive loads of 65%, 80%, and 93% of a single repetition maximum (1-RM) load. All drop jumps were performed on a specially constructed sledge and force platform apparatus. Flight time, ground contact time, peak ground reaction force, reactive strength index, and leg stiffness were the dependent variables. Repeated-measures analysis of variance found that all resistive loads reduced (P benefit performance. However, it is unknown if these acute changes will produce any long-term adaptations to muscle function.

Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique

Science.gov (United States)

Bandaru, Sunith; Deb, Kalyanmoy

2011-09-01

In this article, a methodology is proposed for automatically extracting innovative design principles which make a system or process (subject to conflicting objectives) optimal using its Pareto-optimal dataset. Such 'higher knowledge' would not only help designers to execute the system better, but also enable them to predict how changes in one variable would affect other variables if the system has to retain its optimal behaviour. This in turn would help solve other similar systems with different parameter settings easily without the need to perform a fresh optimization task. The proposed methodology uses a clustering-based optimization technique and is capable of discovering hidden functional relationships between the variables, objective and constraint functions and any other function that the designer wishes to include as a 'basis function'. A number of engineering design problems are considered for which the mathematical structure of these explicit relationships exists and has been revealed by a previous study. A comparison with the multivariate adaptive regression splines (MARS) approach reveals the practicality of the proposed approach due to its ability to find meaningful design principles. The success of this procedure for automated innovization is highly encouraging and indicates its suitability for further development in tackling more complex design scenarios.

Optimization of ciprofloxacin complex loaded PLGA nanoparticles for pulmonary treatment of cystic fibrosis infections: Design of experiments approach.

Science.gov (United States)

Günday Türeli, Nazende; Türeli, Akif Emre; Schneider, Marc

2016-12-30

Design of Experiments (DoE) is a powerful tool for systematic evaluation of process parameters' effect on nanoparticle (NP) quality with minimum number of experiments. DoE was employed for optimization of ciprofloxacin loaded PLGA NPs for pulmonary delivery against Pseudomonas aeruginosa infections in cystic fibrosis (CF) lungs. Since the biofilm produced by bacteria was shown to be a complicated 3D barrier with heterogeneous meshes ranging from 100nm to 500nm, nanoformulations small enough to travel through those channels were assigned as target quality. Nanoprecipitation was realized utilizing MicroJet Reactor (MJR) technology based on impinging jets principle. Effect of MJR parameters flow rate, temperature and gas pressure on particle size and PDI was investigated using Box-Behnken design. The relationship between process parameters and particle quality was demonstrated by constructed fit functions (R 2 =0.9934 p65%. Response surface plots provided experimental data-based understanding of MJR parameters' effect, thus NP quality. Presented work enables ciprofloxacin loaded PLGA nanoparticle preparations with pre-defined quality to fulfill the requirements of local drug delivery under CF disease conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Two-stage discrete-continuous multi-objective load optimization: An industrial consumer utility approach to demand response

International Nuclear Information System (INIS)

Abdulaal, Ahmed; Moghaddass, Ramin; Asfour, Shihab

2017-01-01

Highlights: •Two-stage model links discrete-optimization to real-time system dynamics operation. •The solutions obtained are non-dominated Pareto optimal solutions. •Computationally efficient GA solver through customized chromosome coding. •Modest to considerable savings are achieved depending on the consumer’s preference. -- Abstract: In the wake of today’s highly dynamic and competitive energy markets, optimal dispatching of energy sources requires effective demand responsiveness. Suppliers have adopted a dynamic pricing strategy in efforts to control the downstream demand. This method however requires consumer awareness, flexibility, and timely responsiveness. While residential activities are more flexible and schedulable, larger commercial consumers remain an obstacle due to the impacts on industrial performance. This paper combines methods from quadratic, stochastic, and evolutionary programming with multi-objective optimization and continuous simulation, to propose a two-stage discrete-continuous multi-objective load optimization (DiCoMoLoOp) autonomous approach for industrial consumer demand response (DR). Stage 1 defines discrete-event load shifting targets. Accordingly, controllable loads are continuously optimized in stage 2 while considering the consumer’s utility. Utility functions, which measure the loads’ time value to the consumer, are derived and weights are assigned through an analytical hierarchy process (AHP). The method is demonstrated for an industrial building model using real data. The proposed method integrates with building energy management system and solves in real-time with autonomous and instantaneous load shifting in the hour-ahead energy price (HAP) market. The simulation shows the occasional existence of multiple load management options on the Pareto frontier. Finally, the computed savings, based on the simulation analysis with real consumption, climate, and price data, ranged from modest to considerable amounts

Bioactive Molecule-loaded Drug Delivery Systems to Optimize Bone Tissue Repair.

Science.gov (United States)

Oshiro, Joao Augusto; Sato, Mariana Rillo; Scardueli, Cassio Rocha; Lopes de Oliveira, Guilherme Jose Pimentel; Abucafy, Marina Paiva; Chorilli, Marlus

2017-01-01

Bioactive molecules such as peptides and proteins can optimize the repair of bone tissue; however, the results are often unpredictable when administered alone, owing to their short biological half-life and instability. Thus, the development of bioactive molecule-loaded drug delivery systems (DDS) to repair bone tissue has been the subject of intense research. DDS can optimize the repair of bone tissue owing to their physicochemical properties, which improve cellular interactions and enable the incorporation and prolonged release of bioactive molecules. These characteristics are fundamental to favor bone tissue homeostasis, since the biological activity of these factors depends on how accessible they are to the cell. Considering the importance of these DDS, this review aims to present relevant information on DDS when loaded with osteogenic growth peptide and bone morphogenetic protein. These are bioactive molecules that are capable of modulating the differentiation and proliferation of mesenchymal cells in bone tissue cells. Moreover, we will present different approaches using these peptide and protein-loaded DDS, such as synthetic membranes and scaffolds for bone regeneration, synthetic grafts, bone cements, liposomes, and micelles, which aim at improving the therapeutic effectiveness, and we will compare their advantages with commercial systems. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Optimization of Boiler Control for Improvement of Load Following Capabilities of Existing Power Plants

DEFF Research Database (Denmark)

Mortensen, J. H.; Mølbak, T.; Pedersen, Tom Søndergaard

1997-01-01

An An optimizing control system for improving the load following capabilities of power plant units has been developed. The system is implemented as a complement producing additive control signals to the existing boiler control system, a concept which has various practical advantages in terms...... of implementation and commissioning. The optimizing control system takes into account the multivariable and nonlinear characteristics of the boiler process as a gain-scheduled LQG-controller is utilized. Simulation results indicate that a reduction of steam temperature deviations of about 75% can be obtained.......optimizing control system for improving the load following capabilities of power plant units has been developed. The system is implemented as a complement producing additive control signals to the existing boiler control system, a concept which has various practical advantages in terms of implementation...

Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation

Directory of Open Access Journals (Sweden)

Jafar Jallad

2018-05-01

Full Text Available In a radial distribution network integrated with distributed generation (DG, frequency and voltage instability could occur due to grid disconnection, which would result in an islanded network. This paper proposes an optimal load shedding scheme to balance the electricity demand and the generated power of DGs. The integration of the Firefly Algorithm and Particle Swarm Optimization (FAPSO is proposed for the application of the planned load shedding and under frequency load shedding (UFLS scheme. In planning mode, the hybrid optimization maximizes the amount of load remaining and improves the voltage profile of load buses within allowable limits. Moreover, the hybrid optimization can be used in UFLS scheme to identify the optimal combination of loads that need to be shed from a network in operation mode. In order to assess the capabilities of the hybrid optimization, the IEEE 33-bus radial distribution system and part of the Malaysian distribution network with different types of DGs were used. The response of the proposed optimization method in planning and operation were compared with other optimization techniques. The simulation results confirmed the effectiveness of the proposed hybrid optimization in planning mode and demonstrated that the proposed UFLS scheme is quick enough to restore the system frequency without overshooting in less execution time.

Relationship between Maximum Principle and Dynamic Programming for Stochastic Recursive Optimal Control Problems and Applications

Directory of Open Access Journals (Sweden)

Jingtao Shi

2013-01-01

Full Text Available This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.

Multi-objective/loading optimization for rotating composite flexbeams

Science.gov (United States)

Hamilton, Brian K.; Peters, James R.

1989-01-01

With the evolution of advanced composites, the feasibility of designing bearingless rotor systems for high speed, demanding maneuver envelopes, and high aircraft gross weights has become a reality. These systems eliminate the need for hinges and heavily loaded bearings by incorporating a composite flexbeam structure which accommodates flapping, lead-lag, and feathering motions by bending and twisting while reacting full blade centrifugal force. The flight characteristics of a bearingless rotor system are largely dependent on hub design, and the principal element in this type of system is the composite flexbeam. As in any hub design, trade off studies must be performed in order to optimize performance, dynamics (stability), handling qualities, and stresses. However, since the flexbeam structure is the primary component which will determine the balance of these characteristics, its design and fabrication are not straightforward. It was concluded that: pitchcase and snubber damper representations are required in the flexbeam model for proper sizing resulting from dynamic requirements; optimization is necessary for flexbeam design, since it reduces the design iteration time and results in an improved design; and inclusion of multiple flight conditions and their corresponding fatigue allowables is necessary for the optimization procedure.

Towards Cost and Comfort Based Hybrid Optimization for Residential Load Scheduling in a Smart Grid

Directory of Open Access Journals (Sweden)

Nadeem Javaid

2017-10-01

Full Text Available In a smart grid, several optimization techniques have been developed to schedule load in the residential area. Most of these techniques aim at minimizing the energy consumption cost and the comfort of electricity consumer. Conversely, maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task. Therefore, in this paper, we aim to minimize the electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyse the performance of a traditional dynamic programming (DP technique and two heuristic optimization techniques: genetic algorithm (GA and binary particle swarm optimization (BPSO for residential load management. Based on these techniques, we propose a hybrid scheme named GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi dimensional knapsack is used to ensure that the load of electricity consumer will not escalate during peak hours. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analysed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with GA, BPSO and DP, and validate that the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.

Application of ELD and load forecast in optimal operation of industrial boiler plants equipped with thermal stores

International Nuclear Information System (INIS)

Cao Jiacong

2007-01-01

Optimal operation of industrial boiler plants with objects of high energy efficiency and low fuel cost is still well worth investigating when energy problem becomes a world's concern, for there are a great number of boiler plants serving industries. The optimization of operation is a measure that is less expensive and easier to carry out than many other measures. Economic load dispatch (ELD) is an effective approach to optimal operation of industrial boiler plants. In the paper a newly developed method referred to as the method of minimum-departure model (MDM) is used in the ELD for boiler plants. It is more convenient for carrying out ELD when boiler plants are equipped with thermal energy stores that usually adopt the working mode of optimal segmentation of a daily load curve. In the case of industrial boiler plants, ELD needs a prerequisite, viz., the accurate load forecast, which is performed using artificial neural networks in this paper. A computer program for the optimal operation was completed and applied to an example, which results the minimum daily fuel cost of the whole boiler plant

Preliminary Study on Structural Optimization with Control Variables Using Equivalent Static Loads for Spring-damper Control Systems

International Nuclear Information System (INIS)

Yoo, Nam-sun; Jung, Ui-Jin; Park, Gyung-Jin; Kim, Tai-Kyung

2014-01-01

An optimization method is proposed for the simultaneous design of structural and control systems using the equivalent static loads. In the past researches, the control parameters of such feedback gains are obtained to improve some performance in the steady-state. However, the actuators which have position and velocity feedback gains should be designed to exhibit a good performance in the time domain. In other words, the system analysis should be conducted for the transient-state in dynamic manner. In this research, a new equivalent static loads method is presented to treat the control variables as the design variables. The equivalent static loads (ESLs) set is defined as a static load set which generates the same displacement field as that from dynamic loads at a certain time. The calculated sets of ESLs are applied as multiple loading conditions in the optimization process. Several examples are solved to validate the proposed method

Continuum topology optimization considering uncertainties in load locations based on the cloud model

Science.gov (United States)

Liu, Jie; Wen, Guilin

2018-06-01

Few researchers have paid attention to designing structures in consideration of uncertainties in the loading locations, which may significantly influence the structural performance. In this work, cloud models are employed to depict the uncertainties in the loading locations. A robust algorithm is developed in the context of minimizing the expectation of the structural compliance, while conforming to a material volume constraint. To guarantee optimal solutions, sufficient cloud drops are used, which in turn leads to low efficiency. An innovative strategy is then implemented to enormously improve the computational efficiency. A modified soft-kill bi-directional evolutionary structural optimization method using derived sensitivity numbers is used to output the robust novel configurations. Several numerical examples are presented to demonstrate the effectiveness and efficiency of the proposed algorithm.

Evolution strategy based optimal chiller loading for saving energy

International Nuclear Information System (INIS)

Chang, Y.-C.; Lee, C.-Y.; Chen, C.-R.; Chou, C.-J.; Chen, W.-H.; Chen, W.-H.

2009-01-01

This study employs evolution strategy (ES) to solve optimal chiller loading (OCL) problem. ES overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW-PLR (partial load ratio) curves include convex functions and concave functions simultaneously. The complicated process of evolution by the genetic algorithm (GA) method for solving OCL can also be simplified by the ES method. This study uses the PLR of chiller as the variable to be solved for the decoupled air conditioning system. After analysis and comparison of the case study, it has been concluded that this method not only solves the problems of Lagrangian method and GA method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems

Using Maximal Isometric Force to Determine the Optimal Load for Measuring Dynamic Muscle Power

Science.gov (United States)

Spiering, Barry A.; Lee, Stuart M. C.; Mulavara, Ajitkumar P.; Bentley, Jason R.; Nash, Roxanne E.; Sinka, Joseph; Bloomberg, Jacob J.

2009-01-01

Maximal power output occurs when subjects perform ballistic exercises using loads of 30-50% of one-repetition maximum (1-RM). However, performing 1-RM testing prior to power measurement requires considerable time, especially when testing involves multiple exercises. Maximal isometric force (MIF), which requires substantially less time to measure than 1-RM, might be an acceptable alternative for determining the optimal load for power testing. PURPOSE: To determine the optimal load based on MIF for maximizing dynamic power output during leg press and bench press exercises. METHODS: Twenty healthy volunteers (12 men and 8 women; mean +/- SD age: 31+/-6 y; body mass: 72 +/- 15 kg) performed isometric leg press and bench press movements, during which MIF was measured using force plates. Subsequently, subjects performed ballistic leg press and bench press exercises using loads corresponding to 20%, 30%, 40%, 50%, and 60% of MIF presented in randomized order. Maximal instantaneous power was calculated during the ballistic exercise tests using force plates and position transducers. Repeated-measures ANOVA and Fisher LSD post hoc tests were used to determine the load(s) that elicited maximal power output. RESULTS: For the leg press power test, six subjects were unable to be tested at 20% and 30% MIF because these loads were less than the lightest possible load (i.e., the weight of the unloaded leg press sled assembly [31.4 kg]). For the bench press power test, five subjects were unable to be tested at 20% MIF because these loads were less than the weight of the unloaded aluminum bar (i.e., 11.4 kg). Therefore, these loads were excluded from analysis. A trend (p = 0.07) for a main effect of load existed for the leg press exercise, indicating that the 40% MIF load tended to elicit greater power output than the 60% MIF load (effect size = 0.38). A significant (p . 0.05) main effect of load existed for the bench press exercise; post hoc analysis indicated that the effect of

Optimization of vitamins A and D3 loading in re-assembled casein micelles and effect of loading on stability of vitamin D3 during storage.

Science.gov (United States)

Loewen, Anisa; Chan, Benny; Li-Chan, Eunice C Y

2018-02-01

The objectives of this study were to apply response surface methodology to optimize fat-soluble vitamin loading in re-assembled casein micelles, and to evaluate vitamin D stability of dry formulations during ambient or accelerated storage and in fortified fluid skim milk stored under refrigeration. Optimal loading of vitamin A (1.46-1.48mg/100mgcasein) was found at 9.7mM phosphate, 5.5mM citrate and 30.0mM calcium, while optimal loading of vitamin D (1.38-1.46mg/100mg casein) was found at 4.9mM phosphate, 4.0mM citrate and 26.1mM calcium. In general, more vitamin D was retained in vitamin D-re-assembled casein micelles than control powders during storage, while vitamin D loss was not different for vitamin D-re-assembled casein micelles and control fortified milks after 21days of refrigerated storage with light exposure. In conclusion, re-assembled casein micelles with high loading efficiency show promise for improving vitamin D stability during dry storage. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Optimization of Boiler Control to Improve the Load-following Capability of Power-plant Units

DEFF Research Database (Denmark)

Mortensen, J. H.; Mølbak, T.; Andersen, Palle

The capability to perform fast load changes has been an important issue in the power market, and will become increasingly more so due to the incresing commercialisation of the European power market. An optimizing control system for improving the load-following capability of power-plant units has...... tests on a 265 MW coal-fired power-plant unit reveals that the maximum allowable load gradient that can be imposed on the plant, can be increased from 4 MW/min. to 8 MW/min....

Optimization of Boiler Control to Improve the Load-following Capability of Power-plant Units

DEFF Research Database (Denmark)

Mortensen, J. H.; Mølbak, T.; Andersen, Palle

1998-01-01

The capability to perform fast load changes has been an important issue in the power market, and will become increasingly more so due to the incresing commercialisation of the European power market. An optimizing control system for improving the load-following capability of power-plant units has...... tests on a 265 MW coal-fired power-plant unit reveals that the maximum allowable load gradient that can be imposed on the plant, can be increased from 4 MW/min. to 8 MW/min....

Loading pattern optimization with maximum utilization of discharging fuel employing adaptively constrained discontinuous penalty function

International Nuclear Information System (INIS)

Park, T. K.; Joo, H. G.; Kim, C. H.

2010-01-01

In order to find the most economical loading pattern (LP) considering multi-cycle fuel loading, multi-objective fuel LP optimization problems are examined by employing an adaptively constrained discontinuous penalty function (ACDPF) method. This is an improved method to simplify the complicated acceptance logic of the original DPF method in that the stochastic effects caused by the different random number sequence can be reduced. The effectiveness of the multi-objective simulated annealing (SA) algorithm employing ACDPF is examined for the reload core LP of Cycle 4 of Yonggwang Nuclear Unit 4. Several optimization runs are performed with different numbers of objectives consisting of cycle length and average burnup of fuels to be discharged or reloaded. The candidate LPs obtained from the multi-objective optimization runs turn out to be better than the reference LP in the aspects of cycle length and utilization of given fuels. It is note that the proposed ACDPF based MOSA algorithm can be a practical method to obtain an economical LP considering multi-cycle fuel loading. (authors)

Optimization strategies for cask design and container loading in long term spent fuel storage

International Nuclear Information System (INIS)

2006-12-01

As delays are incurred in implementing reprocessing and in planning for geologic repositories, storage of increasing quantities of spent fuel for extended durations is becoming a growing reality. Accordingly, effective management of spent fuel continues to be a priority topic. In response, the IAEA has organized a series of meetings to identify cask loading optimisation issues in preparation for a technical publication on Optimization Strategies for Cask/Container Loading in Long Term Spent Fuel Storage. This publication outlines the optimisation process for cask design, licensing and utilization, describing three principal groups of optimization activities in terms of relevant technical considerations such as criticality, shielding, structural design, operations, maintenance and retrievability. The optimization process for cask design, licensing, and utilization is outlined. The general objectives for the design of storage casks, including storage casks that are intended to be transportable, are summarized. The nature of optimization within the design process is described. The typical regulatory and licensing process is outlined, focusing on the roles of safety regulations, the regulator, and the designer/applicant in the optimization process. Based on the foregoing, a description of the three principal groups of optimization activities is provided. The subsequent chapters of this document then describe the specific optimization activities within these three activity groups, in each of the several design disciplines

Aripiprazole loaded poly(caprolactone) nanoparticles: Optimization and in vivo pharmacokinetics

Energy Technology Data Exchange (ETDEWEB)

Sawant, Krutika; Pandey, Abhijeet; Patel, Sneha

2016-09-01

In the present investigation, a Quality by Design strategy was applied for formulation and optimization of aripiprazole (APZ) loaded PCL nanoparticles (APNPs) using nanoprecipitation method keeping entrapment efficiency (%EE) and particle size (PS) as critical quality attributes. Establishment of design space was done followed by analysis of its robustness and sensitivity. Characterization of optimized APNPs was done using DSC, FT-IR, PXRD and TEM studies and was evaluated for drug release, hemocompatibility and nasal toxicity. PS, zeta potential and %EE of optimized APNPs were found to be 199.2 ± 5.65 nm, − 21.4 ± 4.6 mV and 69.2 ± 2.34% respectively. In vitro release study showed 90 ± 2.69% drug release after 8 h. Nasal toxicity study indicated safety of developed formulation for intranasal administration. APNPs administered via intranasal route facilitated the brain distribution of APZ incorporated with the AUC{sub 0→8} in rat brain approximately 2 times higher than that of APNPs administered via intravenous route. Increase in C{sub max} was observed which might help in dose reduction along with reduction in dose related side effects. The results of the study indicate that intranasally administered APZ loaded PCL NPs can potentially transport APZ via nose to brain and can serve as a non-invasive alternative for the delivery of APZ to brain. - Highlights: • It explores intra-nasal route for treatment of schizophrenia. • Quality by Design strategy has been used for optimization and assessesment of design space robustness. • PCL nanoparticles enhance penetration of drug into brain leading to increased C{sub max} and decrease in T{sub max}. • It can act as potential platform for treatment of schizophrenia with decreased dose related toxicities.

Research reactor loading pattern optimization using estimation of distribution algorithms

International Nuclear Information System (INIS)

Jiang, S.; Ziver, K.; Carter, J. N.; Pain, C. C.; Eaton, M. D.; Goddard, A. J. H.; Franklin, S. J.; Phillips, H. J.

2006-01-01

A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K eff ) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K eff with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristic Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)

Energy-aware hybrid fruitfly optimization for load balancing in cloud environments for EHR applications

Directory of Open Access Journals (Sweden)

M. Lawanyashri

Full Text Available Cloud computing has gained precise attention from the research community and management of IT, due to its scalable and dynamic capabilities. It is evolving as a vibrant technology to modernize and restructure healthcare organization to provide best services to the consumers. The rising demand for healthcare services and applications in cloud computing leads to the imbalance in resource usage and drastically increases the power consumption resulting in high operating cost. To achieve fast execution time and optimum utilization of the virtual machines, we propose a multi-objective hybrid fruitfly optimization technique based on simulated annealing to improve the convergence rate and optimization accuracy. The proposed approach is used to achieve the optimal resource utilization and reduces the energy consumption and cost in cloud computing environment. The result attained in our proposed technique provides an improved solution. The experimental results show that the proposed algorithm efficiently outperforms compared to the existing load balancing algorithms. Keywords: Cloud computing, Electronic Health Records (EHR, Load balancing, Fruitfly Optimization Algorithm (FOA, Simulated Annealing (SA, Energy consumption

Optimization of composite sandwich cover panels subjected to compressive loadings

Science.gov (United States)

Cruz, Juan R.

1991-01-01

An analysis and design method is presented for the design of composite sandwich cover panels that include the transverse shear effects and damage tolerance considerations. This method is incorporated into a sandwich optimization computer program entitled SANDOP. As a demonstration of its capabilities, SANDOP is used in the present study to design optimized composite sandwich cover panels for for transport aircraft wing applications. The results of this design study indicate that optimized composite sandwich cover panels have approximately the same structural efficiency as stiffened composite cover panels designed to satisfy individual constraints. The results also indicate that inplane stiffness requirements have a large effect on the weight of these composite sandwich cover panels at higher load levels. Increasing the maximum allowable strain and the upper percentage limit of the 0 degree and +/- 45 degree plies can yield significant weight savings. The results show that the structural efficiency of these optimized composite sandwich cover panels is relatively insensitive to changes in core density. Thus, core density should be chosen by criteria other than minimum weight (e.g., damage tolerance, ease of manufacture, etc.).

Experimental design and optimization of raloxifene hydrochloride loaded nanotransfersomes for transdermal application

Directory of Open Access Journals (Sweden)

Mahmood S

2014-09-01

Full Text Available Syed Mahmood, Muhammad Taher, Uttam Kumar Mandal Department of Pharmaceutical Technology, Kulliyyah of Pharmacy, International Islamic University Malaysia (IIUM, Pahang Darul Makmur, Malaysia Abstract: Raloxifene hydrochloride, a highly effective drug for the treatment of invasive breast cancer and osteoporosis in post-menopausal women, shows poor oral bioavailability of 2%. The aim of this study was to develop, statistically optimize, and characterize raloxifene hydrochloride-loaded transfersomes for transdermal delivery, in order to overcome the poor bioavailability issue with the drug. A response surface methodology experimental design was applied for the optimization of transfersomes, using Box-Behnken experimental design. Phospholipon® 90G, sodium deoxycholate, and sonication time, each at three levels, were selected as independent variables, while entrapment efficiency, vesicle size, and transdermal flux were identified as dependent variables. The formulation was characterized by surface morphology and shape, particle size, and zeta potential. Ex vivo transdermal flux was determined using a Hanson diffusion cell assembly, with rat skin as a barrier medium. Transfersomes from the optimized formulation were found to have spherical, unilamellar structures, with a ­homogeneous distribution and low polydispersity index (0.08. They had a particle size of 134±9 nM, with an entrapment efficiency of 91.00%±4.90%, and transdermal flux of 6.5±1.1 µg/cm2/hour. Raloxifene hydrochloride-loaded transfersomes proved significantly superior in terms of amount of drug permeated and deposited in the skin, with enhancement ratios of 6.25±1.50 and 9.25±2.40, respectively, when compared with drug-loaded conventional liposomes, and an ethanolic phosphate buffer saline. Differential scanning calorimetry study revealed a greater change in skin structure, compared with a control sample, during the ex vivo drug diffusion study. Further, confocal laser

Concurrent material-fabrication optimization of metal-matrix laminates under thermo-mechanical loading

Science.gov (United States)

Saravanos, D. A.; Morel, M. R.; Chamis, C. C.

1991-01-01

A methodology is developed to tailor fabrication and material parameters of metal-matrix laminates for maximum loading capacity under thermomechanical loads. The stresses during the thermomechanical response are minimized subject to failure constrains and bounds on the laminate properties. The thermomechanical response of the laminate is simulated using nonlinear composite mechanics. Evaluations of the method on a graphite/copper symmetric cross-ply laminate were performed. The cross-ply laminate required different optimum fabrication procedures than a unidirectional composite. Also, the consideration of the thermomechanical cycle had a significant effect on the predicted optimal process.

Optimal Operation Method of Smart House by Controllable Loads based on Smart Grid Topology

Science.gov (United States)

Yoza, Akihiro; Uchida, Kosuke; Yona, Atsushi; Senju, Tomonobu

2013-08-01

From the perspective of global warming suppression and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all electrification apartment house or residence such as DC smart house have increased in recent years. However, due to fluctuating power from renewable energy sources and loads, supply-demand balancing fluctuations of power system become problematic. Therefore, "smart grid" has become very popular in the worldwide. This article presents a methodology for optimal operation of a smart grid to minimize the interconnection point power flow fluctuations. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuations, it is possible to reduce the maximum electric power consumption and the electric cost. This system consists of photovoltaics generator, heat pump, battery, solar collector, and load. In order to verify the effectiveness of the proposed system, MATLAB is used in simulations.

Optimization of methazolamide-loaded solid lipid nanoparticles for ophthalmic delivery using Box-Behnken design.

Science.gov (United States)

Wang, Fengzhen; Chen, Li; Jiang, Sunmin; He, Jun; Zhang, Xiumei; Peng, Jin; Xu, Qunwei; Li, Rui

2014-09-01

The purpose of the present study was to optimize methazolamide (MTZ)-loaded solid lipid nanoparticles (SLNs) which were used as topical eye drops by evaluating the relationship between design factors and experimental data. A three factor, three-level Box-Behnken design (BBD) was used for the optimization procedure, choosing the amount of GMS, the amount of phospholipid, the concentration of surfactant as the independent variables. The chosen dependent variables were entrapment efficiency, dosage loading, and particle size. The generated polynomial equations and response surface plots were used to relate the dependent and independent variables. The optimal nanoparticles were formulated with 100 mg GMS, 150 mg phospholipid, and 1% Tween80 and PEG 400 (1:1, w/v). A new formulation was prepared according to these levels. The observed responses were close to the predicted values of the optimized formulation. The particle size was 197.8 ± 4.9 nm. The polydispersity index of particle size was 0.239 ± 0.01 and the zeta potential was 32.7 ± 2.6 mV. The entrapment efficiency and dosage loading were about 68.39% and 2.49%, respectively. Fourier transform infrared spectroscopy (FT-IR) study indicated that the drug was entrapped in nanoparticles. The optimized formulation showed a sustained release followed the Peppas model. MTZ-SLNs showed significant prolonged decreasing intraocular pressure effect comparing with MTZ solution in vivo pharmacodynamics studies. The results of acute eye irritation study indicated that MTZ-SLNs and AZOPT both had no eye irritation. Furthermore, the MTZ-SLNs were suitable to be stored at low temperature (4 °C).

Formulation and Optimization of Multiparticulate Drug Delivery System Approach for High Drug Loading.

Science.gov (United States)

Shah, Neha; Mehta, Tejal; Gohel, Mukesh

2017-08-01

The aim of the present work was to develop and optimize multiparticulate formulation viz. pellets of naproxen by employing QbD and risk assessment approach. Mixture design with extreme vertices was applied to the formulation with high loading of drug (about 90%) and extrusion-spheronization as a process for manufacturing pellets. Independent variables chosen were level of microcrystalline cellulose (MCC)-X 1 , polyvinylpyrrolidone K-90 (PVP K-90)-X 2 , croscarmellose sodium (CCS)-X 3 , and polacrilin potassium (PP)-X 4 . Dependent variables considered were disintegration time (DT)-Y 1 , sphericity-Y 2 , and percent drug release-Y 3 . The formulation was optimized based on the batches generated by MiniTab 17 software. The batch with maximum composite desirability (0.98) proved to be optimum. From the evaluation of design batches, it was observed that, even in low variation, the excipients affect the pelletization property of the blend and also the final drug release. In conclusion, pellets with high drug loading can be effectively manufactured and optimized systematically using QbD approach.

