Optimization methods for activities selection problems
Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia
2017-08-01
Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.
Optimal Recognition Method of Human Activities Using Artificial Neural Networks
Directory of Open Access Journals (Sweden)
Oniga Stefan
2015-12-01
Full Text Available The aim of this research is an exhaustive analysis of the various factors that may influence the recognition rate of the human activity using wearable sensors data. We made a total of 1674 simulations on a publically released human activity database by a group of researcher from the University of California at Berkeley. In a previous research, we analyzed the influence of the number of sensors and their placement. In the present research we have examined the influence of the number of sensor nodes, the type of sensor node, preprocessing algorithms, type of classifier and its parameters. The final purpose is to find the optimal setup for best recognition rates with lowest hardware and software costs.
Directory of Open Access Journals (Sweden)
Iván Machín
2015-03-01
Full Text Available This paper presents a set of procedures based on mathematical optimization methods to establish optimal active sulphide phases with higher HDS activity. This paper proposes a list of active phases as a guide for orienting the experimental work in the search of new catalysts that permit optimize the HDS process. Studies in this paper establish Co-S, Cr-S, Nb-S and Ni-S systems have the greatest potential to improve HDS activity.
Directory of Open Access Journals (Sweden)
Olimpia PECINGINA
2016-05-01
Full Text Available Throughout the ages, man has continuously been involved with the process of optimization. In its earliest form, optimization consisted of unscientific rituals and prejudices like pouring libations and sacrificing animals to the gods, con- sulting the oracles, observing the positions of the stars, and watching the flight of birds. When the circumstances were appropriate, the timing was thought to be auspicious (or optimum for planting the crops or embarking on a war.
Planning and Optimization Methods for Active Distribution Systems
DEFF Research Database (Denmark)
Abbey, Chad; Baitch, Alex; Bak-Jensen, Birgitte
distribution planning. Active distribution networks (ADNs) have systems in place to control a combination of distributed energy resources (DERs), defined as generators, loads and storage. With these systems in place, the AND becomes an Active Distribution System (ADS). Distribution system operators (DSOs) have...
The Method of Optimization of Hydropower Plant Performance for Use in Group Active Power Controller
Directory of Open Access Journals (Sweden)
Glazyrin G.V.
2017-04-01
Full Text Available The problem of optimization of hydropower plant performance is considered in this paper. A new method of calculation of optimal load-sharing is proposed. The method is based on application of incremental water flow curves representing relationship between the per unit increase of water flow and active power. The optimal load-sharing is obtained by solving the nonlinear equation governing the balance of total active power and the station power set point with the same specific increase of water flow for all turbines. Unlike traditional optimization techniques, the solution of the equation is obtained without taking into account unit safe operating zones. Instead, if calculated active power of a unit violates the permissible power range, load-sharing is recalculated for the remaining generating units. Thus, optimal load-sharing algorithm suitable for digital control systems is developed. The proposed algorithm is implemented in group active power controller in Novosibirsk hydropower plant. An analysis of operation of group active power controller proves that the application of the proposed method allows obtaining optimal load-sharing at each control step with sufficient precision.
OPTIMIZATION METHOD AND SOFTWARE FOR FUEL COST REDUCTION IN CASE OF ROAD TRANSPORT ACTIVITY
Directory of Open Access Journals (Sweden)
György Kovács
2017-06-01
Full Text Available The transport activity is one of the most expensive processes in the supply chain and the fuel cost is the highest cost among the cost components of transportation. The goal of the research is to optimize the transport costs in case of a given transport task both by the selecting the optimal petrol station and by determining the optimal amount of the refilled fuel. Recently, in practice, these two decisions have not been made centrally at the forwarding company, but they depend on the individual decision of the driver. The aim of this study is to elaborate a precise and reliable mathematical method for selecting the optimal refuelling stations and determining the optimal amount of the refilled fuel to fulfil the transport demands. Based on the elaborated model, new decision-supporting software is developed for the economical fulfilment of transport trips.
Validation of an activity optimization method for nuclear medicine in planar studies
Energy Technology Data Exchange (ETDEWEB)
Perez D, M. [Central University of Las Villas, CEETI, Camajuani Road Km 5.5, Santa Clara 54830 Villa Clara (Cuba); Diaz R, O. [Institute for Sciences and Advanced Technologies (Cuba); Farias L, F. [Federal University of Pernambuco (Brazil)]. e-mail: mperez@uclv.edu.cu
2006-07-01
A method for optimizing the administered activity in Static Nuclear Medicine Studies is validated by comparison with ROC curve. Linear Discriminant analysis of image quality in gamma cameras was the applied statistical technique. The constructed linear discriminant function owns as dependent parameters, the differentiated levels of image quality obtained by observer's criterion. The independent parameters in the function were physical variables, as Signal-to Background ratios and Signal-to-Noise ratios. They were obtained from the selection of Regions of Interest in images obtained from a Jaszczak phantom, corresponding to lesion and background sites. The percentage of cases correctly classified by discriminant analysis was analyzed to grade the proposed discriminant method. The minimum value of the administered activity, which permits good image quality, (it means good results for the parameters selected by the discriminant function), can be proposed as an optimized value of activity for planar studies of Nuclear Medicine. The method was tested using images from a Jaszczak phantom, acquired under four activities (1088 MBq, 962 MBq, 740 MBq and 562 MBq) with a gamma camera equipped with a high resolution - low energy- parallel-hole collimator. The gamma camera was tested by a NEMA protocol. Image quality was graded by three expert observers who also developed a rated procedure which consist in analyzing the images for ROC analysis. Two of the six measured Background-to-Signal ratios were the parameters able to construct the linear discriminant function with high correlation respect to the observer criterion, from all the measured physical variables. The value of 740 MBq was the optimum after discriminant method application in this particular experiment. The results were coincident with the application of ROC-analysis. The optimal activity value obtained with the proposed discriminant procedure coincided with the activity value for which the area under the ROC
Discriminant method for the optimization of radionuclide activity in studies of nuclear medicine
International Nuclear Information System (INIS)
Perez Diaz, Marlen
2003-01-01
It is presented a method for the optimization of the radionuclidic activity to administer to mature patients in studies of Nuclear Medicine. The method is based in technical of discriminant analysis to build a function that discriminates groups with image quality differed on the base of physical parameters as they are the contrast image and the aleatory noise. The image quality is the dependent variable and it is selected by means of experts' evaluation and technical of clustering. The function is a lineal combination of a reduced group of variables physical-medical, able to discriminate the groups starting from a big group of variables measures. The method allows, also, to establish the relative weight of each discriminant variable selected . The behavior of the same ones is analyzed among studies carried out with different administered activity, with the objective of determining the minimum value of this that still allows good results in the image quality (Approach of activity optimization). It is validated the method by means of results comparison with the grateful Curved ROC in studies carried out with the Mannequins of Jaszczak (for planar studies) and of Insert Heart (for studies of SPECT). The optim activity value of the 99mTc, obtained with the application of the method, was coincident with the one obtained after the application of the method ROC to 6 expert observers as much in planar studies as in SPECT for two different cameras gamma. The method was applied later on in static, dynamic studies and of SPECT carried out with camera gamma to a mature population of 210 patient. The decisive variables of the quality of the image were obtained in the nuclear venticulography in rest, the bony gammagraphy, the nuclear renogram, the renal gammagraphy and the cerebral SPECT, as well as some activity values optimized for the equipment conditions and available radiopharmac in the country, allowing to establish a better commitment relationship between image quality
The application of multi-objective optimization method for activated sludge process: a review.
Dai, Hongliang; Chen, Wenliang; Lu, Xiwu
2016-01-01
The activated sludge process (ASP) is the most generally applied biological wastewater treatment approach. Depending on the design and specific application, activated sludge wastewater treatment plants (WWTPs) can achieve biological nitrogen (N) and phosphorus (P) removal, besides the removal of organic carbon substances. However, the effluent N and P limits are getting tighter because of increased emphasis on environmental protection, and the needs for energy conservation as well as the operational reliability. Therefore, the balance between treatment performance and cost becomes a critical issue for the operations of WWTPs, which necessitates a multi-objective optimization (MOO). Recent studies in this field have shown promise in utilizing MOO to address the multiple conflicting criteria (i.e. effluent quality, operation cost, operation stability), including studying the ASP models that are primarily responsible for the process, and developing the method of MOO in the wastewater treatment process, which facilitates better optimization of process performance. Based on a better understanding of the application of MOO for ASP, a comprehensive review is conducted to offer a clear vision of the advances, and potential areas for future research are also proposed in the field.
Methods of mathematical optimization
Vanderplaats, G. N.
The fundamental principles of numerical optimization methods are reviewed, with an emphasis on potential engineering applications. The basic optimization process is described; unconstrained and constrained minimization problems are defined; a general approach to the design of optimization software programs is outlined; and drawings and diagrams are shown for examples involving (1) the conceptual design of an aircraft, (2) the aerodynamic optimization of an airfoil, (3) the design of an automotive-engine connecting rod, and (4) the optimization of a 'ski-jump' to assist aircraft in taking off from a very short ship deck.
Stochastic optimization methods
Marti, Kurt
2005-01-01
Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.
Practical methods of optimization
Fletcher, R
2013-01-01
Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practical aspects in conjunction with the heuristics useful in making them perform more reliably and efficiently. To this end, it presents comparative numerical studies to give readers a feel for possibile applications and to illustrate the problems in assessing evidence. Also provides theoretical background which provides insights into how methods are derived. This edition offers rev
Kanthiah, Selvakumar; Kannappan, Valliappan
2017-08-01
This study describes a specific, precise, sensitive and accurate method for simultaneous determination of hydroxyzine, loratadine, terfenadine, rupatadine and their main active metabolites cetirizine, desloratadine and fexofenadine, in serum and urine using meclizine as an internal standard. Solid-phase extraction method for sample clean-up and preconcentration of analytes was carried out using Phenomenex Strata-X-C and Strata X polymeric cartridges. Chromatographic analysis was performed on a Phenomenex cyano (150 × 4.6 mm i.d., 5 μm) analytical column. A D-optimal mixture design methodology was used to evaluate the effect of changes in mobile phase compositions on dependent variables and optimization of the response of interest. The mixture design experiments were performed and results were analyzed. The region of ideal mobile phase composition consisting of acetonitrile-methanol-ammonium acetate buffer (40 mm; pH 3.8 adjusted with acetic acid): 18:36:46% v/v/v was identified by a graphical optimization technique using an overlay plot. While using this optimized condition all analytes were baseline resolved in rate and analytes peaks were detected at 222 nm. The proposed bioanalytical method was validated according to US Food and Drug Administration guidelines. The proposed method was sensitive with detection limits of 0.06-0.15 μg/mL in serum and urine samples. Relative standard deviation for inter- and intra-day precision data was found to be <7%. The proposed method may find application in the determination of selected antihistaminic drugs in biological fluids. Copyright © 2017 John Wiley & Sons, Ltd.
Stochastic optimization methods
Marti, Kurt
2008-01-01
Optimization problems arising in practice involve random model parameters. This book features many illustrations, several examples, and applications to concrete problems from engineering and operations research.
Analytical methods of optimization
Lawden, D F
2006-01-01
Suitable for advanced undergraduates and graduate students, this text surveys the classical theory of the calculus of variations. It takes the approach most appropriate for applications to problems of optimizing the behavior of engineering systems. Two of these problem areas have strongly influenced this presentation: the design of the control systems and the choice of rocket trajectories to be followed by terrestrial and extraterrestrial vehicles.Topics include static systems, control systems, additional constraints, the Hamilton-Jacobi equation, and the accessory optimization problem. Prereq
Li, Ran; Duan, Meng-Ying; Wu, Hong-Xin
2017-01-01
Response surface methodology (RSM) was used to investigate the extraction condition of polysaccharide from cup plant (Silphium perfoliatum L.) (named CPP). Water to raw material ratio (10–30 mL/g), extraction time (40–80 min) and extraction temperature (60–100°C) were set as the 3 independent variables, and their effects on the extraction yield of CPP were measured. In addition, the effects of drying methods including hot air drying (HD), vacuum drying (VD) and freeze drying (FD) on the antioxidant activities of CPP were evaluated. The results showed that the optimal condition to extract CPP was: water to raw material ratio (15 mL/g), extraction time (61 min), and extraction temperature (97°C), a maximum CPP yield of 6.49% was obtained under this condition. CPP drying with FD method showed stronger reducing power (0.943 at 6 mg/mL) and radical scavenging capacities against DPPH radical (75.71% at 1.2 mg/mL) and ABTS radical (98.06 at 1.6 mg/mL) than CPP drying with HD and VD methods. Therefore, freeze drying served as a good method for keeping the antioxidant activities of polysaccharide from cup plant. The polysaccharide from cup plant has potential to use as a natural antioxidant. PMID:28837625
Optimization methods for logical inference
Chandru, Vijay
2011-01-01
Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though ""solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks. . . it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs."" Presenting powerful, proven optimization techniques for logic in
Tiwari, S. P.; Singh, S.; Kumar, A.; Kumar, K.
2016-05-01
In present work, an optimized solvothermal method has been chosen to synthesize the singly doped Er3+ activator ions with La2O3 host matrix. The sample is annealed at 500 °C in order to remove the moisture and other organic impurities. The sample is characterized by using XRD and FESEM to find out the phase and surface morphology. The observed particle size is found almost 80 nm with spherical agglomerated shape. Upconversion spectra are recorded at room temperature using 976 nm diode laser excitation sources and consequently the emission peaks in green and red region are observed. The color coordinate diagram shows the results that the present material may be applicable in different light emitting sources.
Optimization methods in structural design
Rothwell, Alan
2017-01-01
This book offers an introduction to numerical optimization methods in structural design. Employing a readily accessible and compact format, the book presents an overview of optimization methods, and equips readers to properly set up optimization problems and interpret the results. A ‘how-to-do-it’ approach is followed throughout, with less emphasis at this stage on mathematical derivations. The book features spreadsheet programs provided in Microsoft Excel, which allow readers to experience optimization ‘hands-on.’ Examples covered include truss structures, columns, beams, reinforced shell structures, stiffened panels and composite laminates. For the last three, a review of relevant analysis methods is included. Exercises, with solutions where appropriate, are also included with each chapter. The book offers a valuable resource for engineering students at the upper undergraduate and postgraduate level, as well as others in the industry and elsewhere who are new to these highly practical techniques.Whi...
DEFF Research Database (Denmark)
Ding, Tao; Yang, Qingrun; Yang, Yongheng
2018-01-01
To address the uncertain output of distributed generators (DGs) for reactive power optimization in active distribution networks, the stochastic programming model is widely used. The model is employed to find an optimal control strategy with minimum expected network loss while satisfying all......, in this paper, a data-driven modeling approach is introduced to assume that the probability distribution from the historical data is uncertain within a confidence set. Furthermore, a data-driven stochastic programming model is formulated as a two-stage problem, where the first-stage variables find the optimal...... the physical constraints. Therein, the probability distribution of uncertainties in the stochastic model is always pre-defined by the historical data. However, the empirical distribution can be biased due to a limited amount of historical data and thus result in a suboptimal control decision. Therefore...
Optimizing How We Teach Research Methods
Cvancara, Kristen E.
2017-01-01
Courses: Research Methods (undergraduate or graduate level). Objective: The aim of this exercise is to optimize the ability for students to integrate an understanding of various methodologies across research paradigms within a 15-week semester, including a review of procedural steps and experiential learning activities to practice each method, a…
International Nuclear Information System (INIS)
Franken, K.
1987-06-01
The positron emitter fluorine-18 (T 1/2 = 110 min) is an ideal radionuclide for analogue tracers in positron emission tomography (PET). In this study the production of the electrophilic species [ 18 F]-F 2 , [ 18 F]-CH 3 CO 2 F and to some extent [ 18 F]-XeF 2 has been optimized with respect to yield and specific activity. Selectivity and reactivity of these species have been studied in simple aromatic model compounds. Fluorine was produced via the 20 Ne(d,α) 18 F reaction. The effect of target material, dimensions, amount of carrier (F 2 ), pressure, beam current and irradiation time was studied. Reactivity of [ 18 F]-F 2 and [ 18 F]-CH 3 CO 2 F with respect to hydrogen subsitution was systematically studied in a series of benzene derivatives (C 6 H 5 X, X = CF 3 , I, Br, CL, F, H, CH 3 , OCH 3 , OH) in various solvents (CHCl 3 , CFCl 3 , CH 3 CN, CH 3 OH, CF 3 COOH). The radiochemical yield of 18 F-for-H-substitution in the aromatic ring increased with increasing acceptor number (AN) of the solvent. The electrophilic nature of both fluorination agents was confirmed by a Hammett plot. As expected, [ 18 F]-CH 3 CO 2 F showed a higher selectivity than [ 18 F]-F 2 . Direct radiofluorination with [ 18 F]-F 2 and [ 18 F]-CH 3 CO 2 F was successfully applied to the biomolecules phenylalanine, tyrosine and DOPA. As potential methods for no-carrier-added (n.c.a.) radiofluorination some less common dediazoniation reactions were also studied. (orig./RB) [de
Optimization of Medical Teaching Methods
Directory of Open Access Journals (Sweden)
Wang Fei
2015-12-01
Full Text Available In order to achieve the goal of medical education, medicine and adapt to changes in the way doctors work, with the rapid medical teaching methods of modern science and technology must be reformed. Based on the current status of teaching in medical colleges method to analyze the formation and development of medical teaching methods, characteristics, about how to achieve optimal medical teaching methods for medical education teachers and management workers comprehensive and thorough change teaching ideas and teaching concepts provide a theoretical basis.
Distributed optimization system and method
Hurtado, John E.; Dohrmann, Clark R.; Robinett, III, Rush D.
2003-06-10
A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.
Optimal control linear quadratic methods
Anderson, Brian D O
2007-01-01
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material.The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the
van Noorden, C. J.; Vogels, I. M.; James, J.; Tas, J.
1982-01-01
A sensitive cytochemical staining method for glucose-6-phosphate dehydrogenase activity in individual human erythrocytes is described. This staining method can be used for the rapid routine discrimination of patients with a deficiency of the enzyme in its homozygote or heterozygote form, but also
Mozheiko, E Yu; Prokopenko, S V; Alekseevich, G V
To reason the choice of methods of restoration of advanced hand activity depending on severity of motor disturbance in the top extremity. Eighty-eight patients were randomized into 3 groups: 1) the mCIMT group, 2) the 'touch glove' group, 3) the control group. For assessment of physical activity of the top extremity Fugl-Meyer Assessment Upper Extremity, Nine-Hole Peg Test, Motor Assessment Scale were used. Assessment of non-use phenomenon was carried out with the Motor Activity Log scale. At a stage of severe motor dysfunction, there was a restoration of proximal departments of a hand in all groups, neither method was superior to the other. In case of moderate severity of motor deficiency of the upper extremity the most effective was the method based on the principle of biological feedback - 'a touch glove'. In the group with mild severity of motor dysfunction, the best recovery was achieved in the mCIMT group.
International Nuclear Information System (INIS)
Hartley, B.M.
1990-01-01
The accurate determiantion of the potential alpha energy of the descendants of radon relies on the determination of the individual number of atoms of those isotopes present. These are usually found by counting the particles emitted during radioactive decay of the individual atoms. By fitting the experimental count curve to the theoretical curve by a least squares method and using the number of atoms of the individual descendants present as the variable parameters, an optimal result can be obtained. Examination of the algorithm for generating the best fit indicates that it could be done in real time using microprocessors and gives the possibility of continuous evaluation of the number of atoms present and of the total potential alpha energy during counting. A comparison of ten different counting methods has been done theoretically using computer simulations of the count. For short counting times the method which can distinguish between each of the alpha particles and the beta particles is the most precise method available. It is shown that other methods of counting give comparable results when counting time is extended to over 2000 seconds. 4 refs., 1 tab., 2 figs
Evolutionary optimization methods for accelerator design
Poklonskiy, Alexey A.
Many problems from the fields of accelerator physics and beam theory can be formulated as optimization problems and, as such, solved using optimization methods. Despite growing efficiency of the optimization methods, the adoption of modern optimization techniques in these fields is rather limited. Evolutionary Algorithms (EAs) form a relatively new and actively developed optimization methods family. They possess many attractive features such as: ease of the implementation, modest requirements on the objective function, a good tolerance to noise, robustness, and the ability to perform a global search efficiently. In this work we study the application of EAs to problems from accelerator physics and beam theory. We review the most commonly used methods of unconstrained optimization and describe the GATool, evolutionary algorithm and the software package, used in this work, in detail. Then we use a set of test problems to assess its performance in terms of computational resources, quality of the obtained result, and the tradeoff between them. We justify the choice of GATool as a heuristic method to generate cutoff values for the COSY-GO rigorous global optimization package for the COSY Infinity scientific computing package. We design the model of their mutual interaction and demonstrate that the quality of the result obtained by GATool increases as the information about the search domain is refined, which supports the usefulness of this model. We Giscuss GATool's performance on the problems suffering from static and dynamic noise and study useful strategies of GATool parameter tuning for these and other difficult problems. We review the challenges of constrained optimization with EAs and methods commonly used to overcome them. We describe REPA, a new constrained optimization method based on repairing, in exquisite detail, including the properties of its two repairing techniques: REFIND and REPROPT. We assess REPROPT's performance on the standard constrained
International Nuclear Information System (INIS)
Petroni, Robson; Moreira, Edson G.
2013-01-01
In this study optimization of procedures and standardization of Instrumental Neutron Activation Analysis (INAA) methods were carried out for the determination of the elements arsenic, chromium, cobalt, iron, rubidium, scandium, selenium and zinc in biological materials. The aim is to validate the analytical methods for future accreditation at the National Institute of Metrology, Quality and Technology (INMETRO). The 2 k experimental design was applied for evaluation of the individual contribution of selected variables of the analytical procedure in the final mass fraction result. Samples of Mussel Tissue Certified Reference Material and multi-element standards were analyzed considering the following variables: sample decay time, counting time and sample distance to detector. The standard multi-element concentration (comparator standard), mass of the sample and irradiation time were maintained constant in this procedure. By means of the statistical analysis and theoretical and experimental considerations it was determined the optimized experimental conditions for the analytical methods that will be adopted for the validation procedure of INAA methods in the Neutron Activation Analysis Laboratory (LAN) of the Research Reactor Center (CRPq) at the Nuclear and Energy Research Institute (IPEN - CNEN/SP). Optimized conditions were estimated based on the results of z-score tests, main effect and interaction effects. The results obtained with the different experimental configurations were evaluated for accuracy (precision and trueness) for each measurement. (author)
Ouattara, Bazoumana; Duplessis, Mélissa; Girard, Christiane L
2013-10-16
Methylmalonyl-CoA mutase (MCM) is an adenosylcobalamin-dependent enzyme that catalyses the interconversion of (2R)-methylmalonyl-CoA to succinyl-CoA. In humans, a deficit in activity of MCM, due to an impairment of intracellular formation of adenosylcobalamin and methylcobalamin results in a wide spectrum of clinical manifestations ranging from moderate to fatal. Consequently, MCM is the subject of abundant literature. However, there is a lack of consensus on the reliable method to monitor its activity. This metabolic pathway is highly solicited in ruminants because it is essential for the utilization of propionate formed during ruminal fermentation. In lactating dairy cows, propionate is the major substrate for glucose formation. In present study, a reversed-phase high performance liquid chromatography (RP-HPLC) was optimized and validated to evaluate MCM activity in bovine liver. The major aim of the study was to describe the conditions to optimize reproducibility of the method and to determine stability of the enzyme and its product during storage and processing of samples. Specificity of the method was good, as there was no interfering peak from liver extract at the retention times corresponding to methylmalonyl-CoA or succinyl-CoA. Repeatability of the method was improved as compared to previous RP-HPLC published data. Using 66 μg of protein, intra-assay coefficient of variation (CV) of specific activities, ranged from 0.90 to 8.05% and the CV inter-day was 7.40%. Storage and processing conditions (frozen homogenate of fresh tissue vs. fresh homogenate of tissue snapped in liquid nitrogen) did not alter the enzyme activity. The analyte was also stable in liver crude extract for three frozen/thawed cycles when stored at -20°C and thawed to room temperature. The improved method provides a way for studying the effects of stages of lactation, diet composition, and physiology in cattle on MCM activity over long periods of time, such as a complete lactation period
A topological derivative method for topology optimization
DEFF Research Database (Denmark)
Norato, J.; Bendsøe, Martin P.; Haber, RB
2007-01-01
We propose a fictitious domain method for topology optimization in which a level set of the topological derivative field for the cost function identifies the boundary of the optimal design. We describe a fixed-point iteration scheme that implements this optimality criterion subject to a volumetric...
Shang, Hongmei; Zhou, Haizhu; Duan, Mengying; Li, Ran; Wu, Hongxin; Lou, Yujie
2018-06-01
This study was designed to investigate the extraction conditions of polysaccharides from comfrey (Symphytum officinale L.) root (CRPs) using response surface methodology (RSM). The effects of three variables including liquid-solid ratio, extraction time and extraction temperature on the extraction yield of CRPs were taken into consideration. Moreover, the effects of drying methods including hot air drying (HD), vacuum drying (VD) and freeze drying (FD) on the physicochemical properties and antioxidant activities of CRPs were evaluated. The optimal conditions to extract the polysaccharides were as follows: liquid-solid ratio (15mL/g), extraction time (74min), and extraction temperature (95°C), allowed a maximum polysaccharides yield of 22.87%. Different drying methods had significant effects on the physicochemical properties of CRPs such as the chemical composition (contents of total polysaccharides and uronic acid), relative viscosity, solubility and molecular weight. CRPs drying with FD method showed stronger reducing power and radical scavenging capacities against DPPH and ABTS radicals compared with CRPs drying with HD and VD methods. Therefore, freeze drying served as a good method for keeping the antioxidant activities of polysaccharides from comfrey root. Copyright © 2018 Elsevier B.V. All rights reserved.
Biologically inspired optimization methods an introduction
Wahde, M
2008-01-01
The advent of rapid, reliable and cheap computing power over the last decades has transformed many, if not most, fields of science and engineering. The multidisciplinary field of optimization is no exception. First of all, with fast computers, researchers and engineers can apply classical optimization methods to problems of larger and larger size. In addition, however, researchers have developed a host of new optimization algorithms that operate in a rather different way than the classical ones, and that allow practitioners to attack optimization problems where the classical methods are either not applicable or simply too costly (in terms of time and other resources) to apply.This book is intended as a course book for introductory courses in stochastic optimization algorithms (in this book, the terms optimization method and optimization algorithm will be used interchangeably), and it has grown from a set of lectures notes used in courses, taught by the author, at the international master programme Complex Ada...
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Improved Chicken Swarm Optimization Method for Reentry Trajectory Optimization
Directory of Open Access Journals (Sweden)
Yu Wu
2018-01-01
Full Text Available Reentry trajectory optimization has been researched as a popular topic because of its wide applications in both military and civilian use. It is a challenging problem owing to its strong nonlinearity in motion equations and constraints. Besides, it is a high-dimensional optimization problem. In this paper, an improved chicken swarm optimization (ICSO method is proposed considering that the chicken swarm optimization (CSO method is easy to fall into local optimum when solving high-dimensional optimization problem. Firstly, the model used in this study is described, including its characteristic, the nonlinear constraints, and cost function. Then, by introducing the crossover operator, the principles and the advantages of the ICSO algorithm are explained. Finally, the ICSO method solving the reentry trajectory optimization problem is proposed. The control variables are discretized at a set of Chebyshev collocation points, and the angle of attack is set to fit with the flight velocity to make the optimization efficient. Based on those operations, the process of ICSO method is depicted. Experiments are conducted using five algorithms under different indexes, and the superiority of the proposed ICSO algorithm is demonstrated. Another group of experiments are carried out to investigate the influence of hen percentage on the algorithm’s performance.
Intelligent structural optimization: Concept, Model and Methods
International Nuclear Information System (INIS)
Lu, Dagang; Wang, Guangyuan; Peng, Zhang
2002-01-01
Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented
Optimization of time characteristics in activation analysis
International Nuclear Information System (INIS)
Gurvich, L.G.; Umaraliev, A.T.
2006-01-01
Full text: The activation analysis temporal characteristics optimization methods developed at present are aimed at determination of optimal values of the three important parameters - irradiation time, cooling time and measurement time. In the performed works, especially in [1-5] the activation analysis processes are described, the optimal values of optimization parameters are obtained from equations solved, and the computational results are given for these parameters for a number of elements. However, the equations presented in [2] were inaccurate, did not allow one to have optimization parameters results for one element content calculations, and it did not take into account background dependence of time. Therefore, we proposed modified equations to determine the optimal temporal parameters and iteration processes for the solution of these equations. It is well-known that the activity of studied sample during measurements does not change significantly, i.e. measurement time is much shorter than the half-life, thus the processes taking place can be described by the Poisson probability distribution, and in general case one can apply binomial distribution. The equation and iteration processes use in this research describe both probability distributions. Expectedly, the cooling time iteration expressions obtained for one element analysis case are similar for the both distribution types, as the optimised time values occurred to be of the same order as half-life values, whereas the cooling time, as we observed, depends on the ratio of the studied sample's peak value to the background peak, and can be significantly larger than the half-life value. This pattern is general, and can be derived from the optimized time expressions, which is supported by the experimental data on short-living isotopes [3,4]. For the isotopes with large half-lives, up to years, like cobalt-60, the cooling time values given in the above mentioned works are equal to months which, apparently
OPTIMIZATION METHODS IN TRANSPORTATION OF FOREST PRODUCTS
Directory of Open Access Journals (Sweden)
Selçuk Gümüş
2008-04-01
Full Text Available Turkey has total of 21.2 million ha (27 % forest land. In this area, average 9 million m3 of logs and 5 million stere of fuel wood have been annually produced by the government forest enterprises. The total annual production is approximately 13million m3 Considering the fact that the costs of transporting forest products was about . 160 million TL in the year of 2006, the importance of optimizing the total costs in transportation can be better understood. Today, there is not common optimization method used at whole transportation problems. However, the decision makers select the most appropriate methods according to their aims.Comprehending of features and capacity of optimization methods is important for selecting of the most appropriate method. The evaluation of optimization methods that can be used at forest products transportation is aimed in this study.