Optimal control of a fuel cell/wind/PV/grid hybrid system with thermal heat pump load

CSIR Research Space (South Africa)

Sichilalu, S

2016-10-01

Full Text Available This paper presents an optimal energy management strategy for a grid-tied photovoltaic–wind-fuel cell hybrid power supply system. The hybrid system meets the load demand consisting of an electrical load and a heat pump water heater supplying thermal...

Loading pattern calculated by inverse optimization vs traditional dosimetry systems of intracavitary brachytherapy of cervical cancer: a dosimetric study

International Nuclear Information System (INIS)

Jamema, S.V.; Deshpande, D.D.; Kirisits, C.; Trnkova, P.; Poetter, R.; Mahantshetty, U.; Shrivastava, S.K.; Dinshaw, K.A.

2008-01-01

In the recent past, inverse planning algorithms were introduced for intracavitary brachytherapy planning (ICBT) for cervical cancer. The loading pattern of these algorithms in comparison with traditional systems may not be similar. The purpose of this study was to objectively compare the loading patterns of traditional systems with the inverse optimization. Based on the outcome of the comparison, an attempt was made to obtain a loading pattern that takes into account the experience made with the inverse optimization

Microeconomic principles explain an optimal genome size in bacteria.

Science.gov (United States)

Ranea, Juan A G; Grant, Alastair; Thornton, Janet M; Orengo, Christine A

2005-01-01

Bacteria can clearly enhance their survival by expanding their genetic repertoire. However, the tight packing of the bacterial genome and the fact that the most evolved species do not necessarily have the biggest genomes suggest there are other evolutionary factors limiting their genome expansion. To clarify these restrictions on size, we studied those protein families contributing most significantly to bacterial-genome complexity. We found that all bacteria apply the same basic and ancestral 'molecular technology' to optimize their reproductive efficiency. The same microeconomics principles that define the optimum size in a factory can also explain the existence of a statistical optimum in bacterial genome size. This optimum is reached when the bacterial genome obtains the maximum metabolic complexity (revenue) for minimal regulatory genes (logistic cost).

Optimization, formulation, and characterization of multiflavonoids-loaded flavanosome by bulk or sequential technique

Directory of Open Access Journals (Sweden)

Karthivashan G

2016-07-01

Full Text Available Govindarajan Karthivashan,1 Mas Jaffri Masarudin,2 Aminu Umar Kura,1 Faridah Abas,3,4 Sharida Fakurazi1,5 1Laboratory of Vaccines and Immunotherapeutics, Institute of Bioscience, 2Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular Sciences, 3Department of Food Science, Faculty of Food Science and Technology, 4Laboratory of Natural Products, Institute of Bioscience, 5Department of Human Anatomy, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia Abstract: This study involves adaptation of bulk or sequential technique to load multiple flavonoids in a single phytosome, which can be termed as “flavonosome”. Three widely established and therapeutically valuable flavonoids, such as quercetin (Q, kaempferol (K, and apigenin (A, were quantified in the ethyl acetate fraction of Moringa oleifera leaves extract and were commercially obtained and incorporated in a single flavonosome (QKA–phosphatidylcholine through four different methods of synthesis – bulk (M1 and serialized (M2 co-sonication and bulk (M3 and sequential (M4 co-loading. The study also established an optimal formulation method based on screening the synthesized flavonosomes with respect to their size, charge, polydispersity index, morphology, drug–carrier interaction, antioxidant potential through in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics, and cytotoxicity evaluation against human hepatoma cell line (HepaRG. Furthermore, entrapment and loading efficiency of flavonoids in the optimal flavonosome have been identified. Among the four synthesis methods, sequential loading technique has been optimized as the best method for the synthesis of QKA–phosphatidylcholine flavonosome, which revealed an average diameter of 375.93±33.61 nm, with a zeta potential of -39.07±3.55 mV, and the entrapment efficiency was >98% for all the flavonoids, whereas the drug-loading capacity of Q, K, and A was 31.63%±0

Optimal planning in a developing industrial microgrid with sensitive loads

Directory of Open Access Journals (Sweden)

M. Naderi

2017-11-01

Full Text Available Computer numerical control (CNC machines are known as sensitive loads in industrial estates. These machines require reliable and qualified electricity in their often long work periods. Supplying these loads with distributed energy resources (DERs in a microgrid (MG can be done as an appropriate solution. The aim of this paper is to analyze the implementation potential of a real and developing MG in Shad-Abad industrial estate, Tehran, Iran. Three MG planning objectives are considered including assurance of sustainable and secure operation of CNC machines as sensitive loads, minimizing the costs of MG construction and operation, and using available capacities to penetrate the highest possible renewable energy sources (RESs which subsequently results in decreasing the air pollutants specially carbon dioxide (CO2. The HOMER (hybrid optimization model for electric renewable software is used to specify the technical feasibility of MG planning and to select the best plan economically and environmentally. Different scenarios are considered in this regard to determine suitable capacity of production participants, and to assess the MG indices such as the reliability.

The Effects of Social Cue Principles on Cognitive Load, Situational Interest, Motivation, and Achievement in Pedagogical Agent Multimedia Learning

Science.gov (United States)

Park, Sanghoon

2015-01-01

Animated pedagogical agents have become popular in multimedia learning with combined delivery of verbal and non-verbal forms of information. In order to reduce unnecessary cognitive load caused by such multiple forms of information and also to foster generative cognitive processing, multimedia design principles with social cues are suggested…

Optimization principles for preparation methods and properties of fine ferrite materials

Science.gov (United States)

Borisova, N. M.; Golubenko, Z. V.; Kuz'micheva, T. G.; Ol'khovik, L. P.; Shabatin, V. P.

1992-08-01

The paper is devoted to the problems of development of fine materials based on Ba-ferrite for vertical magnetic recording in particular. Taking an analogue — BaFe 12-2 xCo xTe xO 19 — we have optimized the melt co-precipitation method and shown a new opportunity to provide chemical homogeneity of microcrystallites by means of cryotechnology. Magnetic characteristics of the magnetic tape experimental sample for digital video recording are presented. A series of principles of consistent control of ferrite powder properties are formulated and illustrated with specific developments.

Research reactor loading pattern optimization using estimation of distribution algorithms

Energy Technology Data Exchange (ETDEWEB)

Jiang, S. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); Ziver, K. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); AMCG Group, RM Consultants, Abingdon (United Kingdom); Carter, J. N.; Pain, C. C.; Eaton, M. D.; Goddard, A. J. H. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); Franklin, S. J.; Phillips, H. J. [Imperial College, Reactor Centre, Silwood Park, Buckhurst Road, Ascot, Berkshire, SL5 7TE (United Kingdom)

2006-07-01

A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K{sub eff}) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K{sub eff} with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristic Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)

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

Science.gov (United States)

Komoda, M.

1976-01-01

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

Optimization of reload core design for PWR

International Nuclear Information System (INIS)

Shen Wei; Xie Zhongsheng; Yin Banghua

1995-01-01

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

Curcumin-loaded mixed micelles: preparation, optimization, physicochemical properties and cytotoxicity in vitro.

Science.gov (United States)

Duan, Yuwei; Wang, Juan; Yang, Xiaoye; Du, Hongliang; Xi, Yanwei; Zhai, Guangxi

2015-01-01

Although curcumin (CUR) can inhibit proliferation and induce apoptosis of tumors, the poor water solubility restricted its clinical application. The aim of this study was to improve the aqueous solubility of CUR and make more favorable changes to bioactivity by preparing curcumin-loaded phospholipid-sodium deoxycholate-mixed micelles (CUR-PC-SDC-MMs). CUR-PC-SDC-MMs were prepared by the thin-film dispersion method. Based on the results of single factor exploration, the preparation technology was optimized using the central composite design-response surface methodology with drug loading and entrapment efficiency (EE%) as indicators. The images of transmission electron microscopy showed that the optimized CUR-PC-SDC-MMs were spherical and well dispersed. The average size of the mixed micelles was 66.5 nm, the zeta potential was about -26.96 mV and critical micelle concentration was 0.0087 g/l. CUR was encapsulated in PC-SDC-MMs with loading capacity of 13.12%, EE% of 87.58%, and the solubility of CUR in water was 3.14 mg/ml. The release results in vitro showed that the mixed micelles presented sustained release behavior compared to the propylene glycol solution of CUR. The IC50 values of CUR-loaded micelles and free drug in human breast carcinoma cell lines were 4.10 μg/ml and 6.93 µg/ml, respectively. It could be concluded from the above results that the CUR-PC-SDC-MMs system might serve as a promising nanocarrier to improve the solubility and bioactivity of CUR.

Efficiency Optimization Methods in Low-Power High-Frequency Digitally Controlled SMPS

Directory of Open Access Journals (Sweden)

Aleksandar Prodić

2010-06-01

Full Text Available This paper gives a review of several power efficiency optimization techniques that are utilizing advantages of emerging digital control in high frequency switch-mode power supplies (SMPS, processing power from a fraction of watt to several hundreds of watts. Loss mechanisms in semiconductor components are briefly reviewed and the related principles of online efficiency optimization through power stage segmentation and gate voltage variation presented. Practical implementations of such methods utilizing load prediction or data extraction from a digital control loop are shown. The benefits of the presented efficiency methods are verified through experimental results, showing efficiency improvements, ranging from 2% to 30%,depending on the load conditions.

EPR: High load variation performances with the 'Tmode' core control

International Nuclear Information System (INIS)

Grossetete, A.

2008-01-01

The load variation performances on a PWR are directly linked to the core control design. This design is mainly characterized by the definition of the control rod banks and the way to both perform the banks movements and to modify the core boron concentration by injection of boric acid or water. The following paper presents the principles of the T mode, the new fully automatic core control mode for the EPR which provides high performance in terms of maneuverability and optimizes the effluents. First, the paper describes the division of the control rods into two control banks (Pbank for temperature and Hbank for power distribution). Then typical movements of these banks during power changes are shown. Then, the principle of the 3 control loops (Tave, AO, Pmax), used to obtain these desired control rod movements, is given. Finally, a load following transient simulation is presented. (authors)

EPR: high load variation performances with the 'TMODE' core control

International Nuclear Information System (INIS)

Pairot, Frederic

2008-01-01

The load variation performances on a PWR are directly linked to the core control design. This design is mainly characterized by the definition of the control rod banks and the way to both perform the banks movements and to modify the core boron concentration by injection of boric acid or water. The following paper presents the principles of the T mode, the new fully automatic core control mode for the EPR which provides high performance in terms of maneuverability and optimizes the effluents. First, the paper describes the division of the control rods into two control banks (Pbank for temperature and Hbank for power distribution). Then typical movements of these banks during power changes are shown. Then, the principle of the 3 control loops (Tave, AO, Pmax), used to obtain these desired control rod movements, is given. Finally, a load following transient simulation is presented. (author)

Short-Term Fuzzy Load Forecasting Model Using Genetic–Fuzzy and Ant Colony–Fuzzy Knowledge Base Optimization

Directory of Open Access Journals (Sweden)

Murat Luy

2018-05-01

Full Text Available The estimation of hourly electricity load consumption is highly important for planning short-term supply–demand equilibrium in sources and facilities. Studies of short-term load forecasting in the literature are categorized into two groups: classical conventional and artificial intelligence-based methods. Artificial intelligence-based models, especially when using fuzzy logic techniques, have more accurate load estimations when datasets include high uncertainty. However, as the knowledge base—which is defined by expert insights and decisions—gets larger, the load forecasting performance decreases. This study handles the problem that is caused by the growing knowledge base, and improves the load forecasting performance of fuzzy models through nature-inspired methods. The proposed models have been optimized by using ant colony optimization and genetic algorithm (GA techniques. The training and testing processes of the proposed systems were performed on historical hourly load consumption and temperature data collected between 2011 and 2014. The results show that the proposed models can sufficiently improve the performance of hourly short-term load forecasting. The mean absolute percentage error (MAPE of the monthly minimum in the forecasting model, in terms of the forecasting accuracy, is 3.9% (February 2014. The results show that the proposed methods make it possible to work with large-scale rule bases in a more flexible estimation environment.

Improving the principles of short-term electric load forecasting of the Irkutsk region

Directory of Open Access Journals (Sweden)

Kornilov Vladimir

2017-01-01

Full Text Available Forecasting of electric load (EL is an important task for both electric power entities and large consumers of electricity [1]. Large consumers are faced with the need to compose applications for the planned volume of EL, and the deviation of subsequent real consumption from previously announced leads to the appearance of penalties from the wholesale market. In turn, electricity producers are interested in forecasting the demand for electricity for prompt response to its fluctuations and for the purpose of optimal infrastructure development. The most difficult and urgent task is the hourly forecasting of EL, which is extremely important for the successful solution of problems of optimization of generating capacities, minimization of power losses, dispatching control, security assessment of power supply, etc. Ultimately, such forecasts allow optimizing the cash costs for electricity and fuel or water consumption during generation. This paper analyzes the experience of the branch of JSC "SO UPS" Irkutsk Regional Dispatch Office of the procedure for short-term forecasting of the EL of the Irkutsk region.

Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction

Directory of Open Access Journals (Sweden)

Changbin Hu

2015-02-01

Full Text Available According to the topological structure of wind-storage-load complementation microgrids, this paper proposes a method for energy coordinative optimization which focuses on improvement of the economic benefits of microgrids in the prediction framework. First of all, the external characteristic mathematical model of distributed generation (DG units including wind turbines and storage batteries are established according to the requirements of the actual constraints. Meanwhile, using the minimum consumption costs from the external grid as the objective function, a grey prediction model with residual modification is introduced to output the predictive wind turbine power and load at specific periods. Second, based on the basic framework of receding horizon optimization, an intelligent genetic algorithm (GA is applied to figure out the optimum solution in the predictive horizon for the complex non-linear coordination control model of microgrids. The optimum results of the GA are compared with the receding solution of mixed integer linear programming (MILP. The obtained results show that the method is a viable approach for energy coordinative optimization of microgrid systems for energy flow and reasonable schedule. The effectiveness and feasibility of the proposed method is verified by examples.

Optimization and public radiation exposure. Some problems in principle and practice

International Nuclear Information System (INIS)

Mitchell, N.T.

1979-01-01

In its 1977 recommendations the International Commission on Radiological Protection has laid particular emphasis on application of the principle of optimization in setting controls on the disposal of radioactive wastes that will result in radiation exposure to the public. This principle has been followed in the UK for a long time though it is only recently that it has been possible to apply an even semiquantitative technique in its application. The paper examines the principles of differential cost-benefit analysis and discusses problems in applying this technique. Consideration is given to the assessment of parameter values to be used in the differential cost-benefit equation, these being protection costs, collective dose commitment (and, from it, health detriment) and the more difficult process of attaching a cost to social detriment. Finally, the application of the technique in practice is discussed by illustration of experience gained in the control of liquid effluents from nuclear power stations and a fuel reprocessing plant. It is found that despite the complexity of the technique and the technical difficulties in estimation of many of the parameter values, especially detriment, differential cost-benefit analysis fills a useful if limited role. However, a great many value judgements, some of them implicit in developing data to put into the overall equation, are still required. (author)

Algorithmic Principles of Mathematical Programming

NARCIS (Netherlands)

Faigle, Ulrich; Kern, Walter; Still, Georg

2002-01-01

Algorithmic Principles of Mathematical Programming investigates the mathematical structures and principles underlying the design of efficient algorithms for optimization problems. Recent advances in algorithmic theory have shown that the traditionally separate areas of discrete optimization, linear

Comparison of particle swarm optimization and dynamic programming for large scale hydro unit load dispatch

International Nuclear Information System (INIS)

Cheng Chuntian; Liao Shengli; Tang Zitian; Zhao Mingyan

2009-01-01

Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.

Comparison of particle swarm optimization and dynamic programming for large scale hydro unit load dispatch

Energy Technology Data Exchange (ETDEWEB)

Cheng Chuntian, E-mail: ctcheng@dlut.edu.c [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Liao Shengli; Tang Zitian [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Zhao Mingyan [Department of Environmental Science and Engineering, Tsinghua University, 100084 Beijing (China)

2009-12-15

Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.

Comparison of particle swarm optimization and dynamic programming for large scale hydro unit load dispatch

Energy Technology Data Exchange (ETDEWEB)

Chun-tian Cheng; Sheng-li Liao; Zi-Tian Tang [Dept. of Civil and Hydraulic Engineering, Dalian Univ. of Technology, 116024 Dalian (China); Ming-yan Zhao [Dept. of Environmental Science and Engineering, Tsinghua Univ., 100084 Beijing (China)

2009-12-15

Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations. (author)

Optimal Waste Load Allocation Using Multi-Objective Optimization and Multi-Criteria Decision Analysis

Directory of Open Access Journals (Sweden)

L. Saberi

2016-10-01

Full Text Available Introduction: Increasing demand for water, depletion of resources of acceptable quality, and excessive water pollution due to agricultural and industrial developments has caused intensive social and environmental problems all over the world. Given the environmental importance of rivers, complexity and extent of pollution factors and physical, chemical and biological processes in these systems, optimal waste-load allocation in river systems has been given considerable attention in the literature in the past decades. The overall objective of planning and quality management of river systems is to develop and implement a coordinated set of strategies and policies to reduce or allocate of pollution entering the rivers so that the water quality matches by proposing environmental standards with an acceptable reliability. In such matters, often there are several different decision makers with different utilities which lead to conflicts. Methods/Materials: In this research, a conflict resolution framework for optimal waste load allocation in river systems is proposed, considering the total treatment cost and the Biological Oxygen Demand (BOD violation characteristics. There are two decision-makers inclusive waste load discharges coalition and environmentalists who have conflicting objectives. This framework consists of an embedded river water quality simulator, which simulates the transport process including reaction kinetics. The trade-off curve between objectives is obtained using the Multi-objective Particle Swarm Optimization Algorithm which these objectives are minimization of the total cost of treatment and penalties that must be paid by discharges and a violation of water quality standards considering BOD parameter which is controlled by environmentalists. Thus, the basic policy of river’s water quality management is formulated in such a way that the decision-makers are ensured their benefits will be provided as far as possible. By using MOPSO

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

Directory of Open Access Journals (Sweden)

Chong Chen

2018-04-01

Full Text Available In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP, and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL, are still imperfect, which make it difficult for the active distribution network (ADN to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.

The Optimization dispatching of Micro Grid Considering Load Control

Science.gov (United States)

Zhang, Pengfei; Xie, Jiqiang; Yang, Xiu; He, Hongli

2018-01-01

This paper proposes an optimization control of micro-grid system economy operation model. It coordinates the new energy and storage operation with diesel generator output, so as to achieve the economic operation purpose of micro-grid. In this paper, the micro-grid network economic operation model is transformed into mixed integer programming problem, which is solved by the mature commercial software, and the new model is proved to be economical, and the load control strategy can reduce the charge and discharge times of energy storage devices, and extend the service life of the energy storage device to a certain extent.

Enhanced method of fast re-routing with load balancing in software-defined networks

Science.gov (United States)

Lemeshko, Oleksandr; Yeremenko, Oleksandra

2017-11-01

A two-level method of fast re-routing with load balancing in a software-defined network (SDN) is proposed. The novelty of the method consists, firstly, in the introduction of a two-level hierarchy of calculating the routing variables responsible for the formation of the primary and backup paths, and secondly, in ensuring a balanced load of the communication links of the network, which meets the requirements of the traffic engineering concept. The method provides implementation of link, node, path, and bandwidth protection schemes for fast re-routing in SDN. The separation in accordance with the interaction prediction principle along two hierarchical levels of the calculation functions of the primary (lower level) and backup (upper level) routes allowed to abandon the initial sufficiently large and nonlinear optimization problem by transiting to the iterative solution of linear optimization problems of half the dimension. The analysis of the proposed method confirmed its efficiency and effectiveness in terms of obtaining optimal solutions for ensuring balanced load of communication links and implementing the required network element protection schemes for fast re-routing in SDN.

Numerical investigation of optimal yaw misalignment and collective pitch angle for load imbalance reduction of rigid and flexible HAWT blades under sheared inflow

International Nuclear Information System (INIS)

Jeong, Min-Soo; Cha, Myung-Chan; Kim, Sang-Woo; Lee, In

2015-01-01

Wind shear can strongly influence the cyclic loading on horizontal axis wind turbine blades. These load fluctuation causes a variation of power output and introduces fatigue load. Thus, individual pitch controllers have been developed that are focused on the load alleviations, however, comes at a price of actuator requirements for control. Moreover, these controllers are unable to apply to already existing wind turbines with active yaw and collective pitch control system. Therefore, the investigations for minimizing load imbalance through the adjustments of yaw misalignment and collective pitch angle are implemented for the rigid and flexible blades under the sheared inflow. By applying the optimization process based on a sequential quadratic programming approach, the optimal yaw and pitch angle can be estimated. Then, the numerical simulations for predicting the performance are performed. The results showed that the fluctuation range of the root flapwise bending moment for the rigid blades can be reduced by 84.5%, whereas the vibratory bending moment for the flexible blades can be reduced by up to approximately 82.4% in the best case. Therefore, the magnitudes of load imbalance can be minimized by the adjustment of the optimal yaw misalignment and collective pitch angle without any power loss. - Highlights: • We propose a novel method for the reduction of load imbalance under sheared inflow. • We estimate optimal yaw misalignment and collective pitch angle through optimization. • Numerical results of performance are predicted for rigid and flexible blades. • By applying optimal angles, load variations are reduced without any power loss

Performance of an optimally contact-cooled high-heat-load mirror at the APS

International Nuclear Information System (INIS)

Cai, Z.; Khounsary, A.; Lai, B.; McNulty, I.; Yun, W.

1998-01-01

X-ray undulator beamlines at third-generation synchrotrons facilities use either a monochromator or a mirror as the first optical element. In this paper, the thermal and optical performance of an optimally designed contact-cooled high-heat-load x-ray mirror used as the first optical element on the 2ID undulator beamline at the Advanced Photon Source (APS) is reported. It is shown that this simple and economical mirror design can comfortably handle the high heat load of undulator beamlines and provide good performance with long-term reliability and ease of operation. Availability and advantages of such mirrors can make the mirror-first approach to high-heat-load beamline design an attractive alternative to monochromator-first beamlines in many circumstances

Optimization of Boiler Control to Improve the Load-following Capability of Power-plant Units

OpenAIRE

Mortensen, J. H.; Mølbak, T.; Andersen, Palle; Pedersen, Tom Søndergaard

1998-01-01

The capability to perform fast load changes has been an important issue in the power market, and will become increasingly more so due to the incresing commercialisation of the European power market. An optimizing control system for improving the load-following capability of power-plant units has therefore been developed. The system is implemented as a complement, producing control signals to be added to those of the existing boiler control system, a concept which has various practical advanta...

Optimisation of load control

International Nuclear Information System (INIS)

Koponen, P.

1998-01-01

Electricity cannot be stored in large quantities. That is why the electricity supply and consumption are always almost equal in large power supply systems. If this balance were disturbed beyond stability, the system or a part of it would collapse until a new stable equilibrium is reached. The balance between supply and consumption is mainly maintained by controlling the power production, but also the electricity consumption or, in other words, the load is controlled. Controlling the load of the power supply system is important, if easily controllable power production capacity is limited. Temporary shortage of capacity causes high peaks in the energy price in the electricity market. Load control either reduces the electricity consumption during peak consumption and peak price or moves electricity consumption to some other time. The project Optimisation of Load Control is a part of the EDISON research program for distribution automation. The following areas were studied: Optimization of space heating and ventilation, when electricity price is time variable, load control model in power purchase optimization, optimization of direct load control sequences, interaction between load control optimization and power purchase optimization, literature on load control, optimization methods and field tests and response models of direct load control and the effects of the electricity market deregulation on load control. An overview of the main results is given in this chapter

Optimisation of load control

Energy Technology Data Exchange (ETDEWEB)

Koponen, P [VTT Energy, Espoo (Finland)

1998-08-01

Electricity cannot be stored in large quantities. That is why the electricity supply and consumption are always almost equal in large power supply systems. If this balance were disturbed beyond stability, the system or a part of it would collapse until a new stable equilibrium is reached. The balance between supply and consumption is mainly maintained by controlling the power production, but also the electricity consumption or, in other words, the load is controlled. Controlling the load of the power supply system is important, if easily controllable power production capacity is limited. Temporary shortage of capacity causes high peaks in the energy price in the electricity market. Load control either reduces the electricity consumption during peak consumption and peak price or moves electricity consumption to some other time. The project Optimisation of Load Control is a part of the EDISON research program for distribution automation. The following areas were studied: Optimization of space heating and ventilation, when electricity price is time variable, load control model in power purchase optimization, optimization of direct load control sequences, interaction between load control optimization and power purchase optimization, literature on load control, optimization methods and field tests and response models of direct load control and the effects of the electricity market deregulation on load control. An overview of the main results is given in this chapter

Culture of safety. Indicators of culture of safety. Stage of culture of safety. Optimization of radiating protection. Principle of precaution. Principle ALARA. Procedure ALARA

International Nuclear Information System (INIS)

Mursa, E.

2006-01-01

Object of research: is the theory and practice of optimization of radiating protection according to recommendations of the international organizations, realization of principle ALARA and maintenance of culture of safety (SC) on the nuclear power plant. The purpose of work - to consider the general aspects of realization of principle ALARA, conceptual bases of culture of safety, as principle of management, and practice of their introduction on the nuclear power plant. The work has the experts' report character in which the following questions are presented: The recommendations materials of the IAEA and other international organizations have been assembled, systematized and analyzed. The definitions, characteristics and universal SC features, and also indicators as a problem of parameters and quantitative SC measurements are described in details advanced. The ALARA principles - principle of precaution; not acceptance of zero risk; choice of a principle ALARA; model of acceptable radiation risk are described. The methodology of an estimation of culture of safety level and practical realization of the ALARA principle in separate organization is shown on a practical example. The SC general estimation at a national level in Republic of Moldova have been done. Taking into consideration that now Safety Culture politics are introduced only in relation to APS, in this paper the attempt of application of Safety Culture methodology to Radiological Objects have been made (Oncological Institute of the Republic of Moldova and Special Objects No.5101 and 5102 for a long time Storage of the Radioactive Waste). (authors)

Optimization of scintillator loading with the tellurium-130 isotope for long-term stability

Science.gov (United States)

Duhamel, Lauren; Song, Xiaoya; Goutnik, Michael; Kaptanoglu, Tanner; Klein, Joshua; SNO+ Collaboration

2017-09-01

Tellurium-130 was selected as the isotope for the SNO + neutrinoless double beta decay search, as 130Te decays to 130Xe via double beta decay. Linear alkyl benzene(LAB) is the liquid scintillator for the SNO + experiment. To load tellurium into scintillator, it is combined with 1,2-butanediol to form an organometallic complex, commonly called tellurium butanediol (TeBD). This study focuses on maximizing the percentage of tellurium loaded into scintillator and evaluates the complex's long-term stability. Studies on the effect of nucleation due to imperfections in the detector's surface and external particulates were employed by filtration and induced nucleation. The impact of water on the stability of TeBD complex was evaluated by liquid-nitrogen sparging, variability in pH and induced humidity. Alternative loading methods were evaluated, including the addition of stability-inducing organic compounds. Samples of tellurium-loaded scintillator were synthesized, treated, and consistently monitored in a controlled environment. It was found that the hydronium ions cause precipitation in the loaded scintillator, demonstrating that water has a detrimental effect on long-term stability. Optimization of loaded scintillator stability can contribute to the SNO + double beta decay search.

Principles of root water uptake, soil salinity and crop yield for optimizing irrigation management

International Nuclear Information System (INIS)

Dirksen, C.

1983-01-01

The paper reviews the principles of water and salt transport, root water uptake, crop salt tolerance, water quality, and irrigation methods which should be considered in optimizing irrigation management for sustained, viable agriculture with protection of the quality of land and water resources. In particular, the advantages of high-frequency irrigation at small leaching fractions with closed systems are discussed, for which uptake-weighted mean salinity is expected to correlate best with crop yields. Optimization of irrigation management depends on the scale considered. Non-technical problems which are often much harder to solve than technical problems, may well be most favourable for new projects in developing countries. (author)

Cost optimization of load carrying thin-walled precast high performance concrete sandwich panels

DEFF Research Database (Denmark)

Hodicky, Kamil; Hansen, Sanne; Hulin, Thomas

2015-01-01

and HPCSP’s geometrical parameters as well as on material cost function in the HPCSP design. Cost functions are presented for High Performance Concrete (HPC), insulation layer, reinforcement and include labour-related costs. The present study reports the economic data corresponding to specific manufacturing......The paper describes a procedure to find the structurally and thermally efficient design of load-carrying thin-walled precast High Performance Concrete Sandwich Panels (HPCSP) with an optimal economical solution. A systematic optimization approach is based on the selection of material’s performances....... The solution of the optimization problem is performed in the computer package software Matlab® with SQPlab package and integrates the processes of HPCSP design, quantity take-off and cost estimation. The proposed optimization process outcomes in complex HPCSP design proposals to achieve minimum cost of HPCSP....