Engineering applications of heuristic multilevel optimization methods
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Hybrid intelligent optimization methods for engineering problems
Pehlivanoglu, Yasin Volkan
quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles.
Ways optimization physical activity students
Directory of Open Access Journals (Sweden)
Vasilij Sutula
2014-12-01
Full Text Available Purpose: on the basis of the analysis of results of poll of students, first, to define structure and the importance of the factors influencing formation of motivation at them to sports and sports activity, secondly, to allocate possible subjects for extension of the maintenance of theoretical and methodical-practical components of sports formation of student's youth. Material and Methods: the study involved students of first and second courses of the Institute for training bodies and the Faculty of Law of the National University №9 Yaroslav the Wise and the students of the Kyiv National University of Culture and Arts and Zhytomyr State University named after Ivan Franko. Results: it is established that during training at national law university interests of students concerning factors which motivate them to sports and sports activity significantly change. The analyses data testify that a key factor which prevents students to be engaged in sports and sports activity, lack of free time is. It is proved that students consider necessary to receive information on the physical state. Conclusions: results of research allowed allocating the most significant factors which motivate students to be engaged in sports and sports activity. It is established subjects of theoretical and methodical and practical components of sports education which interest students of NLU and KNUCA and ZSU. It is shown that for students of Law University of importance topic of theoretical and methodological and practical components of physical education strongly depends on the year of their training.
Universal Method for Stochastic Composite Optimization Problems
Gasnikov, A. V.; Nesterov, Yu. E.
2018-01-01
A fast gradient method requiring only one projection is proposed for smooth convex optimization problems. The method has a visual geometric interpretation, so it is called the method of similar triangles (MST). Composite, adaptive, and universal versions of MST are suggested. Based on MST, a universal method is proposed for the first time for strongly convex problems (this method is continuous with respect to the strong convexity parameter of the smooth part of the functional). It is shown how the universal version of MST can be applied to stochastic optimization problems.
Topology optimization theory, methods, and applications
Bendsøe, Martin P
2004-01-01
The topology optimization method solves the basic engineering problem of distributing a limited amount of material in a design space. The first edition of this book has become the standard text on optimal design which is concerned with the optimization of structural topology, shape and material. This edition has been substantially revised and updated to reflect progress made in modelling and computational procedures. It also encompasses a comprehensive and unified description of the state-of-the-art of the so-called material distribution method, based on the use of mathematical programming and finite elements. Applications treated include not only structures but also MEMS and materials.
Topology optimization using the finite volume method
DEFF Research Database (Denmark)
Computational procedures for topology optimization of continuum problems using a material distribution method are typically based on the application of the finite element method (FEM) (see, e.g. [1]). In the present work we study a computational framework based on the finite volume method (FVM, see......, e.g. [2]) in order to develop methods for topology design for applications where conservation laws are critical such that element--wise conservation in the discretized models has a high priority. This encompasses problems involving for example mass and heat transport. The work described...... in this presentation is focused on a prototype model for topology optimization of steady heat diffusion. This allows for a study of the basic ingredients in working with FVM methods when dealing with topology optimization problems. The FVM and FEM based formulations differ both in how one computes the design...
Topology optimization using the finite volume method
DEFF Research Database (Denmark)
Gersborg-Hansen, Allan; Bendsøe, Martin P.; Sigmund, Ole
2005-01-01
Computational procedures for topology optimization of continuum problems using a material distribution method are typically based on the application of the finite element method (FEM) (see, e.g. [1]). In the present work we study a computational framework based on the finite volume method (FVM, s......: the Finite Volume Method. London: Longman Scientific Technical......Computational procedures for topology optimization of continuum problems using a material distribution method are typically based on the application of the finite element method (FEM) (see, e.g. [1]). In the present work we study a computational framework based on the finite volume method (FVM, see......, e.g. [2]) in order to develop methods for topology design for applications where conservation laws are critical such that element--wise conservation in the discretized models has a high priority. This encompasses problems involving for example mass and heat transport. The work described...
The optimal homotopy asymptotic method engineering applications
Marinca, Vasile
2015-01-01
This book emphasizes in detail the applicability of the Optimal Homotopy Asymptotic Method to various engineering problems. It is a continuation of the book “Nonlinear Dynamical Systems in Engineering: Some Approximate Approaches”, published at Springer in 2011, and it contains a great amount of practical models from various fields of engineering such as classical and fluid mechanics, thermodynamics, nonlinear oscillations, electrical machines, and so on. The main structure of the book consists of 5 chapters. The first chapter is introductory while the second chapter is devoted to a short history of the development of homotopy methods, including the basic ideas of the Optimal Homotopy Asymptotic Method. The last three chapters, from Chapter 3 to Chapter 5, are introducing three distinct alternatives of the Optimal Homotopy Asymptotic Method with illustrative applications to nonlinear dynamical systems. The third chapter deals with the first alternative of our approach with two iterations. Five application...
Adam: A Method for Stochastic Optimization
Kingma, D.P.; Ba, L.J.
2015-01-01
We introduce Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions. The method is straightforward to implement and is based on adaptive estimates of lower-order moments of the gradients. The method is computationally efficient, has little memory
Optimization of breeding methods when introducing multiple ...
African Journals Online (AJOL)
Optimization of breeding methods when introducing multiple resistance genes from American to Chinese wheat. JN Qi, X Zhang, C Yin, H Li, F Lin. Abstract. Stripe rust is one of the most destructive diseases of wheat worldwide. Growing resistant cultivars with resistance genes is the most effective method to control this ...
A method optimization study for atomic absorption ...
African Journals Online (AJOL)
A sensitive, reliable and relative fast method has been developed for the determination of total zinc in insulin by atomic absorption spectrophotometer. This designed study was used to optimize the procedures for the existing methods. Spectrograms of both standard and sample solutions of zinc were recorded by measuring ...
Process control and optimization with simple interval calculation method
DEFF Research Database (Denmark)
Pomerantsev, A.; Rodionova, O.; Høskuldsson, Agnar
2006-01-01
for the quality improvement in the course of production. The latter is an active quality optimization, which takes into account the actual history of the process. The advocate approach is allied to the conventional method of multivariate statistical process control (MSPC) as it also employs the historical process......Methods of process control and optimization are presented and illustrated with a real world example. The optimization methods are based on the PLS block modeling as well as on the simple interval calculation methods of interval prediction and object status classification. It is proposed to employ...... the series of expanding PLS/SIC models in order to support the on-line process improvements. This method helps to predict the effect of planned actions on the product quality and thus enables passive quality control. We have also considered an optimization approach that proposes the correcting actions...
Process control and optimization with simple interval calculation method
DEFF Research Database (Denmark)
Pomerantsev, A.; Rodionova, O.; Høskuldsson, Agnar
2006-01-01
Methods of process control and optimization are presented and illustrated with a real world example. The optimization methods are based on the PLS block modeling as well as on the simple interval calculation methods of interval prediction and object status classification. It is proposed to employ...... the series of expanding PLS/SIC models in order to support the on-line process improvements. This method helps to predict the effect of planned actions on the product quality and thus enables passive quality control. We have also considered an optimization approach that proposes the correcting actions...... for the quality improvement in the course of production. The latter is an active quality optimization, which takes into account the actual history of the process. The advocate approach is allied to the conventional method of multivariate statistical process control (MSPC) as it also employs the historical process...
State space Newton's method for topology optimization
DEFF Research Database (Denmark)
Evgrafov, Anton
2014-01-01
We introduce a new algorithm for solving certain classes of topology optimization problems, which enjoys fast local convergence normally achieved by the full space methods while working in a smaller reduced space. The computational complexity of Newton’s direction finding subproblem in the algori......We introduce a new algorithm for solving certain classes of topology optimization problems, which enjoys fast local convergence normally achieved by the full space methods while working in a smaller reduced space. The computational complexity of Newton’s direction finding subproblem...
An introduction to harmony search optimization method
Wang, Xiaolei; Zenger, Kai
2014-01-01
This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and its variants and also their drawbacks. The authors show how weaknesses can be amended by hybridization with other optimization methods. The Harmony Search Method with Applications will be of value to researchers in computational intelligence in demonstrating the state of the art of research on an algorithm of current interest. It also helps researche
Optimal boarding method for airline passengers
Energy Technology Data Exchange (ETDEWEB)
Steffen, Jason H.; /Fermilab
2008-02-01
Using a Markov Chain Monte Carlo optimization algorithm and a computer simulation, I find the passenger ordering which minimizes the time required to board the passengers onto an airplane. The model that I employ assumes that the time that a passenger requires to load his or her luggage is the dominant contribution to the time needed to completely fill the aircraft. The optimal boarding strategy may reduce the time required to board and airplane by over a factor of four and possibly more depending upon the dimensions of the aircraft. I explore some features of the optimal boarding method and discuss practical modifications to the optimal. Finally, I mention some of the benefits that could come from implementing an improved passenger boarding scheme.
Path optimization method for the sign problem
Directory of Open Access Journals (Sweden)
Ohnishi Akira
2018-01-01
Full Text Available We propose a path optimization method (POM to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t(f ϵ R and by optimizing f(t to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.
Optimization of radiation monitoring methods of environment
International Nuclear Information System (INIS)
Bondarkov, M.D.
2012-01-01
Full text : Report is devoted to the substantiation of the ways to optimize methods of providing radioecological monitoring (RM) in Ukraine. For this purpose the design features of RM at different levels, the analysis of modern requirements for the RM, the methods for RM ensuring were considered in the dissertation, the use for instrumentation supply of laboratories of new simplified methods, that were developed in this paper, was proposed. This work proposed to strengthen radiobiological component of monitoring, the advantages and disadvantages of the proposed methods were analyzed. The research of the spatial and vertical distribution of radionuclides in soils of the most polluted part of the Chernobyl zone was conducted using the proposed methods. For the first time the parameters of vertical migration of the isotopes 154Eu, 238-240Pu and 241Am in soil profiles of Ch NPP close zone were calculated. The parameters of vertical migration of 90Sr, 137Cs were refined. The calculations of effective environmental and semi-refined periods of above mentioned isotopes for different soil types were conducted, the estimation of dose rates to biota was done, and radioecological characterization of the test sites of the cooling pond was conducted. The features of radioecology of birds, rodents and shrews, bats and amphibians were studied. The dose rates for these species were assessed and their compliance with 103 ICRP Guiding. The species differences in the pollution of wild rodents, insectivores, passerine birds, amphibians and bats on a large amount of factual material were estimated. The investigation of the radioecological contamination of the features of the urbanized landscape was conducted on the example of Pripyat silty. The practical significance of the work is that the developed methods of non radiochemical determination of radiostrontium activity, alpha emitting isotopes of plutonium, which can significantly hasten and facilitate the evaluation of the
Adaptive finite element method for shape optimization
Morin, Pedro
2012-01-16
We examine shape optimization problems in the context of inexact sequential quadratic programming. Inexactness is a consequence of using adaptive finite element methods (AFEM) to approximate the state and adjoint equations (via the dual weighted residual method), update the boundary, and compute the geometric functional. We present a novel algorithm that equidistributes the errors due to shape optimization and discretization, thereby leading to coarse resolution in the early stages and fine resolution upon convergence, and thus optimizing the computational effort. We discuss the ability of the algorithm to detect whether or not geometric singularities such as corners are genuine to the problem or simply due to lack of resolution - a new paradigm in adaptivity. © EDP Sciences, SMAI, 2012.
Method for optimizing harvesting of crops
DEFF Research Database (Denmark)
2010-01-01
In order e.g. to optimize harvesting crops of the kind which may be self dried on a field prior to a harvesting step (116, 118), there is disclosed a method of providing a mobile unit (102) for working (114, 116, 118) the field with crops, equipping the mobile unit (102) with crop biomass measuring...
Optimal Allocation of Workstation Activities
Directory of Open Access Journals (Sweden)
Olga-Ioana Amariei
2017-12-01
Full Text Available In this paper we started from a case study in which we wanted to develop an own methodology of designing lower rank productions systems, and of simulation-optimization of production flows, using several software’s. Because of it's complexity, the study is truncated, making it the subject of several specialized articles. In this article we calculate the efficiency of an assembly cell, using the software Flexible Line Balancing.
A Gradient Taguchi Method for Engineering Optimization
Hwang, Shun-Fa; Wu, Jen-Chih; He, Rong-Song
2017-10-01
To balance the robustness and the convergence speed of optimization, a novel hybrid algorithm consisting of Taguchi method and the steepest descent method is proposed in this work. Taguchi method using orthogonal arrays could quickly find the optimum combination of the levels of various factors, even when the number of level and/or factor is quite large. This algorithm is applied to the inverse determination of elastic constants of three composite plates by combining numerical method and vibration testing. For these problems, the proposed algorithm could find better elastic constants in less computation cost. Therefore, the proposed algorithm has nice robustness and fast convergence speed as compared to some hybrid genetic algorithms.
Global Optimization Ensemble Model for Classification Methods
Directory of Open Access Journals (Sweden)
Hina Anwar
2014-01-01
Full Text Available Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity.
STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION
Directory of Open Access Journals (Sweden)
Nataša Krejić
2014-12-01
Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.
Layout optimization with algebraic multigrid methods
Regler, Hans; Ruede, Ulrich
1993-01-01
Finding the optimal position for the individual cells (also called functional modules) on the chip surface is an important and difficult step in the design of integrated circuits. This paper deals with the problem of relative placement, that is the minimization of a quadratic functional with a large, sparse, positive definite system matrix. The basic optimization problem must be augmented by constraints to inhibit solutions where cells overlap. Besides classical iterative methods, based on conjugate gradients (CG), we show that algebraic multigrid methods (AMG) provide an interesting alternative. For moderately sized examples with about 10000 cells, AMG is already competitive with CG and is expected to be superior for larger problems. Besides the classical 'multiplicative' AMG algorithm where the levels are visited sequentially, we propose an 'additive' variant of AMG where levels may be treated in parallel and that is suitable as a preconditioner in the CG algorithm.
Adiabatic optimization versus diffusion Monte Carlo methods
Jarret, Michael; Jordan, Stephen P.; Lackey, Brad
2016-10-01
Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .
Layout optimization using the homogenization method
Suzuki, Katsuyuki; Kikuchi, Noboru
1993-01-01
A generalized layout problem involving sizing, shape, and topology optimization is solved by using the homogenization method for three-dimensional linearly elastic shell structures in order to seek a possibility of establishment of an integrated design system of automotive car bodies, as an extension of the previous work by Bendsoe and Kikuchi. A formulation of a three-dimensional homogenized shell, a solution algorithm, and several examples of computing the optimum layout are presented in this first part of the two articles.
Lifecycle-Based Swarm Optimization Method for Numerical Optimization
Directory of Open Access Journals (Sweden)
Hai Shen
2014-01-01
Full Text Available Bioinspired optimization algorithms have been widely used to solve various scientific and engineering problems. Inspired by biological lifecycle, this paper presents a novel optimization algorithm called lifecycle-based swarm optimization (LSO. Biological lifecycle includes four stages: birth, growth, reproduction, and death. With this process, even though individual organism died, the species will not perish. Furthermore, species will have stronger ability of adaptation to the environment and achieve perfect evolution. LSO simulates Biological lifecycle process through six optimization operators: chemotactic, assimilation, transposition, crossover, selection, and mutation. In addition, the spatial distribution of initialization population meets clumped distribution. Experiments were conducted on unconstrained benchmark optimization problems and mechanical design optimization problems. Unconstrained benchmark problems include both unimodal and multimodal cases the demonstration of the optimal performance and stability, and the mechanical design problem was tested for algorithm practicability. The results demonstrate remarkable performance of the LSO algorithm on all chosen benchmark functions when compared to several successful optimization techniques.
portfolio optimization based on nonparametric estimation methods
Directory of Open Access Journals (Sweden)
mahsa ghandehari
2017-03-01
Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.
Directory of Open Access Journals (Sweden)
Elisa Mitiko Kawamato
2002-09-01
Full Text Available We investigated the kinetic analysis of human platelet Nitric Oxide Synthase (NOS activity by the rate of conversion of [³H] arginine to [³H]-citrulline in unstimulated fresh platelets. NOS activity was present in the membrane fraction and cytosol, and was Ca2+- and calmodulin dependent which is a characteristic of endothelial NOS. NOS activity was also dependent of NADPH since the omission of this cofactor induced an important decrease (85,2% in the enzyme activity. The kinetic varied with protein and arginine concentration but optimum concentrations were found up to 60 minutes, and up to 80 µg of protein at 120 nM of arginine and 0.5 µCi of ³H-arginine. NOS activity in the absence of FAD (flavin adenine dinucleotide, FMN (flavin mononucleotide and BH4 (tetrahydrobiopterin was only 2.8% of the activity measured in the presence of these three cofactors. The enzyme activity was completely inhibited by L-NAME (1 mM (98.1 % and EGTA (5 mM (98.8 %. Trifluoperazine (TFP caused 73.2% inhibition of the enzyme activity at 200 µM and 83.8 % at 500 µM. Under basal conditions, NOS Km for L-arginine was 0.84 ± 0.08 µM and mean Vmax values were 0.122 ± 0.025 pmol.mg-1.min-1. Mean human NOS platelet activity was 0.020 ± 0.010 pmol.mg-1.min-1. Results indicate that the eNOS in human platelet can be evaluated by conversion of [³H]-arginine to [³H]citrulline in an optimized method, which provide reproducible and accurate results with good sensitivity to clinical experiments involving neurological and psychiatric diseases.A análise cinética da atividade da óxido nítrico sintase (NOS plaquetária foi avaliada pela conversão de [³H]-arginina em [³H]-citrulina em plaquetas humanas frescas não estimuladas. A atividade da NOS foi detectada na fração citosólica e na membrana, além de ser dependente de Ca2+-calmodulina, que é uma característica da NOS endotelial (eNOS. A omissão de NADPH levou à diminuição da atividade da NOS dependente da
Optimal Combination of Aircraft Maintenance Tasks by a Novel Simplex Optimization Method
Directory of Open Access Journals (Sweden)
Huaiyuan Li
2015-01-01
Full Text Available Combining maintenance tasks into work packages is not only necessary for arranging maintenance activities, but also critical for the reduction of maintenance cost. In order to optimize the combination of maintenance tasks by fuzzy C-means clustering algorithm, an improved fuzzy C-means clustering model is introduced in this paper. In order to reduce the dimension, variables representing clustering centers are eliminated in the improved cluster model. So the improved clustering model can be directly solved by the optimization method. To optimize the clustering model, a novel nonlinear simplex optimization method is also proposed in this paper. The novel method searches along all rays emitting from the center to each vertex, and those search directions are rightly n+1 positive basis. The algorithm has both theoretical convergence and good experimental effect. Taking the optimal combination of some maintenance tasks of a certain aircraft as an instance, the novel simplex optimization method and the clustering model both exhibit excellent performance.
MIND. Optimization method for industrial energy systems
Energy Technology Data Exchange (ETDEWEB)
Nilsson, Katarina.
1990-04-01
It is of great importance to encourage the consciousness of energy demand and energy conservation issues in industrial applications as the potential for savings in many cases is very good. The MIND optimization method is a tool for life cycle cost minimization of a flexible range of industrial energy systems. It can be used in analyses of energy systems in response to changes within the systems, changes of the boundary conditions and synthesis of industrial energy systems. The aim is to find an optimal structure in the energy system where several alternative process routes and kinds of energy are available. Equipment alternatives may concern choices of recondition, exchange, new tehnology, time of investment and size considerations. Energy can be supplied to the industrial energy system as electricity, steam and with various kinds of fuel. Energy and material flows are represented in the optimization as well as non-linearities in energy demand functions and investment cost functions. Boundary conditions and process variations can be represented with a time division where the length of each time step and the number of time steps can be chosen. Two applications are presented to show the flexibility of the MIND method, heat treating processes in the engineering industry and milk processing in a dairy. (36 refs.).
METHODS OF INTEGRATED OPTIMIZATION MAGLEV TRANSPORT SYSTEMS
Directory of Open Access Journals (Sweden)
A. Lasher
2013-09-01
example, this research proved the sustainability of the proposed integrated optimization parameters of transport systems. This approach could be applied not only for MTS, but also for other transport systems. Originality. The bases of the complex optimization of transport presented are the new system of universal scientific methods and approaches that ensure high accuracy and authenticity of calculations with the simulation of transport systems and transport networks taking into account the dynamics of their development. Practical value. The development of the theoretical and technological bases of conducting the complex optimization of transport makes it possible to create the scientific tool, which ensures the fulfillment of the automated simulation and calculating of technical and economic structure and technology of the work of different objects of transport, including its infrastructure.
Methods for Distributed Optimal Energy Management
DEFF Research Database (Denmark)
Brehm, Robert
micro-grids by prevention of meteorologic power flows into high voltage grids. A method, based on mathematical optimisation and a consensus algorithm is introduced and evaluated to coordinate charge/discharge scheduling for batteries between a number of buildings in order to improve self......The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast......-consumption of renewable energy resources in low voltage grids. It can be shown that this method prevents mutual discharging of batteries and prevents peak loads, a supervisory control instance can dictate the level of autarchy from the utility grid. Further it is shown that the problem of optimal energy flow management...
Parametric Method For Evaluating Optimal Ship Deadweight
Directory of Open Access Journals (Sweden)
Michalski Jan P.
2014-04-01
Full Text Available The paper presents a method of choosing the optimal value of the cargo ships deadweight. The method may be useful at the stage of establishing the main owners requirements concerning the ship design parameters as well as for choosing a proper ship for a given transportation task. The deadweight is determined on the basis of a selected economic measure of the transport effectiveness of ship - the Required Freight Rate (RFR. The mathematical model of the problem is of a deterministic character and the simplifying assumptions are justified for ships operating in the liner trade. The assumptions are so selected that solution of the problem is obtained in analytical closed form. The presented method can be useful for application in the pre-investment ships designing parameters simulation or transportation task studies.
Management of nuclear PRs activity with optimal conditions
International Nuclear Information System (INIS)
Ohnishi, Teruaki
1997-01-01
A methodology is proposed to derive optimal conditions for the activity of nuclear public relations (PRs). With the use of data-bases available at present, expressions were derived which connect the budget allocated for the PRs activity with the intensity of stimulus for four types of activity of the advertisement in the press, the exclusive publicity, the pamphlet and the advertisement on television. Optimal conditions for the activity were determined by introducing a model describing a relation between the intensity of stimulus and the extent of the change of public's attitude to nuclear energy, namely the effect of PRs activity, and also by giving the optimal ratio of allocation of the budget among the four types of activity as a function of cost versus effectiveness of each type. Those optimal conditions, being for the ratio of allocation of the budget, the execution time and the intensity of each type of activity at that time, vary depending on the number of household in a target region, the target class of demography, the duration time of activity, and the amount of budget for the activity. It becomes clear from numerical calculation that the optimal conditions and the effect of activity show quite strong non-linearity with respect to the variation of those variables, and that the effect of PRs activity averaged over all public in the target region becomes to be maximum, in Japan, when the activity is executed with the optimal conditions determined for the target class of middle- and advanced-aged women. The management of nuclear PRs activity becomes possible by introducing such a method of fixation of optimal conditions for the activity as described here. (author)
Global optimization methods for engineering design
Arora, Jasbir S.
1990-01-01
The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated.
PRODUCT OPTIMIZATION METHOD BASED ON ANALYSIS OF OPTIMAL VALUES OF THEIR CHARACTERISTICS
Directory of Open Access Journals (Sweden)
Constantin D. STANESCU
2016-05-01
Full Text Available The paper presents an original method of optimizing products based on the analysis of optimal values of their characteristics . Optimization method comprises statistical model and analytical model . With this original method can easily and quickly obtain optimal product or material .
Optimal Variational Method for Truly Nonlinear Oscillators
Directory of Open Access Journals (Sweden)
Vasile Marinca
2013-01-01
Full Text Available The Optimal Variational Method (OVM is introduced and applied for calculating approximate periodic solutions of “truly nonlinear oscillators”. The main advantage of this procedure consists in that it provides a convenient way to control the convergence of approximate solutions in a very rigorous way and allows adjustment of convergence regions where necessary. This approach does not depend upon any small or large parameters. A very good agreement was found between approximate and numerical solution, which proves that OVM is very efficient and accurate.
International Nuclear Information System (INIS)
Joly, Jean-François; Béland, Laurent Karim; Brommer, Peter; Mousseau, Normand; El-Mellouhi, Fedwa
2012-01-01
We present two major optimizations for the kinetic Activation-Relaxation Technique (k-ART), an off-lattice self-learning kinetic Monte Carlo (KMC) algorithm with on-the-fly event search THAT has been successfully applied to study a number of semiconducting and metallic systems. K-ART is parallelized in a non-trivial way: A master process uses several worker processes to perform independent event searches for possible events, while all bookkeeping and the actual simulation is performed by the master process. Depending on the complexity of the system studied, the parallelization scales well for tens to more than one hundred processes. For dealing with large systems, we present a near order 1 implementation. Techniques such as Verlet lists, cell decomposition and partial force calculations are implemented, and the CPU time per time step scales sublinearly with the number of particles, providing an efficient use of computational resources.
An Optimal Method to Design Wireless Sensor Network Structures
Directory of Open Access Journals (Sweden)
Yang Ling
2018-01-01
Full Text Available In order to optimize the structure of wireless sensor network, an improved wireless sensor network sleep mechanism is proposed. First, some nodes in the area with too high redundancy are dormant by density control, so that the active nodes are even more distributed. Then, the active node is subjected to circular coverage redundancy decision. Different circumferential coverage decision methods are used for network boundary nodes and non-boundary nodes. As a result, the boundary nodes and non-boundary nodes are well dormant, and the network redundancy is reduced. The simulation results show that the improved dormancy mechanism makes the number of active nodes in the network smaller and more evenly, and the network lifetime is extended on the basis of maintaining the original coverage of the network. Therefore, the proposed method can achieve optimal coverage in wireless sensor networks. The network prolongs network lifetime while ensuring reliable monitoring performance.
DEFF Research Database (Denmark)
Siano, P.; Chen, Peiyuan; Chen, Zhe
2012-01-01
a hybrid optimization method that aims of maximizing the Net Present Value related to the Investment made by Wind Turbines developers in an active distribution network. The proposed network combines a Genetic Algorithm with a multi-period optimal power flow. The method, integrating active management...
The methods and applications of optimization of radiation protection
International Nuclear Information System (INIS)
Liu Hua
2007-01-01
Optimization is the most important principle in radiation protection. The present article briefs the concept and up-to-date progress of optimization of protection, introduces some methods used in current optimization analysis, and presents various applications of optimization of protection. The author emphasizes that optimization of protection is a forward-looking iterative process aimed at preventing exposures before they occur. (author)
Circular SAR Optimization Imaging Method of Buildings
Directory of Open Access Journals (Sweden)
Wang Jian-feng
2015-12-01
Full Text Available The Circular Synthetic Aperture Radar (CSAR can obtain the entire scattering properties of targets because of its great ability of 360° observation. In this study, an optimal orientation of the CSAR imaging algorithm of buildings is proposed by applying a combination of coherent and incoherent processing techniques. FEKO software is used to construct the electromagnetic scattering modes and simulate the radar echo. The FEKO imaging results are compared with the isotropic scattering results. On comparison, the optimal azimuth coherent accumulation angle of CSAR imaging of buildings is obtained. Practically, the scattering directions of buildings are unknown; therefore, we divide the 360° echo of CSAR into many overlapped and few angle echoes corresponding to the sub-aperture and then perform an imaging procedure on each sub-aperture. Sub-aperture imaging results are applied to obtain the all-around image using incoherent fusion techniques. The polarimetry decomposition method is used to decompose the all-around image and further retrieve the edge information of buildings successfully. The proposed method is validated with P-band airborne CSAR data from Sichuan, China.
Computational methods applied to wind tunnel optimization
Lindsay, David
This report describes computational methods developed for optimizing the nozzle of a three-dimensional subsonic wind tunnel. This requires determination of a shape that delivers flow to the test section, typically with a speed increase of 7 or more and a velocity uniformity of .25% or better, in a compact length without introducing boundary layer separation. The need for high precision, smooth solutions, and three-dimensional modeling required the development of special computational techniques. These include: (1) alternative formulations to Neumann and Dirichlet boundary conditions, to deal with overspecified, ill-posed, or cyclic problems, and to reduce the discrepancy between numerical solutions and boundary conditions; (2) modification of the Finite Element Method to obtain solutions with numerically exact conservation properties; (3) a Matlab implementation of general degree Finite Element solvers for various element designs in two and three dimensions, exploiting vector indexing to obtain optimal efficiency; (4) derivation of optimal quadrature formulas for integration over simplexes in two and three dimensions, and development of a program for semi-automated generation of formulas for any degree and dimension; (5) a modification of a two-dimensional boundary layer formulation to provide accurate flow conservation in three dimensions, and modification of the algorithm to improve stability; (6) development of multi-dimensional spline functions to achieve smoother solutions in three dimensions by post-processing, new three-dimensional elements for C1 basis functions, and a program to assist in the design of elements with higher continuity; and (7) a development of ellipsoidal harmonics and Lame's equation, with generalization to any dimension and a demonstration that Cartesian, cylindrical, spherical, spheroidal, and sphero-conical harmonics are all limiting cases. The report includes a description of the Finite Difference, Finite Volume, and domain remapping
Optimal correction and design parameter search by modern methods of rigorous global optimization
International Nuclear Information System (INIS)
Makino, K.; Berz, M.
2011-01-01
optics for the computation of aberrations allow the determination of particularly sharp underestimators for large regions. As a consequence, the subsequent progressive pruning of the allowed search space as part of the optimization progresses is carried out particularly effectively. The end result is the rigorous determination of the single or multiple optimal solutions of the parameter optimization, regardless of their location, their number, and the starting values of optimization. The methods are particularly powerful if executed in interplay with genetic optimizers generating their new populations within the currently active unpruned space. Their current best guess provides rigorous upper bounds of the minima, which can then beneficially be used for better pruning. Examples of the method and its performance will be presented, including the determination of all operating points of desired tunes or chromaticities, etc. in storage ring lattices.
On Best Practice Optimization Methods in R
Directory of Open Access Journals (Sweden)
John C. Nash
2014-09-01
Full Text Available R (R Core Team 2014 provides a powerful and flexible system for statistical computations. It has a default-install set of functionality that can be expanded by the use of several thousand add-in packages as well as user-written scripts. While R is itself a programming language, it has proven relatively easy to incorporate programs in other languages, particularly Fortran and C. Success, however, can lead to its own costs: • Users face a confusion of choice when trying to select packages in approaching a problem. • A need to maintain workable examples using early methods may mean some tools offered as a default may be dated. • In an open-source project like R, how to decide what tools offer "best practice" choices, and how to implement such a policy, present a serious challenge. We discuss these issues with reference to the tools in R for nonlinear parameter estimation (NLPE and optimization, though for the present article `optimization` will be limited to function minimization of essentially smooth functions with at most bounds constraints on the parameters. We will abbreviate this class of problems as NLPE. We believe that the concepts proposed are transferable to other classes of problems seen by R users.
Chattopadhyay, Sudip; Chaudhuri, Rajat K; Freed, Karl F
2011-04-28
The improved virtual orbital (IVO) complete active space (CAS) configuration interaction (IVO-CASCI) method is a simplified CAS self-consistent field (SCF), CASSCF, method. Unlike the CASSCF approach, the IVO-CASCI method does not require iterations beyond an initial SCF calculation, rendering the IVO-CASCI scheme computationally more tractable than the CASSCF method and devoid of the convergence problems that sometimes plague CASSCF calculations as the CAS size increases, while retaining all the essential positive benefits of the CASSCF method. Earlier applications demonstrate that the IVO-CASCI energies are at least as accurate as those from the CASSCF and provide the impetus for our recent development of the analytical derivative procedures that are necessary for a wide applicability of the IVO-CASCI approach. Here we test the ability of the analytic energy gradient IVO-CASCI approach (which can treat both closed- and open-shell molecules of arbitrary spin multiplicity) to compute the equilibrium geometries of four organic radicaloid species, namely, (i) the diradicals trimethylenemethane (TMM), 2,6-pyridyne, and the 2,6-pyridynium cation and (ii) a triradical 1,2,3-tridehydrobenzene (TDB), using various basis sets and different choices for the active space. Although these systems and related molecules have fascinated theoretical chemists for many years, their strong multireference character makes their description quite difficult with most standard many-body approaches. Thus, they provide ideal tests to assess the performance of the IVO-CASCI method. The present work demonstrates consistent agreement with far more expensive benchmark state-of-the-art ab initio calculations and thereby indicates that this new gradient method is able to describe the geometries of various radicaloids very accurately, even when small, but qualitatively correct, reference spaces are used. For example, the IVO-CASCI method leads to a monocyclic structure for the 2,6-isomers of the
Battery equalization active methods
Gallardo-Lozano, Javier; Romero-Cadaval, Enrique; Milanes-Montero, M. Isabel; Guerrero-Martinez, Miguel A.
2014-01-01
Many different battery technologies are available for the applications which need energy storage. New researches are being focused on Lithium-based batteries, since they are becoming the most viable option for portable energy storage applications. As most of the applications need series battery strings to meet voltage requirements, battery imbalance is an important matter to be taken into account, since it leads the individual battery voltages to drift apart over time, and premature cells degradation, safety hazards, and capacity reduction will occur. A large number of battery equalization methods can be found, which present different advantages/disadvantages and are suitable for different applications. The present paper presents a summary, comparison and evaluation of the different active battery equalization methods, providing a table that compares them, which is helpful to select the suitable equalization method depending on the application. By applying the same weight to the different parameters of comparison, switch capacitor and double-tiered switching capacitor have the highest ratio. Cell bypass methods are cheap and cell to cell ones are efficient. Cell to pack, pack to cell and cell to pack to cell methods present a higher cost, size, and control complexity, but relatively low voltage and current stress in high-power applications.
Numerical methods and optimization a consumer guide
Walter, Éric
2014-01-01
Initial training in pure and applied sciences tends to present problem-solving as the process of elaborating explicit closed-form solutions from basic principles, and then using these solutions in numerical applications. This approach is only applicable to very limited classes of problems that are simple enough for such closed-form solutions to exist. Unfortunately, most real-life problems are too complex to be amenable to this type of treatment. Numerical Methods and Optimization – A Consumer Guide presents methods for dealing with them. Shifting the paradigm from formal calculus to numerical computation, the text makes it possible for the reader to · discover how to escape the dictatorship of those particular cases that are simple enough to receive a closed-form solution, and thus gain the ability to solve complex, real-life problems; · understand the principles behind recognized algorithms used in state-of-the-art numerical software; · learn the advantag...
Optimizing human activity patterns using global sensitivity analysis.
Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M
2014-12-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.
Method for optimizing harvesting of crops
DEFF Research Database (Denmark)
2008-01-01
In order e.g. to optimize harvesting crops of the kind which may be self dried on a field prior to a harvesting step (116, 118), there is disclosed a method of providing a mobile unit (102) for working (114, 116, 118) the field with crops, equipping the mobile unit (102) with crop biomass...... measuring means (108) and with crop moisture content measurement means (106), measuring crop biomass (107a, 107b) and crop moisture content (109a, 109b) of the crop, providing a spatial crop biomass and crop moisture content characteristics map of the field based on the biomass data (107a, 107b) provided...... from moving the mobile unit on the field and the moisture content (109a, 109b), and determining an optimised drying time (104a, 104b) prior to the following harvesting step (116, 118) in response to the spatial crop biomass and crop moisture content characteristics map and in response to a weather...
Bellman – Ford Method for Solving the Optimal Route Problem
Directory of Open Access Journals (Sweden)
Laima Greičiūnė
2014-12-01
Full Text Available The article aims to adapt the dynamic programming method for optimal route determination using real-time data on ITS equipment. For this purpose, VBA code has been applied for solving the Bellman - Ford method for an optimal route considering optimality criteria for time, distance and the amount of emissions.
A Review of Design Optimization Methods for Electrical Machines
Directory of Open Access Journals (Sweden)
Gang Lei
2017-11-01
Full Text Available Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines.
Topology Optimization Methods for Acoustic-Mechanical Coupling Problems
DEFF Research Database (Denmark)
Jensen, Jakob Søndergaard; Dilgen, Cetin Batur; Dilgen, Sümer Bartug
2017-01-01
A comparative overview of methods for topology optimization of acoustic mechanical coupling problems is provided. The goal is to pave the road for developing efficient optimization schemes for the design of complex acoustic devices such as hearingaids.......A comparative overview of methods for topology optimization of acoustic mechanical coupling problems is provided. The goal is to pave the road for developing efficient optimization schemes for the design of complex acoustic devices such as hearingaids....
A Review of Deterministic Optimization Methods in Engineering and Management
Directory of Open Access Journals (Sweden)
Ming-Hua Lin
2012-01-01
Full Text Available With the increasing reliance on modeling optimization problems in practical applications, a number of theoretical and algorithmic contributions of optimization have been proposed. The approaches developed for treating optimization problems can be classified into deterministic and heuristic. This paper aims to introduce recent advances in deterministic methods for solving signomial programming problems and mixed-integer nonlinear programming problems. A number of important applications in engineering and management are also reviewed to reveal the usefulness of the optimization methods.
Method of optimization onboard communication network
Platoshin, G. A.; Selvesuk, N. I.; Semenov, M. E.; Novikov, V. M.
2018-02-01
In this article the optimization levels of onboard communication network (OCN) are proposed. We defined the basic parameters, which are necessary for the evaluation and comparison of modern OCN, we identified also a set of initial data for possible modeling of the OCN. We also proposed a mathematical technique for implementing the OCN optimization procedure. This technique is based on the principles and ideas of binary programming. It is shown that the binary programming technique allows to obtain an inherently optimal solution for the avionics tasks. An example of the proposed approach implementation to the problem of devices assignment in OCN is considered.
On the Convergence Analysis of the Optimized Gradient Method.
Kim, Donghwan; Fessler, Jeffrey A
2017-01-01
This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov's fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization.
A simple method to optimize HMC performance
Bussone, Andrea; Drach, Vincent; Hansen, Martin; Hietanen, Ari; Rantaharju, Jarno; Pica, Claudio
2016-01-01
We present a practical strategy to optimize a set of Hybrid Monte Carlo parameters in simulations of QCD and QCD-like theories. We specialize to the case of mass-preconditioning, with multiple time-step Omelyan integrators. Starting from properties of the shadow Hamiltonian we show how the optimal setup for the integrator can be chosen once the forces and their variances are measured, assuming that those only depend on the mass-preconditioning parameter.
A simple method to optimize HMC performance
Bussone, A.; Della Morte, M.; Drach, V.; Hansen, M.; Hietanen, A.; Rantaharju, J.; Pica, C.
We present a practical strategy to optimize a set of Hybrid Monte Carlo parameters in simulations of QCD and QCD-like theories. We specialize to the case of mass-preconditioning, with multiple time-step Omelyan integrators. Starting from properties of the shadow Hamiltonian we show how the optimal setup for the integrator can be chosen once the forces and their variances are measured, assuming that those only depend on the mass-preconditioning parameter.
Gao, F.; Song, X. H.; Zhang, Y.; Li, J. F.; Zhao, S. S.; Ma, W. Q.; Jia, Z. Y.
2017-05-01
In order to reduce the adverse effects of uncertainty on optimal dispatch in active distribution network, an optimal dispatch model based on chance-constrained programming is proposed in this paper. In this model, the active and reactive power of DG can be dispatched at the aim of reducing the operating cost. The effect of operation strategy on the cost can be reflected in the objective which contains the cost of network loss, DG curtailment, DG reactive power ancillary service, and power quality compensation. At the same time, the probabilistic constraints can reflect the operation risk degree. Then the optimal dispatch model is simplified as a series of single stage model which can avoid large variable dimension and improve the convergence speed. And the single stage model is solved using a combination of particle swarm optimization (PSO) and point estimate method (PEM). Finally, the proposed optimal dispatch model and method is verified by the IEEE33 test system.
Topology optimization based on the harmony search method
International Nuclear Information System (INIS)
Lee, Seung-Min; Han, Seog-Young
2017-01-01
A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.
Topology optimization based on the harmony search method
Energy Technology Data Exchange (ETDEWEB)
Lee, Seung-Min; Han, Seog-Young [Hanyang University, Seoul (Korea, Republic of)
2017-06-15
A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.
Optimized Pulse Width Modulation for transformerless active-NPC inverters
DEFF Research Database (Denmark)
Achilladelis, Nikolaos; Koutroulis, Eftichios; Blaabjerg, Frede
2014-01-01
The transformerless DC/AC inverter topologies are employed in Photovoltaic systems in order to improve the power conversion efficiency, power density and cost. The Active-Neutral Point Clamped (Active-NPC) transformerless inverters have the advantage of achieving better thermal balance among...... their power semiconductors. In this paper, a new modulation technique is proposed for optimally controlling the power switches employed in transformerless Active-NPC inverters. The design results demonstrate that compared to the existing PWM strategies, using the proposed method results in lower total power...... losses and significantly better distribution of the power losses among the semiconductors of the Active-NPC inverter....
Zhang, Songchuan; Xia, Youshen
2018-01-01
Much research has been devoted to complex-variable optimization problems due to their engineering applications. However, the complex-valued optimization method for solving complex-variable optimization problems is still an active research area. This paper proposes two efficient complex-valued optimization methods for solving constrained nonlinear optimization problems of real functions in complex variables, respectively. One solves the complex-valued nonlinear programming problem with linear equality constraints. Another solves the complex-valued nonlinear programming problem with both linear equality constraints and an -norm constraint. Theoretically, we prove the global convergence of the proposed two complex-valued optimization algorithms under mild conditions. The proposed two algorithms can solve the complex-valued optimization problem completely in the complex domain and significantly extend existing complex-valued optimization algorithms. Numerical results further show that the proposed two algorithms have a faster speed than several conventional real-valued optimization algorithms.
Review of design optimization methods for turbomachinery aerodynamics
Li, Zhihui; Zheng, Xinqian
2017-08-01
In today's competitive environment, new turbomachinery designs need to be not only more efficient, quieter, and ;greener; but also need to be developed at on much shorter time scales and at lower costs. A number of advanced optimization strategies have been developed to achieve these requirements. This paper reviews recent progress in turbomachinery design optimization to solve real-world aerodynamic problems, especially for compressors and turbines. This review covers the following topics that are important for optimizing turbomachinery designs. (1) optimization methods, (2) stochastic optimization combined with blade parameterization methods and the design of experiment methods, (3) gradient-based optimization methods for compressors and turbines and (4) data mining techniques for Pareto Fronts. We also present our own insights regarding the current research trends and the future optimization of turbomachinery designs.
A Method for Determining Optimal Residential Energy Efficiency Packages
Energy Technology Data Exchange (ETDEWEB)
Polly, B. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gestwick, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bianchi, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Anderson, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Horowitz, S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Christensen, C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Judkoff, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2011-04-01
This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location.
A method for optimizing the performance of buildings
Energy Technology Data Exchange (ETDEWEB)
Pedersen, Frank
2006-07-01
lower bounds, or they can be required to assume certain values. The optimization problem makes it possible to optimize virtually any aspect of the building performance; however, the primary focus of this study is on energy consumption, economy, and indoor environment. The performance measures regarding the energy and indoor environment are calculated using existing simulation software, with minor modifications. The cost of constructing the building is calculating using unit prices for construction jobs, which can be found in price catalogues. Simple algebraic expressions are used as models for these prices. The model parameters are found by using data-fitting. In order to solve the optimization problem formulated earlier, a gradient-free sequential quadratic programming (SQP) filter algorithm is proposed. The algorithm does not require information about the first partial derivatives of the functions that define the optimization problem. This means that techniques such as using finite difference approximations can be avoided, which reduces the time needed for solving the optimization problem. Furthermore, the algorithm uses so-called domain constraint functions in order to ensure that the input to the simulation software is feasible. Using this technique avoids performing time-consuming simulations for unrealistic design decisions. The algorithm is evaluated by applying it to a set of test problems with known solutions. The results indicate that the algorithm converges fast and in a stable manner, as long as there are no active domain constraints. In this case, convergence is either deteriorated or prevented. This case is described in the thesis. The proposed building optimization method uses the gradient-free SQP filter algorithm in order to solve the formulated optimization problem, which involves performance measures that are calculated using simulation software for buildings. The method is tested by applying it to a building design problem involving an office
COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U
Energy Technology Data Exchange (ETDEWEB)
Sun, Y.; Borland, Michael
2017-06-25
Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.
Augmented Lagrangian Method For Discretized Optimal Control ...
African Journals Online (AJOL)
In this paper, we are concerned with one-dimensional time invariant optimal control problem, whose objective function is quadratic and the dynamical system is a differential equation with initial condition .Since most real life problems are nonlinear and their analytical solutions are not readily available, we resolve to ...
METHOD FOR OPTIMIZING THE ENERGY OF PUMPS
Skovmose Kallesøe, Carsten; De Persis, Claudio
2013-01-01
The device for energy-optimization on operation of several centrifugal pumps controlled in rotational speed, in a hydraulic installation, begins firstly with determining which pumps as pilot pumps are assigned directly to a consumer and which pumps are hydraulically connected in series upstream of
Parallel optimization methods for agile manufacturing
Energy Technology Data Exchange (ETDEWEB)
Meza, J.C.; Moen, C.D.; Plantenga, T.D.; Spence, P.A.; Tong, C.H. [Sandia National Labs., Livermore, CA (United States); Hendrickson, B.A.; Leland, R.W.; Reese, G.M. [Sandia National Labs., Albuquerque, NM (United States)
1997-08-01
The rapid and optimal design of new goods is essential for meeting national objectives in advanced manufacturing. Currently almost all manufacturing procedures involve the determination of some optimal design parameters. This process is iterative in nature and because it is usually done manually it can be expensive and time consuming. This report describes the results of an LDRD, the goal of which was to develop optimization algorithms and software tools that will enable automated design thereby allowing for agile manufacturing. Although the design processes vary across industries, many of the mathematical characteristics of the problems are the same, including large-scale, noisy, and non-differentiable functions with nonlinear constraints. This report describes the development of a common set of optimization tools using object-oriented programming techniques that can be applied to these types of problems. The authors give examples of several applications that are representative of design problems including an inverse scattering problem, a vibration isolation problem, a system identification problem for the correlation of finite element models with test data and the control of a chemical vapor deposition reactor furnace. Because the function evaluations are computationally expensive, they emphasize algorithms that can be adapted to parallel computers.
Advanced Topology Optimization Methods for Conceptual Architectural Design
DEFF Research Database (Denmark)
Aage, Niels; Amir, Oded; Clausen, Anders
2015-01-01
in topological optimization: Interactive control and continuous visualization; embedding flexible voids within the design space; consideration of distinct tension / compression properties; and optimization of dual material systems. In extension, optimization procedures for skeletal structures such as trusses......This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities...
Logic-based methods for optimization combining optimization and constraint satisfaction
Hooker, John
2011-01-01
A pioneering look at the fundamental role of logic in optimization and constraint satisfaction While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible
Trajectory Optimization Based on Multi-Interval Mesh Refinement Method
Directory of Open Access Journals (Sweden)
Ningbo Li
2017-01-01
Full Text Available In order to improve the optimization accuracy and convergence rate for trajectory optimization of the air-to-air missile, a multi-interval mesh refinement Radau pseudospectral method was introduced. This method made the mesh endpoints converge to the practical nonsmooth points and decreased the overall collocation points to improve convergence rate and computational efficiency. The trajectory was divided into four phases according to the working time of engine and handover of midcourse and terminal guidance, and then the optimization model was built. The multi-interval mesh refinement Radau pseudospectral method with different collocation points in each mesh interval was used to solve the trajectory optimization model. Moreover, this method was compared with traditional h method. Simulation results show that this method can decrease the dimensionality of nonlinear programming (NLP problem and therefore improve the efficiency of pseudospectral methods for solving trajectory optimization problems.
Numerical methods of mathematical optimization with Algol and Fortran programs
Künzi, Hans P; Zehnder, C A; Rheinboldt, Werner
1971-01-01
Numerical Methods of Mathematical Optimization: With ALGOL and FORTRAN Programs reviews the theory and the practical application of the numerical methods of mathematical optimization. An ALGOL and a FORTRAN program was developed for each one of the algorithms described in the theoretical section. This should result in easy access to the application of the different optimization methods.Comprised of four chapters, this volume begins with a discussion on the theory of linear and nonlinear optimization, with the main stress on an easily understood, mathematically precise presentation. In addition
Primal Interior-Point Method for Large Sparse Minimax Optimization
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
2009-01-01
Roč. 45, č. 5 (2009), s. 841-864 ISSN 0023-5954 R&D Projects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : unconstrained optimization * large-scale optimization * minimax optimization * nonsmooth optimization * interior-point methods * modified Newton methods * variable metric methods * computational experiments Subject RIV: BA - General Mathematics Impact factor: 0.445, year: 2009 http://dml.cz/handle/10338.dmlcz/140034
Devgan, Manish; Nanda, Arun; Ansari, Shahid Husain
2013-09-01
The aim of the present study was to assess the anti-diabetic activity of Pterocarpus marsupium Roxb. heartwood in alloxan induced diabetic rats using extracts obtained by optimized conventional and non conventional extraction methods. Aqueous and ethanol extracts of Pterocarpus marsupium heartwood were prepared by conventional methods (infusion, decoction, maceration and percolation) and non conventional methods, such as ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE). The crude aqueous extracts were administered orally to both normal and alloxan induced male albino rats (Sprague-Dawley strain). The experimental set up consisted of 48 male albino rats divided into 6 groups: Normal control, diabetic control (sterile normal saline, 1 ml/100 g body weight), standard (gliclazide, 25 mg/1000g of body weight), groups 4-6 (crude aqueous percolation, optimized UAE and MAE extract, 250 mg/1000g of body weight). In acute treatment, the reduction of blood glucose level was statistically significant with the oral administration of UAE and percolation aqueous extracts to the hyperglycemic rats. In sub-acute treatment, the UAE aqueous extract led to consistent and statistically significant (p<0.001) reduction in the blood glucose levels. There was no abnormal change in body weight of the hyperglycemic animals after 10 days of administration of plant extracts and gliclazide. This study justifies the traditional claim and provides a rationale for the use of Pterocarpus marsupium to treat diabetes mellitus. The antidiabetic activity of Pterocarpus marsupium can be enhanced by extracting the heartwood by non conventional method of UAE.
Review of dynamic optimization methods in renewable natural resource management
Williams, B.K.
1989-01-01
In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. The applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.
Zayapragassarazan, Z.; Kumar, Santosh
2012-01-01
Present generation students are primarily active learners with varied learning experiences and lecture courses may not suit all their learning needs. Effective learning involves providing students with a sense of progress and control over their own learning. This requires creating a situation where learners have a chance to try out or test their…
Optimization and control methods in industrial engineering and construction
Wang, Xiangyu
2014-01-01
This book presents recent advances in optimization and control methods with applications to industrial engineering and construction management. It consists of 15 chapters authored by recognized experts in a variety of fields including control and operation research, industrial engineering, and project management. Topics include numerical methods in unconstrained optimization, robust optimal control problems, set splitting problems, optimum confidence interval analysis, a monitoring networks optimization survey, distributed fault detection, nonferrous industrial optimization approaches, neural networks in traffic flows, economic scheduling of CCHP systems, a project scheduling optimization survey, lean and agile construction project management, practical construction projects in Hong Kong, dynamic project management, production control in PC4P, and target contracts optimization. The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and c...
Full-step interior-point methods for symmetric optimization
Gu, G.
2009-01-01
In [SIAM J. Optim., 16(4):1110--1136 (electronic), 2006] Roos proposed a full-Newton step Infeasible Interior-Point Method (IIPM) for Linear Optimization (LO). It is a primal-dual homotopy method; it differs from the classical IIPMs in that it uses only full steps. This means that no line searches
Willbur, Jaime F.; Vail, Justin D.; Mitchell, Lindsey N.; Jakeman, David L.; Timmons, Shannon C.
2016-01-01
The development and implementation of research-inspired, discovery-based experiences into science laboratory curricula is a proven strategy for increasing student engagement and ownership of experiments. In the novel laboratory module described herein, students learn to express, purify, and characterize a carbohydrate-active enzyme using modern…
Gradient-based methods for production optimization of oil reservoirs
Energy Technology Data Exchange (ETDEWEB)
Suwartadi, Eka
2012-07-01
Production optimization for water flooding in the secondary phase of oil recovery is the main topic in this thesis. The emphasis has been on numerical optimization algorithms, tested on case examples using simple hypothetical oil reservoirs. Gradientbased optimization, which utilizes adjoint-based gradient computation, is used to solve the optimization problems. The first contribution of this thesis is to address output constraint problems. These kinds of constraints are natural in production optimization. Limiting total water production and water cut at producer wells are examples of such constraints. To maintain the feasibility of an optimization solution, a Lagrangian barrier method is proposed to handle the output constraints. This method incorporates the output constraints into the objective function, thus avoiding additional computations for the constraints gradient (Jacobian) which may be detrimental to the efficiency of the adjoint method. The second contribution is the study of the use of second-order adjoint-gradient information for production optimization. In order to speedup convergence rate in the optimization, one usually uses quasi-Newton approaches such as BFGS and SR1 methods. These methods compute an approximation of the inverse of the Hessian matrix given the first-order gradient from the adjoint method. The methods may not give significant speedup if the Hessian is ill-conditioned. We have developed and implemented the Hessian matrix computation using the adjoint method. Due to high computational cost of the Newton method itself, we instead compute the Hessian-timesvector product which is used in a conjugate gradient algorithm. Finally, the last contribution of this thesis is on surrogate optimization for water flooding in the presence of the output constraints. Two kinds of model order reduction techniques are applied to build surrogate models. These are proper orthogonal decomposition (POD) and the discrete empirical interpolation method (DEIM
Toward solving the sign problem with path optimization method
Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira
2017-12-01
We propose a new approach to circumvent the sign problem in which the integration path is optimized to control the sign problem. We give a trial function specifying the integration path in the complex plane and tune it to optimize the cost function which represents the seriousness of the sign problem. We call it the path optimization method. In this method, we do not need to solve the gradient flow required in the Lefschetz-thimble method and then the construction of the integration-path contour arrives at the optimization problem where several efficient methods can be applied. In a simple model with a serious sign problem, the path optimization method is demonstrated to work well; the residual sign problem is resolved and precise results can be obtained even in the region where the global sign problem is serious.
Probabilistic methods for maintenance program optimization
International Nuclear Information System (INIS)
Liming, J.K.; Smith, M.J.; Gekler, W.C.
1989-01-01
In today's regulatory and economic environments, it is more important than ever that managers, engineers, and plant staff join together in developing and implementing effective management plans for safety and economic risk. This need applied to both power generating stations and other process facilities. One of the most critical parts of these management plans is the development and continuous enhancement of a maintenance program that optimizes plant or facility safety and profitability. The ultimate objective is to maximize the potential for station or facility success, usually measured in terms of projected financial profitability, while meeting or exceeding meaningful and reasonable safety goals, usually measured in terms of projected damage or consequence frequencies. This paper describes the use of the latest concepts in developing and evaluating maintenance programs to achieve maintenance program optimization (MPO). These concepts are based on significant field experience gained through the integration and application of fundamentals developed for industry and Electric Power Research Institute (EPRI)-sponsored projects on preventive maintenance (PM) program development and reliability-centered maintenance (RCM)
Mixed methods for viscoelastodynamics and topology optimization
Directory of Open Access Journals (Sweden)
Giacomo Maurelli
2014-07-01
Full Text Available A truly-mixed approach for the analysis of viscoelastic structures and continua is presented. An additive decomposition of the stress state into a viscoelastic part and a purely elastic one is introduced along with an Hellinger-Reissner variational principle wherein the stress represents the main variable of the formulation whereas the kinematic descriptor (that in the case at hand is the velocity field acts as Lagrange multiplier. The resulting problem is a Differential Algebraic Equation (DAE because of the need to introduce static Lagrange multipliers to comply with the Cauchy boundary condition on the stress. The associated eigenvalue problem is known in the literature as constrained eigenvalue problem and poses several difficulties for its solution that are addressed in the paper. The second part of the paper proposes a topology optimization approach for the rationale design of viscoelastic structures and continua. Details concerning density interpolation, compliance problems and eigenvalue-based objectives are given. Worked numerical examples are presented concerning both the dynamic analysis of viscoelastic structures and their topology optimization.
Computation of Optimal Monotonicity Preserving General Linear Methods
Ketcheson, David I.
2009-07-01
Monotonicity preserving numerical methods for ordinary differential equations prevent the growth of propagated errors and preserve convex boundedness properties of the solution. We formulate the problem of finding optimal monotonicity preserving general linear methods for linear autonomous equations, and propose an efficient algorithm for its solution. This algorithm reliably finds optimal methods even among classes involving very high order accuracy and that use many steps and/or stages. The optimality of some recently proposed methods is verified, and many more efficient methods are found. We use similar algorithms to find optimal strong stability preserving linear multistep methods of both explicit and implicit type, including methods for hyperbolic PDEs that use downwind-biased operators.
Directory of Open Access Journals (Sweden)
Cugnata Noelia Melina
2017-06-01
Full Text Available American Foulbrood (AFB is a bacterial disease, caused by Paenibacillus larvae, that affects honeybees (Apis mellifera. Alternative strategies to control AFB are based on the treatment of the beehives with antimicrobial natural substances such as extracts, essential oils and/or pure compounds from plants, honey by-products, bacteria and moulds. The broth microdilution method is currently one of the most widely used methods to determine the minimum inhibitory concentration (MIC of a substance. In this regard, the fact that most natural products, due to their lipophilic nature, must be dissolved in organic solvents or their aqueous mixtures is an issue of major concern because the organic solvent becomes part of the dilution in the incubation medium, and therefore, can interfere with bacterial viability depending on its nature and concentration. A systematic study was carried out to determine by the broth microdilution method the MIC and the maximum non inhibitory concentration (MNIC against P. larvae of the most common organic solvents used to extract or dissolve natural products, i.e. ethanol, methanol, acetonitrile, n-butanol, dimethylsulfoxide, and acidified hydromethanolic solutions. From the MIC and MNIC for each organic solvent, recommended maximum concentrations in contact with P. larvae were established: DMSO 5% (v/v, acetonitrile 7.5% (v/v, ethanol 7.5% (v/v, methanol 12% (v/v, n-butanol 1% (v/v, and methanol-water-acetic acid (1.25:98.71:0.04, v/v/v.
Present-day Problems and Methods of Optimization in Mechatronics
Directory of Open Access Journals (Sweden)
Tarnowski Wojciech
2017-06-01
Full Text Available It is justified that design is an inverse problem, and the optimization is a paradigm. Classes of design problems are proposed and typical obstacles are recognized. Peculiarities of the mechatronic designing are specified as a proof of a particle importance of optimization in the mechatronic design. Two main obstacles of optimization are discussed: a complexity of mathematical models and an uncertainty of the value system, in concrete case. Then a set of non-standard approaches and methods are presented and discussed, illustrated by examples: a fuzzy description, a constraint-based iterative optimization, AHP ranking method and a few MADM functions in Matlab.