The Effect of mechanical resistive loading on optimal respiratory signals and breathing patterns under added dead space and CO2 breathing

Directory of Open Access Journals (Sweden)

Lin Shyan-Lung

2016-01-01

Full Text Available Current study aims to investigate how the respiratory resistive loading affects the behaviour of the optimal chemical-mechanical respiratory control model, the respiratory signals and breathing pattern are optimized under external dead space loading and CO2 breathing. The respiratory control was modelled to include a neuro-muscular drive as the control output to derive the waveshapes of instantaneous airflow, lung volume profiles, and breathing pattern, including total/alveolar ventilation, breathing frequency, tidal volume, inspiratory/expiratory duration, duty cycle, and arterial CO2 pressure. The simulations were performed under various respiratory resistive loads, including no load, inspiratory resistive load, expiratory resistive load, and continuous resistive load. The dead space measurement was described with Gray’s derivation, and simulation results were studied and compared with experimental findings.

Development of andrographolide loaded PLGA microspheres: optimization, characterization and in vitro-in vivo correlation.

Science.gov (United States)

Jiang, Yunxia; Wang, Fang; Xu, Hui; Liu, Hui; Meng, Qingguo; Liu, Wanhui

2014-11-20

The purpose of this study was to develop a sustained-release drug delivery system based on the injectable PLGA microspheres loaded with andrographolide. The andrographolide loaded PLGA microspheres were prepared by emulsion solvent evaporation method with optimization of formulation using response surface methodology (RSM). Physicochemical characterization, in vitro release behavior and in vivo pharmacokinetics of the optimized formulation were then evaluated. The percent absorbed in vivo was determined by deconvolution using the Loo-Riegelman method, and then the in vitro-in vivo correlation (IVIVC) was established. Results showed that the microspheres were spherical with a smooth surface. Average particle size, entrapment efficiency and drug loading were found to be 53.18±2.11 μm, 75.79±3.02% and 47.06±2.18%, respectively. In vitro release study showed a low initial burst release followed by a prolonged release up to 9 days and the release kinetics followed the Korsmeyer-Peppas model. After a single intramuscular injection, the microspheres maintained relatively high plasma concentration of andrographolide over one week. A good linear relationship was observed between the in vitro and in vivo release behavior (R(2)=0.9951). These results suggest the PLGA microspheres could be developed as a potential delivery system for andrographolide with high drug loading capacity and sustained drug release. Copyright © 2014 Elsevier B.V. All rights reserved.

Collapsing of multigroup cross sections in optimization problems solved by means of the maximum principle of Pontryagin

International Nuclear Information System (INIS)

Anton, V.

1979-05-01

A new formulation of multigroup cross section collapsing based on the conservation of point or zone value of hamiltonian is presented. This attempt is proper to optimization problems solved by means of maximum principle of Pontryagin. (author)

Residential CCHP microgrid with load aggregator: Operation mode, pricing strategy, and optimal dispatch

International Nuclear Information System (INIS)

Gu, Wei; Lu, Shuai; Wu, Zhi; Zhang, Xuesong; Zhou, Jinhui; Zhao, Bo; Wang, Jun

2017-01-01

Highlights: •A bilateral transaction mode for the residential CCHP microgrid is proposed. •An energy pricing strategy for the residential CCHP system is proposed. •A novel integrated demand response for the residential loads is proposed. •Two-stage operation optimization model for the CCHP microgrid is proposed. •Operations of typical days and annual scale of the CCHP microgrid are studied. -- Abstract: As the global energy crisis, environmental pollution, and global warming grow in intensity, increasing attention is being paid to combined cooling, heating, and power (CCHP) systems that realize high-efficiency cascade utilization of energy. This paper proposes a bilateral transaction mechanism between a residential CCHP system and a load aggregator (LA). The variable energy cost of the CCHP system is analyzed, based on which an energy pricing strategy for the CCHP system is proposed. Under this pricing strategy, the electricity price is constant, while the heat/cool price is ladder-shaped and dependent on the relationship between the electrical, heat, and cool loads. For the LA, an integrated demand response program is proposed that combines electricity-load shifting and a flexible heating/cooling supply, in which a thermodynamic model of buildings is used to determine the appropriate range of heating/cooling supply. Subsequently, a two-stage optimal dispatch model is proposed for the energy system that comprises the CCHP system and the LA. Case studies consisting of three scenarios (winter, summer, and excessive seasons) are delivered to demonstrate the effectiveness of the proposed approach, and the performance of the proposed pricing strategy is also evaluated by annual operation simulations.

Dynamic Response and Optimal Design of Curved Metallic Sandwich Panels under Blast Loading

Science.gov (United States)

Yang, Shu; Han, Shou-Hong; Lu, Zhen-Hua

2014-01-01

It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances. PMID:25126606

Dynamic response and optimal design of curved metallic sandwich panels under blast loading.

Science.gov (United States)

Qi, Chang; Yang, Shu; Yang, Li-Jun; Han, Shou-Hong; Lu, Zhen-Hua

2014-01-01

It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a "soft" outer face and a "hard" inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances.

Dynamic Response and Optimal Design of Curved Metallic Sandwich Panels under Blast Loading

Directory of Open Access Journals (Sweden)

Chang Qi

2014-01-01

Full Text Available It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances.

Mathematical Optimization Algorithm for Minimizing the Cost Function of GHG Emission in AS/RS Using Positive Selection Based Clonal Selection Principle

Science.gov (United States)

Mahalakshmi; Murugesan, R.

2018-04-01

This paper regards with the minimization of total cost of Greenhouse Gas (GHG) efficiency in Automated Storage and Retrieval System (AS/RS). A mathematical model is constructed based on tax cost, penalty cost and discount cost of GHG emission of AS/RS. A two stage algorithm namely positive selection based clonal selection principle (PSBCSP) is used to find the optimal solution of the constructed model. In the first stage positive selection principle is used to reduce the search space of the optimal solution by fixing a threshold value. In the later stage clonal selection principle is used to generate best solutions. The obtained results are compared with other existing algorithms in the literature, which shows that the proposed algorithm yields a better result compared to others.

Optimization of piezoelectric bimorph actuators with active damping for static and dynamic loads

DEFF Research Database (Denmark)

Donoso, Alberto; Sigmund, Ole

2009-01-01

The paper considers optimal design problems in the context of active damping. More specifically, we are interested in controlling the tip-deflection of a cantilever beam subjected to static and time-harmonic loading on its free extreme. First, the thickness profile of a piezoelectric bimorph...... actuator is optimized and second, the width profile. In the thickness study, formulation and results depend on whether the electric field or the applied voltage is kept constant. For the latter case we propose a differentiable model that connects electric field and piezo-actuator thickness to include...

Studies of fuel loading pattern optimization for a typical pressurized water reactor (PWR) using improved pivot particle swarm method

International Nuclear Information System (INIS)

Liu, Shichang; Cai, Jiejin

2012-01-01

Highlights: ► The mathematical model of loading pattern problems for PWR has been established. ► IPPSO was integrated with ‘donjon’ and ‘dragon’ into fuel arrangement optimizing code. ► The novel method showed highly efficiency for the LP problems. ► The core effective multiplication factor increases by about 10% in simulation cases. ► The power peaking factor decreases by about 0.6% in simulation cases. -- Abstract: An in-core fuel reload design tool using the improved pivot particle swarm method was developed for the loading pattern optimization problems in a typical PWR, such as Daya Bay Nuclear Power Plant. The discrete, multi-objective improved pivot particle swarm optimization, was integrated with the in-core physics calculation code ‘donjon’ based on finite element method, and assemblies’ group constant calculation code ‘dragon’, composing the optimization code for fuel arrangement. The codes of both ‘donjon’ and ‘dragon’ were programmed by Institute of Nuclear Engineering of Polytechnique Montréal, Canada. This optimization code was aiming to maximize the core effective multiplication factor (Keff), while keeping the local power peaking factor (Ppf) lower than a predetermined value to maintain fuel integrity. At last, the code was applied to the first cycle loading of Daya Bay Nuclear Power Plant. The result showed that, compared with the reference loading pattern design, the core effective multiplication factor increased by 9.6%, while the power peaking factor decreased by 0.6%, meeting the safety requirement.

Genetic algorithm for the optimization of the loading pattern for reactor core fuel management

International Nuclear Information System (INIS)

Zhou Sheng; Hu Yongming; zheng Wenxiang

2000-01-01

The paper discusses the application of a genetic algorithm to the optimization of the loading pattern for in-core fuel management with the NP characteristics. The algorithm develops a matrix model for the fuel assembly loading pattern. The burnable poisons matrix was assigned randomly considering the distributed nature of the poisons. A method based on the traveling salesman problem was used to solve the problem. A integrated code for in-core fuel management was formed by combining this code with a reactor physics code

A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System

Directory of Open Access Journals (Sweden)

Yan Bao

2018-01-01

Full Text Available Fast charging stations enable the high-powered rapid recharging of electric vehicles. However, these stations also face challenges due to power fluctuations, high peak loads, and low load factors, affecting the reliable and economic operation of charging stations and distribution networks. This paper introduces a battery energy storage system (BESS for charging load control, which is a more user-friendly approach and is more robust to perturbations. With the goals of peak-shaving, total electricity cost reduction, and minimization of variation in the state-of-charge (SOC range, a BESS-based bi-level optimization strategy for the charging load regulation of fast charging stations is proposed in this paper. At the first level, a day-ahead optimization strategy generates the optimal planned load curve and the deviation band to be used as a reference for ensuring multiple control objectives through linear programming, and even for avoiding control failure caused by insufficient BESS energy. Based on this day-ahead optimal plan, at a second level, real-time rolling optimization converts the control process to a multistage decision-making problem. The predictive control-based real-time rolling optimization strategy in the proposed model was used to achieve the above control objectives and maintain battery life. Finally, through a horizontal comparison of two control approaches in each case study, and a longitudinal comparison of the control robustness against different degrees of load disturbances in three cases, the results indicated that the proposed control strategy was able to significantly improve the charging load characteristics, even with large disturbances. Meanwhile, the proposed approach ensures the least amount of variation in the range of battery SOC and reduces the total electricity cost, which will be of a considerable benefit to station operators.

Radiation protection principles

International Nuclear Information System (INIS)

Ismail Bahari

2007-01-01

The presentation outlines the aspects of radiation protection principles. It discussed the following subjects; radiation hazards and risk, the objectives of radiation protection, three principles of the system - justification of practice, optimization of protection and safety, dose limit

Optimization of the RF cavity heat load and trip rates for CEBAF at 12 GeV

Energy Technology Data Exchange (ETDEWEB)

Zhang, He [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Roblin, Yves R. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Freyberger, Arne P. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Krafft, Geoffrey A. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Terzic, Balsa P. [Old Dominion Univ., Norfolk, VA (United States)

2017-05-01

The Continuous Electron Beam Accelerator Facility at JLab has 200 RF cavities in the north linac and the south linac respectively after the 12 GeV upgrade. The purpose of this work is to simultaneously optimize the heat load and the trip rate for the cavities and to reconstruct the pareto-optimal front in a timely manner when some of the cavities are turned down. By choosing an efficient optimizer and strategically creating the initial gradients, the pareto-optimal front for no more than 15 cavities down can be re-established within 20 seconds.

An Optimization Waste Load Allocation Model in River Systems

Science.gov (United States)

Amirpoor Daylami, A.; jarihani, A. A.; Aminisola, K.

2012-04-01

In many river systems, increasing of the waste discharge leads to increasing pollution of these water bodies. While the capacity of the river flow for pollution acceptance is limited and the ability of river to clean itself is restricted, the dischargers have to release their waste into the river after a primary pollution treatment process. Waste Load Allocation as a well-known water quality control strategy is used to determine the optimal pollutant removal at a number of point sources along the river. This paper aim at developing a new approach for treatment and management of wastewater inputs into the river systems, such that water quality standards in these receiving waters are met. In this study, inspired by the fact that cooperation among some single point source waste dischargers can lead to a more waste acceptance capacity and/or more optimum quality control in a river, an efficient approach was implemented to determine both primary waste water treatment levels and/or the best releasing points of the waste into the river. In this methodology, a genetic algorithm is used as an optimization tool to calculate optimal fraction removal levels of each one of single or shared discharger. Besides, a sub-model embedded to optimization model was used to simulate water quality of the river in each one of discharging scenarios based on the modified Streeter and Phelps quality equations. The practical application of the model is illustrated with a case study of the Gharesoo river system in west of Iran.

The rule of nuclear power in the base-load portfolio optimization process

International Nuclear Information System (INIS)

Desiata, L.; D'Alberti, F.

2007-01-01

The pursuit of optimal portfolios, maximizing long-term profitability, is the main strategic challenge faced by electricity producers nowadays. Investment decisions, worth billions of euros, are affected by spot factors (such as current fuel prices volatility) that often lead to unbalanced generation mixes. Our analysis presents a statistical-financial approach that highlights the role of nuclear within the base-load portfolio optimisation process [it

Cooling load and coefficient of performance optimizations for real air-refrigerators

International Nuclear Information System (INIS)

Tu Youming; Chen Lingen; Sun Fengrui; Wu Chih

2006-01-01

Based on a simple irreversible variable-temperature heat reservoir air (Brayton) refrigeration cycle model, a performance analysis and optimization of a real air refrigerator is carried out using finite-time thermodynamics. To maximize the cooling load and the coefficient of performance (COP) of the cycle, the allocation of a fixed total heat-exchanger inventory and thermal-capacity rate matching between the working fluid and heat reservoirs are optimized, respectively. The influences of pressure ratio, the total heat-exchanger inventory, the efficiencies of the compressor and expander, the thermal capacity rate of the working fluid and the ratio of the thermal-capacity rates of the heat reservoirs on the performance of the cycle are shown by numerical examples. The results obtained provide guidances for the design of practical air-refrigeration plants

Polyurethane foam loaded with sodium dodecylsulfate for the extraction of 'quat' pesticides from aqueous medium: Optimization of loading conditions.

Science.gov (United States)

Vinhal, Jonas O; Lima, Claudio F; Cassella, Ricardo J

2016-09-01

The cationic herbicides paraquat, diquat and difenzoquat are largely used in different cultures worldwide. With this, there is an intrinsic risk of environmental contamination when these herbicides achieve natural waters. The goal of this work was to propose a novel and low-cost sorbent for the removal of the cited herbicides from aqueous medium. The proposed sorbent was prepared by loading polyurethane foam with sodium dodecylsulfate. The influence of several parameters (SDS concentration, HCl concentration and shaking time) on the loading process was investigated. The results obtained in this work demonstrated that all studied variables influenced the loading process, having significant effect on the extraction efficiency of the resulted PUF-SDS. At optimized conditions, the PUF was loaded by shaking 200mg of crushed foam with 200mL of a solution containing 5.0×10(-3)molL(-1) SDS and 0.25molL(-1) HCl, for 30min. The obtained PUF-SDS was efficient for removing the three herbicides from aqueous medium, achieving extraction percentages higher than 90%. The sorption process followed a pseudo second-order kinetics, which presented excellent predictive capacity of the amount of herbicide retained with time. Copyright © 2016 Elsevier Inc. All rights reserved.

Topology optimization for elastic base under rectangular plate subjected to moving load

Directory of Open Access Journals (Sweden)

Jilavyan Samvel H.

2015-09-01

Full Text Available Distribution optimization of elastic material under elastic isotropic rectangular thin plate subjected to concentrated moving load is investigated in the present paper. The aim of optimization is to damp its vibrations in finite (fixed time. Accepting Kirchhoff hypothesis with respect to the plate and Winkler hypothesis with respect to the base, the mathematical model of the problem is constructed as two-dimensional bilinear equation, i.e. linear in state and control function. The maximal quantity of the base material is taken as optimality criterion to be minimized. The Fourier distributional transform and the Bubnov-Galerkin procedures are used to reduce the problem to integral equality type constraints. The explicit solution in terms of two- dimensional Heaviside‘s function is obtained, describing piecewise-continuous distribution of the material. The determination of the switching points is reduced to a problem of nonlinear programming. Data from numerical analysis are presented.

Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.

Science.gov (United States)

Feng, Jianyuan; Feng, Zhiyong

2017-09-11

Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.

Derivative load voltage and particle swarm optimization to determine optimum sizing and placement of shunt capacitor in improving line losses

Directory of Open Access Journals (Sweden)

Mohamed Milad Baiek

2016-12-01

Full Text Available The purpose of this research is to study optimal size and placement of shunt capacitor in order to minimize line loss. Derivative load bus voltage was calculated to determine the sensitive load buses which further being optimum with the placement of shunt capacitor. Particle swarm optimization (PSO was demonstrated on the IEEE 14 bus power system to find optimum size of shunt capacitor in reducing line loss. The objective function was applied to determine the proper placement of capacitor and get satisfied solutions towards constraints. The simulation was run over Matlab under two scenarios namely base case and increasing 100% load. Derivative load bus voltage was simulated to determine the most sensitive load bus. PSO was carried out to determine the optimum sizing of shunt capacitor at the most sensitive bus. The results have been determined that the most sensitive bus was bus number 14 for the base case and increasing 100% load. The optimum sizing was 8.17 Mvar for the base case and 23.98 Mvar for increasing load about 100%. Line losses were able to reduce approximately 0.98% for the base case and increasing 100% load reduced about 3.16%. The proposed method was also proven as a better result compared with harmony search algorithm (HSA method. HSA method recorded loss reduction ratio about 0.44% for the base case and 2.67% when the load was increased by 100% while PSO calculated loss reduction ratio about 1.12% and 4.02% for the base case and increasing 100% load respectively. The result of this study will support the previous study and it is concluded that PSO was successfully able to solve some engineering problems as well as to find a solution in determining shunt capacitor sizing on the power system simply and accurately compared with other evolutionary optimization methods.

Unequal-thickness billet optimization in transitional region during isothermal local loading forming of Ti-alloy rib-web component using response surface method

Directory of Open Access Journals (Sweden)

Ke WEI

2018-04-01

Full Text Available Avoiding the folding defect and improving the die filling capability in the transitional region are desired in isothermal local loading forming of a large-scale Ti-alloy rib-web component (LTRC. To achieve a high-precision LTRC, the folding evolution and die filling process in the transitional region were investigated by 3D finite element simulation and experiment using an equal-thickness billet (ETB. It is found that the initial volume distribution in the second-loading region can greatly affect the amount of material transferred into the first-loading region during the second-loading step, and thus lead to the folding defect. Besides, an improper initial volume distribution results in non-concurrent die filling in the cavities of ribs after the second-loading step, and then causes die underfilling. To this end, an unequal-thickness billet (UTB was employed with the initial volume distribution optimized by the response surface method (RSM. For a certain eigenstructure, the critical value of the percentage of transferred material determined by the ETB was taken as a constraint condition for avoiding the folding defect in the UTB optimization process, and the die underfilling rate was considered as the optimization objective. Then, based on the RSM models of the percentage of transferred material and the die underfilling rate, non-folding parameter combinations and optimum die filling were achieved. Lastly, an optimized UTB was obtained and verified by the simulation and experiment. Keywords: Die filling, Folding defect, Isothermal local loading forming, Transitional region, Unequal-thickness billet optimization

Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation

Directory of Open Access Journals (Sweden)

Mohammad Dreidy

2017-01-01

Full Text Available Recently, several environmental problems are beginning to affect all aspects of life. For this reason, many governments and international agencies have expressed great interest in using more renewable energy sources (RESs. However, integrating more RESs with distribution networks resulted in several critical problems vis-à-vis the frequency stability, which might lead to a complete blackout if not properly treated. Therefore, this paper proposed a new Under Frequency Load Shedding (UFLS scheme for islanding distribution network. This scheme uses three meta-heuristics techniques, binary evolutionary programming (BEP, Binary genetic algorithm (BGA, and Binary particle swarm optimization (BPSO, to determine the optimal combination of loads that needs to be shed from the islanded distribution network. Compared with existing UFLS schemes using fixed priority loads, the proposed scheme has the ability to restore the network frequency without any overshooting. Furthermore, in terms of execution time, the simulation results show that the BEP technique is fast enough to shed the optimal combination of loads compared with BGA and BPSO techniques.

Optimal design method to minimize users' thinking mapping load in human-machine interactions.

Science.gov (United States)

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

The discrepancy between human cognition and machine requirements/behaviors usually results in serious mental thinking mapping loads or even disasters in product operating. It is important to help people avoid human-machine interaction confusions and difficulties in today's mental work mastered society. Improving the usability of a product and minimizing user's thinking mapping and interpreting load in human-machine interactions. An optimal human-machine interface design method is introduced, which is based on the purpose of minimizing the mental load in thinking mapping process between users' intentions and affordance of product interface states. By analyzing the users' thinking mapping problem, an operating action model is constructed. According to human natural instincts and acquired knowledge, an expected ideal design with minimized thinking loads is uniquely determined at first. Then, creative alternatives, in terms of the way human obtains operational information, are provided as digital interface states datasets. In the last, using the cluster analysis method, an optimum solution is picked out from alternatives, by calculating the distances between two datasets. Considering multiple factors to minimize users' thinking mapping loads, a solution nearest to the ideal value is found in the human-car interaction design case. The clustering results show its effectiveness in finding an optimum solution to the mental load minimizing problems in human-machine interaction design.

A Precision-Positioning Method for a High-Acceleration Low-Load Mechanism Based on Optimal Spatial and Temporal Distribution of Inertial Energy

Directory of Open Access Journals (Sweden)

Xin Chen

2015-09-01

Full Text Available High-speed and precision positioning are fundamental requirements for high-acceleration low-load mechanisms in integrated circuit (IC packaging equipment. In this paper, we derive the transient nonlinear dynamicresponse equations of high-acceleration mechanisms, which reveal that stiffness, frequency, damping, and driving frequency are the primary factors. Therefore, we propose a new structural optimization and velocity-planning method for the precision positioning of a high-acceleration mechanism based on optimal spatial and temporal distribution of inertial energy. For structural optimization, we first reviewed the commonly flexible multibody dynamic optimization using equivalent static loads method (ESLM, and then we selected the modified ESLM for optimal spatial distribution of inertial energy; hence, not only the stiffness but also the inertia and frequency of the real modal shapes are considered. For velocity planning, we developed a new velocity-planning method based on nonlinear dynamic-response optimization with varying motion conditions. Our method was verified on a high-acceleration die bonder. The amplitude of residual vibration could be decreased by more than 20% via structural optimization and the positioning time could be reduced by more than 40% via asymmetric variable velocity planning. This method provides an effective theoretical support for the precision positioning of high-acceleration low-load mechanisms.

Application of Minimum-time Optimal Control System in Buck-Boost Bi-linear Converters

Directory of Open Access Journals (Sweden)

S. M. M. Shariatmadar

2017-08-01

Full Text Available In this study, the theory of minimum-time optimal control system in buck-boost bi-linear converters is described, so that output voltage regulation is carried out within minimum time. For this purpose, the Pontryagin's Minimum Principle is applied to find optimal switching level applying minimum-time optimal control rules. The results revealed that by utilizing an optimal switching level instead of classical switching patterns, output voltage regulation will be carried out within minimum time. However, transient energy index of increased overvoltage significantly reduces in order to attain minimum time optimal control in reduced output load. The laboratory results were used in order to verify numerical simulations.

Optimal Design and Real Time Implementation of Autonomous Microgrid Including Active Load

Directory of Open Access Journals (Sweden)

Mohamed A. Hassan

2018-05-01

Full Text Available Controller gains and power-sharing parameters are the main parameters affect the dynamic performance of the microgrid. Considering an active load to the autonomous microgrid, the stability problem will be more involved. In this paper, the active load effect on microgrid dynamic stability is explored. An autonomous microgrid including three inverter-based distributed generations (DGs with an active load is modeled and the associated controllers are designed. Controller gains of the inverters and active load as well as Phase Locked Loop (PLL parameters are optimally tuned to guarantee overall system stability. A weighted objective function is proposed to minimize the error in both measured active power and DC voltage based on time-domain simulations. Different AC and DC disturbances are applied to verify and assess the effectiveness of the proposed control strategy. The results demonstrate the potential of the proposed controller to enhance the microgrid stability and to provide efficient damping characteristics. Additionally, the proposed controller is compared with the literature to demonstrate its superiority. Finally, the microgrid considered has been established and implemented on real time digital simulator (RTDS. The experimental results validate the simulation results and approve the effectiveness of the proposed controllers to enrich the stability of the considered microgrid.

Combination of Markov chain and optimal control solved by Pontryagin’s Minimum Principle for a fuel cell/supercapacitor vehicle

International Nuclear Information System (INIS)

Hemi, Hanane; Ghouili, Jamel; Cheriti, Ahmed

2015-01-01

Highlights: • A combination of Markov chain and an optimal control solved by Pontryagin’s Minimum Principle is presented. • This strategy is applied to hybrid electric vehicle dynamic model. • The hydrogen consumption is analyzed for two different vehicle mass and drive cycle. • The supercapacitor and fuel cell behavior is analyzed at high or sudden required power. - Abstract: In this article, a real time optimal control strategy based on Pontryagin’s Minimum Principle (PMP) combined with the Markov chain approach is used for a fuel cell/supercapacitor electrical vehicle. In real time, at high power and at high speed, two phenomena are observed. The first is obtained at higher required power, and the second is observed at sudden power demand. To avoid these situations, the Markov chain model is proposed to predict the future power demand during a driving cycle. The optimal control problem is formulated as an equivalent consumption minimization strategy (ECMS), that has to be solved by using the Pontryagin’s Minimum Principle. A Markov chain model is added as a separate block for a prediction of required power. This approach and the whole system are modeled and implemented using the MATLAB/Simulink. The model without Markov chain block and the model is with it are compared. The results presented demonstrate the importance of a Markov chain block added to a model

MTR core loading pattern optimization using burnup dependent group constants

Directory of Open Access Journals (Sweden)

Iqbal Masood

2008-01-01

Full Text Available A diffusion theory based MTR fuel management methodology has been developed for finding superior core loading patterns at any stage for MTR systems, keeping track of burnup of individual fuel assemblies throughout their history. It is based on using burnup dependent group constants obtained by the WIMS-D/4 computer code for standard fuel elements and control fuel elements. This methodology has been implemented in a computer program named BFMTR, which carries out detailed five group diffusion theory calculations using the CITATION code as a subroutine. The core-wide spatial flux and power profiles thus obtained are used for calculating the peak-to-average power and flux-ratios along with the available excess reactivity of the system. The fuel manager can use the BFMTR code for loading pattern optimization for maximizing the excess reactivity, keeping the peak-to-average power as well as flux-ratio within constraints. The results obtained by the BFMTR code have been found to be in good agreement with the corresponding experimental values for the equilibrium core of the Pakistan Research Reactor-1.

Chaotic particle swarm optimization algorithm in a support vector regression electric load forecasting model

International Nuclear Information System (INIS)

Hong, W.-C.

2009-01-01

Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. Recently, support vector regression (SVR), with nonlinear mapping capabilities of forecasting, has been successfully employed to solve nonlinear regression and time series problems. However, it is still lack of systematic approaches to determine appropriate parameter combination for a SVR model. This investigation elucidates the feasibility of applying chaotic particle swarm optimization (CPSO) algorithm to choose the suitable parameter combination for a SVR model. The empirical results reveal that the proposed model outperforms the other two models applying other algorithms, genetic algorithm (GA) and simulated annealing algorithm (SA). Finally, it also provides the theoretical exploration of the electric load forecasting support system (ELFSS)

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Optimization for steady-state and hybrid operations of ITER by using scaling models of divertor heat load

International Nuclear Information System (INIS)

Murakami, Yoshiki; Itami, Kiyoshi; Sugihara, Masayoshi; Fujieda, Hirobumi.

1992-09-01

Steady-state and hybrid mode operations of ITER are investigated by 0-D power balance calculations assuming no radiation and charge-exchange cooling in divertor region. Operation points are optimized with respect to divertor heat load which must be reduced to the level of ignition mode (∼5 MW/m 2 ). Dependence of the divertor heat load on the variety of the models, i.e., constant-χ model, Bohm-type-χ model and JT-60U empirical scaling model, is also discussed. The divertor heat load increases linearly with the fusion power (P FUS ) in all models. The possible highest fusion power much differs for each model with an allowable divertor heat load. The heat load evaluated by constant-χ model is, for example, about 1.8 times larger than that by Bohm-type-χ model at P FUS = 750 MW. Effect of reduction of the helium accumulation, improvements of the confinement capability and the current-drive efficiency are also investigated aiming at lowering the divertor heat load. It is found that NBI power should be larger than about 60 MW to obtain a burn time longer than 2000 s. The optimized operation point, where the minimum divertor heat load is achieved, does not depend on the model and is the point with the minimum-P FUS and the maximum-P NBI . When P FUS = 690 MW and P NBI = 110 MW, the divertor heat load can be reduced to the level of ignition mode without impurity seeding if H = 2.2 is achieved. Controllability of the current-profile is also discussed. (J.P.N.)

Application of metaheuristics to Loading Pattern Optimization problems based on the IAEA-3D and BIBLIS-2D data

International Nuclear Information System (INIS)

Meneses, Anderson Alvarenga de Moura; Araujo, Lenilson Moreira; Nast, Fernando Nogueira; Da Silva, Patrick Vasconcelos; Schirru, Roberto

2018-01-01

Highlights: •Metaheuristics were applied to Loading Pattern Optimization problems and compared. •The problems are based on data of the benchmarks IAEA and BIBLIS. •The metaheuristics compared were PSO, Cross-Entropy, PBIL and Artificial Bee Colony. •Angra 1 NPP data were also used for further comparison of the algorithms. -- Abstract: The Loading Pattern Optimization (LPO) of a Nuclear Power Plant (NPP), or in-core fuel management optimization, is a real-world and prominent problem in Nuclear Engineering with the goal of finding an optimal (or near-optimal) Loading Pattern (LP), in terms of energy production, within adequate safety margins. Most of the reactor models used in the LPO problem are particular cases, such as research or power reactors with technical data that cannot be made available for several reasons, which makes the reproducibility of tests unattainable. In the present article we report the results of LPO of problems based upon reactor physics benchmarks. Since such data are well-known and widely available in the literature, it is possible to reproduce tests for comparison of techniques. We performed the LPO with the data of the benchmarks IAEA-3D and BIBLIS-2D. The Reactor Physics code RECNOD, which was used in previous works for the optimization of Angra 1 NPP in Brazil, was also used for further comparison. Four Optimization Metaheuristics (OMHs) were applied to those problems: Particle Swarm Optimization (PSO), Cross-Entropy algorithm (CE), Artificial Bee Colony (ABC) and Population-Based Incremental Learning (PBIL). For IAEA-3D, the best algorithm was the ABC. For BIBLIS-2D, PBIL was the best OMH. For Angra 1 / RECNOD optimization problem, PBIL, ABC and CE were the best OMHs.