Control Methods Utilizing Energy Optimizing Schemes in Refrigeration Systems
DEFF Research Database (Denmark)
Larsen, L.S; Thybo, C.; Stoustrup, Jakob
2003-01-01
The potential energy savings in refrigeration systems using energy optimal control has been proved to be substantial. This however requires an intelligent control that drives the refrigeration systems towards the energy optimal state. This paper proposes an approach for a control, which drives...... the condenser pressure towards an optimal state. The objective of this is to present a feasible method that can be used for energy optimizing control. A simulation model of a simple refrigeration system will be used as basis for testing the control method....
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
A new secant method for unconstrained optimization
Vavasis, Stephen A.
2008-01-01
We present a gradient-based algorithm for unconstrained minimization derived from iterated linear change of basis. The new method is equivalent to linear conjugate gradient in the case of a quadratic objective function. In the case of exact line search it is a secant method. In practice, it performs comparably to BFGS and DFP and is sometimes more robust.
A method optimization study for atomic absorption ...
African Journals Online (AJOL)
Sadia Ata
2014-04-24
Apr 24, 2014 ... Abstract A sensitive, reliable and relative fast method has been developed for the determination of total zinc in insulin by atomic absorption spectrophotometer. This designed study was used to opti- mize the procedures for the existing methods. Spectrograms of both standard and sample solutions.
Optimizing Usability Studies by Complementary Evaluation Methods
Schmettow, Martin; Bach, Cedric; Scapin, Dominique
2014-01-01
This paper examines combinations of complementary evaluation methods as a strategy for efficient usability problem discovery. A data set from an earlier study is re-analyzed, involving three evaluation methods applied to two virtual environment applications. Results of a mixed-effects logistic
Willbur, Jaime F; Vail, Justin D; Mitchell, Lindsey N; Jakeman, David L; Timmons, Shannon C
2016-01-01
The development and implementation of research-inspired, discovery-based experiences into science laboratory curricula is a proven strategy for increasing student engagement and ownership of experiments. In the novel laboratory module described herein, students learn to express, purify, and characterize a carbohydrate-active enzyme using modern techniques and instrumentation commonly found in a research laboratory. Unlike in a traditional cookbook-style experiment, students generate their own hypotheses regarding expression conditions and quantify the amount of protein isolated using their selected variables. Over the course of three 3-hour laboratory periods, students learn to use sterile technique to express a protein using recombinant DNA in E. coli, purify the resulting enzyme via affinity chromatography and dialysis, analyze the success of their purification scheme via SDS-PAGE, assess the activity of the enzyme via an HPLC-based assay, and quantify the amount of protein isolated via a Bradford assay. Following the completion of this experiment, students were asked to evaluate their experience via an optional survey. All students strongly agreed that this laboratory module was more interesting to them than traditional experiments because of its lack of a pre-determined outcome and desired additional opportunities to participate in the experimental design process. This experiment serves as an example of how research-inspired, discovery-based experiences can benefit both the students and instructor; students learned important skills necessary for real-world biochemistry research and a more concrete understanding of the research process, while generating new knowledge to enhance the scholarly endeavors of the instructor. © 2015 The International Union of Biochemistry and Molecular Biology.
Models and Methods for Free Material Optimization
DEFF Research Database (Denmark)
Weldeyesus, Alemseged Gebrehiwot
conditions for physical attainability, in the context that, it has to be symmetric and positive semidefinite. FMO problems have been studied for the last two decades in many articles that led to the development of a wide range of models, methods, and theories. As the design variables in FMO are the local...... programs. The method has successfully obtained solutions to large-scale classical FMO problems of simultaneous analysis and design, nested and dual formulations. The second goal is to extend the method and the FMO problem formulations to general laminated shell structures. The thesis additionally addresses...
Flexible and generalized uncertainty optimization theory and methods
Lodwick, Weldon A
2017-01-01
This book presents the theory and methods of flexible and generalized uncertainty optimization. Particularly, it describes the theory of generalized uncertainty in the context of optimization modeling. The book starts with an overview of flexible and generalized uncertainty optimization. It covers uncertainties that are both associated with lack of information and that more general than stochastic theory, where well-defined distributions are assumed. Starting from families of distributions that are enclosed by upper and lower functions, the book presents construction methods for obtaining flexible and generalized uncertainty input data that can be used in a flexible and generalized uncertainty optimization model. It then describes the development of such a model in detail. All in all, the book provides the readers with the necessary background to understand flexible and generalized uncertainty optimization and develop their own optimization model. .
Extremal Optimization: Methods Derived from Co-Evolution
Energy Technology Data Exchange (ETDEWEB)
Boettcher, S.; Percus, A.G.
1999-07-13
We describe a general-purpose method for finding high-quality solutions to hard optimization problems, inspired by self-organized critical models of co-evolution such as the Bak-Sneppen model. The method, called Extremal Optimization, successively eliminates extremely undesirable components of sub-optimal solutions, rather than ''breeding'' better components. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, Extremal Optimization improves on a single candidate solution by treating each of its components as species co-evolving according to Darwinian principles. Unlike Simulated Annealing, its non-equilibrium approach effects an algorithm requiring few parameters to tune. With only one adjustable parameter, its performance proves competitive with, and often superior to, more elaborate stochastic optimization procedures. We demonstrate it here on two classic hard optimization problems: graph partitioning and the traveling salesman problem.
Support method for solving an optimal xenon shutdown problem
International Nuclear Information System (INIS)
Dung, L.C.
1992-01-01
Since the discovering of the maximum principle by Pontriagin in 1956, methods for solving optimal control problems have been developed fast. There are the efforts to solve an optimal problem of transient process in a nuclear reactor using its ideas. However, the classical maximum principle does not show how to construct an optimal control or suboptimal control with a given exactness. We exploit mainly in the present work the ideas of the support method proposed by Gabasov and Kirillova for linear systems, in order to solve an optimal control problem for non-linear systems. The constructive maximum principle for non-linear dynamic systems with controllable structure received by us in this paper is new result. The ε - maximum principle is used for receiving an 7-phase ε - optimal control of optimal xenon shutdown problem. (author)
An efficient multilevel optimization method for engineering design
Vanderplaats, G. N.; Yang, Y. J.; Kim, D. S.
1988-01-01
An efficient multilevel deisgn optimization technique is presented. The proposed method is based on the concept of providing linearized information between the system level and subsystem level optimization tasks. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to use. The disadvantage is that the coupling between subsystems is not dealt with in a precise mathematical manner.
Response surface method applied to optimization of estradiol ...
Indian Academy of Sciences (India)
An optimization process based on response surface methodology was carried out in order to develop a statistical model which describes the relationship between active independent variables and estradiol flux. This model can be used to find out a combination of factor levels during response optimization. Possible options ...
Instrument design optimization with computational methods
Energy Technology Data Exchange (ETDEWEB)
Moore, Michael H. [Old Dominion Univ., Norfolk, VA (United States)
2017-08-01
Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density uctuations from the liquid hydrogen (LH2) target used in the Q_{wea}k experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentum Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5:5 deg to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.
Honey Bees Inspired Optimization Method: The Bees Algorithm
Directory of Open Access Journals (Sweden)
Ernesto Mastrocinque
2013-11-01
Full Text Available Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.
A hybrid optimization method for biplanar transverse gradient coil design
International Nuclear Information System (INIS)
Qi Feng; Tang Xin; Jin Zhe; Jiang Zhongde; Shen Yifei; Meng Bin; Zu Donglin; Wang Weimin
2007-01-01
The optimization of transverse gradient coils is one of the fundamental problems in designing magnetic resonance imaging gradient systems. A new approach is presented in this paper to optimize the transverse gradient coils' performance. First, in the traditional spherical harmonic target field method, high order coefficients, which are commonly ignored, are used in the first stage of the optimization process to give better homogeneity. Then, some cosine terms are introduced into the series expansion of stream function. These new terms provide simulated annealing optimization with new freedoms. Comparison between the traditional method and the optimized method shows that the inhomogeneity in the region of interest can be reduced from 5.03% to 1.39%, the coil efficiency increased from 3.83 to 6.31 mT m -1 A -1 and the minimum distance of these discrete coils raised from 1.54 to 3.16 mm
Optimizing Robinson Operator with Ant Colony Optimization As a Digital Image Edge Detection Method
Yanti Nasution, Tarida; Zarlis, Muhammad; K. M Nasution, Mahyuddin
2017-12-01
Edge detection serves to identify the boundaries of an object against a background of mutual overlap. One of the classic method for edge detection is operator Robinson. Operator Robinson produces a thin, not assertive and grey line edge. To overcome these deficiencies, the proposed improvements to edge detection method with the approach graph with Ant Colony Optimization algorithm. The repairs may be performed are thicken the edge and connect the edges cut off. Edge detection research aims to do optimization of operator Robinson with Ant Colony Optimization then compare the output and generated the inferred extent of Ant Colony Optimization can improve result of edge detection that has not been optimized and improve the accuracy of the results of Robinson edge detection. The parameters used in performance measurement of edge detection are morphology of the resulting edge line, MSE and PSNR. The result showed that Robinson and Ant Colony Optimization method produces images with a more assertive and thick edge. Ant Colony Optimization method is able to be used as a method for optimizing operator Robinson by improving the image result of Robinson detection average 16.77 % than classic Robinson result.
Optimizing Cognitive Rehabilitation: Effective Instructional Methods
Sohlberg, McKay Moore; Turkstra, Lyn S.
2011-01-01
Rehabilitation professionals face a key challenge when working with clients with acquired cognitive impairments: how to teach new skills to individuals who have difficulty learning. Unique in its focus, this book presents evidence-based instructional methods specifically designed to help this population learn more efficiently. The expert authors…
Methods for Large-Scale Nonlinear Optimization.
1980-05-01
haves more like an iterative method since it has the potential of converging in fewer than, or more than, ns - t iterations. Recently, Dembo (1979) has...R., Powell, M. J. D. and Reid, J. K. (1974). On the estimation of sparse Jacobian matrices, J. Inst. Maths Applics., 13, pp. 117-119. Dembo , R. S
Exact and useful optimization methods for microeconomics
Balder, E.J.
2011-01-01
This paper points out that the treatment of utility maximization in current textbooks on microeconomic theory is deficient in at least three respects: breadth of coverage, completeness-cum-coherence of solution methods and mathematical correctness. Improvements are suggested in the form of a
OPTIMAL SIGNAL PROCESSING METHODS IN GPR
Directory of Open Access Journals (Sweden)
Saeid Karamzadeh
2014-01-01
Full Text Available In the past three decades, a lot of various applications of Ground Penetrating Radar (GPR took place in real life. There are important challenges of this radar in civil applications and also in military applications. In this paper, the fundamentals of GPR systems will be covered and three important signal processing methods (Wavelet Transform, Matched Filter and Hilbert Huang will be compared to each other in order to get most accurate information about objects which are in subsurface or behind the wall.
Activity based costing (ABC Method
Directory of Open Access Journals (Sweden)
Prof. Ph.D. Saveta Tudorache
2008-05-01
Full Text Available In the present paper the need and advantages are presented of using the Activity BasedCosting method, need arising from the need of solving the information pertinence issue. This issue has occurreddue to the limitation of classic methods in this field, limitation also reflected by the disadvantages ofsuch classic methods in establishing complete costs.
OPTIMIZATION METHODS FOR HYDROECOLOGICAL MONITORING SYSTEMS
Directory of Open Access Journals (Sweden)
Inna Pivovarova
2016-09-01
Full Text Available The paper describes current approaches to the rational distribution of monitoring stations. A short review and the organization of the system of hydro-geological observations in different countries are presented. On the basis of real data we propose a solution to the problem of how to calculate the average area per one hydrological station, which is the main indicator of the efficiency and performance of the monitoring system in general. We conclude that a comprehensive approach to the monitoring system organization is important, because only hydrometric and hydrochemical activities coordinated in time provide possibilities needed to analyse the underline causes of the observed pollutants content dynamics in water bodies in the long term.
Optimal PMU Placement with Uncertainty Using Pareto Method
Directory of Open Access Journals (Sweden)
A. Ketabi
2012-01-01
Full Text Available This paper proposes a method for optimal placement of Phasor Measurement Units (PMUs in state estimation considering uncertainty. State estimation has first been turned into an optimization exercise in which the objective function is selected to be the number of unobservable buses which is determined based on Singular Value Decomposition (SVD. For the normal condition, Differential Evolution (DE algorithm is used to find the optimal placement of PMUs. By considering uncertainty, a multiobjective optimization exercise is hence formulated. To achieve this, DE algorithm based on Pareto optimum method has been proposed here. The suggested strategy is applied on the IEEE 30-bus test system in several case studies to evaluate the optimal PMUs placement.
Advanced Topology Optimization Methods for Conceptual Architectural Design
DEFF Research Database (Denmark)
Aage, Niels; Amir, Oded; Clausen, Anders
2014-01-01
This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities in topolo......This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities...
Advanced Topology Optimization Methods for Conceptual Architectural Design
DEFF Research Database (Denmark)
Aage, Niels; Amir, Oded; Clausen, Anders
2015-01-01
This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities in topolo......This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities...
Mazoyer, J.; Pueyo, L.; N'Diaye, M.; Fogarty, K.; Zimmerman, N.; Soummer, R.; Shaklan, S.; Norman, C.
2018-01-01
High-contrast imaging and spectroscopy provide unique constraints for exoplanet formation models as well as for planetary atmosphere models. Instrumentation techniques in this field have greatly improved over the last two decades, with the development of stellar coronagraphy, in parallel with specific methods of wavefront sensing and control. Next generation space- and ground-based telescopes will enable the characterization of cold solar-system-like planets for the first time and maybe even in situ detection of bio-markers. However, the growth of primary mirror diameters, necessary for these detections, comes with an increase of their complexity (segmentation, secondary mirror features). These discontinuities in the aperture can greatly limit the performance of coronagraphic instruments. In this context, we introduced a new technique, Active Correction of Aperture Discontinuities-Optimized Stroke Minimization (ACAD-OSM), to correct for the diffractive effects of aperture discontinuities in the final image plane of a coronagraph, using deformable mirrors. In this paper, we present several tools that can be used to optimize the performance of this technique for its application to future large missions. In particular, we analyzed the influence of the deformable setup (size and separating distance) and found that there is an optimal point for this setup, optimizing the performance of the instrument in contrast and throughput while minimizing the strokes applied to the deformable mirrors. These results will help us design future coronagraphic instruments to obtain the best performance.
Modifying nodal pricing method considering market participants optimality and reliability
Directory of Open Access Journals (Sweden)
A. R. Soofiabadi
2015-06-01
Full Text Available This paper develops a method for nodal pricing and market clearing mechanism considering reliability of the system. The effects of components reliability on electricity price, market participants’ profit and system social welfare is considered. This paper considers reliability both for evaluation of market participant’s optimality as well as for fair pricing and market clearing mechanism. To achieve fair pricing, nodal price has been obtained through a two stage optimization problem and to achieve fair market clearing mechanism, comprehensive criteria has been introduced for optimality evaluation of market participant. Social welfare of the system and system efficiency are increased under proposed modified nodal pricing method.
Malliavin method for optimal investment in financial markets with memory
Directory of Open Access Journals (Sweden)
An Qiguang
2016-01-01
Full Text Available We consider a financial market with memory effects in which wealth processes are driven by mean-field stochastic Volterra equations. In this financial market, the classical dynamic programming method can not be used to study the optimal investment problem, because the solution of mean-field stochastic Volterra equation is not a Markov process. In this paper, a new method through Malliavin calculus introduced in [1], can be used to obtain the optimal investment in a Volterra type financial market. We show a sufficient and necessary condition for the optimal investment in this financial market with memory by mean-field stochastic maximum principle.
Method and system for SCR optimization
Lefebvre, Wesley Curt [Boston, MA; Kohn, Daniel W [Cambridge, MA
2009-03-10
Methods and systems are provided for controlling SCR performance in a boiler. The boiler includes one or more generally cross sectional areas. Each cross sectional area can be characterized by one or more profiles of one or more conditions affecting SCR performance and be associated with one or more adjustable desired profiles of the one or more conditions during the operation of the boiler. The performance of the boiler can be characterized by boiler performance parameters. A system in accordance with one or more embodiments of the invention can include a controller input for receiving a performance goal for the boiler corresponding to at least one of the boiler performance parameters and for receiving data values corresponding to boiler control variables and to the boiler performance parameters. The boiler control variables include one or more current profiles of the one or more conditions. The system also includes a system model that relates one or more profiles of the one or more conditions in the boiler to the boiler performance parameters. The system also includes an indirect controller that determines one or more desired profiles of the one or more conditions to satisfy the performance goal for the boiler. The indirect controller uses the system model, the received data values and the received performance goal to determine the one or more desired profiles of the one or more conditions. The system model also includes a controller output that outputs the one or more desired profiles of the one or more conditions.
Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms
Kanevski, Mikhail; Volpi, Michele; Copa, Loris
2010-05-01
The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of
Hybrid DFP-CG method for solving unconstrained optimization problems
Osman, Wan Farah Hanan Wan; Asrul Hery Ibrahim, Mohd; Mamat, Mustafa
2017-09-01
The conjugate gradient (CG) method and quasi-Newton method are both well known method for solving unconstrained optimization method. In this paper, we proposed a new method by combining the search direction between conjugate gradient method and quasi-Newton method based on BFGS-CG method developed by Ibrahim et al. The Davidon-Fletcher-Powell (DFP) update formula is used as an approximation of Hessian for this new hybrid algorithm. Numerical result showed that the new algorithm perform well than the ordinary DFP method and proven to posses both sufficient descent and global convergence properties.
Numerical optimization methods for controlled systems with parameters
Tyatyushkin, A. I.
2017-10-01
First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.
Method for Determining Optimal Residential Energy Efficiency Retrofit Packages
Energy Technology Data Exchange (ETDEWEB)
Polly, B.; Gestwick, M.; Bianchi, M.; Anderson, R.; Horowitz, S.; Christensen, C.; Judkoff, R.
2011-04-01
Businesses, government agencies, consumers, policy makers, and utilities currently have limited access to occupant-, building-, and location-specific recommendations for optimal energy retrofit packages, as defined by estimated costs and energy savings. This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location. Energy savings and incremental costs are calculated relative to a minimum upgrade reference scenario, which accounts for efficiency upgrades that would occur in the absence of a retrofit because of equipment wear-out and replacement with current minimum standards.
Closed Loop Optimal Control of a Stewart Platform Using an Optimal Feedback Linearization Method
Directory of Open Access Journals (Sweden)
Hami Tourajizadeh
2016-06-01
Full Text Available Optimal control of a Stewart robot is performed in this paper using a sequential optimal feedback linearization method considering the jack dynamics. One of the most important applications of a Stewart platform is tracking a machine along a specific path or from a defined point to another point. However, the control procedure of these robots is more challenging than that of serial robots since their dynamics are extremely complicated and non-linear. In addition, saving energy, together with achieving the desired accuracy, is one of the most desirable objectives. In this paper, a proper non-linear optimal control is employed to gain the maximum accuracy by applying the minimum force distribution to the jacks. Dynamics of the jacks are included in this paper to achieve more accurate results. Optimal control is performed for a six-DOF hexapod robot and its accuracy is increased using a sequential feedback linearization method, while its energy optimization is realized using the LQR method for the linearized system. The efficiency of the proposed optimal control is verified by simulating a six-DOF hexapod robot in MATLAB, and its related results are gained and analysed. The actual position of the end-effector, its velocity, the initial and final forces of the jacks and the length and velocity of the jacks are obtained and then compared with open loop and non-optimized systems; analytical comparisons show the efficiency of the proposed methods.
On some other preferred method for optimizing the welded joint
Directory of Open Access Journals (Sweden)
Pejović Branko B.
2016-01-01
Full Text Available The paper shows an example of performed optimization of sizes in terms of welding costs in a characteristic loaded welded joint. Hence, in the first stage, the variables and constant parameters are defined, and mathematical shape of the optimization function is determined. The following stage of the procedure defines and places the most important constraint functions that limit the design of structures, that the technologist and the designer should take into account. Subsequently, a mathematical optimization model of the problem is derived, that is efficiently solved by a proposed method of geometric programming. Further, a mathematically based thorough optimization algorithm is developed of the proposed method, with a main set of equations defining the problem that are valid under certain conditions. Thus, the primary task of optimization is reduced to the dual task through a corresponding function, which is easier to solve than the primary task of the optimized objective function. The main reason for this is a derived set of linear equations. Apparently, a correlation is used between the optimal primary vector that minimizes the objective function and the dual vector that maximizes the dual function. The method is illustrated on a computational practical example with a different number of constraint functions. It is shown that for the case of a lower level of complexity, a solution is reached through an appropriate maximization of the dual function by mathematical analysis and differential calculus.
A method for optimizing the performance of buildings
DEFF Research Database (Denmark)
Pedersen, Frank
2007-01-01
This thesis describes a method for optimizing the performance of buildings. Design decisions made in early stages of the building design process have a significant impact on the performance of buildings, for instance, the performance with respect to the energy consumption, economical aspects......, and the indoor environment. The method is intended for supporting design decisions for buildings, by combining methods for calculating the performance of buildings with numerical optimization methods. The method is able to find optimum values of decision variables representing different features of the building...... is calculating using unit prices for construction jobs, which can be found in price catalogues. Simple algebraic expressions are used as models for these prices. The model parameters are found by using data-fitting. In order to solve the optimization problem formulated earlier, a gradient-free sequential...
ROTAX: a nonlinear optimization program by axes rotation method
International Nuclear Information System (INIS)
Suzuki, Tadakazu
1977-09-01
A nonlinear optimization program employing the axes rotation method has been developed for solving nonlinear problems subject to nonlinear inequality constraints and its stability and convergence efficiency were examined. The axes rotation method is a direct search of the optimum point by rotating the orthogonal coordinate system in a direction giving the minimum objective. The searching direction is rotated freely in multi-dimensional space, so the method is effective for the problems represented with the contours having deep curved valleys. In application of the axes rotation method to the optimization problems subject to nonlinear inequality constraints, an improved version of R.R. Allran and S.E.J. Johnsen's method is used, which deals with a new objective function composed of the original objective and a penalty term to consider the inequality constraints. The program is incorporated in optimization code system SCOOP. (auth.)
Topology Optimization of Active Transport Flows
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe
2017-01-01
optimization to the design of multiphase flow components. The work is a natural extension of the density based topology optimization procedure applied to design of passive mixers and coolers where the transported matter is not influencing the properties of the governing fluid flow model. In this work thee...... effective properties of the fluid is changing with concentration. In this work a multiphase fluid flow model is combined with a Brinkman penalizationin order to introduce the design of the fluid component. Gradient based optimization is applied in order to optimize the performance of flow components......Fluid flows with particle transport are common in many industrial processes and components. The design of components for addition or removal of particles as well as mixing or stratification is of great importance in the specific processes. This work presents a methodology to apply topology...
Directory of Open Access Journals (Sweden)
Ruisheng Sun
2016-01-01
Full Text Available This paper presents a new parametric optimization approach based on a modified particle swarm optimization (PSO to design a class of impulsive-correction projectiles with discrete, flexible-time interval, and finite-energy control. In terms of optimal control theory, the task is described as the formulation of minimum working number of impulses and minimum control error, which involves reference model linearization, boundary conditions, and discontinuous objective function. These result in difficulties in finding the global optimum solution by directly utilizing any other optimization approaches, for example, Hp-adaptive pseudospectral method. Consequently, PSO mechanism is employed for optimal setting of impulsive control by considering the time intervals between two neighboring lateral impulses as design variables, which makes the briefness of the optimization process. A modification on basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. In addition, a suboptimal control and guidance law based on PSO technique are put forward for the real-time consideration of the online design in practice. Finally, a simulation case coupled with a nonlinear flight dynamic model is applied to validate the modified PSO control algorithm. The results of comparative study illustrate that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately and provides a reference approach to handling such impulsive-correction problem.
SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available An important stage in problem solving process for aerospace and aerostructures designing is calculating their main charac- teristics optimization. The results of the four constrained optimization problems related to the design of various technical systems: such as determining the best parameters of welded beams, pressure vessel, gear, spring are presented. The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. That is why using classical approach for extremum seeking is not efficient. Here comes the necessity of using such methods of optimization that allow to find a near optimal solution in acceptable amount of time with the minimum waste of computer power. Such methods include the methods of Swarm Intelligence: spiral dy- namics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. The Swarm Intelligence methods are designed in such a way that a swarm consisting of agents carries out the search for extremum. In search for the point of extremum, the parti- cles exchange information and consider their experience as well as the experience of population leader and the neighbors in some area. To solve the listed problems there has been designed a program complex, which efficiency is illustrated by the solutions of four applied problems. Each of the considered applied optimization problems is solved with all the three chosen methods. The ob- tained numerical results can be compared with the ones found in a swarm with a particle method. The author gives recommenda- tions on how to choose methods parameters and penalty function value, which consider inequality constraints.
Genetic-evolution-based optimization methods for engineering design
Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.
1990-01-01
This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.
Singer, G; Ebramzadeh, E; Jones, N F; Meals, R
1998-10-01
The current trend toward early active flexion after repair of the flexor tendons necessitates a stronger repair than that provided by a modified Kessler technique with use of 4-0 nylon suture. The purpose of the current study was to determine, with use of the Taguchi method of analysis, the strongest and most consistent repair of the flexor tendons. Flexor tendons were obtained from fresh-frozen hands of human cadavera. Eight flexor tendons initially were repaired with the modified Kessler technique with use of 4-0 nylon core suture and 6-0 nylon epitenon suture. A test matrix was used to analyze a total of twenty variables in sixty-four tests. These variables included eight techniques for core-suture repair, four types of core suture, two sizes of core suture, four techniques for suture of the epitenon, and two distances from the repair site for placement of the core suture. After each repair, the specimens were mounted in a servohydraulic mechanical testing machine for tension-testing to failure. The optimum combination of variables was determined, with the Taguchi method, to be an augmented Becker technique with use of 3-0 Mersilene core suture, placed 0.75 centimeter from the cut edge with volar epitenon suture. The four-strand, double modified Kessler technique provided the second strongest repair. Five tendons that had been repaired with use of the optimum combination then were tested and compared with tendons that had been repaired with the standard modified Kessler technique. With the optimum combination of variables, the strength of the repair improved from a mean (and standard deviation) of 17.2 +/- 2.9 to 128 +/- 5.6 newtons, and the stiffness improved from a mean of 4.6 to 16.2 newtons per millimeter.
A class of trust-region methods for parallel optimization
Energy Technology Data Exchange (ETDEWEB)
P. D. Hough; J. C. Meza
1999-03-01
The authors present a new class of optimization methods that incorporates a Parallel Direct Search (PDS) method within a trust-region Newton framework. This approach combines the inherent parallelism of PDS with the rapid and robust convergence properties of Newton methods. Numerical tests have yielded favorable results for both standard test problems and engineering applications. In addition, the new method appears to be more robust in the presence of noisy functions that are inherent in many engineering simulations.
RELATIVE CAMERA POSE ESTIMATION METHOD USING OPTIMIZATION ON THE MANIFOLD
Directory of Open Access Journals (Sweden)
C. Cheng
2017-05-01
Full Text Available To solve the problem of relative camera pose estimation, a method using optimization with respect to the manifold is proposed. Firstly from maximum-a-posteriori (MAP model to nonlinear least squares (NLS model, the general state estimation model using optimization is derived. Then the camera pose estimation model is applied to the general state estimation model, while the parameterization of rigid body transformation is represented by Lie group/algebra. The jacobian of point-pose model with respect to Lie group/algebra is derived in detail and thus the optimization model of rigid body transformation is established. Experimental results show that compared with the original algorithms, the approaches with optimization can obtain higher accuracy both in rotation and translation, while avoiding the singularity of Euler angle parameterization of rotation. Thus the proposed method can estimate relative camera pose with high accuracy and robustness.
Oil Reservoir Production Optimization using Single Shooting and ESDIRK Methods
DEFF Research Database (Denmark)
Capolei, Andrea; Völcker, Carsten; Frydendall, Jan
2012-01-01
the injections and oil production such that flow is uniform in a given geological structure. Even in the case of conventional water flooding, feedback based optimal control technologies may enable higher oil recovery than with conventional operational strategies. The optimal control problems that must be solved......Conventional recovery techniques enable recovery of 10-50% of the oil in an oil field. Advances in smart well technology and enhanced oil recovery techniques enable significant larger recovery. To realize this potential, feedback model-based optimal control technologies are needed to manipulate...... are large-scale problems and require specialized numerical algorithms. In this paper, we combine a single shooting optimization algorithm based on sequential quadratic programming (SQP) with explicit singly diagonally implicit Runge-Kutta (ESDIRK) integration methods and the a continuous adjoint method...
Continuation methods in multiobjective optimization for combined structure control design
Milman, M.; Salama, M.; Scheid, R.; Bruno, R.; Gibson, J. S.
1990-01-01
A homotopy approach involving multiobjective functions is developed to outline the methods that have evolved for the combined control-structure optimization of physical systems encountered in the technology of large space structures. A method to effect a timely consideration of the control performance prior to the finalization of the structural design involves integrating the control and structural design processes into a unified design methodology that combines the two optimization problems into a single formulation. This study uses the combined optimization problem as a family of weighted structural and control costs. Connections with vector optimizations are described; an analysis of the zero-set of required conditions is made, and a numerical example is given.