Biomechanical optimization of implant diameter and length for immediate loading: a nonlinear finite element analysis.

Science.gov (United States)

Kong, Liang; Gu, Zexu; Li, Tao; Wu, Junjie; Hu, Kaijin; Liu, Yanpu; Zhou, Hongzhi; Liu, Baolin

2009-01-01

A nonlinear finite element method was applied to examine the effects of implant diameter and length on the maximum von Mises stresses in the jaw, and to evaluate the maximum displacement of the implant-abutment complex in immediate-loading models. The implant diameter (D) ranged from 3.0 to 5.0 mm and implant length (L) ranged from 6.0 to 16.0 mm. The results showed that the maximum von Mises stress in cortical bone was decreased by 65.8% under a buccolingual load with an increase in D. In cancellous bone, it was decreased by 71.5% under an axial load with an increase in L. The maximum displacement in the implant-abutment complex decreased by 64.8% under a buccolingual load with an increase in D. The implant was found to be more sensitive to L than to D under axial loads, while D played a more important role in enhancing its stability under buccolingual loads. When D exceeded 4.0 mm and L exceeded 11.0 mm, both minimum stress and displacement were obtained. Therefore, these dimensions were the optimal biomechanical selections for immediate-loading implants in type B/2 bone.

Towards optimization of nuclear waste glass: Constraints, property models, and waste loading

International Nuclear Information System (INIS)

Hrma, P.

1994-04-01

Vitrification of both low- and high-level wastes from 177 tanks at Hanford poses a great challenge to glass makers, whose task is to formulate a system of glasses that are acceptable to the federal repository for disposal. The enormous quantity of the waste requires a glass product of the lowest possible volume. The incomplete knowledge of waste composition, its variability, and lack of an appropriate vitrification technology further complicates this difficult task. A simple relationship between the waste loading and the waste glass volume is presented and applied to the predominantly refractory (usually high-activity) and predominantly alkaline (usually low-activity) waste types. Three factors that limit waste loading are discussed, namely product acceptability, melter processing, and model validity. Glass formulation and optimization problems are identified and a broader approach to uncertainties is suggested

Quality by design approach for formulation, evaluation and statistical optimization of diclofenac-loaded ethosomes via transdermal route.

Science.gov (United States)

Jain, Shashank; Patel, Niketkumar; Madan, Parshotam; Lin, Senshang

2015-06-01

The objective of this study was to fabricate and understand ethosomal formulations of diclofenac (DF) for enhanced anti-inflammatory activity using quality by design approach. DF-loaded ethosomal formulations were prepared using 4 × 5 full-factorial design with phosphatidylcholine:cholesterol (PC:CH) ratios ranging between 50:50 and 90:10, and ethanol concentration ranging between 0% and 30% as formulation variables. These formulations were characterized in terms of physicochemical properties and skin permeation kinetics. The interaction of formulation variables had a significant effect on both physicochemical properties and permeation kinetics. The results of multivariate regression analysis illustrated that vesicle size and elasticity of ethosomes were the dominating physicochemical properties affecting skin permeation, and could be suitably controlled by manipulation of formulation variables to optimize the formulation and enhance the skin permeation of DF-loaded ethosomes. The optimized formulation had ethanol concentration of 22.9% and PC:CH ratio of 88.4:11.6, with vesicle size of 144 ± 5 nm, zeta potential of -23.0 ± 3.76 mV, elasticity of 2.48 ± 0.75 and entrapment efficiency of 71 ± 4%. Permeation flux for the optimized formulation was 12.9 ± 1.0 µg/h cm(2), which was significantly higher than the drug-loaded conventional liposome, ethanolic or aqueous solution. The in vivo study indicated that optimized ethosomal hydrogel exhibited enhanced anti-inflammatory activity compared with liposomal and plain drug hydrogel formulations.

Automatic loading pattern optimization tool for Loviisa VVER-440 reactors

Energy Technology Data Exchange (ETDEWEB)

Kuopanportti, Jaakko [Fortum Power and Heat, Fortum (Finland). Nuclear Competence Center

2013-09-15

An automatic loading pattern optimization tool called ALPOT has been developed for Loviisa VVER-440 reactors. The ALPOT code utilizes combination of three different optimization methods. The first method is the imitation of the equilibrium pattern that is the optimized pattern in case the cycle length and the operation conditions are constant and the same shuffling pattern is repeated from cycle to cycle. In practice, the algorithm imitates assemblies' operation year distribution of the equilibrium pattern stochastically. The function of the imitation algorithm is to provide initial patterns quickly for the next optimization phase, which is performed either with the stochastic guided binary search algorithm or the deterministic burnup kernel method depending on the choice of the user. The former is a modified version of the standard binary search. The standard version goes through all possible swaps of the assemblies and chooses the best swap at each iteration round. The guided version chooses one assembly, tries to swap it with every other possible assembly and performs the best swap at each iteration round. The search is guided so that the algorithm chooses the assemblies at or near the most restrictive fuel assembly first. The kernel method creates burnup kernel functions to estimate burnup variations that are required to achieve desired changes in the power distribution of the reactor. The idea of the kernel method is first determine the optimal burnup distribution that minimizes the maximum relative assembly power using the created kernel functions and a common solver routine. Then, the burnups of the available fuel assemblies are matched with the obtained burnup distribution. (orig.)

Automatic loading pattern optimization tool for Loviisa VVER-440 reactors

International Nuclear Information System (INIS)

Kuopanportti, Jaakko

2013-01-01

An automatic loading pattern optimization tool called ALPOT has been developed for Loviisa VVER-440 reactors. The ALPOT code utilizes combination of three different optimization methods. The first method is the imitation of the equilibrium pattern that is the optimized pattern in case the cycle length and the operation conditions are constant and the same shuffling pattern is repeated from cycle to cycle. In practice, the algorithm imitates assemblies' operation year distribution of the equilibrium pattern stochastically. The function of the imitation algorithm is to provide initial patterns quickly for the next optimization phase, which is performed either with the stochastic guided binary search algorithm or the deterministic burnup kernel method depending on the choice of the user. The former is a modified version of the standard binary search. The standard version goes through all possible swaps of the assemblies and chooses the best swap at each iteration round. The guided version chooses one assembly, tries to swap it with every other possible assembly and performs the best swap at each iteration round. The search is guided so that the algorithm chooses the assemblies at or near the most restrictive fuel assembly first. The kernel method creates burnup kernel functions to estimate burnup variations that are required to achieve desired changes in the power distribution of the reactor. The idea of the kernel method is first determine the optimal burnup distribution that minimizes the maximum relative assembly power using the created kernel functions and a common solver routine. Then, the burnups of the available fuel assemblies are matched with the obtained burnup distribution. (orig.)

Optimization of Boiling Water Reactor Loading Pattern Using Two-Stage Genetic Algorithm

International Nuclear Information System (INIS)

Kobayashi, Yoko; Aiyoshi, Eitaro

2002-01-01

A new two-stage optimization method based on genetic algorithms (GAs) using an if-then heuristic rule was developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). In the first stage, the LP is optimized using an improved GA operator. In the second stage, an exposure-dependent control rod pattern (CRP) is sought using GA with an if-then heuristic rule. The procedure of the improved GA is based on deterministic operators that consist of crossover, mutation, and selection. The handling of the encoding technique and constraint conditions by that GA reflects the peculiar characteristics of the BWR. In addition, strategies such as elitism and self-reproduction are effectively used in order to improve the search speed. The LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and constraints dependent on three dimensions have always necessitated the use of three-dimensional core simulators for BWRs, so that optimization of computational efficiency is required. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant in two phases. One phase is only LP optimization applying the Haling technique. The other phase is an LP optimization that considers the CRP during reactor operation. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained

Multiobjective CVaR Optimization Model and Solving Method for Hydrothermal System Considering Uncertain Load Demand

Directory of Open Access Journals (Sweden)

Zhongfu Tan

2015-01-01

Full Text Available In order to solve the influence of load uncertainty on hydrothermal power system operation and achieve the optimal objectives of system power generation consumption, pollutant emissions, and first-stage hydropower station storage capacity, this paper introduced CVaR method and built a multiobjective optimization model and its solving method. In the optimization model, load demand’s actual values and deviation values are regarded as random variables, scheduling objective is redefined to meet confidence level requirement and system operation constraints and loss function constraints are taken into consideration. To solve the proposed model, this paper linearized nonlinear constraints, applied fuzzy satisfaction, fuzzy entropy, and weighted multiobjective function theories to build a fuzzy entropy multiobjective CVaR model. The model is a mixed integer linear programming problem. Then, six thermal power plants and three cascade hydropower stations are taken as the hydrothermal system for numerical simulation. The results verified that multiobjective CVaR method is applicable to solve hydrothermal scheduling problems. It can better reflect risk level of the scheduling result. The fuzzy entropy satisfaction degree solving algorithm can simplify solving difficulty and get the optimum operation scheduling scheme.

A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification

Directory of Open Access Journals (Sweden)

Wei Gao

2016-01-01

Full Text Available According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration. Finally, numerical and experimental examples are utilized to validate the performance of the QFM. Furthermore, the Generalized Cross-Validation (GCV method and the L-curve method are taken as the comparison methods. The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load.

Multi-load Optimal Design of Burner-inner-liner Under Performance Index Constraint by Second-Order Polynomial Taylor Series Method

Directory of Open Access Journals (Sweden)

Tu Gaoqiao

2016-01-01

Full Text Available Using maximum expansion pressure of n-decane, the aeroengine burner-inner-liner combustion pressure load is computed. Aerodynamic loads are obtained from internal gas pressure load and gas momentum. Multi-load second-order Taylor series equations are established using multi-variant polynomials and their sensitivities. Optimal designs are carried out using various performance index constraints. When 0.25 to 0.8 rectifications of different design variants are implemented, they converge under 5×10‒4 d-norm difference ratio.

MEMS resonant load cells for micro-mechanical test frames: feasibility study and optimal design

Science.gov (United States)

Torrents, A.; Azgin, K.; Godfrey, S. W.; Topalli, E. S.; Akin, T.; Valdevit, L.

2010-12-01

This paper presents the design, optimization and manufacturing of a novel micro-fabricated load cell based on a double-ended tuning fork. The device geometry and operating voltages are optimized for maximum force resolution and range, subject to a number of manufacturing and electromechanical constraints. All optimizations are enabled by analytical modeling (verified by selected finite elements analyses) coupled with an efficient C++ code based on the particle swarm optimization algorithm. This assessment indicates that force resolutions of ~0.5-10 nN are feasible in vacuum (~1-50 mTorr), with force ranges as large as 1 N. Importantly, the optimal design for vacuum operation is independent of the desired range, ensuring versatility. Experimental verifications on a sub-optimal device fabricated using silicon-on-glass technology demonstrate a resolution of ~23 nN at a vacuum level of ~50 mTorr. The device demonstrated in this article will be integrated in a hybrid micro-mechanical test frame for unprecedented combinations of force resolution and range, displacement resolution and range, optical (or SEM) access to the sample, versatility and cost.

Research of Impact Load in Large Electrohydraulic Load Simulator

Directory of Open Access Journals (Sweden)

Yongguang Liu

2014-01-01

Full Text Available The stronger impact load will appear in the initial phase when the large electric cylinder is tested in the hardware-in-loop simulation. In this paper, the mathematical model is built based on AMESim, and then the reason of the impact load is investigated through analyzing the changing tendency of parameters in the simulation results. The inhibition methods of impact load are presented according to the structural invariability principle and applied to the actual system. The final experimental result indicates that the impact load is inhibited, which provides a good experimental condition for the electric cylinder and promotes the study of large load simulator.

Clinical application of 'Justification' and 'Optimization' principle of ALARA in pediatric CT imaging: "How many children can be protected from unnecessary radiation?".

Science.gov (United States)

Sodhi, Kushaljit S; Krishna, Satheesh; Saxena, Akshay K; Sinha, Anindita; Khandelwal, Niranjan; Lee, Edward Y

2015-09-01

Practice of ALARA (as low as reasonably achievable) principle in the developed world is currently well established. However, there is striking lack of published data regarding such experience in the developing countries. Therefore, the goal of this study is to prospectively evaluate CT request forms to assess how many children could be protected from harmful radiation exposure if 'Justification' and 'Optimization' principles of ALARA are applied before obtaining CT imaging in a developing country. This can save children from potential radiation risks including development of brain cancer and leukemia. Consecutive CT request forms over a six month study period (May 16, 2013 to November 15, 2013) in a tertiary pediatric children's hospital in India were prospectively reviewed by two pediatric radiologists before obtaining CT imaging. First, 'Justification' of CT was evaluated and then 'Optimization' was applied for evaluation of appropriateness of the requested CT studies. The number (and percentage) of CT studies avoided by applying 'Justification' and 'Optimization' principle of ALARA were calculated. The difference in number of declined and optimized CT requests between CT requests from inpatient and outpatient departments was compared using Chi-Square test. A total of 1302 consecutive CT request forms were received during the study period. Some of the request forms (n=86; 6.61%) had requests for more than one (multiple) anatomical regions, hence, a total of 1392 different anatomical CT requests were received. Based on evaluation of the CT request forms for 'Justification' and 'Optimization' principle of ALARA by pediatric radiology reviewers, 111 individual anatomic part CT requests from 105 pediatric patients were avoided. Therefore, 8.06% (105 out of 1302 pediatric patients) were protected from unnecessary or additional radiation exposure.The rates of declined or optimized CT requests from inpatient department was significantly higher than that from outpatient

Assessment of Masonry Buildings Subjected to Landslide-Induced Settlements: From Load Path Method to Evolutionary Optimization Method

Science.gov (United States)

Palmisano, Fabrizio; Elia, Angelo

2017-10-01

One of the main difficulties, when dealing with landslide structural vulnerability, is the diagnosis of the causes of crack patterns. This is also due to the excessive complexity of models based on classical structural mechanics that makes them inappropriate especially when there is the necessity to perform a rapid vulnerability assessment at the territorial scale. This is why, a new approach, based on a ‘simple model’ (i.e. the Load Path Method, LPM), has been proposed by Palmisano and Elia for the interpretation of the behaviour of masonry buildings subjected to landslide-induced settlements. However, the LPM is very useful for rapidly finding the 'most plausible solution' instead of the exact solution. To find the solution, optimization algorithms are necessary. In this scenario, this article aims to show how the Bidirectional Evolutionary Structural Optimization method by Huang and Xie, can be very useful to optimize the strut-and-tie models obtained by using the Load Path Method.

Optimal auxiliary Hamiltonians for truncated boson-space calculations by means of a maximal-decoupling variational principle

International Nuclear Information System (INIS)

Li, C.

1991-01-01

A new method based on a maximal-decoupling variational principle is proposed to treat the Pauli-principle constraints for calculations of nuclear collective motion in a truncated boson space. The viability of the method is demonstrated through an application to the multipole form of boson Hamiltonians for the single-j and nondegenerate multi-j pairing interactions. While these boson Hamiltonians are Hermitian and contain only one- and two-boson terms, they are also the worst case for truncated boson-space calculations because they are not amenable to any boson truncations at all. By using auxiliary Hamiltonians optimally determined by the maximal-decoupling variational principle, however, truncations in the boson space become feasible and even yield reasonably accurate results. The method proposed here may thus be useful for doing realistic calculations of nuclear collective motion as well as for obtaining a viable interacting-boson-model type of boson Hamiltonian from the shell model

Optimal Load Shedding and Generation Rescheduling for Overload Suppression in Large Power Systems.

Science.gov (United States)

Moon, Young-Hyun

Ever-increasing size, complexity and operation costs in modern power systems have stimulated the intensive study of an optimal Load Shedding and Generator Rescheduling (LSGR) strategy in the sense of a secure and economic system operation. The conventional approach to LSGR has been based on the application of LP (Linear Programming) with the use of an approximately linearized model, and the LP algorithm is currently considered to be the most powerful tool for solving the LSGR problem. However, all of the LP algorithms presented in the literature essentially lead to the following disadvantages: (i) piecewise linearization involved in the LP algorithms requires the introduction of a number of new inequalities and slack variables, which creates significant burden to the computing facilities, and (ii) objective functions are not formulated in terms of the state variables of the adopted models, resulting in considerable numerical inefficiency in the process of computing the optimal solution. A new approach is presented, based on the development of a new linearized model and on the application of QP (Quadratic Programming). The changes in line flows as a result of changes to bus injection power are taken into account in the proposed model by the introduction of sensitivity coefficients, which avoids the mentioned second disadvantages. A precise method to calculate these sensitivity coefficients is given. A comprehensive review of the theory of optimization is included, in which results of the development of QP algorithms for LSGR as based on Wolfe's method and Kuhn -Tucker theory are evaluated in detail. The validity of the proposed model and QP algorithms has been verified and tested on practical power systems, showing the significant reduction of both computation time and memory requirements as well as the expected lower generation costs of the optimal solution as compared with those obtained from computing the optimal solution with LP. Finally, it is noted that an

The principle of the Internet evolving and a conjecture on the optimal structure of the Internet

International Nuclear Information System (INIS)

Ying, Li; Hong-Duo, Cao; Xiu-Ming, Shan; Yong, Ren; Jian, Yuan

2009-01-01

In this paper we will give the statistical characteristics and general principles of an optimal structure of the Internet, which is a scale-free network. Since the purpose of the Internet is to allow fast and easy communication, the average path length is used to measure the performance of the network, and the number of edges of the network is used as a metric of its cost. Based on this, the goal of this Internet optimization problem is to obtain the highest performance with the lowest cost. A multi goal optimization problem is proposed to model this problem. By using two empirical formulas of and , we are able to find the statistical characteristics of the optimal structure. There is a critical power law exponent α c for the Internet with power law degree distribution, at which the Internet can obtain a relatively good performance with a low cost. We find that this α c is approximately 2.1

Optimization of preparation method for ketoprofen-loaded microspheres consisting polymeric blends using simplex lattice mixture design

Energy Technology Data Exchange (ETDEWEB)

Das, Sanjoy Kumar, E-mail: sanjoydasju@gmail.com; Khanam, Jasmina; Nanda, Arunabha

2016-12-01

In the present investigation, simplex lattice mixture design was applied for formulation development and optimization of a controlled release dosage form of ketoprofen microspheres consisting polymers like ethylcellulose and Eudragit{sup ®}RL 100; when those were formed by oil-in-oil emulsion solvent evaporation method. The investigation was carried out to observe the effects of polymer amount, stirring speed and emulsifier concentration (% w/w) on percentage yield, average particle size, drug entrapment efficiency and in vitro drug release in 8 h from the microspheres. Analysis of variance (ANOVA) was used to estimate the significance of the models. Based on the desirability function approach numerical optimization was carried out. Optimized formulation (KTF-O) showed close match between actual and predicted responses with desirability factor 0.811. No adverse reaction between drug and polymers were observed on the basis of Fourier transform infrared (FTIR) spectroscopy and Differential scanning calorimetric (DSC) analysis. Scanning electron microscopy (SEM) was carried out to show discreteness of microspheres (149.2 ± 1.25 μm) and their surface conditions during pre and post dissolution operations. The drug release pattern from KTF-O was best explained by Korsmeyer-Peppas and Higuchi models. The batch of optimized microspheres were found with maximum entrapment (~ 90%), minimum loss (~ 10%) and prolonged drug release for 8 h (91.25%) which may be considered as favourable criteria of controlled release dosage form. - Graphical abstract: Optimization of preparation method for ketoprofen-loaded microspheres consisting polymeric blends using simplex lattice mixture design. - Highlights: • Simplex lattice design was used to optimize ketoprofen-loaded microspheres. • Polymeric blend (Ethylcellulose and Eudragit® RL 100) was used. • Microspheres were prepared by oil-in-oil emulsion solvent evaporation method. • Optimized formulation depicted favourable

Development and statistical optimization of nefopam hydrochloride loaded nanospheres for neuropathic pain using Box-Behnken design.

Science.gov (United States)

Sukhbir, S; Yashpal, S; Sandeep, A

2016-09-01

Nefopam hydrochloride (NFH) is a non-opioid centrally acting analgesic drug used to treat chronic condition such as neuropathic pain. In current research, sustained release nefopam hydrochloride loaded nanospheres (NFH-NS) were auspiciously synthesized using binary mixture of eudragit RL 100 and RS 100 with sorbitan monooleate as surfactant by quasi solvent diffusion technique and optimized by 3 5 Box-Behnken designs to evaluate the effects of process and formulation variables. Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetric (DSC) and X-ray diffraction (XRD) affirmed absence of drug-polymer incompatibility and confirmed formation of nanospheres. Desirability function scrutinized by design-expert software for optimized formulation was 0.920. Optimized batch of NFH-NS had mean particle size 328.36 nm ± 2.23, % entrapment efficiency (% EE) 84.97 ± 1.23, % process yield 83.60 ± 1.31 and % drug loading (% DL) 21.41 ± 0.89. Dynamic light scattering (DLS), zeta potential analysis and scanning electron microscopy (SEM) validated size, charge and shape of nanospheres, respectively. In-vitro drug release study revealed biphasic release pattern from optimized nanospheres. Korsmeyer Peppas found excellent kinetics model with release exponent less than 0.45. Chronic constricted injury (CCI) model of optimized NFH-NS in Wistar rats produced significant difference in neuropathic pain behavior ( p  accelerated stability testing of optimized NFH-NS revealed degradation rate constant 1.695 × 10 -4 and shelf-life 621 days at 25 ± 2 °C/60% ± 5% RH.

ALARA Principle Application for Loading Spent Nuclear Fuel Assemblies from Nuclear Research Reactor WR-S Mergal-Bucharest Romania into Transportation Casks

International Nuclear Information System (INIS)

Dragusin, M.

2009-01-01

Safety implementation of Spent Nuclear Fuels Assemblies (SNFA) handling procedures at the WR-S reactor site is ensured by technical perfection and reliability of equipment, monitoring of its condition, qualification and discipline of personnel as well as organization and execution of work complied with requirements of regulatory documents, process procedures, guidance and manuals. The personnel training for execution loading of SNF FAs is other important aspect for radiation protection and safely activities. Estimations carried out using Micro Shield software show that maximal dose rate upon working site when loading four FAs into basket of cask will not exceed 1.7 and 956;Sv/h, excluding natural radiation. Radiation Safety Analyses estimates for loading 70 SNFA in 18 transportation casks are: maximal individual dose: 4274.7 and 956;Sv, maximal expected collective dose persons: 17 031.2 man and 956;Sv. By application ALARA principle with technical and administrative measures the loading process developed in the following conditions: maximal individual dose: 68 and 956;Sv, the collective dose persons: 732 man and 956;Sv. The work will presented the technical measures and procedures applied in loading process.

A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network

International Nuclear Information System (INIS)

Yu, Feng; Xu, Xiaozhong

2014-01-01

Highlights: • A detailed data processing will make more accurate results prediction. • Taking a full account of more load factors to improve the prediction precision. • Improved BP network obtains higher learning convergence. • Genetic algorithm optimized by chaotic cat map enhances the global search ability. • The combined GA–BP model improved by modified additional momentum factor is superior to others. - Abstract: This paper proposes an appropriate combinational approach which is based on improved BP neural network for short-term gas load forecasting, and the network is optimized by the real-coded genetic algorithm. Firstly, several kinds of modifications are carried out on the standard neural network to accelerate the convergence speed of network, including improved additional momentum factor, improved self-adaptive learning rate and improved momentum and self-adaptive learning rate. Then, it is available to use the global search capability of optimized genetic algorithm to determine the initial weights and thresholds of BP neural network to avoid being trapped in local minima. The ability of GA is enhanced by cat chaotic mapping. In light of the characteristic of natural gas load for Shanghai, a series of data preprocessing methods are adopted and more comprehensive load factors are taken into account to improve the prediction accuracy. Such improvements facilitate forecasting efficiency and exert maximum performance of the model. As a result, the integration model improved by modified additional momentum factor gets more ideal solutions for short-term gas load forecasting, through analyses and comparisons of the above several different combinational algorithms

Partial storage optimization and load control strategy of cloud data centers.

Science.gov (United States)

Al Nuaimi, Klaithem; Mohamed, Nader; Al Nuaimi, Mariam; Al-Jaroodi, Jameela

2015-01-01

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner.

Partial Storage Optimization and Load Control Strategy of Cloud Data Centers

Science.gov (United States)

2015-01-01

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner. PMID:25973444

Optimal dynamic premium control in non-life insurance. Maximizing dividend pay-outs

DEFF Research Database (Denmark)

Højgaard, Bjarne

2002-01-01

In this paper we consider the problem of finding optimal dynamic premium policies in non-life insurance. The reserve of a company is modeled using the classical Cramér-Lundberg model with premium rates calculated via the expected value principle. The company controls dynamically the relative safety...... loading with the possibility of gaining or loosing customers. It distributes dividends according to a 'barrier strategy' and the objective of the company is to find an optimal premium policy and dividend barrier maximizing the expected total, discounted pay-out of dividends. In the case of exponential...

Optimizing physicians' instruction of PACS through e-learning: cognitive load theory applied.

Science.gov (United States)

Devolder, P; Pynoo, B; Voet, T; Adang, L; Vercruysse, J; Duyck, P

2009-03-01

This article outlines the strategy used by our hospital to maximize the knowledge transfer to referring physicians on using a picture archiving and communication system (PACS). We developed an e-learning platform underpinned by the cognitive load theory (CLT) so that in depth knowledge of PACS' abilities becomes attainable regardless of the user's prior experience with computers. The application of the techniques proposed by CLT optimizes the learning of the new actions necessary to obtain and manipulate radiological images. The application of cognitive load reducing techniques is explained with several examples. We discuss the need to safeguard the physicians' main mental processes to keep the patient's interests in focus. A holistic adoption of CLT techniques both in teaching and in configuration of information systems could be adopted to attain this goal. An overview of the advantages of this instruction method is given both on the individual and organizational level.

Principles of the Energy Conservation Bill

International Nuclear Information System (INIS)

Zeman, J.

1995-01-01

The paper describes 21 principles of the draft Energy Conservation Bill. The principles lay down fundamental responsibilities of the government, the municipalities, business entities, citizens and power plants in the field of economical energy management. Included are principles to minimize energy consumption and to stimulate a reasonable energy management, the role of the energy distribution network, responsibilities of the central load dispatching center, and power plant output regulation schemes. (J.B.)

Scale up, optimization and stability analysis of Curcumin C3 complex-loaded nanoparticles for cancer therapy

Science.gov (United States)

2012-01-01

Background Nanoparticle based delivery of anticancer drugs have been widely investigated. However, a very important process for Research & Development in any pharmaceutical industry is scaling nanoparticle formulation techniques so as to produce large batches for preclinical and clinical trials. This process is not only critical but also difficult as it involves various formulation parameters to be modulated all in the same process. Methods In our present study, we formulated curcumin loaded poly (lactic acid-co-glycolic acid) nanoparticles (PLGA-CURC). This improved the bioavailability of curcumin, a potent natural anticancer drug, making it suitable for cancer therapy. Post formulation, we optimized our process by Reponse Surface Methodology (RSM) using Central Composite Design (CCD) and scaled up the formulation process in four stages with final scale-up process yielding 5 g of curcumin loaded nanoparticles within the laboratory setup. The nanoparticles formed after scale-up process were characterized for particle size, drug loading and encapsulation efficiency, surface morphology, in vitro release kinetics and pharmacokinetics. Stability analysis and gamma sterilization were also carried out. Results Results revealed that that process scale-up is being mastered for elaboration to 5 g level. The mean nanoparticle size of the scaled up batch was found to be 158.5 ± 9.8 nm and the drug loading was determined to be 10.32 ± 1.4%. The in vitro release study illustrated a slow sustained release corresponding to 75% drug over a period of 10 days. The pharmacokinetic profile of PLGA-CURC in rats following i.v. administration showed two compartmental model with the area under the curve (AUC0-∞) being 6.139 mg/L h. Gamma sterilization showed no significant change in the particle size or drug loading of the nanoparticles. Stability analysis revealed long term physiochemical stability of the PLGA-CURC formulation. Conclusions A successful effort towards

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression

Science.gov (United States)

Miller, Christopher

2017-01-01

These slide sets describe the OCLA formulation and associated algorithms as a set of new technologies in the first practical application of load limiting flight control utilizing load feedback as a primary control measurement. Slide set one describes Experiment Development and slide set two describes Flight-Test Performance.

A scenario of vehicle-to-grid implementation and its double-layer optimal charging strategy for minimizing load variance within regional smart grids

International Nuclear Information System (INIS)

Jian, Linni; Zhu, Xinyu; Shao, Ziyun; Niu, Shuangxia; Chan, C.C.

2014-01-01

Highlights: • A scenario of vehicle-to-grid implementation within regional smart grid is discussed and mathematically formulated. • A double-layer optimal charging strategy for plug-in electric vehicles is proposed. • The proposed double-layer optimal charging algorithm aims to minimize power grid’s load variance. • The performance of proposed double-layer optimal charging algorithm is evaluated through comparative study. - Abstract: As an emerging new electrical load, plug-in electric vehicles (PEVs)’ impact on the power grid has drawn increasing attention worldwide. An optimal scenario is that by digging the potential of PEVs as a moveable energy storage device, they may not harm the power grid by, for example, triggering extreme surges in demand at rush hours, conversely, the large-scale penetration of PEVs could benefit the grid through flattening the power load curve, hence, increase the stability, security and operating economy of the grid. This has become a hot issue which is known as vehicle-to-grid (V2G) technology within the framework of smart grid. In this paper, a scenario of V2G implementation within regional smart grids is discussed. Then, the problem is mathematically formulated. It is essentially an optimization problem, and the objective is to minimize the overall load variance. With the increase of the scale of PEVs and charging posts involved, the computational complexity will become tremendously high. Therefore, a double-layer optimal charging (DLOC) strategy is proposed to solve this problem. The comparative study demonstrates that the proposed DLOC algorithm can effectively solve the problem of tremendously high computational complexity arising from the large-scaled PEVs and charging posts involved

On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimation

Directory of Open Access Journals (Sweden)

Antonio Piacentino

2016-12-01

Full Text Available Cogeneration and trigeneration plants are widely recognized as promising technologies for increasing energy efficiency in buildings. However, their overall potential is scarcely exploited, due to the difficulties in achieving economic viability and the risk of investment related to uncertainties in future energy loads and prices. Several stochastic optimization models have been proposed in the literature to account for uncertainties, but these instruments share in a common reliance on user-defined probability functions for each stochastic parameter. Being such functions hard to predict, in this paper an analysis of the influence of erroneous estimation of the uncertain energy loads and prices on the optimal plant design and operation is proposed. With reference to a hotel building, a number of realistic scenarios is developed, exploring all the most frequent errors occurring in the estimation of energy loads and prices. Then, profit-oriented optimizations are performed for the examined scenarios, by means of a deterministic mixed integer linear programming algorithm. From a comparison between the achieved results, it emerges that: (i the plant profitability is prevalently influenced by the average “spark-spread” (i.e., ratio between electricity and fuel price and, secondarily, from the shape of the daily price profiles; (ii the “optimal sizes” of the main components are scarcely influenced by the daily load profiles, while they are more strictly related with the average “power to heat” and “power to cooling” ratios of the building.

Economic emission dispatching with variations of wind power and loads using multi-objective optimization by learning automata

International Nuclear Information System (INIS)

Liao, H.L.; Wu, Q.H.; Li, Y.Z.; Jiang, L.

2014-01-01

Highlights: • Apply multi-objective optimization by learning automata to power system. • Sequentially dimensional search and state memory are incorporated. • Track dispatch under significant variations of wind power and load demand. • Good performance in terms of accuracy, distribution and computation time. - Abstract: This paper is concerned with using multi-objective optimization by learning automata (MOLA) for economic emission dispatching in the environment where wind power and loads vary. With its capabilities of sequentially dimensional search and state memory, MOLA is able to find accurate solutions while satisfying two objectives: fuel cost coupled with environmental emission and voltage stability. Its searching quality and efficiency are measured using the hypervolume indicator for investigating the quality of Pareto front, and demonstrated by tracking the dispatch solutions under significant variations of wind power and load demand. The simulation studies are carried out on the modified midwestern American electric power system and the IEEE 118-bus test system, in which wind power penetration and load variations present. Evaluated on these two power systems, MOLA is fully compared with multi-objective evolutionary algorithm based on decomposition (MOEA/D) and non-dominated sorting genetic algorithm II (NSGA-II). The simulation results have shown the superiority of MOLA over NAGA-II and MOEA/D, as it is able to obtain more accurate and widely distributed Pareto fronts. In the dynamic environment where the operation condition of both wind speed and load demand varies, MOLA outperforms the other two algorithms, with respect to the tracking ability and accuracy of the solutions

Aero-structural optimization of wind turbine blades using a reduced set of design load cases including turbulence

DEFF Research Database (Denmark)

Sessarego, Matias; Shen, Wen Zhong

2018-01-01

Modern wind turbine aero-structural blade design codes generally use a smaller fraction of the full design load base (DLB) or neglect turbulent inflow as defined by the International Electrotechnical Commission standards. The current article describes an automated blade design optimization method...... based on surrogate modeling that includes a very large number of design load cases (DLCs) including turbulence. In the present work, 325 DLCs representative of the full DLB are selected based on the message-passing-interface (MPI) limitations in Matlab. Other methods are currently being investigated, e.......g. a Python MPI implementation, to overcome the limitations in Matlab MPI and ultimately achieve a full DLB optimization framework. The reduced DLB and the annual energy production are computed using the state-of-the-art aero-servo-elastic tool HAWC2. Furthermore, some of the interior dimensions of the blade...

On the optimization of thorium bundle distribution in the initial core loading for a PHWR

International Nuclear Information System (INIS)

Mishra, S.; Ray, S.; Kumar, A.N.; Modak, R.S.; Ganesan, S.

2009-01-01

If the initial core of Indian 220 MWe PHWR is loaded with all fresh Natural Uranium fuel, only about 70% Full Power can be drawn in the initial operation due to large power peaking. It is possible to load few tens of Th bundles at selected locations to get nearly full power without violating any safety limits. Finding the best possible locations is, however, a fairly complex and massive combinatorial optimization problem. Here, optimum solutions are obtained by a latest evolutionary algorithm called EDA implemented on the EKA built at Computational Research Laboratories (CRL) in Pune. The effect of varying the number of Th bundles on results is discussed. (author)

Development and statistical optimization of nefopam hydrochloride loaded nanospheres for neuropathic pain using Box–Behnken design

Directory of Open Access Journals (Sweden)

S. Sukhbir

2016-09-01

Full Text Available Nefopam hydrochloride (NFH is a non-opioid centrally acting analgesic drug used to treat chronic condition such as neuropathic pain. In current research, sustained release nefopam hydrochloride loaded nanospheres (NFH-NS were auspiciously synthesized using binary mixture of eudragit RL 100 and RS 100 with sorbitan monooleate as surfactant by quasi solvent diffusion technique and optimized by 35 Box–Behnken designs to evaluate the effects of process and formulation variables. Fourier transform infrared spectroscopy (FTIR, differential scanning calorimetric (DSC and X-ray diffraction (XRD affirmed absence of drug–polymer incompatibility and confirmed formation of nanospheres. Desirability function scrutinized by design-expert software for optimized formulation was 0.920. Optimized batch of NFH-NS had mean particle size 328.36 nm ± 2.23, % entrapment efficiency (% EE 84.97 ± 1.23, % process yield 83.60 ± 1.31 and % drug loading (% DL 21.41 ± 0.89. Dynamic light scattering (DLS, zeta potential analysis and scanning electron microscopy (SEM validated size, charge and shape of nanospheres, respectively. In-vitro drug release study revealed biphasic release pattern from optimized nanospheres. Korsmeyer Peppas found excellent kinetics model with release exponent less than 0.45. Chronic constricted injury (CCI model of optimized NFH-NS in Wistar rats produced significant difference in neuropathic pain behavior (p < 0.05 as compared to free NFH over 10 h indicating sustained action. Long term and accelerated stability testing of optimized NFH-NS revealed degradation rate constant 1.695 × 10−4 and shelf-life 621 days at 25 ± 2 °C/60% ± 5% RH.

Water-in-Oil Microemulsions for Protein Delivery: Loading Optimization and Stability.

Science.gov (United States)

Perinelli, Diego R; Cespi, Marco; Pucciarelli, Stefania; Vincenzetti, Silvia; Casettari, Luca; Lam, Jenny K W; Logrippo, Serena; Canala, Elisa; Soliman, Mahmoud E; Bonacucina, Giulia; Palmieri, Giovanni F

2017-01-01

Microemulsions are attractive delivery systems for therapeutic proteins and peptides due to their ability to enhance bioavailability. Although different proteins and peptides have been successfully delivered through such ternary systems, no information can be found about protein loading and the formulation stability when such microemulsions are prepared with pharmaceuticallyapproved oils and surfactants. The aim of this work was to optimise a ternary system consisting of water/ ethyl oleate/Span® 80-Tween® 80 and to determine its protein loading capacity and stability, using bovine serum albumin (BSA) as a model of biomolecule. The optimization was carried out using a Central Composite Design and all the prepared formulations were characterised through dynamic light scattering, rheology, optical and polarized microscopy. Subsequently, the maximum loading capacity was determined and the stability of the final microemulsion with the highest content of protein was followed over six months. To investigate the structural features of the protein, BSA was recovered from the microemulsion and analysed through fluorescence spectroscopy. After incorporation of the protein in the microemulsion, a decrease of its aqueous solubility was observed. However, the formulation remained stable over six months and the native-like state of the recovered protein was demonstrated by fluorescence spectroscopy Conclusion: This study demonstrated the feasibility of preparing microemulsions with the highest content of protein and their long-term stability. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Formulation design and optimization for the improvement of nystatin-loaded lipid intravenous emulsion.

Science.gov (United States)

Marín-Quintero, Deiry; Fernández-Campos, Francisco; Calpena-Campmany, Ana C; Montes-López, María J; Clares-Naveros, Beatriz; Del Pozo-Carrascosa, Alfonso

2013-11-01

Nystatin (NYS) is a polyene macrolide with broad antifungal spectrum restricted to topical use owing to its toxicity upon systemic administration. The aims of this work were the design, development, and optimization of NYS-loaded lipid emulsion for intravenous administration. A closed circuit system was designed to apply ultrasound during the elaboration of the lipid intravenous emulsions (LIEs). Additionally, a comparison with the commercially available Intralipid(®) 20% was also performed. Manufacturing conditions were optimized by factorial design. Formulations were evaluated in terms of physicochemical parameters, stability, release profile, and antimicrobial activity. The average droplet size, polydispersity index, zeta-potential, pH, and volume distribution values ranged between 192.5 and 143.0 nm, 0.170 and 0.135, -46 and -44 mV, 7.11 and 7.53, 580 and 670 nm, respectively. The selected NYS-loaded LIE (NYS-LIE54) consisted of soybean oil (30%), soybean lecithin (2%), solutol HS(®) 15 (4%), and glycerol (2.25%) was stable for at least 60 days. In vitro drug release studies of this formulation suggested a sustained-release profile. Equally, NYS-LIE54 showed the best antimicrobial activity being higher than the free drug. Thus, it could be a promising drug delivery system to treat systemic fungal infections. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

The collapsing of multigroup cross sections in optimization problems solved by means of the Pontryagin maximum principle in nuclear reactor dynamics

International Nuclear Information System (INIS)

Anton, V.

1979-12-01

The collapsing formulae for the optimization problems solved by means of the Pontryagin maximum principle in nuclear reactor dynamics are presented. A comparison with the corresponding formulae of the static case is given too. (author)

A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow

Directory of Open Access Journals (Sweden)

Paulo Maciel

2013-07-01

Full Text Available Energy consumption is a matter of common concern in the world today. Research demonstrates that as a consequence of the constantly evolving and expanding field of information technology, data centers are now major consumers of electrical energy. Such high electrical energy consumption emphasizes the issues of sustainability and cost. Against this background, the present paper proposes a power load distribution algorithm (PLDA to optimize energy distribution of data center power infrastructures. The PLDA, which is based on the Ford-Fulkerson algorithm, is supported by an environment called ASTRO, capable of performing the integrated evaluation of dependability, cost and sustainability. More specifically, the PLDA optimizes the flow distribution of the energy flow model (EFM. EFMs are responsible for estimating sustainability and cost issues of data center infrastructures without crossing the restrictions of the power capacity that each device can provide (power system or extract (cooling system. Additionally, a case study is presented that analyzed seven data center power architectures. Significant results were observed, achieving a reduction in power consumption of up to 15.5%.

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

International Nuclear Information System (INIS)

Fadaei, Amir Hosein; Setayeshi, Saeed

2009-01-01

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

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

International Nuclear Information System (INIS)

Shen Wei; Zhongsheng Xie; Banghua Yin

1995-01-01

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

Optimalisatie Draagsysteem (Optimization of the Load Carriage System)

National Research Council Canada - National Science Library

Koerhuis, C. L; Rensink, P; Schijndel, J. van

2008-01-01

Besides positive effects of an earlier developed load carriage system in which the load was carried predominantly on the hips, mobility was increased and protection and load carriage was integrated into one system (ILCS...

Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Bao Wang

2012-11-01

Full Text Available The accuracy of annual electric load forecasting plays an important role in the economic and social benefits of electric power systems. The least squares support vector machine (LSSVM has been proven to offer strong potential in forecasting issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. As a novel meta-heuristic and evolutionary algorithm, the fruit fly optimization algorithm (FOA has the advantages of being easy to understand and fast convergence to the global optimal solution. Therefore, to improve the forecasting performance, this paper proposes a LSSVM-based annual electric load forecasting model that uses FOA to automatically determine the appropriate values of the two parameters for the LSSVM model. By taking the annual electricity consumption of China as an instance, the computational result shows that the LSSVM combined with FOA (LSSVM-FOA outperforms other alternative methods, namely single LSSVM, LSSVM combined with coupled simulated annealing algorithm (LSSVM-CSA, generalized regression neural network (GRNN and regression model.

Optimization of capillary zone electrophoresis for charge heterogeneity testing of biopharmaceuticals using enhanced method development principles.

Science.gov (United States)

Moritz, Bernd; Locatelli, Valentina; Niess, Michele; Bathke, Andrea; Kiessig, Steffen; Entler, Barbara; Finkler, Christof; Wegele, Harald; Stracke, Jan

2017-12-01

CZE is a well-established technique for charge heterogeneity testing of biopharmaceuticals. It is based on the differences between the ratios of net charge and hydrodynamic radius. In an extensive intercompany study, it was recently shown that CZE is very robust and can be easily implemented in labs that did not perform it before. However, individual characteristics of some examined proteins resulted in suboptimal resolution. Therefore, enhanced method development principles were applied here to investigate possibilities for further method optimization. For this purpose, a high number of different method parameters was evaluated with the aim to improve CZE separation. For the relevant parameters, design of experiments (DoE) models were generated and optimized in several ways for different sets of responses like resolution, peak width and number of peaks. In spite of product specific DoE optimization it was found that the resulting combination of optimized parameters did result in significant improvement of separation for 13 out of 16 different antibodies and other molecule formats. These results clearly demonstrate generic applicability of the optimized CZE method. Adaptation to individual molecular properties may sometimes still be required in order to achieve optimal separation but the set screws discussed in this study [mainly pH, identity of the polymer additive (HPC versus HPMC) and the concentrations of additives like acetonitrile, butanolamine and TETA] are expected to significantly reduce the effort for specific optimization. 2017 The Authors. Electrophoresis published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of steam generators of NPP with WWER in operation with variable load

Science.gov (United States)

Parchevskii, V. M.; Shchederkina, T. E.; Gur'yanova, V. V.

2017-11-01

The report addresses the issue of the optimal water level in the horizontal steam generators of NPP with WWER. On the one hand, the level needs to be kept at the lower limit of the allowable range, as gravity separation, steam will have the least humidity and the turbine will operate with higher efficiency. On the other hand, the higher the level, the greater the supply of water in the steam generator, and therefore the higher the security level of the unit, because when accidents involving loss of cooling of the reactor core, the water in the steam generators, can be used for cooling. To quantitatively compare the damage from higher level to the benefit of improving the safety was assessed of the cost of one cubic meter of water in the steam generators, the formulated objective function of optimal levels control. This was used two-dimensional separation characteristics of steam generators. It is demonstrated that the security significantly shifts the optimal values of the levels toward the higher values, and this bias is greater the lower the load unit.

Optimization of economic load dispatch of higher order general cost polynomials and its sensitivity using modified particle swarm optimization

International Nuclear Information System (INIS)

Saber, Ahmed Yousuf; Chakraborty, Shantanu; Abdur Razzak, S.M.; Senjyu, Tomonobu

2009-01-01

This paper presents a modified particle swarm optimization (MPSO) for constrained economic load dispatch (ELD) problem. Real cost functions are more complex than conventional second order cost functions when multi-fuel operations, valve-point effects, accurate curve fitting, etc., are considering in deregulated changing market. The proposed modified particle swarm optimization (PSO) consists of problem dependent variable number of promising values (in velocity vector), unit vector and error-iteration dependent step length. It reliably and accurately tracks a continuously changing solution of the complex cost function and no extra concentration/effort is needed for the complex higher order cost polynomials in ELD. Constraint management is incorporated in the modified PSO. The modified PSO has balance between local and global searching abilities, and an appropriate fitness function helps to converge it quickly. To avoid the method to be frozen, stagnated/idle particles are reset. Sensitivity of the higher order cost polynomials is also analyzed visually to realize the importance of the higher order cost polynomials for the optimization of ELD. Finally, benchmark data sets and methods are used to show the effectiveness of the proposed method. (author)

Temporal Evolution of Design Principles in Engineering Systems: Analogies with Human Evolution

DEFF Research Database (Denmark)

Deb, Kalyanmoy; Bandaru, Sunith; Tutum, Cem Celal

2012-01-01

constructed later during optimization. Interestingly, there exists a simile between evolution of design principles with that of human evolution. Such information about the hierarchy of key design principles should enable designers to have a deeper understanding of their problems.......Optimization of an engineering system or component makes a series of changes in the initial random solution(s) iteratively to form the final optimal shape. When multiple conflicting objectives are considered, recent studies on innovization revealed the fact that the set of Pareto-optimal solutions...... portray certain common design principles. In this paper, we consider a 14-variable bi-objective design optimization of a MEMS device and identify a number of such common design principles through a recently proposed automated innovization procedure. Although these design principles are found to exist...

Statistical Analysis of Solar PV Power Frequency Spectrum for Optimal Employment of Building Loads

Energy Technology Data Exchange (ETDEWEB)

Olama, Mohammed M [ORNL; Sharma, Isha [ORNL; Kuruganti, Teja [ORNL; Fugate, David L [ORNL

2017-01-01

In this paper, a statistical analysis of the frequency spectrum of solar photovoltaic (PV) power output is conducted. This analysis quantifies the frequency content that can be used for purposes such as developing optimal employment of building loads and distributed energy resources. One year of solar PV power output data was collected and analyzed using one-second resolution to find ideal bounds and levels for the different frequency components. The annual, seasonal, and monthly statistics of the PV frequency content are computed and illustrated in boxplot format. To examine the compatibility of building loads for PV consumption, a spectral analysis of building loads such as Heating, Ventilation and Air-Conditioning (HVAC) units and water heaters was performed. This defined the bandwidth over which these devices can operate. Results show that nearly all of the PV output (about 98%) is contained within frequencies lower than 1 mHz (equivalent to ~15 min), which is compatible for consumption with local building loads such as HVAC units and water heaters. Medium frequencies in the range of ~15 min to ~1 min are likely to be suitable for consumption by fan equipment of variable air volume HVAC systems that have time constants in the range of few seconds to few minutes. This study indicates that most of the PV generation can be consumed by building loads with the help of proper control strategies, thereby reducing impact on the grid and the size of storage systems.

Power efficiency optimization of disk-loaded waveguide traveling wave structure of electron linear accelerator

International Nuclear Information System (INIS)

Yang Jinghe; Li Jinhai; Li Chunguang

2014-01-01

Disk-loaded waveguide traveling wave structure (TWS), which is widely used in scientific research and industry, is a vital accelerating structure in electron linear accelerator. The power efficiency is an important parameter for designing TWS, which greatly effects the expenses for the fabrication and commercial running. The key parameters related with power efficiency were studied for TWS optimization. The result was proved by experiment result, and it shows some help for accelerator engineering. (authors)

Automatic boiling water reactor loading pattern design using ant colony optimization algorithm

Energy Technology Data Exchange (ETDEWEB)

Wang, C.-D. [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China); Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China)], E-mail: jdwang@iner.gov.tw; Lin Chaung [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China)

2009-08-15

An automatic boiling water reactor (BWR) loading pattern (LP) design methodology was developed using the rank-based ant system (RAS), which is a variant of the ant colony optimization (ACO) algorithm. To reduce design complexity, only the fuel assemblies (FAs) of one eight-core positions were determined using the RAS algorithm, and then the corresponding FAs were loaded into the other parts of the core. Heuristic information was adopted to exclude the selection of the inappropriate FAs which will reduce search space, and thus, the computation time. When the LP was determined, Haling cycle length, beginning of cycle (BOC) shutdown margin (SDM), and Haling end of cycle (EOC) maximum fraction of limit for critical power ratio (MFLCPR) were calculated using SIMULATE-3 code, which were used to evaluate the LP for updating pheromone of RAS. The developed design methodology was demonstrated using FAs of a reference cycle of the BWR6 nuclear power plant. The results show that, the designed LP can be obtained within reasonable computation time, and has a longer cycle length than that of the original design.

Optimization of Ru{sub x}Se{sub y} electrocatalyst loading for oxygen reduction in a PEMFC

Energy Technology Data Exchange (ETDEWEB)

Gonzalez-Huerta, R.G. [Instituto Politecnico Nacional, Laboratorio de Electroquimica y Corrosion ESIQIE, UPALP, 07738 Mexico, D.F., Mexico (Mexico); Guzman-Guzman, A.; Solorza-Feria, O. [Depto. Quimica, Centro de Investigacion y de Estudios Avanzados del IPN, A. Postal 14-740, 07360 Mexico D.F., Mexico (Mexico)

2010-11-15

The synthesis, characterization and optimization of Ru{sub x}Se{sub y} catalyst loading as a cathode electrode for a single polymer electrolyte membrane fuel cell, PEMFC were investigated. Ru{sub x}Se{sub y} catalyst was synthesized via a decarbonylation of Ru{sub 3}(CO){sub 12} and elemental selenium in 1,6-hexanediol under refluxing conditions for 2 h. The powder electrocatalyst was characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), and examined for the oxygen reduction reaction (ORR) in 0.5M H{sub 2}SO{sub 4} by rotating disk electrode (RDE) and in membrane-electrode assemblies, MEAs for a single PEMFC. Results indicate the formation of agglomerates of crystalline particles with nanometric size embedded in an amorphous phase. The catalyst exhibited high current density and lower overpotential for the ORR compared to that of Ru{sub x} cluster catalyst. Dispersed Ru{sub x}Se{sub y} catalyst loading on Vulcan carbon was optimized as a cathode electrode by performance testing in a single H{sub 2}-O{sub 2} fuel cell. (author)

Use of loading-unloading compression curves in medical device design

Science.gov (United States)

Ciornei, M. C.; Alaci, S.; Ciornei, F. C.; Romanu, I. C.

2017-08-01

The paper presents a method and experimental results regarding mechanical testing of soft materials. In order to characterize the mechanical behaviour of technological materials used in prosthesis, a large number of material constants are required, as well as the comparison to the original. The present paper proposes as methodology the comparison between compression loading-unloading curves corresponding to a soft biological tissue and to a synthetic material. To this purpose, a device was designed based on the principle of the dynamic harness test. A moving load is considered and the force upon the indenter is controlled for loading-unloading phases. The load and specimen deformation are simultaneously recorded. A significant contribution of this paper is the interpolation of experimental data by power law functions, a difficult task because of the instability of the system of equations to be optimized. Finding the interpolation function was simplified, from solving a system of transcendental equations to solving a unique equation. The characteristic parameters of the experimentally curves must be compared to the ones corresponding to actual tissue. The tests were performed for two cases: first, using a spherical punch, and second, for a flat-ended cylindrical punch.

Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines

Directory of Open Access Journals (Sweden)

Alexandre Presas

2018-03-01

Full Text Available Hydropower plants are of paramount importance for the integration of intermittent renewable energy sources in the power grid. In order to match the energy generated and consumed, Large hydraulic turbines have to work under off-design conditions, which may lead to dangerous unstable operating points involving the hydraulic, mechanical and electrical system. Under these conditions, the stability of the grid and the safety of the power plant itself can be compromised. For many Francis Turbines one of these critical points, that usually limits the maximum output power, is the full load instability. Therefore, these machines usually work far away from this unstable point, reducing the effective operating range of the unit. In order to extend the operating range of the machine, working closer to this point with a reasonable safety margin, it is of paramount importance to monitor and to control relevant parameters of the unit, which have to be obtained with an accurate sensor acquisition strategy. Within the framework of a large EU project, field tests in a large Francis Turbine located in Canada (rated power of 444 MW have been performed. Many different sensors were used to monitor several working parameters of the unit for all its operating range. Particularly for these tests, more than 80 signals, including ten type of different sensors and several operating signals that define the operating point of the unit, were simultaneously acquired. The present study, focuses on the optimization of the acquisition strategy, which includes type, number, location, acquisition frequency of the sensors and corresponding signal analysis to detect the full load instability and to prevent the unit from reaching this point. A systematic approach to determine this strategy has been followed. It has been found that some indicators obtained with different types of sensors are linearly correlated with the oscillating power. The optimized strategy has been determined

Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines.

Science.gov (United States)

Presas, Alexandre; Valentin, David; Egusquiza, Mònica; Valero, Carme; Egusquiza, Eduard

2018-03-30

Hydropower plants are of paramount importance for the integration of intermittent renewable energy sources in the power grid. In order to match the energy generated and consumed, Large hydraulic turbines have to work under off-design conditions, which may lead to dangerous unstable operating points involving the hydraulic, mechanical and electrical system. Under these conditions, the stability of the grid and the safety of the power plant itself can be compromised. For many Francis Turbines one of these critical points, that usually limits the maximum output power, is the full load instability. Therefore, these machines usually work far away from this unstable point, reducing the effective operating range of the unit. In order to extend the operating range of the machine, working closer to this point with a reasonable safety margin, it is of paramount importance to monitor and to control relevant parameters of the unit, which have to be obtained with an accurate sensor acquisition strategy. Within the framework of a large EU project, field tests in a large Francis Turbine located in Canada (rated power of 444 MW) have been performed. Many different sensors were used to monitor several working parameters of the unit for all its operating range. Particularly for these tests, more than 80 signals, including ten type of different sensors and several operating signals that define the operating point of the unit, were simultaneously acquired. The present study, focuses on the optimization of the acquisition strategy, which includes type, number, location, acquisition frequency of the sensors and corresponding signal analysis to detect the full load instability and to prevent the unit from reaching this point. A systematic approach to determine this strategy has been followed. It has been found that some indicators obtained with different types of sensors are linearly correlated with the oscillating power. The optimized strategy has been determined based on the

Development and optimization of sulforaphane-loaded nanostructured lipid carriers by the Box-Behnken design for improved oral efficacy against cancer: in vitro, ex vivo and in vivo assessments.

Science.gov (United States)

Soni, Kriti; Rizwanullah, Md; Kohli, Kanchan

2017-11-28

In the present study, sulforaphane (SFN)-loaded nanostructured lipid carriers (NLC) were developed and optimized for improved oral efficacy against cancer. The SFN-loaded NLC formulation was developed by melt emulsification ultrasonication technique and optimized by Box-Behnken statistical design. The optimized SFN-loaded NLC formulation composed of precirol ® ATO 5 (solid lipid) and vitamin E (liquid lipid) as lipid phase (3% w/v), poloxamer 188 (1%) and Tween 80 (1%) as surfactant. The mean particle size, polydispersity index, zeta potential, entrapment efficiency (%) and drug loading (%) of optimized SFN-loaded NLC formulation was observed to be 145.38 ± 4.46 nm, 0.181 ± 0.023, -25.12 ± 2.36 mV, 84.94 ± 3.82% and 14.82 ± 3.46%, respectively. In vitro drug release studies showed that the release of SFN from optimized NLC formulation was significantly higher (86.52 ± 5.48%) compared to SFN suspension (38.47 ± 5.52%) up to 24 h. Ex vivo gut permeation studies revealed a very good enhancement in permeation of drug present in the NLC compared to plain SFN solution and were further confirmed by CLSM. MTT assay in different cancer cell lines showed that the optimized SFN-loaded NLC formulation exhibited significantly improved (p < .05) cytotoxicity compared to free SFN solution. SFN-loaded NLC formulation showed significantly improved antioxidant activity compared to free SFN solution. Furthermore, pharmacokinetic study on albino Wistar rats showed 5.04-fold increase in relative oral bioavailability with NLC (p < .05) compared to SFN suspension. Therefore, NLC represents a great potential for improved efficacy of SFN after oral administration.

Optimal Selection of Clustering Algorithm via Multi-Criteria Decision Analysis (MCDA for Load Profiling Applications

Directory of Open Access Journals (Sweden)

Ioannis P. Panapakidis

2018-02-01

Full Text Available Due to high implementation rates of smart meter systems, considerable amount of research is placed in machine learning tools for data handling and information retrieval. A key tool in load data processing is clustering. In recent years, a number of researches have proposed different clustering algorithms in the load profiling field. The present paper provides a methodology for addressing the aforementioned problem through Multi-Criteria Decision Analysis (MCDA and namely, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS. A comparison of the algorithms is employed. Next, a single test case on the selection of an algorithm is examined. User specific weights are applied and based on these weight values, the optimal algorithm is drawn.

Gas load forecasting based on optimized fuzzy c-mean clustering analysis of selecting similar days

Directory of Open Access Journals (Sweden)

Qiu Jing

2017-08-01

Full Text Available Traditional fuzzy c-means (FCM clustering in short term load forecasting method is easy to fall into local optimum and is sensitive to the initial cluster center.In this paper,we propose to use global search feature of particle swarm optimization (PSO algorithm to avoid these shortcomings,and to use FCM optimization to select similar date of forecast as training sample of support vector machines.This will not only strengthen the data rule of training samples,but also ensure the consistency of data characteristics.Experimental results show that the prediction accuracy of this prediction model is better than that of BP neural network and support vector machine (SVM algorithms.

STANDALONE PHOTOVOLTAIC SYSTEMS SIZING OPTIMIZATION USING DESIGN SPACE APPROACH: CASE STUDY FOR RESIDENTIAL LIGHTING LOAD

Directory of Open Access Journals (Sweden)

D. F. AL RIZA

2015-07-01

Full Text Available This paper presents a sizing optimization methodology of panel and battery capacity in a standalone photovoltaic system with lighting load. Performance of the system is identified by performing Loss of Power Supply Probability (LPSP calculation. Input data used for the calculation is the daily weather data and system components parameters. Capital Cost and Life Cycle Cost (LCC is calculated as optimization parameters. Design space for optimum system configuration is identified based on a given LPSP value, Capital Cost and Life Cycle Cost. Excess energy value is used as an over-design indicator in the design space. An economic analysis, including cost of the energy and payback period, for selected configurations are also studied.