Optimization to the medical facilities for Neutron activation analysis
International Nuclear Information System (INIS)
Franklin Mergarerejo, Ricardo; GarcIa Parra, Lazaro; Desdin, Luis Felipe; Lopez Aldama, Daniel
2001-01-01
A method of detection of the Fluorine is presented by means of the neutron activation analysis. This method supposes an accuracy in the determination of any very high element (of the ppm order); but having the particularity that with Oxygen and Fluorine after certain nuclear reactions are obtained the same reaction product (son). This implies serious inconveniences since an interference he/she takes place among the activation of the Oxygen and of the Fluorine falsifying the reading. To save this inconvenience and to take advantage of the kindness of this method it is known that the Oxygen is activated for neutrons with superior energy to the 10.5 MeV, while the Fluorine for energy of the superior incident neutrons to the 1.5 MeV. We think about as hypothesis that is possible to reduce the interference of the Oxygen using a moderator in order to affect the statistic of the count the less possible thing. The objective of the present work is to design and to optimize an installation to measure concentrations of Fluorine in presence of Oxygen using neutrons of 14 MeV coming from a generator of neutrons of the type NG-12-1. To fulfill our objective leaving of the hypothesis an experimental simulation it was implemented using mathematical methods of having proven efficiency in the transport of neutrons like the method of Mount Carlo (specifically the code MCNP-)
A Finite Element Removal Method for 3D Topology Optimization
Directory of Open Access Journals (Sweden)
M. Akif Kütük
2013-01-01
Full Text Available Topology optimization provides great convenience to designers during the designing stage in many industrial applications. With this method, designers can obtain a rough model of any part at the beginning of a designing stage by defining loading and boundary conditions. At the same time the optimization can be used for the modification of a product which is being used. Lengthy solution time is a disadvantage of this method. Therefore, the method cannot be widespread. In order to eliminate this disadvantage, an element removal algorithm has been developed for topology optimization. In this study, the element removal algorithm is applied on 3-dimensional parts, and the results are compared with the ones available in the related literature. In addition, the effects of the method on solution times are investigated.
Numerical methods for optimal control problems with state constraints
Pytlak, Radosław
1999-01-01
While optimality conditions for optimal control problems with state constraints have been extensively investigated in the literature the results pertaining to numerical methods are relatively scarce. This book fills the gap by providing a family of new methods. Among others, a novel convergence analysis of optimal control algorithms is introduced. The analysis refers to the topology of relaxed controls only to a limited degree and makes little use of Lagrange multipliers corresponding to state constraints. This approach enables the author to provide global convergence analysis of first order and superlinearly convergent second order methods. Further, the implementation aspects of the methods developed in the book are presented and discussed. The results concerning ordinary differential equations are then extended to control problems described by differential-algebraic equations in a comprehensive way for the first time in the literature.
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
Optimization method for quantitative calculation of clay minerals in soil
Indian Academy of Sciences (India)
Therefore, we rec- ommend employing Matlab to solve equations of the kind discussed here. In conclusion, using optimization methods to calculate the clay mineral contents in soil is viable based on the chemical analysis data. Further stud- ies combining this method with X-ray diffraction, differential thermal, and infrared ...
Primal-Dual Interior Point Multigrid Method for Topology Optimization
Czech Academy of Sciences Publication Activity Database
Kočvara, Michal; Mohammed, S.
2016-01-01
Roč. 38, č. 5 (2016), B685-B709 ISSN 1064-8275 Grant - others:European Commission - EC(XE) 313781 Institutional support: RVO:67985556 Keywords : topology optimization * multigrid method s * interior point method Subject RIV: BA - General Mathematics Impact factor: 2.195, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/kocvara-0462418.pdf
Optimal layout of radiological environment monitoring based on TOPSIS method
International Nuclear Information System (INIS)
Li Sufen; Zhou Chunlin
2006-01-01
TOPSIS is a method for multi-objective-decision-making, which can be applied to comprehensive assessment of environmental quality. This paper adopts it to get the optimal layout of radiological environment monitoring, it is proved that this method is a correct, simple and convenient, practical one, and beneficial to supervision departments to scientifically and reasonably layout Radiological Environment monitoring sites. (authors)
Optimization method for quantitative calculation of clay minerals in soil
Indian Academy of Sciences (India)
In this study, an attempt was made to propose an optimization method for the quantitative determination of clay minerals in soil based on bulk chemical composition data. The fundamental principles and processes of the calculation are elucidated. Some samples were used for reliability verification of the method and the ...
Cost optimal river dike design using probabilistic methods
Bischiniotis, K.; Kanning, W.; Jonkman, S.N.
2014-01-01
This research focuses on the optimization of river dikes using probabilistic methods. Its aim is to develop a generic method that automatically estimates the failure probabilities of many river dike cross-sections and gives the one with the least cost, taking into account the boundary conditions and
Directory of Open Access Journals (Sweden)
Mehdi Neshat
2015-11-01
Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.
A solution quality assessment method for swarm intelligence optimization algorithms.
Zhang, Zhaojun; Wang, Gai-Ge; Zou, Kuansheng; Zhang, Jianhua
2014-01-01
Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. It greatly limits the application in practical problems. A solution quality assessment method for intelligent optimization is proposed in this paper. It is an experimental analysis method based on the analysis of search space and characteristic of algorithm itself. Instead of "value performance," the "ordinal performance" is used as evaluation criteria in this method. The feasible solutions were clustered according to distance to divide solution samples into several parts. Then, solution space and "good enough" set can be decomposed based on the clustering results. Last, using relative knowledge of statistics, the evaluation result can be got. To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO), particle swarm optimization (PSO), and artificial fish swarm algorithm (AFS) were taken to solve traveling salesman problem. Computational results indicate the feasibility of proposed method.
A Combined Method in Parameters Optimization of Hydrocyclone
Directory of Open Access Journals (Sweden)
Jing-an Feng
2016-01-01
Full Text Available To achieve efficient separation of calcium hydroxide and impurities in carbide slag by using hydrocyclone, the physical granularity property of carbide slag, hydrocyclone operation parameters for slurry concentration, and the slurry velocity inlet are designed to be optimized. The optimization methods are combined with the Design of Experiment (DOE method and the Computational Fluid Dynamics (CFD method. Based on Design Expert software, the central composite design (CCD with three factors and five levels amounting to five groups of 20 test responses was constructed, and the experiments were performed by numerical simulation software FLUENT. Through the analysis of variance deduced from numerical simulation experiment results, the regression equations of pressure drop, overflow concentration, purity, and separation efficiencies of two solid phases were, respectively, obtained. The influences of factors were analyzed by the responses, respectively. Finally, optimized results were obtained by the multiobjective optimization method through the Design Expert software. Based on the optimized conditions, the validation test by numerical simulation and separation experiment were separately proceeded. The results proved that the combined method could be efficiently used in studying the hydrocyclone and it has a good performance in application engineering.
A Solution Quality Assessment Method for Swarm Intelligence Optimization Algorithms
Directory of Open Access Journals (Sweden)
Zhaojun Zhang
2014-01-01
Full Text Available Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. It greatly limits the application in practical problems. A solution quality assessment method for intelligent optimization is proposed in this paper. It is an experimental analysis method based on the analysis of search space and characteristic of algorithm itself. Instead of “value performance,” the “ordinal performance” is used as evaluation criteria in this method. The feasible solutions were clustered according to distance to divide solution samples into several parts. Then, solution space and “good enough” set can be decomposed based on the clustering results. Last, using relative knowledge of statistics, the evaluation result can be got. To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO, particle swarm optimization (PSO, and artificial fish swarm algorithm (AFS were taken to solve traveling salesman problem. Computational results indicate the feasibility of proposed method.
Methods for Optimizing CRISPR-Cas9 Genome Editing Specificity
Tycko, Josh; Myer, Vic E.; Hsu, Patrick D.
2016-01-01
Summary Advances in the development of delivery, repair, and specificity strategies for the CRISPR-Cas9 genome engineering toolbox are helping researchers understand gene function with unprecedented precision and sensitivity. CRISPR-Cas9 also holds enormous therapeutic potential for the treatment of genetic disorders by directly correcting disease-causing mutations. Although the Cas9 protein has been shown to bind and cleave DNA at off-target sites, the field of Cas9 specificity is rapidly progressing with marked improvements in guide RNA selection, protein and guide engineering, novel enzymes, and off-target detection methods. We review important challenges and breakthroughs in the field as a comprehensive practical guide to interested users of genome editing technologies, highlighting key tools and strategies for optimizing specificity. The genome editing community should now strive to standardize such methods for measuring and reporting off-target activity, while keeping in mind that the goal for specificity should be continued improvement and vigilance. PMID:27494557
A novel optimization method, Gravitational Search Algorithm (GSA), for PWR core optimization
International Nuclear Information System (INIS)
Mahmoudi, S.M.; Aghaie, M.; Bahonar, M.; Poursalehi, N.
2016-01-01
Highlights: • The Gravitational Search Algorithm (GSA) is introduced. • The advantage of GSA is verified in Shekel’s Foxholes. • Reload optimizing in WWER-1000 and WWER-440 cases are performed. • Maximizing K eff , minimizing PPFs and flattening power density is considered. - Abstract: In-core fuel management optimization (ICFMO) is one of the most challenging concepts of nuclear engineering. In recent decades several meta-heuristic algorithms or computational intelligence methods have been expanded to optimize reactor core loading pattern. This paper presents a new method of using Gravitational Search Algorithm (GSA) for in-core fuel management optimization. The GSA is constructed based on the law of gravity and the notion of mass interactions. It uses the theory of Newtonian physics and searcher agents are the collection of masses. In this work, at the first step, GSA method is compared with other meta-heuristic algorithms on Shekel’s Foxholes problem. In the second step for finding the best core, the GSA algorithm has been performed for three PWR test cases including WWER-1000 and WWER-440 reactors. In these cases, Multi objective optimizations with the following goals are considered, increment of multiplication factor (K eff ), decrement of power peaking factor (PPF) and power density flattening. It is notable that for neutronic calculation, PARCS (Purdue Advanced Reactor Core Simulator) code is used. The results demonstrate that GSA algorithm have promising performance and could be proposed for other optimization problems of nuclear engineering field.
Fermentation optimization and antioxidant activities of mycelia ...
African Journals Online (AJOL)
uwerhiavwe
2013-03-13
Mar 13, 2013 ... esculenta mycelia made good use of soybean residues. The optimal media ... volume 10%, temperature 28°C, and fermentation time 56 h. ... seeding media. Soybean residues were used as the base for fermentation medium, with 20 g glucose, 1.5 g MgSO4, 1g KH2PO4 and 1000 ml of water. Soybean ...
Reverse optimization reconstruction method in non-null aspheric interferometry
Zhang, Lei; Liu, Dong; Shi, Tu; Yang, Yongying; Chong, Shiyao; Shen, Yibing; Bai, Jian
2015-10-01
Aspheric non-null test achieves more flexible measurements than the null test. However, the precision calibration for retrace error has always been difficult. A reverse optimization reconstruction (ROR) method is proposed for the retrace error calibration as well as the aspheric figure error extraction based on system modeling. An optimization function is set up with system model, in which the wavefront data from experiment is inserted as the optimization objective while the figure error under test in the model as the optimization variable. The optimization is executed by the reverse ray tracing in the system model until the test wavefront in the model is consistent with the one in experiment. At this point, the surface figure error in the model is considered to be consistent with the one in experiment. With the Zernike fitting, the aspheric surface figure error is then reconstructed in the form of Zernike polynomials. Numerical simulations verifying the high accuracy of the ROR method are presented with error considerations. A set of experiments are carried out to demonstrate the validity and repeatability of ROR method. Compared with the results of Zygo interferometer (null test), the measurement error by the ROR method achieves better than 1/10λ.
Structural Topology Optimization Based on the Smoothed Finite Element Method
Directory of Open Access Journals (Sweden)
Vahid Shobeiri
Full Text Available Abstract In this paper, the smoothed finite element method, incorporated with the level set method, is employed to carry out the topology optimization of continuum structures. The structural compliance is minimized subject to a constraint on the weight of material used. The cell-based smoothed finite element method is employed to improve the accuracy and stability of the standard finite element method. Several numerical examples are presented to prove the validity and utility of the proposed method. The obtained results are compared with those obtained by several standard finite element-based examples in order to access the applicability and effectiveness of the proposed method. The common numerical instabilities of the structural topology optimization problems such as checkerboard pattern and mesh dependency are studied in the examples.
Optimization method for electron beam melting and refining of metals
Donchev, Veliko; Vutova, Katia
2014-03-01
Pure metals and special alloys obtained by electron beam melting and refining (EBMR) in vacuum, using electron beams as a heating source, have a lot of applications in nuclear and airspace industries, electronics, medicine, etc. An analytical optimization problem for the EBMR process based on mathematical heat model is proposed. The used criterion is integral functional minimization of a partial derivative of the temperature in the metal sample. The investigated technological parameters are the electron beam power, beam radius, the metal casting velocity, etc. The optimization problem is discretized using a non-stationary heat model and corresponding adapted Pismen-Rekford numerical scheme, developed by us and multidimensional trapezional rule. Thus a discrete optimization problem is built where the criterion is a function of technological process parameters. The discrete optimization problem is heuristically solved by cluster optimization method. Corresponding software for the optimization task is developed. The proposed optimization scheme can be applied for quality improvement of the pure metals (Ta, Ti, Cu, etc.) produced by the modern and ecological-friendly EBMR process.
METHOD OF CALCULATING THE OPTIMAL HEAT EMISSION GEOTHERMAL WELLS
Directory of Open Access Journals (Sweden)
A. I. Akaev
2015-01-01
Full Text Available This paper presents a simplified method of calculating the optimal regimes of the fountain and the pumping exploitation of geothermal wells, reducing scaling and corrosion during operation. Comparative characteristics to quantify the heat of formation for these methods of operation under the same pressure at the wellhead. The problem is solved graphic-analytical method based on a balance of pressure in the well with the heat pump.
Variable Metric Methods for Unconstrained Optimization and Nonlinear Least Squares
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Spedicato, E.
2000-01-01
Roč. 124, č. 1-2 (2000), s. 61-95 ISSN 0377-0427 R&D Projects: GA ČR GA201/00/0080 Institutional research plan: AV0Z1030915 Keywords : quasi-Newton methods * variable metric methods * unconstrained optimization * nonlinear least squares * sparse problems * partially separable problems * limited-memory methods Subject RIV: BA - General Mathematics Impact factor: 0.455, year: 2000
Optimization of Inventories for Multiple Companies by Fuzzy Control Method
Kawase, Koichi; Konishi, Masami; Imai, Jun
2008-01-01
In this research, Fuzzy control theory is applied to the inventory control of the supply chain between multiple companies. The proposed control method deals with the amountof inventories expressing supply chain between multiple companies. Referring past demand and tardiness, inventory amounts of raw materials are determined by Fuzzy inference. The method that an appropriate inventory control becomes possible optimizing fuzzy control gain by using SA method for Fuzzy control. The variation of ...
Optimization methods and silicon solar cell numerical models
Girardini, K.; Jacobsen, S. E.
1986-01-01
An optimization algorithm for use with numerical silicon solar cell models was developed. By coupling an optimization algorithm with a solar cell model, it is possible to simultaneously vary design variables such as impurity concentrations, front junction depth, back junction depth, and cell thickness to maximize the predicted cell efficiency. An optimization algorithm was developed and interfaced with the Solar Cell Analysis Program in 1 Dimension (SCAP1D). SCAP1D uses finite difference methods to solve the differential equations which, along with several relations from the physics of semiconductors, describe mathematically the performance of a solar cell. A major obstacle is that the numerical methods used in SCAP1D require a significant amount of computer time, and during an optimization the model is called iteratively until the design variables converge to the values associated with the maximum efficiency. This problem was alleviated by designing an optimization code specifically for use with numerically intensive simulations, to reduce the number of times the efficiency has to be calculated to achieve convergence to the optimal solution.
Directory of Open Access Journals (Sweden)
Mojtaba Biglar
2014-01-01
Full Text Available This study addresses new formulation for active vibration control of plates by optimal locations of attached piezotransducers. Free vibrations are solved by Rayleigh-Ritz and transient by assumed modes methods. Optimal orientations of patches are determined by spatial controllability/observability, as well as residual modes to reduce spillover. These criteria are used to achieve optimal fitness function defined for genetic algorithm to find optimal locations. To control vibrations, negative velocity feedback control is designed. Results indicate that, by locating piezopatches at optimal positions, depreciation rate increases and amplitudes of vibrations reduce effectively. The effect of number of piezodevices is analyzed.
Investigation of Optimal Integrated Circuit Raster Image Vectorization Method
Directory of Open Access Journals (Sweden)
Leonas Jasevičius
2011-03-01
Full Text Available Visual analysis of integrated circuit layer requires raster image vectorization stage to extract layer topology data to CAD tools. In this paper vectorization problems of raster IC layer images are presented. Various line extraction from raster images algorithms and their properties are discussed. Optimal raster image vectorization method was developed which allows utilization of common vectorization algorithms to achieve the best possible extracted vector data match with perfect manual vectorization results. To develop the optimal method, vectorized data quality dependence on initial raster image skeleton filter selection was assessed.Article in Lithuanian
Optimal mesh hierarchies in Multilevel Monte Carlo methods
Von Schwerin, Erik
2016-01-08
I will discuss how to choose optimal mesh hierarchies in Multilevel Monte Carlo (MLMC) simulations when computing the expected value of a quantity of interest depending on the solution of, for example, an Ito stochastic differential equation or a partial differential equation with stochastic data. I will consider numerical schemes based on uniform discretization methods with general approximation orders and computational costs. I will compare optimized geometric and non-geometric hierarchies and discuss how enforcing some domain constraints on parameters of MLMC hierarchies affects the optimality of these hierarchies. I will also discuss the optimal tolerance splitting between the bias and the statistical error contributions and its asymptotic behavior. This talk presents joint work with N.Collier, A.-L.Haji-Ali, F. Nobile, and R. Tempone.
Coordinated Optimal Operation Method of the Regional Energy Internet
Directory of Open Access Journals (Sweden)
Rishang Long
2017-05-01
Full Text Available The development of the energy internet has become one of the key ways to solve the energy crisis. This paper studies the system architecture, energy flow characteristics and coordinated optimization method of the regional energy internet. Considering the heat-to-electric ratio of a combined cooling, heating and power unit, energy storage life and real-time electricity price, a double-layer optimal scheduling model is proposed, which includes economic and environmental benefit in the upper layer and energy efficiency in the lower layer. A particle swarm optimizer–individual variation ant colony optimization algorithm is used to solve the computational efficiency and accuracy. Through the calculation and simulation of the simulated system, the energy savings, level of environmental protection and economic optimal dispatching scheme are realized.
Directory of Open Access Journals (Sweden)
Bin He
2014-01-01
Full Text Available In city traffic, it is important to improve transportation efficiency and the spacing of platoon should be shortened when crossing the street. The best method to deal with this problem is automatic control of vehicles. In this paper, a mathematical model is established for the platoon’s longitudinal movement. A systematic analysis of longitudinal control law is presented for the platoon of vehicles. However, the parameter calibration for the platoon model is relatively difficult because the platoon model is complex and the parameters are coupled with each other. In this paper, the particle swarm optimization method is introduced to effectively optimize the parameters of platoon. The proposed method effectively finds the optimal parameters based on simulations and makes the spacing of platoon shorter.
Zheng, Ying; Wang, Shuai; Meng, Xian-Sheng; Bao, Yong-Rui
2013-10-01
To optimize the extraction technology of total flavonoids with antineoplastic activities in Juglans mandshurica, and explore the correlation between total flavonoids and pharmacodynamics indicators. The quantity of antineoplastic components, ratio of extraction and cell inhibition rate were taken as the comprehensive indexes to optimize the main factors that influence the extraction of effective components by orthogonal experiment design. SPSS 17.0 software was used to analyze the Pearson correlation between effective components and pharmacodynamics indexes. The best extracting condition of total flavonoids were as follows: the ratio of 60% ethanol to Juglans mandshurica was 20: 1, extracting for 3 times, each time for 2 hour at 70 degrees C. Flavonoids extraction yield and cell inhibition rate was positively related in the straight line. This study provides a new insight into the optimization of extraction technology for traditional Chinese medicine, and lays a safe and reliable experimental basis for the clinical application of Juglans mandshurica.
Directory of Open Access Journals (Sweden)
Guo-Qiang Zeng
2014-01-01
Full Text Available As a novel evolutionary optimization method, extremal optimization (EO has been successfully applied to a variety of combinatorial optimization problems. However, the applications of EO in continuous optimization problems are relatively rare. This paper proposes an improved real-coded population-based EO method (IRPEO for continuous unconstrained optimization problems. The key operations of IRPEO include generation of real-coded random initial population, evaluation of individual and population fitness, selection of bad elements according to power-law probability distribution, generation of new population based on uniform random mutation, and updating the population by accepting the new population unconditionally. The experimental results on 10 benchmark test functions with the dimension N=30 have shown that IRPEO is competitive or even better than the recently reported various genetic algorithm (GA versions with different mutation operations in terms of simplicity, effectiveness, and efficiency. Furthermore, the superiority of IRPEO to other evolutionary algorithms such as original population-based EO, particle swarm optimization (PSO, and the hybrid PSO-EO is also demonstrated by the experimental results on some benchmark functions.
Pipeline heating method based on optimal control and state estimation
Energy Technology Data Exchange (ETDEWEB)
Vianna, F.L.V. [Dept. of Subsea Technology. Petrobras Research and Development Center - CENPES, Rio de Janeiro, RJ (Brazil)], e-mail: fvianna@petrobras.com.br; Orlande, H.R.B. [Dept. of Mechanical Engineering. POLI/COPPE, Federal University of Rio de Janeiro - UFRJ, Rio de Janeiro, RJ (Brazil)], e-mail: helcio@mecanica.ufrj.br; Dulikravich, G.S. [Dept. of Mechanical and Materials Engineering. Florida International University - FIU, Miami, FL (United States)], e-mail: dulikrav@fiu.edu
2010-07-01
In production of oil and gas wells in deep waters the flowing of hydrocarbon through pipeline is a challenging problem. This environment presents high hydrostatic pressures and low sea bed temperatures, which can favor the formation of solid deposits that in critical operating conditions, as unplanned shutdown conditions, may result in a pipeline blockage and consequently incur in large financial losses. There are different methods to protect the system, but nowadays thermal insulation and chemical injection are the standard solutions normally used. An alternative method of flow assurance is to heat the pipeline. This concept, which is known as active heating system, aims at heating the produced fluid temperature above a safe reference level in order to avoid the formation of solid deposits. The objective of this paper is to introduce a Bayesian statistical approach for the state estimation problem, in which the state variables are considered as the transient temperatures within a pipeline cross-section, and to use the optimal control theory as a design tool for a typical heating system during a simulated shutdown condition. An application example is presented to illustrate how Bayesian filters can be used to reconstruct the temperature field from temperature measurements supposedly available on the external surface of the pipeline. The temperatures predicted with the Bayesian filter are then utilized in a control approach for a heating system used to maintain the temperature within the pipeline above the critical temperature of formation of solid deposits. The physical problem consists of a pipeline cross section represented by a circular domain with four points over the pipe wall representing heating cables. The fluid is considered stagnant, homogeneous, isotropic and with constant thermo-physical properties. The mathematical formulation governing the direct problem was solved with the finite volume method and for the solution of the state estimation problem
Production, optimization, characterization and antifungal activity of ...
African Journals Online (AJOL)
SAM
2014-04-02
Apr 2, 2014 ... the present study, the antifungal activity of crude A. terrus chitinase was investigated against Apergillus niger, Aspergillus oryzae .... Chitinase activity was determined spectrophotometrically by estimating the amount of ..... characterization of two. Bifunctional chitinases lysozyme extracellularly produced by.
Topology optimization of hyperelastic structures using a level set method
Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.
2017-12-01
Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.
Panorama parking assistant system with improved particle swarm optimization method
Cheng, Ruzhong; Zhao, Yong; Li, Zhichao; Jiang, Weigang; Wang, Xin'an; Xu, Yong
2013-10-01
A panorama parking assistant system (PPAS) for the automotive aftermarket together with a practical improved particle swarm optimization method (IPSO) are proposed in this paper. In the PPAS system, four fisheye cameras are installed in the vehicle with different views, and four channels of video frames captured by the cameras are processed as a 360-deg top-view image around the vehicle. Besides the embedded design of PPAS, the key problem for image distortion correction and mosaicking is the efficiency of parameter optimization in the process of camera calibration. In order to address this problem, an IPSO method is proposed. Compared with other parameter optimization methods, the proposed method allows a certain range of dynamic change for the intrinsic and extrinsic parameters, and can exploit only one reference image to complete all of the optimization; therefore, the efficiency of the whole camera calibration is increased. The PPAS is commercially available, and the IPSO method is a highly practical way to increase the efficiency of the installation and the calibration of PPAS in automobile 4S shops.
Activity based costing method
Directory of Open Access Journals (Sweden)
Èuchranová Katarína
2001-06-01
Full Text Available Activity based costing is a method of identifying and tracking the operating costs directly associated with processing items. It is the practice of focusing on some unit of output, such as a purchase order or an assembled automobile and attempting to determine its total as precisely as poccible based on the fixed and variable costs of the inputs.You use ABC to identify, quantify and analyze the various cost drivers (such as labor, materials, administrative overhead, rework. and to determine which ones are candidates for reduction.A processes any activity that accepts inputs, adds value to these inputs for customers and produces outputs for these customers. The customer may be either internal or external to the organization. Every activity within an organization comprimes one or more processes. Inputs, controls and resources are all supplied to the process.A process owner is the person responsible for performing and or controlling the activity.The direction of cost through their contact to partial activity and processes is a new modern theme today. Beginning of this method is connected with very important changes in the firm processes.ABC method is a instrument , that bring a competitive advantages for the firm.
Control and Optimization Methods for Electric Smart Grids
Ilić, Marija
2012-01-01
Control and Optimization Methods for Electric Smart Grids brings together leading experts in power, control and communication systems,and consolidates some of the most promising recent research in smart grid modeling,control and optimization in hopes of laying the foundation for future advances in this critical field of study. The contents comprise eighteen essays addressing wide varieties of control-theoretic problems for tomorrow’s power grid. Topics covered include: Control architectures for power system networks with large-scale penetration of renewable energy and plug-in vehicles Optimal demand response New modeling methods for electricity markets Control strategies for data centers Cyber-security Wide-area monitoring and control using synchronized phasor measurements. The authors present theoretical results supported by illustrative examples and practical case studies, making the material comprehensible to a wide audience. The results reflect the exponential transformation that today’s grid is going...
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods
Directory of Open Access Journals (Sweden)
Philippe Loubaton
2012-11-01
Full Text Available This paper provides a comprehensive introduction of large random matrix methods for input covariance matrix optimization of mutual information of MIMO systems. It is first recalled informally how large system approximations of mutual information can be derived. Then, the optimization of the approximations is discussed, and important methodological points that are not necessarily covered by the existing literature are addressed, including the strict concavity of the approximation, the structure of the argument of its maximum, the accuracy of the large system approach with regard to the number of antennas, or the justification of iterative water-filling optimization algorithms. While the existing papers have developed methods adapted to a specific model, this contribution tries to provide a unified view of the large system approximation approach.
International Nuclear Information System (INIS)
Lee, Seung Min; Kim, Jong Hyun; Kim, Man Cheol; Seong, Poong Hyun
2016-01-01
Highlights: • We propose an appropriate automation rate that enables the best human performance. • We analyze the shortest working time considering Situation Awareness Recovery (SAR). • The optimized automation rate is estimated by integrating the automation and ostracism rate estimation methods. • The process to derive the optimized automation rate is demonstrated through case studies. - Abstract: Automation has been introduced in various industries, including the nuclear field, because it is commonly believed that automation promises greater efficiency, lower workloads, and fewer operator errors through reducing operator errors and enhancing operator and system performance. However, the excessive introduction of automation has deteriorated operator performance due to the side effects of automation, which are referred to as Out-of-the-Loop (OOTL), and this is critical issue that must be resolved. Thus, in order to determine the optimal level of automation introduction that assures the best human operator performance, a quantitative method of optimizing the automation is proposed in this paper. In order to propose the optimization method for determining appropriate automation levels that enable the best human performance, the automation rate and ostracism rate, which are estimation methods that quantitatively analyze the positive and negative effects of automation, respectively, are integrated. The integration was conducted in order to derive the shortest working time through considering the concept of situation awareness recovery (SAR), which states that the automation rate with the shortest working time assures the best human performance. The process to derive the optimized automation rate is demonstrated through an emergency operation scenario-based case study. In this case study, four types of procedures are assumed through redesigning the original emergency operating procedure according to the introduced automation and ostracism levels. Using the
Practical inventory routing: A problem definition and an optimization method
Geiger, Martin Josef; Sevaux, Marc
2011-01-01
The global objective of this work is to provide practical optimization methods to companies involved in inventory routing problems, taking into account this new type of data. Also, companies are sometimes not able to deal with changing plans every period and would like to adopt regular structures for serving customers.
Applying the Taguchi method for optimized fabrication of bovine ...
African Journals Online (AJOL)
The objective of the present study was to optimize the fabrication of bovine serum albumin (BSA) nanoparticle by applying the Taguchi method with characterization of the nanoparticle bioproducts. BSA nanoparticles have been extensively studied in our previous works as suitable carrier for drug delivery, since they are ...
Response surface method to optimize the low cost medium for ...
African Journals Online (AJOL)
A protease producing Bacillus sp. GA CAS10 was isolated from ascidian Phallusia arabica, Tuticorin, Southeast coast of India. Response surface methodology was employed for the optimization of different nutritional and physical factors for the production of protease. Plackett-Burman method was applied to identify ...