Using a multi-state recurrent neural network to optimize loading patterns in BWRs

International Nuclear Information System (INIS)

Ortiz, Juan Jose; Requena, Ignacio

2004-01-01

A Multi-State Recurrent Neural Network is used to optimize Loading Patterns (LP) in BWRs. We have proposed an energy function that depends on fuel assembly positions and their nuclear cross sections to carry out optimisation. Multi-State Recurrent Neural Networks creates LPs that satisfy the Radial Power Peaking Factor and maximize the effective multiplication factor at the Beginning of the Cycle, and also satisfy the Minimum Critical Power Ratio and Maximum Linear Heat Generation Rate at the End of the Cycle, thereby maximizing the effective multiplication factor. In order to evaluate the LPs, we have used a trained back-propagation neural network to predict the parameter values, instead of using a reactor core simulator, which saved considerable computation time in the search process. We applied this method to find optimal LPs for five cycles of Laguna Verde Nuclear Power Plant (LVNPP) in Mexico

Economic Load Dispatch - A Comparative Study on Heuristic Optimization Techniques With an Improved Coordinated Aggregation-Based PSO

DEFF Research Database (Denmark)

Vlachogiannis, Ioannis (John); Lee, KY

2009-01-01

In this paper an improved coordinated aggregation-based particle swarm optimization (ICA-PSO) algorithm is introduced for solving the optimal economic load dispatch (ELD) problem in power systems. In the ICA-PSO algorithm each particle in the swarm retains a memory of its best position ever...... encountered, and is attracted only by other particles with better achievements than its own with the exception of the particle with the best achievement, which moves randomly. Moreover, the population size is increased adaptively, the number of search intervals for the particles is selected adaptively...

Preparation of Salicylic Acid Loaded Nanostructured Lipid Carriers Using Box-Behnken Design: Optimization, Characterization and Physicochemical Stability.

Science.gov (United States)

Pantub, Ketrawee; Wongtrakul, Paveena; Janwitayanuchit, Wicharn

2017-01-01

Nanostructured lipid carriers loaded salicylic acid (NLCs-SA) were developed and optimized by using the design of experiment (DOE). Box-Behnken experimental design of 3-factor, 3-level was applied for optimization of nanostructured lipid carriers prepared by emulsification method. The independent variables were total lipid concentration (X 1 ), stearic acid to Lexol ® GT-865 ratio (X 2 ) and Tween ® 80 concentration (X 3 ) while the particle size was a dependent variable (Y). Box-Behnken design could create 15 runs by setting response optimizer as minimum particle size. The optimized formulation consists of 10% of total lipid, a mixture of stearic acid and capric/caprylic triglyceride at a 4:1 ratio, and 25% of Tween ® 80 which the formulation was applied in order to prepare in both loaded and unloaded salicylic acid. After preparation for 24 hours, the particle size of loaded and unloaded salicylic acid was 189.62±1.82 nm and 369.00±3.37 nm, respectively. Response surface analysis revealed that the amount of total lipid is a main factor which could affect the particle size of lipid carriers. In addition, the stability studies showed a significant change in particle size by time. Compared to unloaded nanoparticles, the addition of salicylic acid into the particles resulted in physically stable dispersion. After 30 days, sedimentation of unloaded lipid carriers was clearly observed. Absolute values of zeta potential of both systems were in the range of 3 to 18 mV since non-ionic surfactant, Tween ® 80, providing steric barrier was used. Differential thermograms indicated a shift of endothermic peak from 55°C for α-crystal form in freshly prepared samples to 60°C for β´-crystal form in storage samples. It was found that the presence of capric/caprylic triglyceride oil could enhance encapsulation efficiency up to 80% and facilitate stability of the particles.

Optimization of a solar driven absorption refrigerator in the transient regime

International Nuclear Information System (INIS)

Hamed, Mouna; Fellah, Ali; Ben Brahim, Ammar

2012-01-01

Highlights: ► Dynamic behavior of a solar absorption refrigerator endoreversible model. ► Using the principles of classical thermodynamics, mass and heat transfers. ► Minimizing heat exchange time to reach maximum performances. ► Major influence of the collector temperature on the model’s characteristics. ► Analogous effects of both the thermal load and the thermal conductance. -- Abstract: This contribution deals with the theoretical study in dynamic mode of an absorption refrigerator endoreversible model. The system is a cold generating station driven by solar energy. The main elements of the cycle are a refrigerated space, an absorption refrigerator and a solar collector form. A mathematical model is developed. It combines the classical thermodynamics and mass and heat transfers principles. The numerical simulation is made for different operating and conceptual conditions. A global minimizing time optimization is performed in view to reach maximum performances. Appropriate dimensionless groups are defined. The results are presented in normalized charts for general applications. The collector temperature presents major influence on the conceptual and functional characteristics compared to the stagnation temperature influence. On the other hand the thermal load in the refrigerated space and the thermal conductance of the walls has analogous effects, therefore important to be considered in actual design. As a result, the model is expected to be a useful tool for simulation, design, and optimization of solar collector based energy systems.

A novel hybrid particle swarm optimization for economic dispatch with valve-point loading effects

Energy Technology Data Exchange (ETDEWEB)

Niknam, Taher, E-mail: niknam@sutech.ac.i [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of); Mojarrad, Hasan Doagou, E-mail: hasan_doagou@yahoo.co [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of); Meymand, Hamed Zeinoddini, E-mail: h.zeinaddini@gmail.co [Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, P.O. 71555-313 (Iran, Islamic Republic of)

2011-04-15

Economic dispatch (ED) is one of the important problems in the operation and management of the electric power systems which is formulated as an optimization problem. Modern heuristics stochastic optimization techniques appear to be efficient in solving ED problem without any restriction because of their ability to seek the global optimal solution. One of modern heuristic algorithms is particle swarm optimization (PSO). In PSO algorithm, particles change place to get close to the best position and find the global minimum point. Also, differential evolution (DE) is a robust statistical method for solving non-linear and non-convex optimization problem. The fast convergence of DE degrades its performance and reduces its search capability that leads to a higher probability towards obtaining a local optimum. In order to overcome this drawback a hybrid method is presented to solve the ED problem with valve-point loading effect by integrating the variable DE with the fuzzy adaptive PSO called FAPSO-VDE. DE is the main optimizer and the PSO is used to maintain the population diversity and prevent leading to misleading local optima for every improvement in the solution of the DE run. The parameters of proposed hybrid algorithm such as inertia weight, mutation and crossover factors are adaptively adjusted. The feasibility and effectiveness of the proposed hybrid algorithm is demonstrated for two case studies and results are compared with those of other methods. It is shown that FAPSO-VDE has high quality solution, superior convergence characteristics and shorter computation time.

Technical note: optimization for improved tube-loading efficiency in the dual-energy computed tomography coupled with balanced filter method.

Science.gov (United States)

Saito, Masatoshi

2010-08-01

This article describes the spectral optimization of dual-energy computed tomography using balanced filters (bf-DECT) to reduce the tube loadings and dose by dedicating to the acquisition of electron density information, which is essential for treatment planning in radiotherapy. For the spectral optimization of bf-DECT, the author calculated the beam-hardening error and air kerma required to achieve a desired noise level in an electron density image of a 50-cm-diameter cylindrical water phantom. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimal combination of tube voltages was 80 kV/140 kV in conjunction with Tb/Hf and Bi/Mo filter pairs; this combination agrees with that obtained in a previous study [M. Saito, "Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method," Med. Phys. 36, 3631-3642 (2009)], although the thicknesses of the filters that yielded a minimum tube output were slightly different from those obtained in the previous study. The resultant tube loading of a low-energy scan of the present bf-DECT significantly decreased from 57.5 to 4.5 times that of a high-energy scan for conventional DECT. Furthermore, the air kerma of bf-DECT could be reduced to less than that of conventional DECT, while obtaining the same figure of merit for the measurement of electron density and effective atomic number. The tube-loading and dose efficiencies of bf-DECT were considerably improved by sacrificing the quality of the noise level in the images of effective atomic number.

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-23

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

Optimal RTP Based Power Scheduling for Residential Load in Smart Grid

Science.gov (United States)

Joshi, Hemant I.; Pandya, Vivek J.

2015-12-01

To match supply and demand, shifting of load from peak period to off-peak period is one of the effective solutions. Presently flat rate tariff is used in major part of the world. This type of tariff doesn't give incentives to the customers if they use electrical energy during off-peak period. If real time pricing (RTP) tariff is used, consumers can be encouraged to use energy during off-peak period. Due to advancement in information and communication technology, two-way communications is possible between consumers and utility. To implement this technique in smart grid, home energy controller (HEC), smart meters, home area network (HAN) and communication link between consumers and utility are required. HEC interacts automatically by running an algorithm to find optimal energy consumption schedule for each consumer. However, all the consumers are not allowed to shift their load simultaneously during off-peak period to avoid rebound peak condition. Peak to average ratio (PAR) is considered while carrying out minimization problem. Linear programming problem (LPP) method is used for minimization. The simulation results of this work show the effectiveness of the minimization method adopted. The hardware work is in progress and the program based on the method described here will be made to solve real problem.

The scope of the LeChatelier Principle

Science.gov (United States)

George M., Lady; Quirk, James P.

2007-07-01

LeChatelier [Comptes Rendus 99 (1884) 786; Ann. Mines 13 (2) (1888) 157] showed that a physical system's “adjustment” to a disturbance to its equilibrium tended to be smaller as constraints were added to the adjustment process. Samuelson [Foundations of Economic Analysis, Harvard University Press, Cambridge, 1947] applied this result to economics in the context of the comparative statics of the actions of individual agents characterized as the solutions to optimization problems; and later (1960), extended the application of the Principle to a stable, multi-market equilibrium and the case of all commodities gross substitutes [e.g., L. Metzler, Stability of multiple markets: the hicks conditions. Econometrica 13 (1945) 277-292]. Refinements and alternative routes of derivation have appeared in the literature since then, e.g., Silberberg [The LeChatelier Principle as a corollary to a generalized envelope theorem, J. Econ. Theory 3 (1971) 146-155; A revision of comparative statics methodology in economics, or, how to do comparative statics on the back of an envelope, J. Econ. Theory 7 (1974) 159-172], Milgrom and Roberts [The LeChatelier Principle, Am. Econ. Rev. 86 (1996) 173-179], W. Suen, E. Silberberg, P. Tseng [The LeChatelier Principle: the long and the short of it, Econ. Theory 16 (2000) 471-476], and Chavas [A global analysis of constrained behavior: the LeChatelier Principle ‘in the large’, South. Econ. J. 72 (3) (2006) 627-644]. In this paper, we expand the scope of the Principle in various ways keyed to Samuelson's proposed means of testing comparative statics results (optimization, stability, and qualitative analysis). In the optimization framework, we show that the converse LeChatelier Principle also can be found in constrained optimization problems and for not initially “conjugate” sensitivities. We then show how the Principle and its converse can be found through the qualitative analysis of any linear system. In these terms, the Principle and

Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization

Science.gov (United States)

Seko, Atsuto; Togo, Atsushi; Hayashi, Hiroyuki; Tsuda, Koji; Chaput, Laurent; Tanaka, Isao

2015-11-01

Compounds of low lattice thermal conductivity (LTC) are essential for seeking thermoelectric materials with high conversion efficiency. Some strategies have been used to decrease LTC. However, such trials have yielded successes only within a limited exploration space. Here, we report the virtual screening of a library containing 54 779 compounds. Our strategy is to search the library through Bayesian optimization using for the initial data the LTC obtained from first-principles anharmonic lattice-dynamics calculations for a set of 101 compounds. We discovered 221 materials with very low LTC. Two of them even have an electronic band gap <1 eV , which makes them exceptional candidates for thermoelectric applications. In addition to those newly discovered thermoelectric materials, the present strategy is believed to be powerful for many other applications in which the chemistry of materials is required to be optimized.

A numerical investigation on piezoresistive behaviour of carbon nanotube/polymer composites: mechanism and optimizing principle

International Nuclear Information System (INIS)

Wang Zhifeng; Ye Xiongying

2013-01-01

Carbon nanotubes (CNTs) filled polymeric composites can be used as a kind of flexible piezoresistive material in potentially many fields. Due to the diversity of CNTs and polymers, the mechanism and features of their piezoresistive behaviour is still not fully understood. This paper reports our investigations into the mechanism and optimization of piezoresistive CNT/polymer composites. Numerical simulation results showed that the junction resistances between CNTs are a major component of the network conductance of the composite as well as the piezoresistive behaviour. Average junction gap variation (AJGV) was introduced as a quantitative description of the conductance variation of a CNT network caused by strain and the conductance variation of the CNT network was found to be dominated by AJGV. Numerical simulation and analytical results indicated that the key parameters affecting AJGV include the orientation and diameter of CNTs, Poisson’s ratio of the polymer, and the concentration of CNTs in the polymer matrix. An optimizing principle was then given for piezoresistive CNT/polymer composites. (paper)

[Optimization of calcium alginate floating microspheres loading aspirin by artificial neural networks and response surface methodology].

Science.gov (United States)

Zhang, An-yang; Fan, Tian-yuan

2010-04-18

To investigate the preparation and optimization of calcium alginate floating microspheres loading aspirin. A model was used to predict the in vitro release of aspirin and optimize the formulation by artificial neural networks (ANNs) and response surface methodology (RSM). The amounts of the material in the formulation were used as inputs, while the release and floating rate of the microspheres were used as outputs. The performances of ANNs and RSM were compared. ANNs were more accurate in prediction. There was no significant difference between ANNs and RSM in optimization. Approximately 90% of the optimized microspheres could float on the artificial gastric juice over 4 hours. 42.12% of aspirin was released in 60 min, 60.97% in 120 min and 78.56% in 240 min. The release of the drug from the microspheres complied with Higuchi equation. The aspirin floating microspheres with satisfying in vitro release were prepared successfully by the methods of ANNs and RSM.

Mechanically braked elliptical Wingate test: modification considerations, load optimization, and reliability.

Science.gov (United States)

Ozkaya, Ozgur; Colakoglu, Muzaffer; Kuzucu, Erinc O; Yildiztepe, Engin

2012-05-01

The 30-second, all-out Wingate test evaluates anaerobic performance using an upper or lower body cycle ergometer (cycle Wingate test). A recent study showed that using a modified electromagnetically braked elliptical trainer for Wingate testing (EWT) leads to greater power outcomes because of larger muscle group recruitment. The main purpose of this study was to modify an elliptical trainer using an easily understandable mechanical brake system instead of an electromagnetically braked modification. Our secondary aim was to determine a proper test load for the EWT to reveal the most efficient anaerobic test outcomes such as peak power (PP), average power (AP), minimum power (MP), power drop (PD), and fatigue index ratio (FI%) and to evaluate the retest reliability of the selected test load. Delta lactate responses (ΔLa) were also analyzed to confirm all the anaerobic performance of the athletes. Thirty healthy and well-trained male university athletes were selected to participate in the study. By analysis of variance, an 18% body mass workload yielded significantly greater test outcomes (PP = 19.5 ± 2.4 W·kg, AP = 13.7 ± 1.7 W·kg, PD = 27.9 ± 5 W·s, FI% = 58.4 ± 3.3%, and ΔLa = 15.4 ± 1.7 mM) than the other (12-24% body mass) tested loads (p braked modification of an elliptical trainer successfully estimated anaerobic power and capacity. A workload of 18% body mass was optimal for measuring maximal and reliable anaerobic power outcomes. Anaerobic testing using an EWT may be more useful to athletes and coaches than traditional cycle ergometers because a greater proportion of muscle groups are worked during exercise on an elliptical trainer.

Enhanced Ungual Permeation of Terbinafine HCl Delivered Through Liposome-Loaded Nail Lacquer Formulation Optimized by QbD Approach.

Science.gov (United States)

Shah, Viral H; Jobanputra, Amee

2018-01-01

The present investigation focused on developing, optimizing, and evaluating a novel liposome-loaded nail lacquer formulation for increasing the transungual permeation flux of terbinafine HCl for efficient treatment of onychomycosis. A three-factor, three-level, Box-Behnken design was employed for optimizing process and formulation parameters of liposomal formulation. Liposomes were formulated by thin film hydration technique followed by sonication. Drug to lipid ratio, sonication amplitude, and sonication time were screened as independent variables while particle size, PDI, entrapment efficiency, and zeta potential were selected as quality attributes for liposomal formulation. Multiple regression analysis was employed to construct a second-order quadratic polynomial equation and contour plots. Design space (overlay plot) was generated to optimize a liposomal system, with software-suggested levels of independent variables that could be transformed to desired responses. The optimized liposome formulation was characterized and dispersed in nail lacquer which was further evaluated for different parameters. Results depicted that the optimized terbinafine HCl-loaded liposome formulation exhibited particle size of 182 nm, PDI of 0.175, zeta potential of -26.8 mV, and entrapment efficiency of 80%. Transungual permeability flux of terbinafine HCl through liposome-dispersed nail lacquer formulation was observed to be significantly higher in comparison to nail lacquer with a permeation enhancer. The developed formulation was also observed to be as efficient as pure drug dispersion in its antifungal activity. Thus, it was concluded that the developed formulation can serve as an efficient tool for enhancing the permeability of terbinafine HCl across human nail plate thereby improving its therapeutic efficiency.

Optimality principles in the regulation of metabolic networks.

Science.gov (United States)

Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Optimality Principles in the Regulation of Metabolic Networks

Directory of Open Access Journals (Sweden)

Jan Berkhout

2012-08-01

Full Text Available One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Optimal Load-Tracking Operation of Grid-Connected Solid Oxide Fuel Cells through Set Point Scheduling and Combined L1-MPC Control

Directory of Open Access Journals (Sweden)

Siwei Han

2018-03-01

Full Text Available An optimal load-tracking operation strategy for a grid-connected tubular solid oxide fuel cell (SOFC is studied based on the steady-state analysis of the system thermodynamics and electrochemistry. Control of the SOFC is achieved by a two-level hierarchical control system. In the upper level, optimal setpoints of output voltage and the current corresponding to unit load demand is obtained through a nonlinear optimization by minimizing the SOFC’s internal power waste. In the lower level, a combined L1-MPC control strategy is designed to achieve fast set point tracking under system nonlinearities, while maintaining a constant fuel utilization factor. To prevent fuel starvation during the transient state resulting from the output power surging, a fuel flow constraint is imposed on the MPC with direct electron balance calculation. The proposed control schemes are testified on the grid-connected SOFC model.

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

International Nuclear Information System (INIS)

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

1979-01-01

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

Basic Knowledge for Market Principle: Approaches to the Price Coordination Mechanism by Using Optimization Theory and Algorithm

Science.gov (United States)

Aiyoshi, Eitaro; Masuda, Kazuaki

On the basis of market fundamentalism, new types of social systems with the market mechanism such as electricity trading markets and carbon dioxide (CO2) emission trading markets have been developed. However, there are few textbooks in science and technology which present the explanation that Lagrange multipliers can be interpreted as market prices. This tutorial paper explains that (1) the steepest descent method for dual problems in optimization, and (2) Gauss-Seidel method for solving the stationary conditions of Lagrange problems with market principles, can formulate the mechanism of market pricing, which works even in the information-oriented modern society. The authors expect readers to acquire basic knowledge on optimization theory and algorithms related to economics and to utilize them for designing the mechanism of more complicated markets.

Problems of radiation protection optimization

International Nuclear Information System (INIS)

Morkunas, G.

2003-01-01

One of the basic principles - optimization of radiation protection - is rather well understood by everybody engaged in protection of humans from ionizing radiation. However, the practical application of this principle is very problematic. This fact can be explained by vagueness of concept of dose constraints, possible legal consequences of any decision based on this principle, traditions of prescriptive system of radiation protection requirements in some countries, insufficiency of qualified expertise. The examples of optimization problems are the different attention given to different kinds of practices, not optimized application of remedial measures, strict requirements for radioactive contamination of imported products, uncertainties in optimization in medical applications of ionizing radiation. Such tools as international co-operation including regional networks of information exchange, training of qualified experts, identification of measurable indicators used for judging about the level of optimization may be the helpful practical means in solving of these problems. It is evident that the principle of optimization can not be replaced by any other alternative despite its complexity. The means for its practical implementation shall be searched for. (author)

Development, optimization, and in vitro characterization of dasatinib-loaded PEG functionalized chitosan capped gold nanoparticles using Box-Behnken experimental design.

Science.gov (United States)

Adena, Sandeep Kumar Reddy; Upadhyay, Mansi; Vardhan, Harsh; Mishra, Brahmeshwar

2018-03-01

The purpose of this research study was to develop, optimize, and characterize dasatinib loaded polyethylene glycol (PEG) stabilized chitosan capped gold nanoparticles (DSB-PEG-Ch-GNPs). Gold (III) chloride hydrate was reduced with chitosan and the resulting nanoparticles were coated with thiol-terminated PEG and loaded with dasatinib (DSB). Plackett-Burman design (PBD) followed by Box-Behnken experimental design (BBD) were employed to optimize the process parameters. Polynomial equations, contour, and 3D response surface plots were generated to relate the factors and responses. The optimized DSB-PEG-Ch-GNPs were characterized by FTIR, XRD, HR-SEM, EDX, TEM, SAED, AFM, DLS, and ZP. The results of the optimized DSB-PEG-Ch-GNPs showed particle size (PS) of 24.39 ± 1.82 nm, apparent drug content (ADC) of 72.06 ± 0.86%, and zeta potential (ZP) of -13.91 ± 1.21 mV. The responses observed and the predicted values of the optimized process were found to be close. The shape and surface morphology studies showed that the resulting DSB-PEG-Ch-GNPs were spherical and smooth. The stability and in vitro drug release studies confirmed that the optimized formulation was stable at different conditions of storage and exhibited a sustained drug release of the drug of up to 76% in 48 h and followed Korsmeyer-Peppas release kinetic model. A process for preparing gold nanoparticles using chitosan, anchoring PEG to the particle surface, and entrapping dasatinib in the chitosan-PEG surface corona was optimized.

Foundational principles of classical Ayurveda research

Directory of Open Access Journals (Sweden)

Somik Raha

2013-01-01

Full Text Available Double-blind randomized controlled trials (RCTs are viewed as the golden standard of drug research in Western medicine. However, RCTs are far from "golden" in many respects. They are impractical for many therapies, such as for surgeries and complex lifestyle changes. They encourage a one-size-fits-all approach to medical treatment that fails to address the huge diversity among individual patients in terms of their physical and emotional symptoms, social and cultural upbringing, and other factors. Perhaps, more importantly, they do not help doctors make the best medical decisions required to produce optimal patient outcomes. To guide a search for an alternate model of medical research, three principles based on Ayurveda, an ancient and powerful system of health care that has stood the test of time, are presented. These principles, arrived at after mining Ayurvedic epistemology, are: Inductive learning, whole systems thinking, and individually optimized therapy. In honor of the ancient sages or "Rishis," whose voice is used to deliver Ayurvedic knowledge in the ancient texts of Ayurveda, these are referred to as the "Rishi principles." Individually optimized therapy is interpreted using the lens of decision analysis. Common research methodologies are examined for embodiment of these principles.

Optimization of waste loading in high-level glass in the presence of uncertainty

International Nuclear Information System (INIS)

Hoza, M.; Fann, G.I.; Hopkins, D.F.

1995-02-01

Hanford high-level liquid waste will be converted into a glass form for long-term storage. The glass must meet certain constraints on its composition and properties in order to have desired properties for processing (e.g., electrical conductivity, viscosity, and liquidus temperature) and acceptable durability for long-term storage. The Optimal Waste Loading (OWL) models, based on rigorous mathematical optimization techniques, have been developed to minimize the number of glass logs required and determine glass-former compositions that will produce a glass meeting all relevant constraints. There is considerable uncertainty in many of the models and data relevant to the formulation of high-level glass. In this paper, we discuss how we handle uncertainty in the glass property models and in the high-level waste composition to the vitrification process. Glass property constraints used in optimization are inequalities that relate glass property models obtained by regression analysis of experimental data to numerical limits on property values. Therefore, these constraints are subject to uncertainty. The sampling distributions of the regression models are used to describe the uncertainties associated with the constraints. The optimization then accounts for these uncertainties by requiring the constraints to be satisfied within specified confidence limits. The uncertainty in waste composition is handled using stochastic optimization. Given means and standard deviations of component masses in the high-level waste stream, distributions of possible values for each component are generated. A series of optimization runs is performed; the distribution of each waste component is sampled for each run. The resultant distribution of solutions is then statistically summarized. The ability of OWL models to handle these forms of uncertainty make them very useful tools in designing and evaluating high-level waste glasses formulations

UES: an optimization software package for power and energy

International Nuclear Information System (INIS)

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

2004-01-01

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

Residential Load Manageability Factor Analyses by Load Sensitivity Affected by Temperature

Directory of Open Access Journals (Sweden)

N. Eskandari

2016-12-01

Full Text Available Load side management is the basic and significant principle to keeping the balance between generation side and consumption side of electrical power energy. Load side management on typical medium voltage feeder is the power energy consumption control of connected loads with variation of essential parameters that loads do reaction to their variation. Knowing amount of load's reaction to each parameters variation in typical medium voltage feeder during the day, leads to gain Load Manageability Factor (LMF for that specific feeder that helps power utilities to manage their connected loads. Calculating this LMF needs to find out each types of load with unique inherent features behavior to each parameters variation. This paper results and future work results will help us to catch mentioned LMF. In this paper analysis of residential load behavior due to temperature variation with training artificial neural network will be done. Load behavior due to other essential parameters variations like energy pricing variation, major event happening, and power utility announcing to the customers, and etc will study in future works. Collecting all related works results in a unit mathematical equation or an artificial neural network will gain LMF.

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-07-26

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.

A General Stochastic Maximum Principle for SDEs of Mean-field Type

International Nuclear Information System (INIS)

Buckdahn, Rainer; Djehiche, Boualem; Li Juan

2011-01-01

We study the optimal control for stochastic differential equations (SDEs) of mean-field type, in which the coefficients depend on the state of the solution process as well as of its expected value. Moreover, the cost functional is also of mean-field type. This makes the control problem time inconsistent in the sense that the Bellman optimality principle does not hold. For a general action space a Peng’s-type stochastic maximum principle (Peng, S.: SIAM J. Control Optim. 2(4), 966–979, 1990) is derived, specifying the necessary conditions for optimality. This maximum principle differs from the classical one in the sense that here the first order adjoint equation turns out to be a linear mean-field backward SDE, while the second order adjoint equation remains the same as in Peng’s stochastic maximum principle.

On the Pontryagin maximum principle for systems with delays. Economic applications

Science.gov (United States)

Kim, A. V.; Kormyshev, V. M.; Kwon, O. B.; Mukhametshin, E. R.

2017-11-01

The Pontryagin maximum principle [6] is the key stone of finite-dimensional optimal control theory [1, 2, 5]. So beginning with opening the maximum principle it was important to extend the maximum principle on various classes of dynamical systems. In t he paper we consider some aspects of application of i-smooth analysis [3, 4] in the theory of the Pontryagin maximum principle [6] for systems with delays, obtained results can be applied by elaborating optimal program controls in economic models with delays.

Optimization of sodium loading on zeolite support for catalyzed transesterification of triolein with methanol.

Science.gov (United States)

Wang, Yu-Yuan; Chou, Hsin-Yu; Chen, Bing-Hung; Lee, Duu-Jong

2013-10-01

Optimization of sodium loading on zeolite HY for catalyzed transesterification of triolein in excess methanol to biodiesel was studied. Zeolite HY catalyst was activated by loading sodium ions to their surface via an ion-exchange method. The effects of ion-exchange process parameters, including the temperature, the process time, the pH value, as well as concentrations and sources of Na(+) cations (NaOH, NaCl and Na2SO4), on the conversion yield of triolein to biodiesel were investigated. Most of these Na(+)-activated zeolite HY catalysts could really facilitate the catalyzed transesterification reaction of triolein to biodiesel at a lower temperature near 65°C. Consequently, a high conversion yield of triglycerides to biodiesel at 97.3% was obtained at 65°C. Moreover, the durability of zeolite catalysts was examined as well. Catalytic performance tests of these zeolite catalysts in transesterification did not show a significant decrease in catalysis at least for three batch cycles. Copyright © 2013 Elsevier Ltd. All rights reserved.

The free-energy principle: a unified brain theory?

Science.gov (United States)

Friston, Karl

2010-02-01

A free-energy principle has been proposed recently that accounts for action, perception and learning. This Review looks at some key brain theories in the biological (for example, neural Darwinism) and physical (for example, information theory and optimal control theory) sciences from the free-energy perspective. Crucially, one key theme runs through each of these theories - optimization. Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle, which suggests that several global brain theories might be unified within a free-energy framework.

Finite Element Analysis and Crashworthiness Optimization of Foam-filled Double Circular under Oblique Loading

Directory of Open Access Journals (Sweden)

Fauzan Djamaluddin

Full Text Available Abstract Finite element analysis and optimization design carry out for the quasi static responses of foam-filled double circular tube is presented in this paper. In the investigation of the crashworthiness capability, some aspects were considered for variations in geometry parameters of tubes and the loading condition to investigate the crashworthiness capability. Empty, foam-filled, and full foam-filled doublé tubes of thin walled structures were observed subjected to oblique impact (0˚ - 40˚. The numerical solution was used to determine the crashworthiness parameters. In addition, NSGA II and Radial Basis Function were used to optimize the crashworthiness capability of tubes. In conclution, the crash performaces of foam-filled double tube is better than the other structures in this work. The outcome that expected is the new design information of various kinds of cylindrical tubes for energy absorber application.

Solving unit commitment and economic load dispatch problems ...

African Journals Online (AJOL)

Economic Load Dispatch (ELD) and Unit Commitment (UC) are very important applications to predict the optimized cost of load in a power system. UC determines working states for existing generating units under some operational constraints and then optimizing the operation cost for all running units w.r.t. load demand ...

LIGHT-WEIGHT LOAD-BEARING STRUCTURE

DEFF Research Database (Denmark)

2009-01-01

The invention relates to a light-weight load-bearing structure (1) with optimized compression zone (2), where along one or more compression zones (2) in the structure (1) to be cast a core (3) of strong concrete is provided, which core (3) is surrounded by concrete of less strength (4) compared...... to the core (3) of strong concrete. The invention also relates to a method of casting of light-weight load-bearing structures (1) with optimized compression zone (2) where one or more channels, grooves, ducts, pipes and/or hoses (5) formed in the load-bearing structure (1) serves as moulds for moulding one...... or more cores (3) of strong concrete in the light-weight load-bearing structure (1)....

Variational principles in physics

CERN Document Server

Basdevant, Jean-Louis

2007-01-01

Optimization under constraints is an essential part of everyday life. Indeed, we routinely solve problems by striking a balance between contradictory interests, individual desires and material contingencies. This notion of equilibrium was dear to thinkers of the enlightenment, as illustrated by Montesquieu’s famous formulation: "In all magistracies, the greatness of the power must be compensated by the brevity of the duration." Astonishingly, natural laws are guided by a similar principle. Variational principles have proven to be surprisingly fertile. For example, Fermat used variational methods to demonstrate that light follows the fastest route from one point to another, an idea which came to be known as Fermat’s principle, a cornerstone of geometrical optics. Variational Principles in Physics explains variational principles and charts their use throughout modern physics. The heart of the book is devoted to the analytical mechanics of Lagrange and Hamilton, the basic tools of any physicist. Prof. Basdev...

Joint Optimization of Power Allocation and Load Balancing for Hybrid VLC/RF Networks

KAUST Repository

Obeed, Mohanad; Salhab, Anas; Zummo, Salam A.; Alouini, Mohamed-Slim

2018-01-01

In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF access point (AP) and multiple VLC APs. An iterative algorithm is proposed to distribute users on APs and distribute the powers of the APs on their users. In the PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for total achievable data rate maximization. In this subproblem, we propose a new efficient algorithm that finds optimal dual variables after formulating them in terms of each other. This new algorithm provides faster convergence and better performance than the traditional subgradient method. In addition, it does not depend on the step size or the initial values of the variables, which we look for, as the subgradient does. Then, we start with the user of the minimum data rate seeking another AP that offers a higher data rate for that user. Users with lower data rates continue reconnecting from one AP to another to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. Two approaches are proposed to have the joint PA and LB performed: a main approach that considers the exact interference information for all users, and a suboptimal approach that aims to decrease the complexity of the first approach by considering only the approximate interference information of users. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.

Joint Optimization of Power Allocation and Load Balancing for Hybrid VLC/RF Networks

KAUST Repository

Obeed, Mohanad

2018-04-18

In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF access point (AP) and multiple VLC APs. An iterative algorithm is proposed to distribute users on APs and distribute the powers of the APs on their users. In the PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for total achievable data rate maximization. In this subproblem, we propose a new efficient algorithm that finds optimal dual variables after formulating them in terms of each other. This new algorithm provides faster convergence and better performance than the traditional subgradient method. In addition, it does not depend on the step size or the initial values of the variables, which we look for, as the subgradient does. Then, we start with the user of the minimum data rate seeking another AP that offers a higher data rate for that user. Users with lower data rates continue reconnecting from one AP to another to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. Two approaches are proposed to have the joint PA and LB performed: a main approach that considers the exact interference information for all users, and a suboptimal approach that aims to decrease the complexity of the first approach by considering only the approximate interference information of users. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.

Optimal control of algae growth by controlling CO 2 and nutrition flow using Pontryagin Maximum Principle

Science.gov (United States)

Mardlijah; Jamil, Ahmad; Hanafi, Lukman; Sanjaya, Suharmadi

2017-09-01

There are so many benefit of algae. One of them is using for renewable energy and sustainable in the future. The greater growth of algae will increasing biodiesel production and the increase of algae growth is influenced by glucose, nutrients and photosynthesis process. In this paper, the optimal control problem of the growth of algae is discussed. The objective function is to maximize the concentration of dry algae while the control is the flow of carbon dioxide and the nutrition. The solution is obtained by applying the Pontryagin Maximum Principle. and the result show that the concentration of algae increased more than 15 %.

Optimization of large scale food production using Lean Manufacturing principles

DEFF Research Database (Denmark)

Engelund, Eva Høy; Friis, Alan; Breum, Gitte

2009-01-01

This paper discusses how the production principles of Lean Manufacturing (Lean) can be applied in a large-scale meal production. Lean principles are briefly presented, followed by a field study of how a kitchen at a Danish hospital has implemented Lean in the daily production. In the kitchen...... not be negatively affected by the rationalisation of production procedures. The field study shows that Lean principles can be applied in meal production and can result in increased production efficiency and systematic improvement of product quality without negative effects on the working environment. The results...... show that Lean can be applied and used to manage the production of meals in the kitchen....

Dry Gel Containing Optimized Felodipine-Loaded Transferosomes: a Promising Transdermal Delivery System to Enhance Drug Bioavailability.

Science.gov (United States)

Kassem, Mohammed Ali; Aboul-Einien, Mona Hassan; El Taweel, Mai Magdy

2018-04-30

Felodipine has a very low bioavailability due to first-pass metabolism. The aim of this study was to enhance its bioavailability by transdermal application. Felodipine-loaded transferosomes were prepared by thin-film hydration using different formulation variables. An optimized formula was designed using statistical experimental design. The independent variables were the used edge activator, its molar ratio to phosphatidylcholine, and presence or absence of cholesterol. The responses were entrapment efficiency of transferosomes, their size, polydispersity index, zeta potential, and percent drug released after 8 h. The optimized formula was subjected to differential scanning calorimetry studies and its stability on storage at 4°C for 6 months was estimated. This formula was improved by incorporation of different permeation enhancers where ex vivo drug flux through mice skin was estimated and the best improved formula was formulated in a gel and lyophilized. The prepared gel was subjected to in vivo study using Plendil® tablets as a reference. According to the calculated desirability, the optimized transferosome formula was that containing sodium deoxycholate as edge activator at 5:1 M ratio to phosphatidylcholine and no cholesterol. The thermograms of this formula indicated the incorporation of felodipine inside the prepared vesicles. None of the tested parameters differed significantly on storage. The lyophilized gel of labrasol-containing formula was chosen for in vivo study. The relative bioavailability of felodipine from the designed gel was 1.7. In conclusion, topically applied lyophilized gel containing felodipine-loaded transferosomes is a promising transdermal delivery system to enhance its bioavailability.

Non-euclidean simplex optimization

International Nuclear Information System (INIS)

Silver, G.L.

1977-01-01

Geometric optimization techniques useful for studying chemical equilibrium traditionally rely upon principles of euclidean geometry, but such algorithms may also be based upon principles of a non-euclidean geometry. The sequential simplex method is adapted to the hyperbolic plane, and application of optimization to problems such as the potentiometric titration of plutonium is suggested

A study on the optimal fuel loading pattern design in pressurized water reactor using the artificial neural network and the fuzzy rule based system

International Nuclear Information System (INIS)

Kim, Han Gon; Chang, Soon Heung; Lee, Byung

2004-01-01

The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. In this paper, an optimal loading pattern is defined that the local power peaking factor is lower than predetermined value during one cycle and the effective multiplication factor is maximized in order to extract maximum energy. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (author)

A study on the optimal fuel loading pattern design in pressurized water reactor using the artificial neural network and the fuzzy rule based system

Energy Technology Data Exchange (ETDEWEB)

Kim, Han Gon; Chang, Soon Heung; Lee, Byung [Department of Nuclear Engineering, Korea Advanced Institute of Science and Technology, Yusong-gu, Taejon (Korea, Republic of)

2004-07-01

The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. In this paper, an optimal loading pattern is defined that the local power peaking factor is lower than predetermined value during one cycle and the effective multiplication factor is maximized in order to extract maximum energy. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (author)

Evaluation of load flow and grid expansion in a unit-commitment and expansion optimization model SciGRID International Conference on Power Grid Modelling

Science.gov (United States)

Senkpiel, Charlotte; Biener, Wolfgang; Shammugam, Shivenes; Längle, Sven

2018-02-01

Energy system models serve as a basis for long term system planning. Joint optimization of electricity generating technologies, storage systems and the electricity grid leads to lower total system cost compared to an approach in which the grid expansion follows a given technology portfolio and their distribution. Modelers often face the problem of finding a good tradeoff between computational time and the level of detail that can be modeled. This paper analyses the differences between a transport model and a DC load flow model to evaluate the validity of using a simple but faster transport model within the system optimization model in terms of system reliability. The main findings in this paper are that a higher regional resolution of a system leads to better results compared to an approach in which regions are clustered as more overloads can be detected. An aggregation of lines between two model regions compared to a line sharp representation has little influence on grid expansion within a system optimizer. In a DC load flow model overloads can be detected in a line sharp case, which is therefore preferred. Overall the regions that need to reinforce the grid are identified within the system optimizer. Finally the paper recommends the usage of a load-flow model to test the validity of the model results.

Large-scale preparation of clove essential oil and eugenol-loaded liposomes using a membrane contactor and a pilot plant.

Science.gov (United States)

Sebaaly, Carine; Greige-Gerges, Hélène; Agusti, Géraldine; Fessi, Hatem; Charcosset, Catherine

2016-01-01

Based on our previous study where optimal conditions were defined to encapsulate clove essential oil (CEO) into liposomes at laboratory scale, we scaled-up the preparation of CEO and eugenol (Eug)-loaded liposomes using a membrane contactor (600 mL) and a pilot plant (3 L) based on the principle of ethanol injection method, both equipped with a Shirasu Porous Glass membrane for injection of the organic phase into the aqueous phase. Homogenous, stable, nanometric-sized and multilamellar liposomes with high phospholipid, Eug loading rates and encapsulation efficiency of CEO components were obtained. Saturation of phospholipids and drug concentration in the organic phase may control the liposome stability. Liposomes loaded with other hydrophobic volatile compounds could be prepared at large scale using the ethanol injection method and a membrane for injection.

Reliability Constrained Priority Load Shedding for Aerospace Power System Automation

Science.gov (United States)

Momoh, James A.; Zhu, Jizhong; Kaddah, Sahar S.; Dolce, James L. (Technical Monitor)

2000-01-01

The need for improving load shedding on board the space station is one of the goals of aerospace power system automation. To accelerate the optimum load-shedding functions, several constraints must be involved. These constraints include congestion margin determined by weighted probability contingency, component/system reliability index, generation rescheduling. The impact of different faults and indices for computing reliability were defined before optimization. The optimum load schedule is done based on priority, value and location of loads. An optimization strategy capable of handling discrete decision making, such as Everett optimization, is proposed. We extended Everett method to handle expected congestion margin and reliability index as constraints. To make it effective for real time load dispatch process, a rule-based scheme is presented in the optimization method. It assists in selecting which feeder load to be shed, the location of the load, the value, priority of the load and cost benefit analysis of the load profile is included in the scheme. The scheme is tested using a benchmark NASA system consisting of generators, loads and network.

A contribution to the solution of the problems raised by the application of the principle of protection optimization to nuclear plants

International Nuclear Information System (INIS)

Lacourly, G.; Demerle, P.

1975-01-01

The radiological protection of populations and the environment rests on two main principles: the dose delivered to the individuals of the most exposed population group must remain below the dose limits set up by regulations; the doses must be kept as low as readly achievable social and economic considerations being taken into account. If the application of the former principle has now become routine work, the application of the latter one implying optimization calculus raises a number of difficult problems. In order to decide whether an exposure can be easily reduced, both the benefits of the reduction and its cost must be considered, which leads to undertake a differential analysis [fr

The optimization of peptide cargo bound to MHC class I molecules by the peptide-loading complex.

Science.gov (United States)

Elliott, Tim; Williams, Anthony

2005-10-01

Major histocompatibility complex (MHC) class I complexes present peptides from both self and foreign intracellular proteins on the surface of most nucleated cells. The assembled heterotrimeric complexes consist of a polymorphic glycosylated heavy chain, non-polymorphic beta(2) microglobulin, and a peptide of typically nine amino acids in length. Assembly of the class I complexes occurs in the endoplasmic reticulum and is assisted by a number of chaperone molecules. A multimolecular unit termed the peptide-loading complex (PLC) is integral to this process. The PLC contains a peptide transporter (transporter associated with antigen processing), a thiooxido-reductase (ERp57), a glycoprotein chaperone (calreticulin), and tapasin, a class I-specific chaperone. We suggest that class I assembly involves a process of optimization where the peptide cargo of the complex is edited by the PLC. Furthermore, this selective peptide loading is biased toward peptides that have a longer off-rate from the assembled complex. We suggest that tapasin is the key chaperone that directs this action of the PLC with secondary contributions from calreticulin and possibly ERp57. We provide a framework model for how this may operate at the molecular level and draw parallels with the proposed mechanism of action of human leukocyte antigen-DM for MHC class II complex optimization.

Discrete PSO algorithm based optimization of transmission lines loading in TNEP problem

International Nuclear Information System (INIS)

Shayeghi, H.; Mahdavi, M.; Bagheri, A.

2010-01-01

Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e. expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using discrete particle swarm optimization (DPSO) algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. The proposed idea has been tested on the Garvers network and an actual transmission network of the Azerbaijan regional electric company, Iran, and the results are compared with the decimal codification genetic algorithm (DCGA) technique. The results evaluation shows that the network will possess maximum efficiency economically. Also, it is shown that precision and convergence speed of the proposed DPSO based method for the solution of the STNEP problem is superior to DCGA approach.

Optimization Strategy for Economic Power Dispatch Utilizing Retired EV Batteries as Flexible Loads

Directory of Open Access Journals (Sweden)

Shubo Hu

2018-06-01

Full Text Available With the increasing penetration of new and renewable energy, incorporating variable adjustable power elements on the demand side is of particular interest. The utilization of batteries as flexible loads is a hot research topic. Lithium-ion batteries are key components in electric vehicles (EVs in terms of capital cost, mass and size. They are retired after around 5 years of service, but still retain up to 80% of their nominal capacity. Disposal of waste batteries will become a significant issue for the automotive industry in the years to come. This work proposes the use of the second life of these batteries as flexible loads to participate in the economic power dispatch. The characteristics of second life batteries (SLBs are varied and diverse, requiring a new optimization strategy for power dispatch at the system level. In this work, SLBs are characterized and their operating curves are obtained analytically for developing an economic power dispatch model involving wind farms and second life batteries. In addition, a dispatch strategy is developed to reduce the dispatch complex brought by the disperse spatial and time distribution of EVs and decrease the system operating cost by introducing incentive and penalty costs in regulating the EV performance. In theory, SLBs are utilized to reduce the peak-valley difference of power loads and to stabilize the power system. Test results based on a ten-unit power system have verified the effectiveness of the proposed dispatch model and the economic benefit of utilizing SLBs as flexible loads in power systems. This work may provide a viable solution to the disposal of waste batteries from EVs and to the stable operation of fluctuating power systems incorporating stochastic renewable energy.

An analytical method for optimal design of MR valve structures

International Nuclear Information System (INIS)

Nguyen, Q H; Choi, S B; Lee, Y S; Han, M S

2009-01-01

This paper proposes an analytical methodology for the optimal design of a magnetorheological (MR) valve structure. The MR valve structure is constrained in a specific volume and the optimization problem identifies geometric dimensions of the valve structure that maximize the yield stress pressure drop of a MR valve or the yield stress damping force of a MR damper. In this paper, the single-coil and two-coil annular MR valve structures are considered. After describing the schematic configuration and operating principle of a typical MR valve and damper, a quasi-static model is derived based on the Bingham model of a MR fluid. The magnetic circuit of the valve and damper is then analyzed by applying Kirchoff's law and the magnetic flux conservation rule. Based on quasi-static modeling and magnetic circuit analysis, the optimization problem of the MR valve and damper is built. In order to reduce the computation load, the optimization problem is simplified and a procedure to obtain the optimal solution of the simplified optimization problem is presented. The optimal solution of the simplified optimization problem of the MR valve structure constrained in a specific volume is then obtained and compared with the solution of the original optimization problem and the optimal solution obtained from the finite element method

Widened Mazing principle for interpreting curves of nonisothermal deformation in tests with hold up

Energy Technology Data Exchange (ETDEWEB)

Kul' chikhin, E T; Martynenko, M E; Sadakov, O S [Chelyabinskij Politekhnicheskij Inst. (USSR)

1979-11-01

Principle of plotting deformation diagrams, is obtained from the results of the analysis of structural model behaviour of cyclically stable medium when using the arbitrary program for repeated-variable non-isothermal loading with hold up (creep, relaxation). The principle uses the instantaneous diagram of intial (or cyclic) deformation and is based on the formation rules of material ''memory'' about loading prehistory. Experimental investigations carried out using the 1Kh18N9T structural alloys show that the above principle is satisfactory.

A Method for Optimal Load Dispatch of a Multi-zone Power System with Zonal Exchange Constraints

Science.gov (United States)

Hazarika, Durlav; Das, Ranjay

2018-04-01

This paper presented a method for economic generation scheduling of a multi-zone power system having inter zonal operational constraints. For this purpose, the generator rescheduling for a multi area power system having inter zonal operational constraints has been represented as a two step optimal generation scheduling problem. At first, the optimal generation scheduling has been carried out for the zone having surplus or deficient generation with proper spinning reserve using co-ordination equation. The power exchange required for the deficit zones and zones having no generation are estimated based on load demand and generation for the zone. The incremental transmission loss formulas for the transmission lines participating in the power transfer process among the zones are formulated. Using these, incremental transmission loss expression in co-ordination equation, the optimal generation scheduling for the zonal exchange has been determined. Simulation is carried out on IEEE 118 bus test system to examine the applicability and validity of the method.

Drug loading optimization and extended drug delivery of corticoids from pHEMA based soft contact lenses hydrogels via chemical and microstructural modifications.

Science.gov (United States)

García-Millán, Eva; Koprivnik, Sandra; Otero-Espinar, Francisco Javier

2015-06-20

This paper proposes an approach to improve drug loading capacity and release properties of poly(2-hydroxyethyl methacrylate) (p(HEMA)) soft contact lenses based on the optimization of the hydrogel composition and microstructural modifications using water during the polymerization process. P(HEMA) based soft contact lenses were prepared by thermal or photopolymerization of 2-hydroxyethyl methacrylate (HEMA) solutions containing ethylene glycol di-methacrylate as crosslinker and different proportions of N-vinyl-2-pyrrolidone (NVP) or methacrylic acid (MA) as co-monomers. Transmittance, water uptake, swelling, microstructure, drug absorption isotherms and in vitro release were characterized using triamcinolone acetonide (TA) as model drug. Best drug loading ratios were obtained with lenses containing the highest amount (200 mM) of MA. Incorporation of 40% V/V of water during the polymerization increases the hydrogel porosity giving a better drug loading capacity. In vitro TA release kinetics shows that MA hydrogels released the drug significantly faster than NVP-hydrogels. Drug release was found to be diffusion controlled and kinetics was shown to be reproducible after consecutive drug loading/release processes. Results of p(HEMA) based soft contact lenses copolymerized with ethylene glycol dimethacrylate (EGDMA) and different co-monomers could be a good alternative to optimize the loading and ocular drug delivery of this corticosteroid drug. Copyright © 2015. Published by Elsevier B.V.

Optimal/flatness based-control of stand-alone power systems using fuel cells, batteries and supercapacitors

Directory of Open Access Journals (Sweden)

Mahdi Benaouadj

2017-03-01

Full Text Available In this work, an optimal control (under constraints based on the Pontryagin’s maximum principle is used to optimally manage energy flows in a basic PEM (Proton Exchange Membrane fuel cells system associated to lithium-ion batteries and supercapacitors through a common DC bus having a voltage to stabilize using the differential flatness approach. The adaptation of voltage levels between different sources and load is ensured by use of three DCDC converters, one boost connected to the PEM fuel cells, while the two others are buck/boost and connected to the lithium-ion batteries and supercapacitors. The aim of this paper is to develop an energy management strategy that is able to satisfy the following objectives: - Impose the power requested by a habitat (representing the load according to a proposed daily consumption profile, - Keep fuel cells working at optimal power delivery conditions, - Maintain constant voltage across the common DC bus, - Stabilize the batteries voltage and stored quantity of charge at desired values given by the optimal control. Results obtained under MATLAB/Simulink environment prove that the cited objectives are satisfied, validating then, effectiveness and complementarity between the optimal and flatness concepts proposed for energy management. Note that this study is currently in experimentally validation within MSE Laboratory.

Conversion Rate Optimization : Visual Neuro Programming Principles

OpenAIRE

Berezhnaya, Anastasia

2016-01-01

The influence of the world wide web has already spread in every business. Consequently, it has become crucial to develop strong online presence and offer qualified user experience for website visitors. Website optimization undeniably has proved its importance in the recent decade. This research was conducted in order to study the practical application and structure of the stages of the CRO (Conversion Rate Optimization) framework that focuses on the most representative website metric – c...

Future residential loads profiles : scenario-based analysis of high penetration of heavy loads and distributed generation

NARCIS (Netherlands)

Asare-Bediako, B.; Kling, W.L.; Ribeiro, P.F.

2014-01-01

Electric load profiles are useful for accurate load forecasting, network planning and optimal generation capacity. They represent electricity demand patterns and are to a large extent predictable. However, new and heavier loads (heat pumps and electric vehicles), distributed generation, and home

Load calculations of radiant cooling systems for sizing the plant

DEFF Research Database (Denmark)

Bourdakis, Eleftherios; Kazanci, Ongun Berk; Olesen, Bjarne W.

2015-01-01

The aim of this study was, by using a building simulation software, to prove that a radiant cooling system should not be sized based on the maximum cooling load but at a lower value. For that reason six radiant cooling models were simulated with two control principles using 100%, 70% and 50......% of the maximum cooling load. It was concluded that all tested systems were able to provide an acceptable thermal environment even when the 50% of the maximum cooling load was used. From all the simulated systems the one that performed the best under both control principles was the ESCS ceiling system. Finally...... it was proved that ventilation systems should be sized based on the maximum cooling load....

The effect of optimal wall loads and blanket technologies on the cost of fusion electricity

International Nuclear Information System (INIS)

Knight, P.J.; Ward, D.J.

2000-01-01

This paper presents a discussion of trends in fusion economics based on technology, as well as, physics arguments. Based on relatively simple physics considerations, supported by detailed systems code calculations, it is shown that optimal wall loads are not high. The results of systems code calculations, focussing on the economic impact of different blanket technologies, are described. These suggest that the economically favourable thermodynamic efficiencies of some blankets capable of operating at higher temperatures may be counterbalanced by the economic penalties of shorter lifetimes

The MIND method: A decision support for optimization of industrial energy systems - Principles and case studies

International Nuclear Information System (INIS)

Karlsson, Magnus

2011-01-01

Changes in complex industrial energy systems require adequate tools to be evaluated satisfactorily. The MIND method (Method for analysis of INDustrial energy systems) is a flexible method constructed as decision support for different types of analyses of industrial energy systems. It is based on Mixed Integer Linear Programming (MILP) and developed at Linkoeping University in Sweden. Several industries, ranging from the food industry to the pulp and paper industry, have hitherto been modelled and analyzed using the MIND method. In this paper the principles regarding the use of the method and the creation of constraints of the modelled system are presented. Two case studies are also included, a dairy and a pulp and paper mill, that focus some measures that can be evaluated using the MIND method, e.g. load shaping, fuel conversion and introduction of energy efficiency measures. The case studies illustrate the use of the method and its strengths and weaknesses. The results from the case studies are related to the main issues stated by the European Commission, such as reduction of greenhouse gas emissions, improvements regarding security of supply and increased use of renewable energy, and show great potential as regards both cost reductions and possible load shifting.

Interactive Distance Education: A Cognitive Load Perspective

Science.gov (United States)

Kalyuga, Slava

2012-01-01

Evidence-based approaches to the design of the next generation of interactive distance education need to take into account established multimedia learning principles. Cognitive load theory is a theory that has significantly contributed to the development of such principles. It has applied our knowledge of major features and processing limitations…

Principles of Emergency Department facility design for optimal management of mass-casualty incidents.

Science.gov (United States)

Halpern, Pinchas; Goldberg, Scott A; Keng, Jimmy G; Koenig, Kristi L

2012-04-01

The Emergency Department (ED) is the triage, stabilization and disposition unit of the hospital during a mass-casualty incident (MCI). With most EDs already functioning at or over capacity, efficient management of an MCI requires optimization of all ED components. While the operational aspects of MCI management have been well described, the architectural/structural principles have not. Further, there are limited reports of the testing of ED design components in actual MCI events. The objective of this study is to outline the important infrastructural design components for optimization of ED response to an MCI, as developed, implemented, and repeatedly tested in one urban medical center. In the authors' experience, the most important aspects of ED design for MCI have included external infrastructure and promoting rapid lockdown of the facility for security purposes; an ambulance bay permitting efficient vehicle flow and casualty discharge; strategic placement of the triage location; patient tracking techniques; planning adequate surge capacity for both patients and staff; sufficient command, control, communications, computers, and information; well-positioned and functional decontamination facilities; adequate, well-located and easily distributed medical supplies; and appropriately built and functioning essential services. Designing the ED to cope well with a large casualty surge during a disaster is not easy, and it may not be feasible for all EDs to implement all the necessary components. However, many of the components of an appropriate infrastructural design add minimal cost to the normal expenditures of building an ED. This study highlights the role of design and infrastructure in MCI preparedness in order to assist planners in improving their ED capabilities. Structural optimization calls for a paradigm shift in the concept of structural and operational ED design, but may be necessary in order to maximize surge capacity, department resilience, and patient and

Optimality principles in the regulation of metabolic networks

NARCIS (Netherlands)

Berkhout, J.; Bruggeman, F.J.; Teusink, B.

2012-01-01

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks

An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Nur Faziera Napis

2018-05-01

Full Text Available The presence of optimized distributed generation (DG with suitable distribution network reconfiguration (DNR in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO is proposed in this research. The objective function is formulated to minimize the total power losses (TPL and to improve the voltage stability index (VSI. The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO and iteration particle swarm optimization (IPSO. Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms.

Two conceptions of legal principles

Directory of Open Access Journals (Sweden)

Spaić Bojan

2017-01-01

Full Text Available The paper discusses the classical understanding of legal principles as the most general norms of a legal order, confronting it with Dworkin's and Alexy's understanding of legal principles as prima facie, unconditional commands. The analysis shows that the common, classical conception brings into question the status of legal principles as norms, by disreguarding their usefulness in judicial reasoning, while, conversely, the latterhas significant import forlegal practice and consequently for legal dogmatics. It is argued that the heuristic fruitfulness of understanding principles as optimization commands thusbecomesapparent. When we understand the relation of priciples to the idea of proportionality, as thespecific mode of their application, which is different from the supsumtive mode of applying rules, the theory of legal principles advanced by Dworkin and Alexy appears therefore to be descriptively better than others, but not without its flaws.

Fuel cells, batteries and super-capacitors stand-alone power systems management using optimal/flatness based-control

Energy Technology Data Exchange (ETDEWEB)

Benaouadj, M.; Aboubou, A.; Bahri, M.; Boucetta, A. [MSE Laboratory, Mohamed khiderBiskra University (Algeria); Ayad, M. Y., E-mail: ayadmy@gmail.com [R& D, Industrial Hybrid Vehicle Applications (France)

2016-07-25

In this work, an optimal control (under constraints) based on the Pontryagin’s maximum principle is used to optimally manage energy flows in a basic PEM (Proton Exchange Membrane) fuel cells system associated to lithium-ion batteries and supercapacitors through a common DC bus having a voltage to stabilize using the differential flatness approach. The adaptation of voltage levels between different sources and load is ensured by use of three DC-DC converters, one boost connected to the PEM fuel cells, while the two others are buck/boost and connected to the lithiumion batteries and supercapacitors. The aim of this paper is to develop an energy management strategy that is able to satisfy the following objectives: Impose the power requested by a habitat (representing the load) according to a proposed daily consumption profile, Keep fuel cells working at optimal power delivery conditions, Maintain constant voltage across the common DC bus, Stabilize the batteries voltage and stored quantity of charge at desired values given by the optimal control. Results obtained under MATLAB/Simulink environment prove that the cited objectives are satisfied, validating then, effectiveness and complementarity between the optimal and flatness concepts proposed for energy management. Note that this study is currently in experimentally validation within MSE Laboratory.