Optimization Methods in Operations Research and Systems Analysis
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 6. Optimization Methods in Operations Research and Systems Analysis. V G Tikekar. Book Review Volume 2 Issue 6 June 1997 pp 91-92. Fulltext. Click here to view fulltext PDF. Permanent link:
Adaptive optimization for active queue management supporting TCP flows
Baldi, S.; Kosmatopoulos, Elias B.; Pitsillides, Andreas; Lestas, Marios; Ioannou, Petros A.; Wan, Y.; Chiu, George; Johnson, Katie; Abramovitch, Danny
2016-01-01
An adaptive decentralized strategy for active queue management of TCP flows over communication networks is presented. The proposed strategy solves locally, at each link, an optimal control problem, minimizing a cost composed of residual capacity and buffer queue size. The solution of the optimal
Error Estimates for Approximate Optimization by the Extended Ritz Method
Czech Academy of Sciences Publication Activity Database
Kůrková, Věra; Sanguineti, M.
2005-01-01
Roč. 15, č. 2 (2005), s. 461-487 ISSN 1052-6234 R&D Projects: GA ČR GA201/02/0428 Institutional research plan: CEZ:AV0Z10300504 Keywords : functional optimization * rates of convergence of suboptimal solutions * (extended) Ritz method * curse of dimensionality * convex best approximation problems * learning from data by kernel methods Subject RIV: BA - General Mathematics Impact factor: 1.238, year: 2005
Hybrid robust predictive optimization method of power system dispatch
Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY
2011-08-02
A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.
Optimization strategies of in-tube extraction (ITEX) methods
Laaks, Jens; Jochmann, Maik A.; Schilling, Beat; Schmidt, Torsten C.
2015-01-01
Microextraction techniques, especially dynamic techniques like in-tube extraction (ITEX), can require an extensive method optimization procedure. This work summarizes the experiences from several methods and gives recommendations for the setting of proper extraction conditions to minimize experimental effort. Therefore, the governing parameters of the extraction and injection stages are discussed. This includes the relative extraction efficiencies of 11 kinds of sorbent tubes, either commerci...
Exergetic optimization of a thermoacoustic engine using the particle swarm optimization method
International Nuclear Information System (INIS)
Chaitou, Hussein; Nika, Philippe
2012-01-01
Highlights: ► Optimization of a thermoacoustic engine using the particle swarm optimization method. ► Exergetic efficiency, acoustic power and their product are the optimized functions. ► PSO method is used successfully for the first time in the TA research. ► The powerful PSO tool is advised to be more involved in the TA research and design. ► EE times AP optimized function is highly recommended to design any new TA devices. - Abstract: Thermoacoustic engines convert heat energy into acoustic energy. Then, the acoustic energy can be used to pump heat or to generate electricity. It is well-known that the acoustic energy and therefore the exergetic efficiency depend on parameters such as the stack’s hydraulic radius, the stack’s position in the resonator and the traveling–standing-wave ratio. In this paper, these three parameters are investigated in order to study and analyze the best value of the produced acoustic energy, the exergetic efficiency and the product of the acoustic energy by the exergetic efficiency of a thermoacoustic engine with a parallel-plate stack. The dimensionless expressions of the thermoacoustic equations are derived and calculated. Then, the Particle Swarm Optimization method (PSO) is introduced and used for the first time in the thermoacoustic research. The use of the PSO method and the optimization of the acoustic energy multiplied by the exergetic efficiency are novel contributions to this domain of research. This paper discusses some significant conclusions which are useful for the design of new thermoacoustic engines.
International Nuclear Information System (INIS)
Alavi, Seyed Arash; Ahmadian, Ali; Aliakbar-Golkar, Masoud
2015-01-01
Highlights: • Energy management is necessary in the active distribution network to reduce operation costs. • Uncertainty modeling is essential in energy management studies in active distribution networks. • Point estimate method is a suitable method for uncertainty modeling due to its lower computation time and acceptable accuracy. • In the absence of Probability Distribution Function (PDF) robust optimization has a good ability for uncertainty modeling. - Abstract: Uncertainty can be defined as the probability of difference between the forecasted value and the real value. As this probability is small, the operation cost of the power system will be less. This purpose necessitates modeling of system random variables (such as the output power of renewable resources and the load demand) with appropriate and practicable methods. In this paper, an adequate procedure is proposed in order to do an optimal energy management on a typical micro-grid with regard to the relevant uncertainties. The point estimate method is applied for modeling the wind power and solar power uncertainties, and robust optimization technique is utilized to model load demand uncertainty. Finally, a comparison is done between deterministic and probabilistic management in different scenarios and their results are analyzed and evaluated
International Nuclear Information System (INIS)
Gao, Hao
2016-01-01
For the treatment planning during intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT), beam fluence maps can be first optimized via fluence map optimization (FMO) under the given dose prescriptions and constraints to conformally deliver the radiation dose to the targets while sparing the organs-at-risk, and then segmented into deliverable MLC apertures via leaf or arc sequencing algorithms. This work is to develop an efficient algorithm for FMO based on alternating direction method of multipliers (ADMM). Here we consider FMO with the least-square cost function and non-negative fluence constraints, and its solution algorithm is based on ADMM, which is efficient and simple-to-implement. In addition, an empirical method for optimizing the ADMM parameter is developed to improve the robustness of the ADMM algorithm. The ADMM based FMO solver was benchmarked with the quadratic programming method based on the interior-point (IP) method using the CORT dataset. The comparison results suggested the ADMM solver had a similar plan quality with slightly smaller total objective function value than IP. A simple-to-implement ADMM based FMO solver with empirical parameter optimization is proposed for IMRT or VMAT. (paper)
Azmi, Nur Iffah Mohamed; Arifin Mat Piah, Kamal; Yusoff, Wan Azhar Wan; Romlay, Fadhlur Rahman Mohd
2018-03-01
Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey- Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the particle velocity limit and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO- PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Furthermore, the physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning method responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a tuning method in the hydraulic positioning system.
The optimal extraction parameters and anti-diabetic activity of ...
African Journals Online (AJOL)
diabetic activity of FIBL on alloxan induced diabetic mice were studied. The optimal extraction parameters of FIBL were obtained by single factor test and orthogonal test, as follows: ethanol concentration 60 %, ratio of solvent to raw material 30 ...
Mathematical programming methods for large-scale topology optimization problems
DEFF Research Database (Denmark)
Rojas Labanda, Susana
for the classical minimum compliance problem. Two of the state-of-the-art optimization algorithms are investigated and implemented for this structural topology optimization problem. A Sequential Quadratic Programming (TopSQP) and an interior point method (TopIP) are developed exploiting the specific mathematical...... structure of the problem. In both solvers, information of the exact Hessian is considered. A robust iterative method is implemented to efficiently solve large-scale linear systems. Both TopSQP and TopIP have successful results in terms of convergence, number of iterations, and objective function values....... Thanks to the use of the iterative method implemented, TopIP is able to solve large-scale problems with more than three millions degrees of freedom....
A Survey of Methods for Gas-Lift Optimization
Directory of Open Access Journals (Sweden)
Kashif Rashid
2012-01-01
Full Text Available This paper presents a survey of methods and techniques developed for the solution of the continuous gas-lift optimization problem over the last two decades. These range from isolated single-well analysis all the way to real-time multivariate optimization schemes encompassing all wells in a field. While some methods are clearly limited due to their neglect of treating the effects of inter-dependent wells with common flow lines, other methods are limited due to the efficacy and quality of the solution obtained when dealing with large-scale networks comprising hundreds of difficult to produce wells. The aim of this paper is to provide an insight into the approaches developed and to highlight the challenges that remain.
The construction of optimal stated choice experiments theory and methods
Street, Deborah J
2007-01-01
The most comprehensive and applied discussion of stated choice experiment constructions available The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making. Many aspects of the design of a generic stated choice experiment are independent of its area of application, and until now there has been no single book describing these constructions. This book begins with a brief description of the various areas where stated choice experiments are applicable, including marketing and health economics, transportation, environmental resource economics, and public welfare analysis. The authors focus on recent research results on the construction of optimal and near-optimal choice experiments and conclude with guidelines and insight on how to properly implement these results. Features of the book include: Construction of generic stated choice experiments for the estimation of main effects...
Systematic method for optimizing plutonium transmutation in LWRs
Sorensen, Reuben T.
We have developed the Systematic Reactor Optimization in 2-Dimensions (SRO2D) code to maximize the transmutation of plutonium in light water reactors (LWRs). The necessary conditions for optimal fuel and burnable absorber loadings are obtained with Pontryagin's maximum principle and a direct adjoining approach to explicitly account for a power peaking inequality constraint. The resulting set of coupled system, Euler-Lagrange (E-L), and optimality equations are solved iteratively with the method of conjugate gradients until no further improvement is achieved in the objective function. To satisfy the power peaking inequality constraint throughout the operating cycle we have employed a backwards diffusion theory (BDT) technique as part of the conjugate gradient optimization package. The BDT approach establishes a relationship between the burnable absorber loading and the power distribution during the cycle, such that constraint violations are reduced with each conjugate gradient iteration and eventually eliminated. Our in-core optimization methodology has been implemented in the SRO2D code, assuming two-group, two-dimensional neutron diffusion theory. The system equations are solved in a quasi-static fashion forward in time from beginning-of-cycle (BOC) to end-of-cycle (EOC), while the E-L equations are solved backwards in time from EOC to BOC to reflect the adjoint nature of the Lagrange multipliers. Cycle length extension calculations of a first cycle AP600 plant verify our implementation effort, yielding a nearly identical loading pattern to that issued by Westinghouse in the AP600 Safety Analysis Report. Utilizing a self-generated Pu recycling mode, our in-core optimization methodology is coupled with an equilibrium cycle methodology to arrive at an optimized asymptotic Pu inventory and composition. Beginning with a poor loading pattern, our LWR optimization package improves the core performance by reducing the maximum power peaking factor from 2.0 to 1
Optimal treatment cost allocation methods in pollution control
International Nuclear Information System (INIS)
Chen Wenying; Fang Dong; Xue Dazhi
1999-01-01
Total emission control is an effective pollution control strategy. However, Chinese application of total emission control lacks reasonable and fair methods for optimal treatment cost allocation, a critical issue in total emission control. The author considers four approaches to allocate treatment costs. The first approach is to set up a multiple-objective planning model and to solve the model using the shortest distance ideal point method. The second approach is to define degree of satisfaction for cost allocation results for each polluter and to establish a method based on this concept. The third is to apply bargaining and arbitration theory to develop a model. The fourth is to establish a cooperative N-person game model which can be solved using the Shapley value method, the core method, the Cost Gap Allocation method or the Minimum Costs-Remaining Savings method. These approaches are compared using a practicable case study
Ludwig, T; Kern, P; Bongards, M; Wolf, C
2011-01-01
The optimization of relaxation and filtration times of submerged microfiltration flat modules in membrane bioreactors used for municipal wastewater treatment is essential for efficient plant operation. However, the optimization and control of such plants and their filtration processes is a challenging problem due to the underlying highly nonlinear and complex processes. This paper presents the use of genetic algorithms for this optimization problem in conjunction with a fully calibrated simulation model, as computational intelligence methods are perfectly suited to the nonconvex multi-objective nature of the optimization problems posed by these complex systems. The simulation model is developed and calibrated using membrane modules from the wastewater simulation software GPS-X based on the Activated Sludge Model No.1 (ASM1). Simulation results have been validated at a technical reference plant. They clearly show that filtration process costs for cleaning and energy can be reduced significantly by intelligent process optimization.
International Nuclear Information System (INIS)
Berthiau, G.
1995-10-01
The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistors geometries ...) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient times ...). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyper-rectangular domain ; equality constraints can be eventually specified. A similar problem consists in fitting component models. In this way, the optimization variables are the model parameters and one aims at minimizing a cost function built on the error between the model response and the data measured on the component. The chosen optimization method for this kind of problem is the simulated annealing method. This method, provided by the combinatorial optimization domain, has been adapted and compared with other global optimization methods for the continuous variables problems. An efficient strategy of variables discretization and a set of complementary stopping criteria have been proposed. The different parameters of the method have been adjusted with analytical functions of which minima are known, classically used in the literature. Our simulated annealing algorithm has been coupled with an open electrical simulator SPICE-PAC of which the modular structure allows the chaining of simulations required by the circuit optimization process. We proposed, for high-dimensional problems, a partitioning technique which ensures proportionality between CPU-time and variables number. To compare our method with others, we have adapted three other methods coming from combinatorial optimization domain - the threshold method, a genetic algorithm and the Tabu search method - The tests have been performed on the same set of test functions and the results allow a first comparison between these methods applied to continuous optimization variables. Finally, our simulated annealing program
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.
GENERALIZED INVERSE INTERVAL METHOD OF GLOBAL CONSTRAINED OPTIMIZATION
Directory of Open Access Journals (Sweden)
A. V. Panteleyev
2014-01-01
Full Text Available The algorithmic and program software of inverse interval method for global constrained optimization are considered. The solution of model examples and the proof of the theorems of the algorithm’s convergence are presented. The generalized scheme of developed algorithms has been created. This scheme has two replaceable modules of compression and check. This module approach allows the users to implement their own versions of the algorithm without loss of the method convergence. This will help to tune the method according to the characteristics of the current problem.
Optimal interpolation method for intercomparison of atmospheric measurements.
Ridolfi, Marco; Ceccherini, Simone; Carli, Bruno
2006-04-01
Intercomparison of atmospheric measurements is often a difficult task because of the different spatial response functions of the experiments considered. We propose a new method for comparison of two atmospheric profiles characterized by averaging kernels with different vertical resolutions. The method minimizes the smoothing error induced by the differences in the averaging kernels by exploiting an optimal interpolation rule to map one profile into the retrieval grid of the other. Compared with the techniques published so far, this method permits one to retain the vertical resolution of the less-resolved profile involved in the intercomparison.
Maximum gradient method for optimization of some reactor operating parameters
International Nuclear Information System (INIS)
Miasnikov, A.
1976-03-01
The method and the algorithm ensuing therefrom are described for the determination of the optimum operating state of a reactor. The optimum operating state is considered to be the extreme of the selected functional of the radial power distribution. The functional extreme is determined numerically, using a method which is one of the possible variants of the maximum gradient method. The radial distribution of the neutron absorption in regulating rods and the fuel element burnup are considered to be the variable parameters used in the optimization. (author)
Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis
Directory of Open Access Journals (Sweden)
Sen Zhang
2015-01-01
Full Text Available One heuristic evolutionary algorithm recently proposed is the grey wolf optimizer (GWO, inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature. This paper presents an extended GWO algorithm based on Powell local optimization method, and we call it PGWO. PGWO algorithm significantly improves the original GWO in solving complex optimization problems. Clustering is a popular data analysis and data mining technique. Hence, the PGWO could be applied in solving clustering problems. In this study, first the PGWO algorithm is tested on seven benchmark functions. Second, the PGWO algorithm is used for data clustering on nine data sets. Compared to other state-of-the-art evolutionary algorithms, the results of benchmark and data clustering demonstrate the superior performance of PGWO algorithm.
Developing Automatic Multi-Objective Optimization Methods for Complex Actuators
Directory of Open Access Journals (Sweden)
CHIS, R.
2017-11-01
Full Text Available This paper presents the analysis and multiobjective optimization of a magnetic actuator. By varying just 8 parameters of the magnetic actuator’s model the design space grows to more than 6 million configurations. Much more, the 8 objectives that must be optimized are conflicting and generate a huge objectives space, too. To cope with this complexity, we use advanced heuristic methods for Automatic Design Space Exploration. FADSE tool is one Automatic Design Space Exploration framework including different state of the art multi-objective meta-heuristics for solving NP-hard problems, which we used for the analysis and optimization of the COMSOL and MATLAB model of the magnetic actuator. We show that using a state of the art genetic multi-objective algorithm, response surface modelling methods and some machine learning techniques, the timing complexity of the design space exploration can be reduced, while still taking into consideration objective constraints so that various Pareto optimal configurations can be found. Using our developed approach, we were able to decrease the simulation time by at least a factor of 10, compared to a run that does all the simulations, while keeping prediction errors to around 1%.
Fermentation optimization and antioxidant activities of mycelia ...
African Journals Online (AJOL)
The mycelia polysaccharides from Morchella esculenta are active ingredients in a number of medicines that play important roles in immunity improvement and tumor growth inhibition. So far, the production of polysaccharides from M. esculenta mycelia has not been commercialized. The aims of this work were to screen and ...
bacteriocin activity of lactobacilli: characterization and optimization ...
African Journals Online (AJOL)
Jude Adeleke
Lactobacillus plantarum F1 and L. brevis OG1 isolated from Nigerian fermented food products, produced bacteriocins that had broad spectrum of inhibition against both pathogenic, food spoilage organisms and various lactic acid bacteria. The test organisms exhibited activities of 6400 and 3200. AU/ml respectively against ...
Design of large Francis turbine using optimal methods
International Nuclear Information System (INIS)
Flores, E; Bornard, L; Tomas, L; Couston, M; Liu, J
2012-01-01
Among a high number of Francis turbine references all over the world, covering the whole market range of heads, Alstom has especially been involved in the development and equipment of the largest power plants in the world : Three Gorges (China −32×767 MW - 61 to 113 m), Itaipu (Brazil- 20x750 MW - 98.7m to 127m) and Xiangjiaba (China - 8x812 MW - 82.5m to 113.6m - in erection). Many new projects are under study to equip new power plants with Francis turbines in order to answer an increasing demand of renewable energy. In this context, Alstom Hydro is carrying out many developments to answer those needs, especially for jumbo units such the planned 1GW type units in China. The turbine design for such units requires specific care by using the state of the art in computation methods and the latest technologies in model testing as well as the maximum feedback from operation of Jumbo plants already in operation. We present in this paper how a large Francis turbine can be designed using specific design methods, including the global and local optimization methods. The design of the spiral case, the tandem cascade profiles, the runner and the draft tube are designed with optimization loops involving a blade design tool, an automatic meshing software and a Navier-Stokes solver, piloted by a genetic algorithm. These automated optimization methods, presented in different papers over the last decade, are nowadays widely used, thanks to the growing computation capacity of the HPC clusters: the intensive use of such optimization methods at the turbine design stage allows to reach very high level of performances, while the hydraulic flow characteristics are carefully studied over the whole water passage to avoid any unexpected hydraulic phenomena.
Design of large Francis turbine using optimal methods
Flores, E.; Bornard, L.; Tomas, L.; Liu, J.; Couston, M.
2012-11-01
Among a high number of Francis turbine references all over the world, covering the whole market range of heads, Alstom has especially been involved in the development and equipment of the largest power plants in the world : Three Gorges (China -32×767 MW - 61 to 113 m), Itaipu (Brazil- 20x750 MW - 98.7m to 127m) and Xiangjiaba (China - 8x812 MW - 82.5m to 113.6m - in erection). Many new projects are under study to equip new power plants with Francis turbines in order to answer an increasing demand of renewable energy. In this context, Alstom Hydro is carrying out many developments to answer those needs, especially for jumbo units such the planned 1GW type units in China. The turbine design for such units requires specific care by using the state of the art in computation methods and the latest technologies in model testing as well as the maximum feedback from operation of Jumbo plants already in operation. We present in this paper how a large Francis turbine can be designed using specific design methods, including the global and local optimization methods. The design of the spiral case, the tandem cascade profiles, the runner and the draft tube are designed with optimization loops involving a blade design tool, an automatic meshing software and a Navier-Stokes solver, piloted by a genetic algorithm. These automated optimization methods, presented in different papers over the last decade, are nowadays widely used, thanks to the growing computation capacity of the HPC clusters: the intensive use of such optimization methods at the turbine design stage allows to reach very high level of performances, while the hydraulic flow characteristics are carefully studied over the whole water passage to avoid any unexpected hydraulic phenomena.
METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and
System and method of cylinder deactivation for optimal engine torque-speed map operation
Sujan, Vivek A; Frazier, Timothy R; Follen, Kenneth; Moon, Suk-Min
2014-11-11
This disclosure provides a system and method for determining cylinder deactivation in a vehicle engine to optimize fuel consumption while providing the desired or demanded power. In one aspect, data indicative of terrain variation is utilized in determining a vehicle target operating state. An optimal active cylinder distribution and corresponding fueling is determined from a recommendation from a supervisory agent monitoring the operating state of the vehicle of a subset of the total number of cylinders, and a determination as to which number of cylinders provides the optimal fuel consumption. Once the optimal cylinder number is determined, a transmission gear shift recommendation is provided in view of the determined active cylinder distribution and target operating state.
Optimization of instrumental activation analysis conditions
International Nuclear Information System (INIS)
Guinn, V.; Gavrilas-Guinn, M.
1993-01-01
In instrumental neutron activation analysis (INAA) work, a good commonsense rule of thumb is that the opium conditions for the measurement of any induced activity, in a multi-element sample matrix, are an irradiation time, a decay time, and a counting time each approximately equal to the half-life of the radionuclide (if feasible). The INAA Advance Computer Program (APCP) was used to test this rule on ten reference materials. For the 280 radionuclide/material combinations traced through all 14 APCP condition sets, the rule predicted the best set for 67% of them, was off by one set for 31% of them, and was only off by two sets of 2% of them. (author) 6 refs.; 1 fig.; 3 tabs
Directory of Open Access Journals (Sweden)
Jin-Wen Shen
2013-01-01
Full Text Available Culture conditions for exopolysaccharide (EPS production by Pleurotus pulmonarius in submerged culture are optimized. The suggested medium composition was as follows: 60 g/L of xylose, 6 g/L of soy extract, 5 mM of KH2PO4 and 5 mM of MgSO4. Under the optimized culture conditions in a 5-litre stirred tank fermentor, the maximum concentration of EPS was 6.36 g/L. Furthermore, the morphological parameters (i.e. average diameter, circularity, roughness and compactness of the pellets and the broth viscosity are characterized. It has been proven that mycelial morphology and broth viscosity may be the critical parameters affecting the EPS yield. After deproteinization using Sevag method, a group of EPS (designated as fraction was obtained from the culture filtrates by gel filtration chromatography. FT-IR analysis of the purified EPS revealed prominent characteristic groups corresponding to polyhydric alcohols. GC analysis showed that the purified EPS were mainly composed of galactose and glucose. Furthermore, thermogravimetric analysis indicated that the degradation temperature of the purified EPS was 217 °C. Finally, the antioxidant activity of the EPS fraction was investigated and the relationship with molecular properties was discussed as well.
Optimal and adaptive methods of processing hydroacoustic signals (review)
Malyshkin, G. S.; Sidel'nikov, G. B.
2014-09-01
Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.
Experimental methods for the analysis of optimization algorithms
Bartz-Beielstein, Thomas; Paquete, Luis; Preuss, Mike
2010-01-01
In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on diffe
A seismic fault recognition method based on ant colony optimization
Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong
2018-05-01
Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.
New design method for valves internals, to optimize process
Energy Technology Data Exchange (ETDEWEB)
Jorge, Leonardo [PDVSA (Venezuela)
2011-07-01
In the heavy oil industry, various methods can be used to reduce the viscosity of oil, one of them being the injection of diluent. This method is commonly used in the Orinoco oil belt but it requires good control of the volume of diluent injected as well as the gas flow to optimize production; thus flow control valves need to be accurate. A new valve with a new method was designed with the characteristic of being very reliable and was then bench tested and compared with the other commercially available valves. Results showed better repeatability, accuracy and reliability with lower maintenance for the new method. The use of this valve provides significant savings while distributing the exact amount of fluids; up to date a less than 2% failure rate has been recorded in the field. The new method developed demonstrated impressive performance and PDVSA has decided to use it in mass.
Comparison of optimization methods for electronic-structure calculations
International Nuclear Information System (INIS)
Garner, J.; Das, S.G.; Min, B.I.; Woodward, C.; Benedek, R.
1989-01-01
The performance of several local-optimization methods for calculating electronic structure is compared. The fictitious first-order equation of motion proposed by Williams and Soler is integrated numerically by three procedures: simple finite-difference integration, approximate analytical integration (the Williams-Soler algorithm), and the Born perturbation series. These techniques are applied to a model problem for which exact solutions are known, the Mathieu equation. The Williams-Soler algorithm and the second Born approximation converge equally rapidly, but the former involves considerably less computational effort and gives a more accurate converged solution. Application of the method of conjugate gradients to the Mathieu equation is discussed
Optimization in engineering sciences approximate and metaheuristic methods
Stefanoiu, Dan; Popescu, Dumitru; Filip, Florin Gheorghe; El Kamel, Abdelkader
2014-01-01
The purpose of this book is to present the main metaheuristics and approximate and stochastic methods for optimization of complex systems in Engineering Sciences. It has been written within the framework of the European Union project ERRIC (Empowering Romanian Research on Intelligent Information Technologies), which is funded by the EU's FP7 Research Potential program and has been developed in co-operation between French and Romanian teaching researchers. Through the principles of various proposed algorithms (with additional references) this book allows the reader to explore various methods o
A discrete optimization method for nuclear fuel management
International Nuclear Information System (INIS)
Argaud, J.P.
1993-04-01
Nuclear loading pattern elaboration can be seen as a combinational optimization problem of tremendous size and with non-linear cost-functions, and search are always numerically expensive. After a brief introduction of the main aspects of nuclear fuel management, this paper presents a new idea to treat the combinational problem by using informations included in the gradient of a cost function. The method is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method, and finally, connections with simulated annealing and genetic algorithms are described as an attempt to improve search processes
Kernel method for clustering based on optimal target vector
International Nuclear Information System (INIS)
Angelini, Leonardo; Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano
2006-01-01
We introduce Ising models, suitable for dichotomic clustering, with couplings that are (i) both ferro- and anti-ferromagnetic (ii) depending on the whole data-set and not only on pairs of samples. Couplings are determined exploiting the notion of optimal target vector, here introduced, a link between kernel supervised and unsupervised learning. The effectiveness of the method is shown in the case of the well-known iris data-set and in benchmarks of gene expression levels, where it works better than existing methods for dichotomic clustering
Multi-objective Design Method for Hybrid Active Power Filter
Yu, Jingrong; Deng, Limin; Liu, Maoyun; Qiu, Zhifeng
2017-10-01
In this paper, a multi-objective optimal design for transformerless hybrid active power filter (HAPF) is proposed. The interactions between the active and passive circuits is analyzed, and by taking the interactions into consideration, a three-dimensional objective problem comprising of performance, efficiency and cost of HAPF system is formulated. To deal with the multiple constraints and the strong coupling characteristics of the optimization model, a novel constraint processing mechanism based on distance measurement and adaptive penalty function is presented. In order to improve the diversity of optimal solution and the local searching ability of the particle swarm optimization (PSO) algorithm, a chaotic mutation operator based on multistage neighborhood is proposed. The simulation results show that the optimums near the ordinate origin of the three-dimension space make better tradeoff among the performance, efficiency and cost of HAPF, and the experimental results of transformerless HAPF verify the effectiveness of the method for multi-objective optimization and design.
Optimization of lead (ii) ions adsorption on to chemically activated ...
African Journals Online (AJOL)
The adsorption of Lead (II) ion on to chemically activated carbon has been studied and optimized in a batch reactor system. The zinc chloride impregnated sugarcane bagasse was thermal activated in a fixed bed reactor in the presence of argon gas. The surface morphology, surface functional group and thermal stability ...
A new placement optimization method for viscoelastic dampers: Energy dissipation method
Qu, Ji-Ting
2012-09-01
A new mathematic model of location optimization for viscoelastic dampers is established through energy analysis based on force analogy method. Three working conditions (three lower limits of the new location index) as well as four ground motions are considered in this study, using MATLAB and SAP2000 in programming and verifying. This paper deals with the optimal placement of viscoelastic dampers and step-by-step time history analyses are carried out. Numerical analysis is illustrated to verify the effectiveness and feasibility of the new mathematic model for structural control. In addition, not only the optimal placement method using force analogy method can confirm dampers' locations all at once and be accurate to each span, but also it is without circular calculating. At last, a few helpful conclusions on viscoelastic dampers' optimal placement are made.
Optimization strategies of in-tube extraction (ITEX) methods.
Laaks, Jens; Jochmann, Maik A; Schilling, Beat; Schmidt, Torsten C
2015-09-01
Microextraction techniques, especially dynamic techniques like in-tube extraction (ITEX), can require an extensive method optimization procedure. This work summarizes the experiences from several methods and gives recommendations for the setting of proper extraction conditions to minimize experimental effort. Therefore, the governing parameters of the extraction and injection stages are discussed. This includes the relative extraction efficiencies of 11 kinds of sorbent tubes, either commercially available or custom made, regarding 53 analytes from different classes of compounds. They cover aromatics, heterocyclic aromatics, halogenated hydrocarbons, fuel oxygenates, alcohols, esters, and aldehydes. The number of extraction strokes and the corresponding extraction flow, also in dependence of the expected analyte concentrations, are discussed as well as the interactions between sample and extraction phase temperature. The injection parameters cover two different injection methods. The first is intended for the analysis of highly volatile analytes and the second either for the analysis of lower volatile analytes or when the analytes can be re-focused by a cold trap. The desorption volume, the desorption temperature, and the desorption flow are compared, together with the suitability of both methods for analytes of varying volatilities. The results are summarized in a flow chart, which can be used to select favorable starting conditions for further method optimization.
Optimization of Management Decision by Network Method used for Chipboards Manufacturing
Directory of Open Access Journals (Sweden)
Ivan Cismaru
2008-03-01
Full Text Available The paper presents a method of an economic analyses through which the bases of the management decision may be set in order to optimize the chipboards manufacturing activity. The method is focused on the national and efficient capitalization of raw materials, as network rate assortments, and depending on the stocks situation within the store, to establish momently the optimal recipe to be implemented according to the manufacturing expenses and the profit implicitely, this recipe being variable in time depending on the supply possibilities.
Khachaturov, R. V.
2016-09-01
It is shown that finding the equivalence set for solving multiobjective discrete optimization problems is advantageous over finding the set of Pareto optimal decisions. An example of a set of key parameters characterizing the economic efficiency of a commercial firm is proposed, and a mathematical model of its activities is constructed. In contrast to the classical problem of finding the maximum profit for any business, this study deals with a multiobjective optimization problem. A method for solving inverse multiobjective problems in a multidimensional pseudometric space is proposed for finding the best project of firm's activities. The solution of a particular problem of this type is presented.