Poly ɛ-caprolactone nanoparticles loaded with Uncaria tomentosa extract: preparation, characterization, and optimization using the Box–Behnken design

Science.gov (United States)

Ribeiro, Ana Ferreira; de Oliveira Rezende, Ricardo Leite; Cabral, Lúcio Mendes; de Sousa, Valéria Pereira

2013-01-01

Purpose The aim of this research was to develop and optimize a process for obtaining poly ɛ-caprolactone (PCL) nanoparticles loaded with Uncaria tomentosa (UT) extract. Methods Nanoparticles were produced by the oil-in-water emulsion solvent evaporation method. Preliminary experiments determined the initial conditions of the organic phase (OP) and of the aqueous phase (AP) that would be utilized for this study. Ultimately, a three-factor three-level Box–Behnken design (BBD) was employed during the optimization process. PCL and polyvinyl alcohol (PVA) concentrations (X1 and X2, respectively) and the AP/OP volume ratio (X3) were the independent variables studied, while entrapment efficiency (Y1), particle mean diameter (Y2), polydispersity (Y3), and zeta potential (Y4) served as the evaluated responses. Results Preliminary experiments revealed that the optimal initial conditions for the preparation of nanoparticles were as follows: OP composed of 5 mL ethyl acetate/acetone (3/2) mixture containing UT extract and PCL, and an AP of buffered PVA (pH 7.5) solution. Statistical analysis of the BBD results indicated that all of the studied factors had significant effects on the responses Y1, Y2, and Y4, and these effects are closely described or fitted by regression equations. Based on the obtained models and the selected desirability function, the nanoparticles were optimized to maximize Y1 and minimize Y2. These optimal conditions were achieved using 3% (w/v) PCL, 1% (w/v) PVA, and an AP/OP ratio of 1.7, with predicted values of 89.1% for Y1 and 280 nm for Y2. Another batch was produced under the same optimal conditions. The entrapment efficiency of this new batch was measured at 81.6% (Y1) and the particles had a mean size of 247 nm (Y2) and a polydispersity index of 0.062 (Y3). Conclusion This investigation obtained UT-loaded nanoparticle formulations with desired characteristics. The BBD approach was a useful tool for nanoparticle development and optimization, and

A Maximum Principle for SDEs of Mean-Field Type

Energy Technology Data Exchange (ETDEWEB)

Andersson, Daniel, E-mail: danieand@math.kth.se; Djehiche, Boualem, E-mail: boualem@math.kth.se [Royal Institute of Technology, Department of Mathematics (Sweden)

2011-06-15

We study the optimal control of a stochastic differential equation (SDE) of mean-field type, where the coefficients are allowed to depend on some functional of the law as well as the state of the process. Moreover the cost functional is also of mean-field type, which makes the control problem time inconsistent in the sense that the Bellman optimality principle does not hold. Under the assumption of a convex action space a maximum principle of local form is derived, specifying the necessary conditions for optimality. These are also shown to be sufficient under additional assumptions. This maximum principle differs from the classical one, where the adjoint equation is a linear backward SDE, since here the adjoint equation turns out to be a linear mean-field backward SDE. As an illustration, we apply the result to the mean-variance portfolio selection problem.

A Maximum Principle for SDEs of Mean-Field Type

International Nuclear Information System (INIS)

Andersson, Daniel; Djehiche, Boualem

2011-01-01

We study the optimal control of a stochastic differential equation (SDE) of mean-field type, where the coefficients are allowed to depend on some functional of the law as well as the state of the process. Moreover the cost functional is also of mean-field type, which makes the control problem time inconsistent in the sense that the Bellman optimality principle does not hold. Under the assumption of a convex action space a maximum principle of local form is derived, specifying the necessary conditions for optimality. These are also shown to be sufficient under additional assumptions. This maximum principle differs from the classical one, where the adjoint equation is a linear backward SDE, since here the adjoint equation turns out to be a linear mean-field backward SDE. As an illustration, we apply the result to the mean-variance portfolio selection problem.

Procedure and methodology of Radiation Protection optimization

International Nuclear Information System (INIS)

Wang Hengde

1995-01-01

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

Optimal Control of Hypersonic Planning Maneuvers Based on Pontryagin’s Maximum Principle

Directory of Open Access Journals (Sweden)

A. Yu. Melnikov

2015-01-01

Full Text Available The work objective is the synthesis of simple analytical formula of the optimal roll angle of hypersonic gliding vehicles for conditions of quasi-horizontal motion, allowing its practical implementation in onboard control algorithms.The introduction justifies relevance, formulates basic control tasks, and describes a history of scientific research and achievements in the field concerned. The author reveals a common disadvantage of the other authors’ methods, i.e. the problem of practical implementation in onboard control algorithms.The similar tasks of hypersonic maneuvers are systemized according to the type of maneuver, control parameters and limitations.In the statement of the problem the glider launched horizontally with a suborbital speed glides passive in the static Atmosphere on a spherical surface of constant radius in the Central field of gravitation.The work specifies a system of equations of motion in the inertial spherical coordinate system, sets the limits on the roll angle and optimization criteria at the end of the flight: high speed or azimuth and the minimum distances to the specified geocentric points.The solution.1 A system of equations of motion is transformed by replacing the time argument with another independent argument – the normal equilibrium overload. The Hamiltonian and the equations of mated parameters are obtained using the Pontryagin’s maximum principle. The number of equations of motion and mated vector is reduced.2 The mated parameters were expressed by formulas using current movement parameters. The formulas are proved through differentiation and substitution in the equations of motion.3 The Formula of optimal roll-position control by condition of maximum is obtained. After substitution of mated parameters, the insertion of constants, and trigonometric transformations the Formula of the optimal roll angle is obtained as functions of the current parameters of motion.The roll angle is expressed as the ratio

Fundamental Safety Principles

International Nuclear Information System (INIS)

Abdelmalik, W.E.Y.

2011-01-01

This work presents a summary of the IAEA Safety Standards Series publication No. SF-1 entitled F UDAMENTAL Safety PRINCIPLES p ublished on 2006. This publication states the fundamental safety objective and ten associated safety principles, and briefly describes their intent and purposes. Safety measures and security measures have in common the aim of protecting human life and health and the environment. These safety principles are: 1) Responsibility for safety, 2) Role of the government, 3) Leadership and management for safety, 4) Justification of facilities and activities, 5) Optimization of protection, 6) Limitation of risks to individuals, 7) Protection of present and future generations, 8) Prevention of accidents, 9)Emergency preparedness and response and 10) Protective action to reduce existing or unregulated radiation risks. The safety principles concern the security of facilities and activities to the extent that they apply to measures that contribute to both safety and security. Safety measures and security measures must be designed and implemented in an integrated manner so that security measures do not compromise safety and safety measures do not compromise security.

Optimization of a permanent magnet synchronous machine with respect to variable loads; Optimierung einer permanenterregten Synchronmaschine unter Beruecksichtigung von Lastspielen

Energy Technology Data Exchange (ETDEWEB)

Kreim, Alexander; Schaefer, Uwe [TU Berlin (Germany). Sek. EM4 Elektrische Antriebstechnik

2010-10-15

This article introduces a nonlinear optimization algorithm for mixed integer problems. The proposed algorithm is a trust region algorithm for an exact penalty function. The quadratic subproblem is used for the integration of discrete variables. This is done by a branch-and-bound approach. The application of the algorithm is shown by minimizing the losses of a permanent magnet synchronous machine. The machine is designed for use in hybrid and electric vehicles. It is shown how load cycles can be included into the optimization process. (orig.)

Heuristic rules embedded genetic algorithm to solve VVER loading pattern optimization problem

International Nuclear Information System (INIS)

Fatih, Alim; Kostandi, Ivanov

2006-01-01

Full text: Loading Pattern (LP) optimization is one of the most important aspects of the operation of nuclear reactors. A genetic algorithm (GA) code GARCO (Genetic Algorithm Reactor Optimization Code) has been developed with embedded heuristic techniques to perform optimization calculations for in-core fuel management tasks. GARCO is a practical tool that includes a unique methodology applicable for all types of Pressurized Water Reactor (PWR) cores having different geometries with an unlimited number of FA types in the inventory. GARCO was developed by modifying the classical representation of the genotype. Both the genotype representation and the basic algorithm have been modified to incorporate the in-core fuel management heuristics rules so as to obtain the best results in a shorter time. GARCO has three modes. Mode 1 optimizes the locations of the fuel assemblies (FAs) in the nuclear reactor core, Mode 2 optimizes the placement of the burnable poisons (BPs) in a selected LP, and Mode 3 optimizes simultaneously both the LP and the BP placement in the core. This study describes the basic algorithm for Mode 1. The GARCO code is applied to the VVER-1000 reactor hexagonal geometry core in this study. The M oby-Dick i s used as reactor physics code to deplete FAs in the core. It was developed to analyze the VVER reactors by SKODA Inc. To use these rules for creating the initial population with GA operators, the worth definition application is developed. Each FA has a worth value for each location. This worth is between 0 and 1. If worth of any FA for a location is larger than 0.5, this FA in this location is a good choice. When creating the initial population of LPs, a subroutine provides a percent of individuals, which have genes with higher than the 0.5 worth. The percentage of the population to be created without using worth definition is defined in the GARCO input. And also age concept has been developed to accelerate the GA calculation process in reaching the

Numerical study of the connection lengths for various magnetic configurations in Wendelstein 7-X to optimize the heat load on the divertor

Energy Technology Data Exchange (ETDEWEB)

Sinha, Priyanjana; Hoelbe, Hauke; Sunn Pedersen, Thomas [Max Planck Institute of Plasma Physics, Greifswald (Germany)

2016-07-01

Fusion has the potential to play an important role as a future energy resource. It has the capacity to produce large-scale clean energy. The two main confinement concepts are the tokamak and the stellarator. The W7-X machine is based on stellarator principle and is using special form of coils to achieve steady-state plasma confinement. Divertors are used in tokamaks and stellarator to control the exhaust of waste gases and impurities from the machine. The divertor concept of W7-X is a so-called island divertor. The island chain isolates the confinement core from regions where the plasma-wall interaction takes place. The area of the divertor that receives the main part of the heat loads, the so-called wetted area, increases with the distance along the magnetic field from the outboard midplane to the divertor target. The connection length is relatively short in tokamaks with conventional divertors. In the stellarator island divertor, the connection length can be varied significantly, which should allow for optimization of the wetted area. We present here a numerical study of the achievable connection lengths in various W7-X configurations and discuss the possibilities for running dedicated experiments to understand the physics of what sets the wetted area.

Strategies to optimize lithium-ion supercapacitors achieving high-performance: Cathode configurations, lithium loadings on anode, and types of separator

Science.gov (United States)

Cao, Wanjun; Li, Yangxing; Fitch, Brian; Shih, Jonathan; Doung, Tien; Zheng, Jim

2014-12-01

The Li-ion capacitor (LIC) is composed of a lithium-doped carbon anode and an activated carbon cathode, which is a half Li-ion battery (LIB) and a half electrochemical double-layer capacitor (EDLC). LICs can achieve much more energy density than EDLC without sacrificing the high power performance advantage of capacitors over batteries. LIC pouch cells were assembled using activated carbon (AC) cathode and hard carbon (HC) + stabilized lithium metal power (SLMP®) anode. Different cathode configurations, various SLMP loadings on HC anode, and two types of separators were investigated to achieve the optimal electrochemical performance of the LIC. Firstly, the cathode binders study suggests that the PTFE binder offers improved energy and power performances for LIC in comparison to PVDF. Secondly, the mass ratio of SLMP to HC is at 1:7 to obtain the optimized electrochemical performance for LIC among all the various studied mass ratios between lithium loading amounts and active anode material. Finally, compared to the separator Celgard PP 3501, cellulose based TF40-30 is proven to be a preferred separator for LIC.

High- and Low-Load Resistance Training: Interpretation and Practical Application of Current Research Findings.

Science.gov (United States)

Fisher, James; Steele, James; Smith, Dave

2017-03-01

Our current state of knowledge regarding the load (lighter or heavier) lifted in resistance training programmes that will result in 'optimal' strength and hypertrophic adaptations is unclear. Despite this, position stands and recommendations are made based on, we propose, limited evidence to lift heavier weights. Here we discuss the state of evidence on the impact of load and how it, as a single variable, stimulates adaptations to take place and whether evidence for recommending heavier loads is available, well-defined, currently correctly interpreted or has been overlooked. Areas of discussion include electromyography amplitude, in vivo and in vitro methods of measuring hypertrophy, and motor schema and skill acquisition. The present piece clarifies to trainers and trainees the impact of these variables by discussing interpretation of synchronous and sequential motor unit recruitment and revisiting the size principle, poor agreement between whole-muscle cross-sectional area (CSA) and biopsy-determined changes in myofibril CSA, and neural adaptations around task specificity. Our opinion is that the practical implications of being able to self-select external load include reducing the need for specific facility memberships, motivating older persons or those who might be less confident using heavy loads, and allowing people to undertake home- or field-based resistance training intervention strategies that might ultimately improve exercise adherence.

Design of a model predictive load-following controller by discrete optimization of control rod speed for PWRs

International Nuclear Information System (INIS)

Kim, Jae Hwan; Park, Soon Ho; Na, Man Gyun

2014-01-01

Highlights: • A model predictive controller for load-following operation was developed. • Genetic algorithm optimizes the five nonlinear discrete control rod speeds. • The boron concentration is adjusted with automatic adjustment logic. • The proposed controller reflects the realistic control rod drive mechanism movement. • The performance was confirmed to be satisfactory by simulation from BOC to EOC. - Abstract: Currently, most existing nuclear power plants alter the reactor power by adjusting the boron concentration in the coolant because it has a smaller effect on the reactor power distribution. Frequent control rod movements for load-following operation induce xenon-oscillation. Therefore, a controller that can subdue this phenomenon effectively is needed. At an APR1400 nuclear power plant which is a pressurized water reactor (PWR), the reactor power is controlled automatically using a Reactor Regulating System (RRS) but the power distribution is controlled manually by operators. Therefore, for APR+ nuclear power plants which is an improved version of APR1400 nuclear reactor, a new concept of a reactor controller is needed to control both the reactor power and power distribution automatically. The model predictive control (MPC) method is applicable to multiple-input multiple-output control, and can be applied for complex and nonlinear systems, such as the nuclear power plants. In this study, an MPC controller was developed by applying a genetic algorithm to optimize the discrete control rod speeds and by reflecting the realistic movement of the control rod drive mechanism that moves at only five discrete speeds. The performance of the proposed controller was confirmed to be satisfactory by simulating the load-following operation of an APR+ nuclear power plant through interface with KISPAC-1D code

Optimal fuzzy logic-based PID controller for load-frequency control including superconducting magnetic energy storage units

International Nuclear Information System (INIS)

Pothiya, Saravuth; Ngamroo, Issarachai

2008-01-01

This paper proposes a new optimal fuzzy logic-based-proportional-integral-derivative (FLPID) controller for load frequency control (LFC) including superconducting magnetic energy storage (SMES) units. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the multiple tabu search (MTS) algorithm is applied to simultaneously tune PID gains, membership functions and control rules of FLPID controller to minimize frequency deviations of the system against load disturbances. The MTS algorithm introduces additional techniques for improvement of search process such as initialization, adaptive search, multiple searches, crossover and restarting process. Simulation results explicitly show that the performance of the optimum FLPID controller is superior to the conventional PID controller and the non-optimum FLPID controller in terms of the overshoot, settling time and robustness against variations of system parameters

An exact model for airline flight network optimization based on transport momentum and aircraft load factor

Directory of Open Access Journals (Sweden)

Daniel Jorge Caetano

2017-12-01

Full Text Available The problem of airline flight network optimization can be split into subproblems such as Schedule Generation (SG and Fleet Assignment (FA, solved in consecutive steps or in an integrated way, usually based on monetary costs and revenue forecasts. A linear pro­gramming model to solve SG and FA in an integrated way is presented, but with an al­ternative approach based on transport momentum and aircraft load factor. This alterna­tive approach relies on demand forecast and allows obtaining solutions considering min­imum average load factors. Results of the proposed model applications to instances of a regional Brazilian airline are presented. The comparison of the schedules generated by the proposed approach against those obtained by applying a model based on mone­tary costs and revenue forecasts demonstrates the validity of this alternative approach for airlines network planning.

On kinematical minimum principles for rates and increments in plasticity

International Nuclear Information System (INIS)

Zouain, N.

1984-01-01

The optimization approach for elastoplastic analysis is discussed showing that some minimum principles related to numerical methods can be derived by means of duality and penalization procedures. Three minimum principles for velocity and plastic multiplier rate fields are presented in the framework of perfect plasticity. The first one is the classical Greenberg formulation. The second one, due to Capurso, is developed here with different motivation, and modified by penalization of constraints so as to arrive at a third principle for rates. The counterparts of these optimization formulations in terms of discrete increments of displacements of displacements and plastic multipliers are discussed. The third one of these minimum principles for finite increments is recognized to be closely related to Maier's formulation of holonomic plasticity. (Author) [pt

Guiding Principles for Data Requirements

Science.gov (United States)

The principles in the document are intended to help guide the identification of data needs, promote and optimize full use of existing knowledge, provide consistency in the data request process across all scientific disciplines for pesticide review.

Modelling and multi-objective optimization of a variable valve-timing spark-ignition engine using polynomial neural networks and evolutionary algorithms

International Nuclear Information System (INIS)

Atashkari, K.; Nariman-Zadeh, N.; Goelcue, M.; Khalkhali, A.; Jamali, A.

2007-01-01

The main reason for the efficiency decrease at part load conditions for four-stroke spark-ignition (SI) engines is the flow restriction at the cross-sectional area of the intake system. Traditionally, valve-timing has been designed to optimize operation at high engine-speed and wide open throttle conditions. Several investigations have demonstrated that improvements at part load conditions in engine performance can be accomplished if the valve-timing is variable. Controlling valve-timing can be used to improve the torque and power curve as well as to reduce fuel consumption and emissions. In this paper, a group method of data handling (GMDH) type neural network and evolutionary algorithms (EAs) are firstly used for modelling the effects of intake valve-timing (V t ) and engine speed (N) of a spark-ignition engine on both developed engine torque (T) and fuel consumption (Fc) using some experimentally obtained training and test data. Using such obtained polynomial neural network models, a multi-objective EA (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism are secondly used for Pareto based optimization of the variable valve-timing engine considering two conflicting objectives such as torque (T) and fuel consumption (Fc). The comparison results demonstrate the superiority of the GMDH type models over feedforward neural network models in terms of the statistical measures in the training data, testing data and the number of hidden neurons. Further, it is shown that some interesting and important relationships, as useful optimal design principles, involved in the performance of the variable valve-timing four-stroke spark-ignition engine can be discovered by the Pareto based multi-objective optimization of the polynomial models. Such important optimal principles would not have been obtained without the use of both the GMDH type neural network modelling and the multi-objective Pareto optimization approach

Applying Cognitive Load Theory Principles to Library Instructional Guidance

Science.gov (United States)

Pickens, Kathleen E.

2017-01-01

If the goal of library instructional guidance is to provide students with the knowledge needed to acquire new skills in order to accomplish their learning objectives, then it is prudent to consider factors that impact learning. Cognitive load theory addresses several of these factors and is applicable to a wide-range of instructional devices used…

The principles of radiation protection

International Nuclear Information System (INIS)

2004-01-01

The aim of radiation protection is to avoid or to reduce the risks linked to ionizing radiation. In order to reduce these risks, the radiation protection uses three great principles: justification, optimization and limitation of radiation doses. to apply these principles, the radiation protection has regulatory and technical means adapted to three different categories of people: public, patients and workers. The nuclear safety authority elaborates the regulation, and carries out monitoring of the reliable application of radiation protection system. (N.C.)

Quasi-static responses and variational principles in gradient plasticity

Science.gov (United States)

Nguyen, Quoc-Son

2016-12-01

Gradient models have been much discussed in the literature for the study of time-dependent or time-independent processes such as visco-plasticity, plasticity and damage. This paper is devoted to the theory of Standard Gradient Plasticity at small strain. A general and consistent mathematical description available for common time-independent behaviours is presented. Our attention is focussed on the derivation of general results such as the description of the governing equations for the global response and the derivation of related variational principles in terms of the energy and the dissipation potentials. It is shown that the quasi-static response under a loading path is a solution of an evolution variational inequality as in classical plasticity. The rate problem and the rate minimum principle are revisited. A time-discretization by the implicit scheme of the evolution equation leads to the increment problem. An increment of the response associated with a load increment is a solution of a variational inequality and satisfies also a minimum principle if the energy potential is convex. The increment minimum principle deals with stables solutions of the variational inequality. Some numerical methods are discussed in view of the numerical simulation of the quasi-static response.

The Cytotoxicity, Characteristics, and Optimization of Insulin-loaded Nanoparticles

Directory of Open Access Journals (Sweden)

Yasemin Budama-Kilinc

2017-04-01

Full Text Available Controlled release systems for insulin are frequent subjects of research, because it is rapidly degraded by proteolytic enzymes in the gastrointestinal tract and minimally absorbed after oral administration. Controlled release systems also provide significant contribution to its stability.  Different techniques are used for the preparation of drug-loaded nanoparticles, and many novel techniques are being developed. The size and morphology of insulin-loaded nanoparticles may vary according to performed techniques, even if the same polymer is used. The aim of this study was to demonstrate the cytotoxicity of insulin loaded nanoparticles and the effect of various synthesis parameters on the particle size, polydispersity index (PdI, loading efficiency, and particle morphology. In the experiments, poly(lactic-co-glycolic acid (PLGA and insulin-loaded PLGA nanoparticles were prepared using the double emulsion (w/o/w method. The characterization of the nanoparticles were performed with a UV spectrometer, the Zeta-sizer system, FTIR spectroscopy, and a scanning probe microscope. Cell toxicity of different concentrations was assayed with MTT methods on L929 fibroblast cells. The optimum size of the insulin-loaded PLGA nanoparticle was obtained with a 96.5% encapsulation efficiency, a 224.5 nm average particle size, and a 0.063 polydispersity index. This study obtained and characterized spherical morphology, determined that the nanoparticles have very low toxicity, and showed the effect of different parameters on particle size and polydispersity. DOI: http://dx.doi.org/10.17807/orbital.v9i1.934 

Optimal control theory an introduction

CERN Document Server

Kirk, Donald E

2004-01-01

Optimal control theory is the science of maximizing the returns from and minimizing the costs of the operation of physical, social, and economic processes. Geared toward upper-level undergraduates, this text introduces three aspects of optimal control theory: dynamic programming, Pontryagin's minimum principle, and numerical techniques for trajectory optimization.Chapters 1 and 2 focus on describing systems and evaluating their performances. Chapter 3 deals with dynamic programming. The calculus of variations and Pontryagin's minimum principle are the subjects of chapters 4 and 5, and chapter

Optimization of the first wall for the DEMO water cooled lithium lead blanket

Energy Technology Data Exchange (ETDEWEB)

Aubert, Julien, E-mail: julien.aubert@cea.fr [CEA Saclay, F-91191 Gif-Sur-Yvette (France); Aiello, Giacomo [CEA Saclay, F-91191 Gif-Sur-Yvette (France); Bachmann, Christian [EFDA, Boltzmannstraße 2, 85748 Garching (Germany); Di Maio, Pietro Alessandro [Università di Palermo, Viale delle Scienze, 90128 Palermo (Italy); Giammusso, Rosario [ENEA C.R. Brasimone, 40032 Camugnano, Bologna (Italy); Li Puma, Antonella; Morin, Alexandre [CEA Saclay, F-91191 Gif-Sur-Yvette (France); Tincani, Amelia [ENEA C.R. Brasimone, 40032 Camugnano, Bologna (Italy)

2015-10-15

temperatures equal to 285 °C/325 °C respectively and based on geometric design parameters such as channel pitch, diameter of pipes and thicknesses. It became clear through the optimization that the advantages of a waved FW are diminished. Given the manufacturing issues of that concept, the waved FW was therefore not pursued further. Even if the optimization study shows that the maximum heat load could in principle be as high as 2.53 MW m{sup −2}, it is reduced to 1.57 MW m{sup −2} when additional constraints are introduced in order not to affect corrosion, manufacturability and Tritium Breeding Ratio in normal condition such as a coolant velocity ≤8 m/s, pipe diameter ≥5 mm and a total FW thickness ≤22 mm. However it is important to note that the FW channels currently fulfill additional functions and are therefore not optimized “at all cost” regarding heat load capacity and the paper points out some recommendations against missing assumptions.

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

Directory of Open Access Journals (Sweden)

Feng Zhou

2015-11-01

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

Efficient Hybrid Genetic Based Multi Dimensional Host Load Aware Algorithm for Scheduling and Optimization of Virtual Machines

OpenAIRE

Thiruvenkadam, T; Karthikeyani, V

2014-01-01

Mapping the virtual machines to the physical machines cluster is called the VM placement. Placing the VM in the appropriate host is necessary for ensuring the effective resource utilization and minimizing the datacenter cost as well as power. Here we present an efficient hybrid genetic based host load aware algorithm for scheduling and optimization of virtual machines in a cluster of Physical hosts. We developed the algorithm based on two different methods, first initial VM packing is done by...

A Review of Multimedia Learning Principles: Split-Attention, Modality, and Redundancy Effects

Directory of Open Access Journals (Sweden)

Pelin YUKSEL ARSLAN

2012-02-01

Full Text Available This study aims to present a literature review on three principles of multimedia learningincluding split attention, modality, and redundancy effects with regard to their contribution to cognitiveload theory. According to cognitive load theory, information should be presented by considering excessiveload on working memory. The first principle states that attending to two distinct sources of informationmay impose a high cognitive load, and this process is referred to as the split-attention effect (Kalyuga,Chandler & Sweller, 1991, 1992. The second principle, Modality effect claims that on-screen text shouldbe presented in an auditory form instead of visually when designing a multimedia environment (Moreno &Mayer, 1999. Using more than one sensory mode augments forceful working memory that producesprogressive effects on learning. The third principle redundancy effect occurs when information presentedrepeatedly interferes with learning. This study provides guidance how to create more effective instructionwith multimedia materials for instructional designers.

Automatic load sharing in inverter modules

Science.gov (United States)

Nagano, S.

1979-01-01

Active feedback loads transistor equally with little power loss. Circuit is suitable for balancing modular inverters in spacecraft, computer power supplies, solar-electric power generators, and electric vehicles. Current-balancing circuit senses differences between collector current for power transistor and average value of load currents for all power transistors. Principle is effective not only in fixed duty-cycle inverters but also in converters operating at variable duty cycles.

Principles of radiological protection: new paradigms

International Nuclear Information System (INIS)

Ximenes, Edmir; Guimaraes, Maria Ines Calil Cury

2009-01-01

Full text: The relationships of workers, patients and physicians to the basic principles of radiological protection were given in this work an historical introduction that emphasizes their development from their beginnings to the current period. The evolution of scientific knowledge as regards the benefits and injuries resulting from the use of the ionizing radiation in human activities is the main focus of the work. These principles (justification, optimization and limitation) are presented in order to offer a broader view of their application fields. The principle of the optimization receives the contribution of techniques aimed to help the decision used in radiological protection. The principle of the limitation of doses is helped by the concept of limit specifically linked to a given segment of the population or a given human activity. Regarding the current relationship between physicians and patients a change of philosophy is discussed in what concerns the radiation dose supplied that should be the minimum one in relation to the diagnosis or cure objectives. The administration of radiation must follow the recommendations of ICRP - International Commission on Radiological Protection. The radiation can bring benefits if used with rationality, efficacy and care. The radiation should not be feared, but respected. (author)

Autotrophic and heterotrophic nitrification-anoxic denitrification dominated the anoxic/oxic sewage treatment process during optimization for higher loading rate and energy savings.

Science.gov (United States)

Zhang, Xueyu; Zheng, Shaokui; Zhang, Hangyu; Duan, Shoupeng

2018-04-30

This study clarified the dominant nitrogen (N)-transformation pathway and the key ammonia-oxidizing microbial species at three loading levels during optimization of the anoxic/oxic (A/O) process for sewage treatment. Comprehensive N-transformation activity analysis showed that ammonia oxidization was performed predominantly by aerobic chemolithotrophic and heterotrophic ammonia oxidization, whereas N 2 production was performed primarily by anoxic denitrification in the anoxic unit. The abundances of ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria, and anaerobic AOB in activated sludge reflected their activities on the basis of high-throughput sequencing data. AOB amoA gene clone libraries revealed that the predominant AOB species in sludge samples shifted from Nitrosomonas europaea (61% at the normal loading level) to Nitrosomonas oligotropha (58% and 81% at the two higher loading levels). Following isolation and sequencing, the predominant culturable heterotrophic AOB in sludge shifted from Agrobacterium tumefaciens (42% at the normal loading level) to Acinetobacter johnsonii (52% at the highest loading level). Copyright © 2018 Elsevier Ltd. All rights reserved.

Design principles of metal-cutting machine tools

CERN Document Server

Koenigsberger, F

1964-01-01

Design Principles of Metal-Cutting Machine Tools discusses the fundamentals aspects of machine tool design. The book covers the design consideration of metal-cutting machine, such as static and dynamic stiffness, operational speeds, gearboxes, manual, and automatic control. The text first details the data calculation and the general requirements of the machine tool. Next, the book discusses the design principles, which include stiffness and rigidity of the separate constructional elements and their combined behavior under load, as well as electrical, mechanical, and hydraulic drives for the op

Application of field synergy principle for optimization fluid flow and convective heat transfer in a tube bundle of a pre-heater

International Nuclear Information System (INIS)

Hamid, Mohammed O.A.; Zhang, Bo; Yang, Luopeng

2014-01-01

The big problems facing solar-assisted MED (multiple-effect distillation) desalination unit are the low efficiency and bulky heat exchangers, which worsen its systematic economic feasibility. In an attempt to develop heat transfer technologies with high energy efficiency, a mathematical study is established, and optimization analysis using FSP (field synergy principle) is proposed to support meaning of heat transfer enhancement of a pre-heater in a solar-assisted MED desalination unit. Numerical simulations are performed on fluid flow and heat transfer characteristics in a circular and elliptical tube bundle. The numerical results are analyzed using the concept of synergy angle and synergy number as an indication of synergy between velocity vector and temperature gradient fields. Heat transfer in elliptical tube bundle is enhanced significantly with increasing initial velocity of the feed seawater and field synergy number and decreasing of synergy angle. Under the same operating conditions of the two designs, the total average synergy angle is 78.97° and 66.31° in circular and elliptical tube bundle, respectively. Optimization of the pre-heater by FSP shows that in case of elliptical tube bundle design, the average synergy number and heat transfer rate are increased by 22.68% and 35.98% respectively. - Highlights: • FSP (field synergy principle) is used to investigate heat transfer enhancement. • Numerical simulations are performed in circular and elliptical tubes pre-heater. • Numerical results are analyzed using concept of synergy angle and synergy number. • Optimization of elliptical tube bundle by FSP has better performance