Optimization and modification of the method for detection of rhamnolipids
Directory of Open Access Journals (Sweden)
Takeshi Tabuchi
2015-10-01
Full Text Available Use of biosurfactants in bioremediation, facilitates and accelerates microbial degradation of hydrocarbons. CTAB/MB agar method created by Siegmund & Wagner for screening of rhamnolipids (RL producing strains, has been widely used but has not improved significantly for more than 20 years. To optimize the technique as a quantitative method, CTAB/MB agar plates were made and different variables were tested, like incubation time, cooling, CTAB concentration, methylene blue presence, wells diameter and inocula volume. Furthermore, a new method for RL detection within halos was developed: precipitation of RL with HCl, allows the formation a new halos pattern, easier to observe and to measure. This research reaffirm that this method is not totally suitable for a fine quantitative analysis, because of the difficulty to accurately correlate RL concentration and the area of the halos. RL diffusion does not seem to have a simple behavior and there are a lot of factors that affect RL migration rate.
Design optimization methods for genomic DNA tiling arrays.
Bertone, Paul; Trifonov, Valery; Rozowsky, Joel S; Schubert, Falk; Emanuelsson, Olof; Karro, John; Kao, Ming-Yang; Snyder, Michael; Gerstein, Mark
2006-02-01
A recent development in microarray research entails the unbiased coverage, or tiling, of genomic DNA for the large-scale identification of transcribed sequences and regulatory elements. A central issue in designing tiling arrays is that of arriving at a single-copy tile path, as significant sequence cross-hybridization can result from the presence of non-unique probes on the array. Due to the fragmentation of genomic DNA caused by the widespread distribution of repetitive elements, the problem of obtaining adequate sequence coverage increases with the sizes of subsequence tiles that are to be included in the design. This becomes increasingly problematic when considering complex eukaryotic genomes that contain many thousands of interspersed repeats. The general problem of sequence tiling can be framed as finding an optimal partitioning of non-repetitive subsequences over a prescribed range of tile sizes, on a DNA sequence comprising repetitive and non-repetitive regions. Exact solutions to the tiling problem become computationally infeasible when applied to large genomes, but successive optimizations are developed that allow their practical implementation. These include an efficient method for determining the degree of similarity of many oligonucleotide sequences over large genomes, and two algorithms for finding an optimal tile path composed of longer sequence tiles. The first algorithm, a dynamic programming approach, finds an optimal tiling in linear time and space; the second applies a heuristic search to reduce the space complexity to a constant requirement. A Web resource has also been developed, accessible at http://tiling.gersteinlab.org, to generate optimal tile paths from user-provided DNA sequences.
Optimization of the measuring method selection for natural radionuclides
International Nuclear Information System (INIS)
Heinrich, T.; Funke, L.; Koehler, M.; Schkade, U.K.; Ullrich, F.; Loebner, W.; Hoepner, J.; Weiss, D.
2007-01-01
The publication is aimed to an optimized selection of measuring methods for the evaluation of natural radionuclides in environmental media, taking into account the required financial and temporal investment besides the informative value of the results. The evaluation is considered as a recommendation for contractors concerning required measurements or for installation or upgrading of laboratory equipment. The evaluation identifies measuring requirements and boundary conditions according to legal regulations and discusses a strategy to reach optimized results. The radiological environment monitoring is focused on the estimation of radiation exposure of personal and public. Requirements for measuring techniques (detection limits, limit values and guideline values) are summarized in tables. The evaluation is covering radionuclide measurements in the following media: air (airborne particulates); water; soils, sediments and residues; residues from natural gas, crude oil and thermal water extraction; uranium containing paints in the porcelain industry; thorium compounds for weld electrodes; filter dusts from the steel industry; biomedia
Newton-type methods for optimization and variational problems
Izmailov, Alexey F
2014-01-01
This book presents comprehensive state-of-the-art theoretical analysis of the fundamental Newtonian and Newtonian-related approaches to solving optimization and variational problems. A central focus is the relationship between the basic Newton scheme for a given problem and algorithms that also enjoy fast local convergence. The authors develop general perturbed Newtonian frameworks that preserve fast convergence and consider specific algorithms as particular cases within those frameworks, i.e., as perturbations of the associated basic Newton iterations. This approach yields a set of tools for the unified treatment of various algorithms, including some not of the Newton type per se. Among the new subjects addressed is the class of degenerate problems. In particular, the phenomenon of attraction of Newton iterates to critical Lagrange multipliers and its consequences as well as stabilized Newton methods for variational problems and stabilized sequential quadratic programming for optimization. This volume will b...
Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium
Directory of Open Access Journals (Sweden)
Xiao Han
2017-12-01
Full Text Available This paper focuses on the optimal intraday scheduling of a distribution system that includes renewable energy (RE generation, energy storage systems (ESSs, and thermostatically controlled loads (TCLs. This system also provides time-of-use pricing to customers. Unlike previous studies, this study attempts to examine how to optimize the allocation of electric energy and to improve the equilibrium of the load curve. Accordingly, we propose a concept of load equilibrium entropy to quantify the overall equilibrium of the load curve and reflect the allocation optimization of electric energy. Based on this entropy, we built a novel multi-objective optimal dispatching model to minimize the operational cost and maximize the load curve equilibrium. To aggregate TCLs into the optimization objective, we introduced the concept of a virtual power plant (VPP and proposed a calculation method for VPP operating characteristics based on the equivalent thermal parameter model and the state-queue control method. The Particle Swarm Optimization algorithm was employed to solve the optimization problems. The simulation results illustrated that the proposed dispatching model can achieve cost reductions of system operations, peak load curtailment, and efficiency improvements, and also verified that the load equilibrium entropy can be used as a novel index of load characteristics.
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.
2018-02-01
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
An Efficient Optimization Method for Solving Unsupervised Data Classification Problems
Directory of Open Access Journals (Sweden)
Parvaneh Shabanzadeh
2015-01-01
Full Text Available Unsupervised data classification (or clustering analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.
A gradient activation method for direct methanol fuel cells
International Nuclear Information System (INIS)
Liu, Guicheng; Yang, Zhaoyi; Halim, Martin; Li, Xinyang; Wang, Manxiang; Kim, Ji Young; Mei, Qiwen; Wang, Xindong; Lee, Joong Kee
2017-01-01
Highlights: • A gradient activation method was reported firstly for direct methanol fuel cells. • The activity recovery of Pt-based catalyst was introduced into the novel activation process. • The new activation method led to prominent enhancement of DMFC performance. • DMFC performance was improved with the novel activation step by step within 7.5 h. - Abstract: To realize gradient activation effect and recover catalytic activity of catalyst in a short time, a gradient activation method has firstly been proposed for enhancing discharge performance and perfecting activation mechanism of the direct methanol fuel cell (DMFC). This method includes four steps, i.e. proton activation, activity recovery activation, H 2 -O 2 mode activation and forced discharging activation. The results prove that the proposed method has gradually realized replenishment of water and protons, recovery of catalytic activity of catalyst, establishment of transfer channels for electrons, protons, and oxygen, and optimization of anode catalyst layer for methanol transfer in turn. Along with the novel activation process going on, the DMFC discharge performance has been improved, step by step, to more than 1.9 times higher than that of the original one within 7.5 h. This method provides a practicable activation way for the real application of single DMFCs and stacks.
Optimizing ETL by a Two-level Data Staging Method
DEFF Research Database (Denmark)
Liu, Xiufeng; Iftikhar, Nadeem; Nielsen, Per Sieverts
2016-01-01
In data warehousing, the data from source systems are populated into a central data warehouse (DW) through extraction, transformation and loading (ETL). The standard ETL approach usually uses sequential jobs to process the data with dependencies, such as dimension and fact data. It is a non......-trivial task to process the so-called early-/late-arriving data, which arrive out of order. This paper proposes a two-level data staging area method to optimize ETL. The proposed method is an all-in-one solution that supports processing different types of data from operational systems, including early......-/late-arriving data, and fast-/slowly-changing data. The introduced additional staging area decouples loading process from data extraction and transformation, which improves ETL flexibility and minimizes intervention to the data warehouse. This paper evaluates the proposed method empirically, which shows...
RELAP-7 Progress Report. FY-2015 Optimization Activities Summary
Energy Technology Data Exchange (ETDEWEB)
Berry, Ray Alden [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zou, Ling [Idaho National Lab. (INL), Idaho Falls, ID (United States); Andrs, David [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-09-01
This report summarily documents the optimization activities on RELAP-7 for FY-2015. It includes the migration from the analytical stiffened gas equation of state for both the vapor and liquid phases to accurate and efficient property evaluations for both equilibrium and metastable (nonequilibrium) states using the Spline-Based Table Look-up (SBTL) method with the IAPWS-95 properties for steam and water. It also includes the initiation of realistic closure models based, where appropriate, on the U.S. Nuclear Regulatory Commission’s TRACE code. It also describes an improved entropy viscosity numerical stabilization method for the nonequilibrium two-phase flow model of RELAP-7. For ease of presentation to the reader, the nonequilibrium two-phase flow model used in RELAP-7 is briefly presented, though for detailed explanation the reader is referred to RELAP-7 Theory Manual [R.A. Berry, J.W. Peterson, H. Zhang, R.C. Martineau, H. Zhao, L. Zou, D. Andrs, “RELAP-7 Theory Manual,” Idaho National Laboratory INL/EXT-14-31366(rev. 1), February 2014].
Gottlieb, Sigal
2015-04-10
High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The search for high order strong stability time-stepping methods with large allowable strong stability coefficient has been an active area of research over the last two decades. This research has shown that explicit SSP Runge-Kutta methods exist only up to fourth order. However, if we restrict ourselves to solving only linear autonomous problems, the order conditions simplify and this order barrier is lifted: explicit SSP Runge-Kutta methods of any linear order exist. These methods reduce to second order when applied to nonlinear problems. In the current work we aim to find explicit SSP Runge-Kutta methods with large allowable time-step, that feature high linear order and simultaneously have the optimal fourth order nonlinear order. These methods have strong stability coefficients that approach those of the linear methods as the number of stages and the linear order is increased. This work shows that when a high linear order method is desired, it may still be worthwhile to use methods with higher nonlinear order.
Multiobjective Optimization Methods for Congestion Management in Deregulated Power Systems
Directory of Open Access Journals (Sweden)
K. Vijayakumar
2012-01-01
Full Text Available Congestion management is one of the important functions performed by system operator in deregulated electricity market to ensure secure operation of transmission system. This paper proposes two effective methods for transmission congestion alleviation in deregulated power system. Congestion or overload in transmission networks is alleviated by rescheduling of generators and/or load shedding. The two objectives conflicting in nature (1 transmission line over load and (2 congestion cost are optimized in this paper. The multiobjective fuzzy evolutionary programming (FEP and nondominated sorting genetic algorithm II methods are used to solve this problem. FEP uses the combined advantages of fuzzy and evolutionary programming (EP techniques and gives better unique solution satisfying both objectives, whereas nondominated sorting genetic algorithm (NSGA II gives a set of Pareto-optimal solutions. The methods propose an efficient and reliable algorithm for line overload alleviation due to critical line outages in a deregulated power markets. The quality and usefulness of the algorithm is tested on IEEE 30 bus system.
An optimized method for counting dopaminergic neurons in zebrafish.
Directory of Open Access Journals (Sweden)
Hideaki Matsui
Full Text Available In recent years, considerable effort has been devoted to the development of a fish model for Parkinson's disease (PD to examine the pathological mechanisms of neurodegeneration. To effectively evaluate PD pathology, the ability to accurately and reliably count dopaminergic neurons is important. However, there is currently no such standardized method. Due to the relatively small number of dopaminergic neurons in fish, stereological estimation would not be suitable. In addition, serial sectioning requires proficiency to not lose any sections, and it permits double counting due to the large size of some of the dopaminergic neurons. In this study, we report an optimized protocol for staining dopaminergic neurons in zebrafish and provide a reliable counting method. Finally, using our optimized protocol, we confirmed that administration of 6-hydroxydopamine (a neurotoxin or the deletion of the PINK1 gene (one of the causative genes of familiar PD in zebrafish caused significant reduction in the number of dopaminergic and noradrenergic neurons. In summary, this method will serve as an important tool for the appropriate evaluation and establishment of fish PD models.
Optimized application of penalized regression methods to diverse genomic data.
Waldron, Levi; Pintilie, Melania; Tsao, Ming-Sound; Shepherd, Frances A; Huttenhower, Curtis; Jurisica, Igor
2011-12-15
Penalized regression methods have been adopted widely for high-dimensional feature selection and prediction in many bioinformatic and biostatistical contexts. While their theoretical properties are well-understood, specific methodology for their optimal application to genomic data has not been determined. Through simulation of contrasting scenarios of correlated high-dimensional survival data, we compared the LASSO, Ridge and Elastic Net penalties for prediction and variable selection. We found that a 2D tuning of the Elastic Net penalties was necessary to avoid mimicking the performance of LASSO or Ridge regression. Furthermore, we found that in a simulated scenario favoring the LASSO penalty, a univariate pre-filter made the Elastic Net behave more like Ridge regression, which was detrimental to prediction performance. We demonstrate the real-life application of these methods to predicting the survival of cancer patients from microarray data, and to classification of obese and lean individuals from metagenomic data. Based on these results, we provide an optimized set of guidelines for the application of penalized regression for reproducible class comparison and prediction with genomic data. A parallelized implementation of the methods presented for regression and for simulation of synthetic data is provided as the pensim R package, available at http://cran.r-project.org/web/packages/pensim/index.html. chuttenh@hsph.harvard.edu; juris@ai.utoronto.ca Supplementary data are available at Bioinformatics online.
Hybrid Training Method for MLP: Optimization of Architecture and Training.
Zanchettin, C; Ludermir, T B; Almeida, L M
2011-08-01
The performance of an artificial neural network (ANN) depends upon the selection of proper connection weights, network architecture, and cost function during network training. This paper presents a hybrid approach (GaTSa) to optimize the performance of the ANN in terms of architecture and weights. GaTSa is an extension of a previous method (TSa) proposed by the authors. GaTSa is based on the integration of the heuristic simulated annealing (SA), tabu search (TS), genetic algorithms (GA), and backpropagation, whereas TSa does not use GA. The main advantages of GaTSa are the following: a constructive process to add new nodes in the architecture based on GA, the ability to escape from local minima with uphill moves (SA feature), and faster convergence by the evaluation of a set of solutions (TS feature). The performance of GaTSa is investigated through an empirical evaluation of 11 public-domain data sets using different cost functions in the simultaneous optimization of the multilayer perceptron ANN architecture and weights. Experiments demonstrated that GaTSa can also be used for relevant feature selection. GaTSa presented statistically relevant results in comparison with other global and local optimization techniques.
Optimization of sequential decisions by least squares Monte Carlo method
DEFF Research Database (Denmark)
Nishijima, Kazuyoshi; Anders, Annett
change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which......The present paper considers the sequential decision optimization problem. This is an important class of decision problems in engineering. Important examples include decision problems on the quality control of manufactured products and engineering components, timing of the implementation of climate....... For the purpose to demonstrate the use and advantages two numerical examples are provided, which is on the quality control of manufactured products....
CSIR Research Space (South Africa)
Debba, Pravesh
2010-11-01
Full Text Available This paper reports on the results from ordinary least squares and ridge regression as statistical methods, and is compared to numerical optimization methods such as the stochastic method for global optimization, simulated annealing, particle swarm...
Zhou, Bao-Rong; Liu, Si-Liang; Zhang, Yong-Jun; Yi, Ying-Qi; Lin, Xiao-Ming
2017-05-01
To mitigate the impact on the distribution networks caused by the stochastic characteristic and high penetration of photovoltaic, a multi-objective optimal power flow model is proposed in this paper. The regulation capability of capacitor, inverter of photovoltaic and energy storage system embedded in active distribution network are considered to minimize the expected value of active power the T loss and probability of voltage violation in this model. Firstly, a probabilistic power flow based on cumulant method is introduced to calculate the value of the objectives. Secondly, NSGA-II algorithm is adopted for optimization to obtain the Pareto optimal solutions. Finally, the best compromise solution can be achieved through fuzzy membership degree method. By the multi-objective optimization calculation of IEEE34-node distribution network, the results show that the model can effectively improve the voltage security and economy of the distribution network on different levels of photovoltaic penetration.
Activated sludge optimization using ATP in pulp and paper industry.
Bäckman, Göran; Gytel, Ulla
2015-01-01
The activated sludge process is an old technology, but still the most commonly used one for treatment of wastewater. Despite the wide spread usage the technology still suffers from instability (Tandoi et al. 2006) and high operating cost. Activated sludge processes often carry a large solids inventory. Managing the total inventory without interference is the key component of the optimization process described in this paper. Use of nutrients is common in pulp and paper effluent treatment. Feeding enough nutrients to support the biomass growth is a delicate balance. Overfeeding or underfeeding of nutrients can result in higher costs. Detrimental substances and toxic components in effluents entering a biological treatment system can cause severe, long lasting disturbances (Hynninen & Ingman 1998; Bergeron & Pelletier 2004). A LumiKem test kit is used to measure biological activity with adenosine triphosphate (ATP) in a pulp and paper mill. ATP data are integrated with other standardized mill parameters. Measurements of active volatile suspended solids based on ATP can be used to quantify the living biomass in the activated sludge process and to ensure that sufficient biomass is present in order to degrade the wastewater constituents entering the process. Information about active biomass will assist in optimizing sludge inventories and feeding of nutrients allowing the living biomass to re-populate to create optimal efficiency. ATP measurements can also be used to alert operators if any components toxic to bacteria are present in wastewater. The bio stress index represents the stress level experienced by the microbiological population. This parameter is very useful in monitoring toxicity in and around bioreactors. Results from the wastewater process optimization and ATP measurements showed that treatment cost could be reduced by approximately 20-30% with fewer disturbances and sustained biological activity compared to the reference period. This was mainly achieved by
Activating teaching methods in french language teaching
Kulhánková, Anna
2009-01-01
The subject of this diploma thesis is activating teaching methods in french language teaching. This thesis outlines the issues acitvating teaching methods in the concept of other teaching methods. There is a definition of teaching method, classification of teaching methods and characteristics of each activating method. In the practical part of this work are given concrete forms of activating teaching methods appropriate for teaching of french language.
Practical optimization of Steiner trees via the cavity method
Braunstein, Alfredo; Muntoni, Anna
2016-07-01
The optimization version of the cavity method for single instances, called Max-Sum, has been applied in the past to the minimum Steiner tree problem on graphs and variants. Max-Sum has been shown experimentally to give asymptotically optimal results on certain types of weighted random graphs, and to give good solutions in short computation times for some types of real networks. However, the hypotheses behind the formulation and the cavity method itself limit substantially the class of instances on which the approach gives good results (or even converges). Moreover, in the standard model formulation, the diameter of the tree solution is limited by a predefined bound, that affects both computation time and convergence properties. In this work we describe two main enhancements to the Max-Sum equations to be able to cope with optimization of real-world instances. First, we develop an alternative ‘flat’ model formulation that allows the relevant configuration space to be reduced substantially, making the approach feasible on instances with large solution diameter, in particular when the number of terminal nodes is small. Second, we propose an integration between Max-Sum and three greedy heuristics. This integration allows Max-Sum to be transformed into a highly competitive self-contained algorithm, in which a feasible solution is given at each step of the iterative procedure. Part of this development participated in the 2014 DIMACS Challenge on Steiner problems, and we report the results here. The performance on the challenge of the proposed approach was highly satisfactory: it maintained a small gap to the best bound in most cases, and obtained the best results on several instances in two different categories. We also present several improvements with respect to the version of the algorithm that participated in the competition, including new best solutions for some of the instances of the challenge.
A spatial domain optimization method to generate plane dependent masks
Wu, Yifeng
2006-01-01
Stochastic screening technique uses a fixed threshold array to generate halftoned images. When this technique is applied to color images, an important problem is how to generate the masks for different color planes. Ideally, a set of plane dependent color masks should have the following characteristics: a) when total ink coverage is less than 100%, no dots in different colors should overlap from each other. b) for each individual mask, dot distribution should be uniform, c) no visual artifact should be visible due to the low frequency patterns. In this paper, we propose a novel color mask generation method in which the optimal dot placement is searched directly in spatial domain. The advantage of using the spatial domain approach is that we can control directly the dot uniformity during the optimization, and we can also cope with the color plane-dependency by introducing some inter-plane constraints. We will show that using this method, we can generate plane dependent color masks with the characteristics mentioned above.
Optimization method for dimensioning a geological HLW waste repository
International Nuclear Information System (INIS)
Ouvrier, N.; Chaudon, L.; Malherbe, L.
1990-01-01
This method was developed by the CEA to optimize the dimensions of a geological repository by taking account of technical and economic parameters. It involves optimizing radioactive waste storage conditions on the basis of economic criteria with allowance for specified thermal constraints. The results are intended to identify trends and guide the choice from among available options: simple and highly flexible models were therefore used in this study, and only nearfield thermal constraints were taken into consideration. Because of the present uncertainty on the physicochemical properties of the repository environment and on the unit cost figures, this study focused on developing a suitable method rather than on obtaining definitive results. The optimum values found for the two media investigated (granite and salt) show that it is advisable to minimize the interim storage time, implying the containers must be separated by buffer material, whereas vertical spacing may not be required after a 30-year interim storage period. Moreover, the boreholes should be as deep as possible, on a close pitch in widely spaced handling drifts. These results depend to a considerable extent on the assumption of high interim storage costs
Method for nonlinear optimization for gas tagging and other systems
Chen, T.; Gross, K.C.; Wegerich, S.
1998-01-06
A method and system are disclosed for providing nuclear fuel rods with a configuration of isotopic gas tags. The method includes selecting a true location of a first gas tag node, selecting initial locations for the remaining n-1 nodes using target gas tag compositions, generating a set of random gene pools with L nodes, applying a Hopfield network for computing on energy, or cost, for each of the L gene pools and using selected constraints to establish minimum energy states to identify optimal gas tag nodes with each energy compared to a convergence threshold and then upon identifying the gas tag node continuing this procedure until establishing the next gas tag node until all remaining n nodes have been established. 6 figs.
Experimental Methods for the Analysis of Optimization Algorithms
DEFF Research Database (Denmark)
of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists......In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However......, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different...
ARSTEC, Nonlinear Optimization Program Using Random Search Method
International Nuclear Information System (INIS)
Rasmuson, D. M.; Marshall, N. H.
1979-01-01
1 - Description of problem or function: The ARSTEC program was written to solve nonlinear, mixed integer, optimization problems. An example of such a problem in the nuclear industry is the allocation of redundant parts in the design of a nuclear power plant to minimize plant unavailability. 2 - Method of solution: The technique used in ARSTEC is the adaptive random search method. The search is started from an arbitrary point in the search region and every time a point that improves the objective function is found, the search region is centered at that new point. 3 - Restrictions on the complexity of the problem: Presently, the maximum number of independent variables allowed is 10. This can be changed by increasing the dimension of the arrays
A discrete optimization method for nuclear fuel management
International Nuclear Information System (INIS)
Argaud, J.P.
1993-04-01
Nuclear loading pattern elaboration can be seen as a combinational optimization problem, of tremendous size and with non-linear cost-functions, and search are always numerically expensive. After a brief introduction of the main aspects of nuclear fuel management, this note presents a new idea to treat the combinational problem by using informations included in the gradient of a cost function. The method is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method, and finally, connections with simulated annealing and genetic algorithms are described as an attempt to improve search processes. (author). 1 fig., 16 refs
International Nuclear Information System (INIS)
Fredriksson, Albin; Bokrantz, Rasmus
2014-01-01
Purpose: To critically evaluate and compare three worst case optimization methods that have been previously employed to generate intensity-modulated proton therapy treatment plans that are robust against systematic errors. The goal of the evaluation is to identify circumstances when the methods behave differently and to describe the mechanism behind the differences when they occur. Methods: The worst case methods optimize plans to perform as well as possible under the worst case scenario that can physically occur (composite worst case), the combination of the worst case scenarios for each objective constituent considered independently (objectivewise worst case), and the combination of the worst case scenarios for each voxel considered independently (voxelwise worst case). These three methods were assessed with respect to treatment planning for prostate under systematic setup uncertainty. An equivalence with probabilistic optimization was used to identify the scenarios that determine the outcome of the optimization. Results: If the conflict between target coverage and normal tissue sparing is small and no dose-volume histogram (DVH) constraints are present, then all three methods yield robust plans. Otherwise, they all have their shortcomings: Composite worst case led to unnecessarily low plan quality in boundary scenarios that were less difficult than the worst case ones. Objectivewise worst case generally led to nonrobust plans. Voxelwise worst case led to overly conservative plans with respect to DVH constraints, which resulted in excessive dose to normal tissue, and less sharp dose fall-off than the other two methods. Conclusions: The three worst case methods have clearly different behaviors. These behaviors can be understood from which scenarios that are active in the optimization. No particular method is superior to the others under all circumstances: composite worst case is suitable if the conflicts are not very severe or there are DVH constraints whereas
Scheduling Internal Audit Activities: A Stochastic Combinatorial Optimization Problem
Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.; Karacaer, S.
2010-01-01
The problem of finding the optimal timing of audit activities within an organisation has been addressed by many researchers. We propose a stochastic programming formulation with Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) certainty-equivalent models. In experiments
Scale-Adaptive Group Optimization for Social Activity Planning
2015-05-22
the process will be tedious and time- consuming , especially for a large social activity, given the complicated social link structure and the diverse...optimize the rap - port among the teammembers to ensure efficient operation. Communication costs can be represented by the graph diameter, the size of the
A novel technique for active vibration control, based on optimal
Indian Academy of Sciences (India)
In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a structure by simultaneously ...
Yang, Guo Sheng; Wang, Xiao Yang; Li, Xue Dong
2018-03-01
With the establishment of the integrated model of relay protection and the scale of the power system expanding, the global setting and optimization of relay protection is an extremely difficult task. This paper presents a kind of application in relay protection of global optimization improved particle swarm optimization algorithm and the inverse time current protection as an example, selecting reliability of the relay protection, selectivity, quick action and flexibility as the four requires to establish the optimization targets, and optimizing protection setting values of the whole system. Finally, in the case of actual power system, the optimized setting value results of the proposed method in this paper are compared with the particle swarm algorithm. The results show that the improved quantum particle swarm optimization algorithm has strong search ability, good robustness, and it is suitable for optimizing setting value in the relay protection of the whole power system.
Advanced Topology Optimization Methods for Conceptual Architectural Design
DEFF Research Database (Denmark)
Aage, Niels; Amir, Oded; Clausen, Anders
2014-01-01
in topological optimization: Interactive control and continuous visualization; embedding flexible voids within the design space; consideration of distinct tension / compression properties; and optimization of dual material systems. In extension, optimization procedures for skeletal structures such as trusses...... and frames are implemented. The developed procedures allow for the exploration of new territories in optimization of architectural structures, and offer new methodological strategies for bridging conceptual gaps between optimization and architectural practice....
Optimization of Spinal Muscular Atrophy subject's muscle activity during gait
Umat, Gazlia; Rambely, Azmin Sham
2014-06-01
Spinal Muscular Atrophy (SMA) is a hereditary disease related muscle nerve disorder caused by degeneration of the anterior cells of the spinal cord. SMA is divided into four types according to the degree of seriousness. SMA patients show different gait with normal people. Therefore, this study focused on the effects of SMA patient muscle actions and the difference that exists between SMA subjects and normal subjects. Therefore, the electromyography (EMG) test will be used to track the behavior of muscle during walking and optimization methods are used to get the muscle stress that is capable of doing the work while walking. Involved objective function is non-linear function of the quadratic and cubic functions. The study concludes with a comparison of the objective function using the force that sought to use the moment of previous studies and the objective function using the data obtained from EMG. The results shows that the same muscles, peroneus longus and bisepsfemoris, were used during walking activity by SMA subjects and control subjects. Muscle stress force best solution achieved from part D in simulation carried out.
Fredriksson, Albin; Bokrantz, Rasmus
2014-08-01
To critically evaluate and compare three worst case optimization methods that have been previously employed to generate intensity-modulated proton therapy treatment plans that are robust against systematic errors. The goal of the evaluation is to identify circumstances when the methods behave differently and to describe the mechanism behind the differences when they occur. The worst case methods optimize plans to perform as well as possible under the worst case scenario that can physically occur (composite worst case), the combination of the worst case scenarios for each objective constituent considered independently (objectivewise worst case), and the combination of the worst case scenarios for each voxel considered independently (voxelwise worst case). These three methods were assessed with respect to treatment planning for prostate under systematic setup uncertainty. An equivalence with probabilistic optimization was used to identify the scenarios that determine the outcome of the optimization. If the conflict between target coverage and normal tissue sparing is small and no dose-volume histogram (DVH) constraints are present, then all three methods yield robust plans. Otherwise, they all have their shortcomings: Composite worst case led to unnecessarily low plan quality in boundary scenarios that were less difficult than the worst case ones. Objectivewise worst case generally led to nonrobust plans. Voxelwise worst case led to overly conservative plans with respect to DVH constraints, which resulted in excessive dose to normal tissue, and less sharp dose fall-off than the other two methods. The three worst case methods have clearly different behaviors. These behaviors can be understood from which scenarios that are active in the optimization. No particular method is superior to the others under all circumstances: composite worst case is suitable if the conflicts are not very severe or there are DVH constraints whereas voxelwise worst case is advantageous if
Shobeiri, Vahid
2016-03-01
In this article, the bi-directional evolutionary structural optimization (BESO) method based on the element-free Galerkin (EFG) method is presented for topology optimization of continuum structures. The mathematical formulation of the topology optimization is developed considering the nodal strain energy as the design variable and the minimization of compliance as the objective function. The EFG method is used to derive the shape functions using the moving least squares approximation. The essential boundary conditions are enforced by the method of Lagrange multipliers. Several topology optimization problems are presented to show the effectiveness of the proposed method. Many issues related to topology optimization of continuum structures, such as chequerboard patterns and mesh dependency, are studied in the examples.
A Pareto-optimal refinement method for protein design scaffolds.
Nivón, Lucas Gregorio; Moretti, Rocco; Baker, David
2013-01-01
Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc.) can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design.
A Pareto-optimal refinement method for protein design scaffolds.
Directory of Open Access Journals (Sweden)
Lucas Gregorio Nivón
Full Text Available Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc. can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design.
Zhang, Li; Wu, Kexin; Liu, Yang
2017-12-01
A multi-objective performance optimization method is proposed, and the problem that single structural parameters of small fan balance the optimization between the static characteristics and the aerodynamic noise is solved. In this method, three structural parameters are selected as the optimization variables. Besides, the static pressure efficiency and the aerodynamic noise of the fan are regarded as the multi-objective performance. Furthermore, the response surface method and the entropy method are used to establish the optimization function between the optimization variables and the multi-objective performances. Finally, the optimized model is found when the optimization function reaches its maximum value. Experimental data shows that the optimized model not only enhances the static characteristics of the fan but also obviously reduces the noise. The results of the study will provide some reference for the optimization of multi-objective performance of other types of rotating machinery.
A method for calculating active feedback system to provide vertical ...
Indian Academy of Sciences (India)
the control of plasma vertical position with active feedback system. Calculation of feed- back control parameters is formulated as an optimization problem and an approximate method to solve the problem is suggested. Numerical simulations are performed with parameters of the T-15M tokamak in order to justify the ...
Optimized t-expansion method for the Rabi Hamiltonian
International Nuclear Information System (INIS)
Travenec, Igor; Samaj, Ladislav
2011-01-01
A polemic arose recently about the applicability of the t-expansion method to the calculation of the ground state energy E 0 of the Rabi model. For specific choices of the trial function and very large number of involved connected moments, the t-expansion results are rather poor and exhibit considerable oscillations. In this Letter, we formulate the t-expansion method for trial functions containing two free parameters which capture two exactly solvable limits of the Rabi Hamiltonian. At each order of the t-series, E 0 is assumed to be stationary with respect to the free parameters. A high accuracy of E 0 estimates is achieved for small numbers (5 or 6) of involved connected moments, the relative error being smaller than 10 -4 (0.01%) within the whole parameter space of the Rabi Hamiltonian. A special symmetrization of the trial function enables us to calculate also the first excited energy E 1 , with the relative error smaller than 10 -2 (1%). -- Highlights: → We study the ground state energy of the Rabi Hamiltonian. → We use the t-expansion method with an optimized trial function. → High accuracy of estimates is achieved, the relative error being smaller than 0.01%. → The calculation of the first excited state energy is made. The method has a general applicability.
Optimization of Production Processes Using the Yamazumi Method
Directory of Open Access Journals (Sweden)
Dušan Sabadka
2017-12-01
Full Text Available Manufacturing companies are now placing great emphasis on competitiveness and looking for ways to explore their resources more efficiently. This paper presents optimum efficiency improvement of the automotive transmission assembly production line by using line balancing. To optimize has been selected 3 assembly stations where is waste and where requirements are not met for achieving the production capacity. Several measures have been proposed on the assembly lines concerned to reduce operations by using eliminating unnecessary activities of the assembly processes, reducing the cycle time, and balancing manpower workload using line balancing through Yamazumi chart and Takt time. The results of the proposed measures were compared with the current situation in terms of increasing the efficiency of the production line.
Information theoretic methods for image processing algorithm optimization
Prokushkin, Sergey F.; Galil, Erez
2015-01-01
Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).
Methods for the design and optimization of shaped tokamaks
International Nuclear Information System (INIS)
Haney, S.W.
1988-05-01
Two major questions associated with the design and optimization of shaped tokamaks are considered. How do physics and engineering constraints affect the design of shaped tokamaks? How can the process of designing shaped tokamaks be improved? The first question is addressed with the aid of a completely analytical procedure for optimizing the design of a resistive-magnet tokamak reactor. It is shown that physics constraints---particularly the MHD beta limits and the Murakami density limit---have an enormous, and sometimes, unexpected effect on the final design. The second question is addressed through the development of a series of computer models for calculating plasma equilibria, estimating poloidal field coil currents, and analyzing axisymmetric MHD stability in the presence of resistive conductors and feedback. The models offer potential advantages over conventional methods since they are characterized by extremely fast computer execution times, simplicity, and robustness. Furthermore, evidence is presented that suggests that very little loss of accuracy is required to achieve these desirable features. 94 refs., 66 figs., 14 tabs
OPTIMIZING THE PAKS METHOD FOR MEASURING AIRBORNE ACROLEIN
Airborne acrolein is produced from the combustion of fuel and tobacco and is of concern due to its potential for respiratory tract irritation and other adverse health effects. DNPH active-sampling is a method widely used for sampling airborne aldehydes and ketones (carbonyls); ...
DMTO – a method for Discrete Material and Thickness Optimization of laminated composite structures
DEFF Research Database (Denmark)
Sørensen, Søren Nørgaard; Sørensen, Rene; Lund, Erik
2014-01-01
This paper presents a gradient based topology optimization method for Discrete Material and Thickness Optimization of laminated composite structures, labelled the DMTOmethod. The capabilities of the proposed method are demonstrated on mass minimization, subject to constraints on the structural...
Convex functions and optimization methods on Riemannian manifolds
Udrişte, Constantin
1994-01-01
This unique monograph discusses the interaction between Riemannian geometry, convex programming, numerical analysis, dynamical systems and mathematical modelling. The book is the first account of the development of this subject as it emerged at the beginning of the 'seventies. A unified theory of convexity of functions, dynamical systems and optimization methods on Riemannian manifolds is also presented. Topics covered include geodesics and completeness of Riemannian manifolds, variations of the p-energy of a curve and Jacobi fields, convex programs on Riemannian manifolds, geometrical constructions of convex functions, flows and energies, applications of convexity, descent algorithms on Riemannian manifolds, TC and TP programs for calculations and plots, all allowing the user to explore and experiment interactively with real life problems in the language of Riemannian geometry. An appendix is devoted to convexity and completeness in Finsler manifolds. For students and researchers in such diverse fields as pu...
Shape optimized headers and methods of manufacture thereof
Perrin, Ian James
2013-11-05
Disclosed herein is a shape optimized header comprising a shell that is operative for collecting a fluid; wherein an internal diameter and/or a wall thickness of the shell vary with a change in pressure and/or a change in a fluid flow rate in the shell; and tubes; wherein the tubes are in communication with the shell and are operative to transfer fluid into the shell. Disclosed herein is a method comprising fixedly attaching tubes to a shell; wherein the shell is operative for collecting a fluid; wherein an internal diameter and/or a wall thickness of the shell vary with a change in pressure and/or a change in a fluid flow rate in the shell; and wherein the tubes are in communication with the shell and are operative to transfer fluid into the shell.
Comparison of operation optimization methods in energy system modelling
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2013-01-01
In areas with large shares of Combined Heat and Power (CHP) production, significant introduction of intermittent renewable power production may lead to an increased number of operational constraints. As the operation pattern of each utility plant is determined by optimization of economics......, possibilities for decoupling production constraints may be valuable. Introduction of heat pumps in the district heating network may pose this ability. In order to evaluate if the introduction of heat pumps is economically viable, we develop calculation methods for the operation patterns of each of the used...... operation constraints, while the third approach uses nonlinear programming. In the present case the non-linearity occurs in the boiler efficiency of power plants and the cv-value of an extraction plant. The linear programming model is used as a benchmark, as this type is frequently used, and has the lowest...
An Optimized Replica Distribution Method in Cloud Storage System
Directory of Open Access Journals (Sweden)
Yan Wang
2017-01-01
Full Text Available Aiming at establishing a shared storage environment, cloud storage systems are typical applications of cloud computing. Therefore, data replication technology has become a key research issue in storage systems. Considering the performance of data access and balancing the relationship between replica consistency maintenance costs and the performance of multiple replicas access, the methods of replica catalog design and the information acquisition method are proposed. Moreover, the deputy catalog acquisition method to design and copy the information is given. Then, the nodes with the global replica of the information replicate data resources, which have the high access frequency and the long response time. Afterwards, the Markov chain model is constructed. And a matrix geometric solution is used to export the steady-state solution of the model. The performance parameters in terms of the average response time, finish time, and the replica frequency are given to optimize the number of replicas in the storage system. Finally, numerical results with analysis are proposed to demonstrate the influence of the above parameters on the system performance.
Fish sampling with active methods
Czech Academy of Sciences Publication Activity Database
Kubečka, Jan; Godo, O. R.; Hickley, P.; Prchalová, Marie; Říha, Milan; Rudstam, L.; Welcomme, R.
2012-01-01
Roč. 123, July (2012), s. 1-3 ISSN 0165-7836 Institutional support: RVO:60077344 Keywords : fish stock assessment * active and passive gear * intercalibration Subject RIV: EH - Ecology, Behaviour Impact factor: 1.695, year: 2012
Polysaccharides in Sipunculus nudus: Extraction condition optimization and antioxidant activities
Zhang, Qin; Dong, Lanfang; Tong, Tong; Wang, Qingchao; Xu, Mingzhu
2017-02-01
Marine organisms constitute unlimited resource of bioactive substances due to their high biodiversity and represent a valuable source of new compounds. This study optimized the alkali-extraction conditions and antioxidant activities of soluble polysaccharides from the body wall of Sipunculus nudus. The effects of solid-liquid ratio, extraction duration, extraction temperature, and alkali concentration on the yield of S. nudus polysaccharides (SNP) were examined, according to which the optimal combination of extraction parameters was obtained by an orthogonal test. The relative influencing importance of different extraction parameters on the yield of SNP followed the order as solid-liquid ratio > extraction temperature > alkali concentration > extraction duration. The highest extraction yield, 1.98%, was achieved under an optimal extraction condition: temperature 60°C, solid-liquid ratio 1:6 g mL-1, duration 5 h, and alkali (NaOH) mass fraction 6%. The in vitro antioxidant activities examination showed that extracted SNP under this optimized condition had strong power in reducing certain hydroxyl and superoxide radical scavenging abilities. The promising results showed that extracted SNP could be a potent natural antioxidant.
Jacob, H. G.
1972-01-01
An optimization method has been developed that computes the optimal open loop inputs for a dynamical system by observing only its output. The method reduces to static optimization by expressing the inputs as series of functions with parameters to be optimized. Since the method is not concerned with the details of the dynamical system to be optimized, it works for both linear and nonlinear systems. The method and the application to optimizing longitudinal landing paths for a STOL aircraft with an augmented wing are discussed. Noise, fuel, time, and path deviation minimizations are considered with and without angle of attack, acceleration excursion, flight path, endpoint, and other constraints.
Modified Newton-Raphson GRAPE methods for optimal control of spin systems
Energy Technology Data Exchange (ETDEWEB)
Goodwin, D. L.; Kuprov, Ilya, E-mail: i.kuprov@soton.ac.uk [School of Chemistry, University of Southampton, Highfield Campus, Southampton SO17 1BJ (United Kingdom)
2016-05-28
Quadratic convergence throughout the active space is achieved for the gradient ascent pulse engineering (GRAPE) family of quantum optimal control algorithms. We demonstrate in this communication that the Hessian of the GRAPE fidelity functional is unusually cheap, having the same asymptotic complexity scaling as the functional itself. This leads to the possibility of using very efficient numerical optimization techniques. In particular, the Newton-Raphson method with a rational function optimization (RFO) regularized Hessian is shown in this work to require fewer system trajectory evaluations than any other algorithm in the GRAPE family. This communication describes algebraic and numerical implementation aspects (matrix exponential recycling, Hessian regularization, etc.) for the RFO Newton-Raphson version of GRAPE and reports benchmarks for common spin state control problems in magnetic resonance spectroscopy.
Modified Newton-Raphson GRAPE methods for optimal control of spin systems
International Nuclear Information System (INIS)
Goodwin, D. L.; Kuprov, Ilya
2016-01-01
Quadratic convergence throughout the active space is achieved for the gradient ascent pulse engineering (GRAPE) family of quantum optimal control algorithms. We demonstrate in this communication that the Hessian of the GRAPE fidelity functional is unusually cheap, having the same asymptotic complexity scaling as the functional itself. This leads to the possibility of using very efficient numerical optimization techniques. In particular, the Newton-Raphson method with a rational function optimization (RFO) regularized Hessian is shown in this work to require fewer system trajectory evaluations than any other algorithm in the GRAPE family. This communication describes algebraic and numerical implementation aspects (matrix exponential recycling, Hessian regularization, etc.) for the RFO Newton-Raphson version of GRAPE and reports benchmarks for common spin state control problems in magnetic resonance spectroscopy.
Zhang, Ke; Hughes-Oliver, Jacqueline M; Young, S Stanley
2013-01-01
A new classification method called the Optimal Bit String Tree is proposed to identify quantitative structure-activity relationships (QSARs). The method introduces the concept of a chromosome to describe the presence/absence context of a combination of descriptors. A descriptor set and its optimal chromosome form the splitting variable. A new stochastic searching scheme that contains a weighted sampling scheme, simulated annealing, and a trimming procedure optimizes the choice of splitting variable. Simulation studies and an application to screening monoamine oxidase (MAO) inhibitors show that OBSTree is advantageous in accurately and effectively identifying QSAR rules and finding different classes of active compounds. Details of the algorithm, SAS code, and simulated and real datasets are available online as supplementary materials.
Simple optimization method for partitioning purification of hydrogen networks
Directory of Open Access Journals (Sweden)
W.M. Shehata
2015-03-01
Full Text Available The Egyptian petroleum fuel market is increasing rapidly nowadays. These fuels must be in the standard specifications of the Egyptian General Petroleum Corporation (EGPC, which required lower sulfur gasoline and diesel fuels. So the fuels must be deep hydrotreated which resulted in increasing hydrogen (H2 consumption for deeper hydrotreating. Along with increased H2 consumption for deeper hydrotreating, additional H2 is needed for processing heavier and higher sulfur crude slates especially in hydrocracking process, in addition to hydrotreating unit, isomerization units and lubricant plants. Purification technology is used to increase the amount of recycled hydrogen. If the amount of recycled hydrogen is increased, the amount of hydrogen that is sent to the furnaces with the off gas will decrease. In this work, El Halwagi et al. (2003 and El Halwagi (2012 optimization methods which are used for recycle/reuse integration systems have been extended to be used in the partitioning purification of hydrogen networks to minimize the hydrogen consumption and the hydrogen discharge. An actual case study and two case studies from the literature are solved to illustrate the proposed method.
A Requirements-Driven Optimization Method for Acoustic Treatment Design
Berton, Jeffrey J.
2016-01-01
Acoustic treatment designers have long been able to target specific noise sources inside turbofan engines. Facesheet porosity and cavity depth are key design variables of perforate-over-honeycomb liners that determine levels of noise suppression as well as the frequencies at which suppression occurs. Layers of these structures can be combined to create a robust attenuation spectrum that covers a wide range of frequencies. Looking to the future, rapidly-emerging additive manufacturing technologies are enabling new liners with multiple degrees of freedom, and new adaptive liners with variable impedance are showing promise. More than ever, there is greater flexibility and freedom in liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. The subject of this paper is an analytical method that derives the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground.
A second-order unconstrained optimization method for canonical-ensemble density-functional methods
Nygaard, Cecilie R.; Olsen, Jeppe
2013-03-01
A second order converging method of ensemble optimization (SOEO) in the framework of Kohn-Sham Density-Functional Theory is presented, where the energy is minimized with respect to an ensemble density matrix. It is general in the sense that the number of fractionally occupied orbitals is not predefined, but rather it is optimized by the algorithm. SOEO is a second order Newton-Raphson method of optimization, where both the form of the orbitals and the occupation numbers are optimized simultaneously. To keep the occupation numbers between zero and two, a set of occupation angles is defined, from which the occupation numbers are expressed as trigonometric functions. The total number of electrons is controlled by a built-in second order restriction of the Newton-Raphson equations, which can be deactivated in the case of a grand-canonical ensemble (where the total number of electrons is allowed to change). To test the optimization method, dissociation curves for diatomic carbon are produced using different functionals for the exchange-correlation energy. These curves show that SOEO favors symmetry broken pure-state solutions when using functionals with exact exchange such as Hartree-Fock and Becke three-parameter Lee-Yang-Parr. This is explained by an unphysical contribution to the exact exchange energy from interactions between fractional occupations. For functionals without exact exchange, such as local density approximation or Becke Lee-Yang-Parr, ensemble solutions are favored at interatomic distances larger than the equilibrium distance. Calculations on the chromium dimer are also discussed. They show that SOEO is able to converge to ensemble solutions for systems that are more complicated than diatomic carbon.
Rosić, Miroslav; Pešić, Dalibor; Kukić, Dragoslav; Antić, Boris; Božović, Milan
2017-01-01
Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine "real best performers". Need for composite road safety index is becoming dominant since road safety presents a complex system where more and more indicators are constantly being developed to describe it. Among wide variety of models and developed composite indexes, a decision maker can come to even bigger dilemma than choosing one adequate risk measure. As DEA and TOPSIS are well-known mathematical models and have recently been increasingly used for risk evaluation in road safety, we used efficiencies (composite indexes) obtained by different models, based on DEA and TOPSIS, to present PROMETHEE-RS model for selection of optimal method for composite index. Method for selection of optimal composite index is based on three parameters (average correlation, average rank variation and average cluster variation) inserted into a PROMETHEE MCDM method in order to choose the optimal one. The model is tested by comparing 27 police departments in Serbia. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cutting Edge: Piezo1 Mechanosensors Optimize Human T Cell Activation.
Liu, Chinky Shiu Chen; Raychaudhuri, Deblina; Paul, Barnali; Chakrabarty, Yogaditya; Ghosh, Amrit Raj; Rahaman, Oindrila; Talukdar, Arindam; Ganguly, Dipyaman
2018-02-15
TCRs recognize peptides on MHC molecules and induce downstream signaling, leading to activation and clonal expansion. In addition to the strength of the interaction of TCRs with peptides on MHC molecules, mechanical forces contribute to optimal T cell activation, as reflected by the superior efficiency of immobilized TCR-cross-linking Abs compared with soluble Abs in TCR triggering, although a dedicated mechanotransduction module is not identified. We found that the professional mechanosensor protein Piezo1 is critically involved in human T cell activation. Although a deficiency in Piezo1 attenuates downstream events on ex vivo TCR triggering, a Piezo1 agonist can obviate the need to immobilize TCR-cross-linking Abs. Piezo1-driven Ca 2+ influx, leading to calpain activation and organization of cortical actin scaffold, links this mechanosensor to optimal TCR signaling. Thus, we discovered a hitherto unknown regulatory mechanism for human T cell activation and provide the first evidence, to our knowledge, for the involvement of Piezo1 mechanosensors in immune regulation. Copyright © 2018 by The American Association of Immunologists, Inc.
Methods and tools for analysis and optimization of power plants
Energy Technology Data Exchange (ETDEWEB)
Assadi, Mohsen
2000-09-01
The most noticeable advantage of the introduction of the computer-aided tools in the field of power generation, has been the ability to study the plant's performance prior to the construction phase. The results of these studies have made it possible to change and adjust the plant layout to match the pre-defined requirements. Further development of computers in recent years has opened up for implementation of new features in the existing tools and also for the development of new tools for specific applications, like thermodynamic and economic optimization, prediction of the remaining component life time, and fault diagnostics, resulting in improvement of the plant's performance, availability and reliability. The most common tools for pre-design studies are heat and mass balance programs. Further thermodynamic and economic optimization of plant layouts, generated by the heat and mass balance programs, can be accomplished by using pinch programs, exergy analysis and thermoeconomics. Surveillance and fault diagnostics of existing systems can be performed by using tools like condition monitoring systems and artificial neural networks. The increased number of tools and their various construction and application areas make the choice of the most adequate tool for a certain application difficult. In this thesis the development of different categories of tools and techniques, and their application area are reviewed and presented. Case studies on both existing and theoretical power plant layouts have been performed using different commercially available tools to illuminate their advantages and shortcomings. The development of power plant technology and the requirements for new tools and measurement systems have been briefly reviewed. This thesis contains also programming techniques and calculation methods concerning part-load calculations using local linearization, which has been implemented in an inhouse heat and mass balance program developed by the author
Optimal Control with Time Delays via the Penalty Method
Directory of Open Access Journals (Sweden)
Mohammed Benharrat
2014-01-01
Full Text Available We prove necessary optimality conditions of Euler-Lagrange type for a problem of the calculus of variations with time delays, where the delay in the unknown function is different from the delay in its derivative. Then, a more general optimal control problem with time delays is considered. Main result gives a convergence theorem, allowing us to obtain a solution to the delayed optimal control problem by considering a sequence of delayed problems of the calculus of variations.
Optimal Homotopy Asymptotic Method for Solving System of Fredholm Integral Equations
Directory of Open Access Journals (Sweden)
Bahman Ghazanfari
2013-08-01
Full Text Available In this paper, optimal homotopy asymptotic method (OHAM is applied to solve system of Fredholm integral equations. The effectiveness of optimal homotopy asymptotic method is presented. This method provides easy tools to control the convergence region of approximating solution series wherever necessary. The results of OHAM are compared with homotopy perturbation method (HPM and Taylor series expansion method (TSEM.
Flow shop scheduling algorithm to optimize warehouse activities
Directory of Open Access Journals (Sweden)
P. Centobelli
2016-01-01
Full Text Available Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.
GMI Instrument Spin Balance Method, Optimization, Calibration, and Test
Ayari, Laoucet; Kubitschek, Michael; Ashton, Gunnar; Johnston, Steve; Debevec, Dave; Newell, David; Pellicciotti, Joseph
2014-01-01
The Global Microwave Imager (GMI) instrument must spin at a constant rate of 32 rpm continuously for the 3 year mission life. Therefore, GMI must be very precisely balanced about the spin axis and CG to maintain stable scan pointing and to minimize disturbances imparted to the spacecraft and attitude control on-orbit. The GMI instrument is part of the core Global Precipitation Measurement (GPM) spacecraft and is used to make calibrated radiometric measurements at multiple microwave frequencies and polarizations. The GPM mission is an international effort managed by the National Aeronautics and Space Administration (NASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and frequent precipitation measurements. Ball Aerospace and Technologies Corporation (BATC) was selected by NASA Goddard Space Flight Center to design, build, and test the GMI instrument. The GMI design has to meet a challenging set of spin balance requirements and had to be brought into simultaneous static and dynamic spin balance after the entire instrument was already assembled and before environmental tests began. The focus of this contribution is on the analytical and test activities undertaken to meet the challenging spin balance requirements of the GMI instrument. The novel process of measuring the residual static and dynamic imbalances with a very high level of accuracy and precision is presented together with the prediction of the optimal balance masses and their locations.
Heyden, Andreas; Bell, Alexis T; Keil, Frerich J
2005-12-08
A combination of interpolation methods and local saddle-point search algorithms is probably the most efficient way of finding transition states in chemical reactions. Interpolation methods such as the growing-string method and the nudged-elastic band are able to find an approximation to the minimum-energy pathway and thereby provide a good initial guess for a transition state and imaginary mode connecting both reactant and product states. Since interpolation methods employ usually just a small number of configurations and converge slowly close to the minimum-energy pathway, local methods such as partitioned rational function optimization methods using either exact or approximate Hessians or minimum-mode-following methods such as the dimer or the Lanczos method have to be used to converge to the transition state. A modification to the original dimer method proposed by [Henkelman and Jonnson J. Chem. Phys. 111, 7010 (1999)] is presented, reducing the number of gradient calculations per cycle from six to four gradients or three gradients and one energy, and significantly improves the overall performance of the algorithm on quantum-chemical potential-energy surfaces, where forces are subject to numerical noise. A comparison is made between the dimer methods and the well-established partitioned rational function optimization methods for finding transition states after the use of interpolation methods. Results for 24 different small- to medium-sized chemical reactions covering a wide range of structural types demonstrate that the improved dimer method is an efficient alternative saddle-point search algorithm on medium-sized to large systems and is often even able to find transition states when partitioned rational function optimization methods fail to converge.
Directory of Open Access Journals (Sweden)
Petr Maca
2014-01-01
Full Text Available The presented paper aims to analyze the influence of the selection of transfer function and training algorithms on neural network flood runoff forecast. Nine of the most significant flood events, caused by the extreme rainfall, were selected from 10 years of measurement on small headwater catchment in the Czech Republic, and flood runoff forecast was investigated using the extensive set of multilayer perceptrons with one hidden layer of neurons. The analyzed artificial neural network models with 11 different activation functions in hidden layer were trained using 7 local optimization algorithms. The results show that the Levenberg-Marquardt algorithm was superior compared to the remaining tested local optimization methods. When comparing the 11 nonlinear transfer functions, used in hidden layer neurons, the RootSig function was superior compared to the rest of analyzed activation functions.
Fan, Sanhong; Hu, Yanan; Li, Chen; Liu, Yanrong
2014-01-01
Protein isolates of pumpkin (Cucurbita pepo L) seeds were hydrolyzed by acid protease to prepare antioxidative peptides. The hydrolysis conditions were optimized through Box-Behnken experimental design combined with response surface method (RSM). The second-order model, developed for the DPPH radical scavenging activity of pumpkin seed hydrolysates, showed good fit with the experiment data with a high value of coefficient of determination (0.9918). The optimal hydrolysis conditions were determined as follows: hydrolyzing temperature 50°C, pH 2.5, enzyme amount 6000 U/g, substrate concentration 0.05 g/ml and hydrolyzing time 5 h. Under the above conditions, the scavenging activity of DPPH radical was as high as 92.82%. PMID:24637721
Networked and Distributed Control Method with Optimal Power Dispatch for Islanded Microgrids
DEFF Research Database (Denmark)
Li, Qiang; Peng, Congbo; Chen, Minyou
2017-01-01
In this paper, a two-layer network and distributed control method is proposed, where there is a top layer communication network over a bottom layer microgrid. The communication network consists of two subgraphs, in which the first is composed of all agents, while the second is only composed...... of controllable agents. The distributed control laws derived from the first subgraph guarantee the supply-demand balance, while further control laws from the second subgraph reassign the outputs of controllable distributed generators, which ensure active and reactive power are dispatched optimally. However......, for reducing the number of edges in the second subgraph, generally a simpler graph instead of a fully connected graph is adopted. In this case, a near-optimal dispatch of active and reactive power can be obtained gradually, only if controllable agents on the second subgraph calculate set points iteratively...
Zhang, Bo; Sun, Jiwei; Wang, Qin; Fan, Niansi; Ni, Jialing; Li, Weicheng; Gao, Yingxin; Li, Yu-You; Xu, Changyou
2017-10-01
The electro-Fenton treatment of coking wastewater was evaluated experimentally in a batch electrochemical reactor. Based on central composite design coupled with response surface methodology, a regression quadratic equation was developed to model the total organic carbon (TOC) removal efficiency. This model was further proved to accurately predict the optimization of process variables by means of analysis of variance. With the aid of the convex optimization method, which is a global optimization method, the optimal parameters were determined as current density of 30.9 mA/cm 2 , Fe 2+ concentration of 0.35 mg/L, and pH of 4.05. Under the optimized conditions, the corresponding TOC removal efficiency was up to 73.8%. The maximum TOC removal efficiency achieved can be further confirmed by the results of gas chromatography-mass spectrum analysis.
Influence of Pareto optimality on the maximum entropy methods
Peddavarapu, Sreehari; Sunil, Gujjalapudi Venkata Sai; Raghuraman, S.
2017-07-01
Galerkin meshfree schemes are emerging as a viable substitute to finite element method to solve partial differential equations for the large deformations as well as crack propagation problems. However, the introduction of Shanon-Jayne's entropy principle in to the scattered data approximation has deviated from the trend of defining the approximation functions, resulting in maximum entropy approximants. Further in addition to this, an objective functional which controls the degree of locality resulted in Local maximum entropy approximants. These are based on information-theoretical Pareto optimality between entropy and degree of locality that are defining the basis functions to the scattered nodes. The degree of locality in turn relies on the choice of locality parameter and prior (weight) function. The proper choices of both plays vital role in attain the desired accuracy. Present work is focused on the choice of locality parameter which defines the degree of locality and priors: Gaussian, Cubic spline and quartic spline functions on the behavior of local maximum entropy approximants.
Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods
Directory of Open Access Journals (Sweden)
Saadia Zahid
2015-01-01
Full Text Available Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount of training data, which handles noise and is suitable for use for real-time applications. Noise in an audio stream is segmented out as environment sound. A hybrid classification approach is used, bagged support vector machines (SVMs with artificial neural networks (ANNs. Audio stream is classified, firstly, into speech and nonspeech segment by using bagged support vector machines; nonspeech segment is further classified into music and environment sound by using artificial neural networks and lastly, speech segment is classified into silence and pure-speech segments on the basis of rule-based classifier. Minimum data is used for training classifier; ensemble methods are used for minimizing misclassification rate and approximately 98% accurate segments are obtained. A fast and efficient algorithm is designed that can be used with real-time multimedia applications.
Analysis of the Criteria of Activation-Based Inverse Electrocardiography using Convex Optimization
Erem, Burak; van Dam, Peter M.; Brooks, Dana H.
2012-01-01
In inverse electrocardiography (ECG), the problem of finding activation times on the heart noninvasively from body surface potentials is typically formulated as a nonlinear least squares optimization problem. Current solutions rely on iterative algorithms which are sensitive to the presence of local minima. As a result, improved initialization approaches for this problem have been of considerable interest. However, in experiments conducted on a subject with Wolff-Parkinson-White syndrome, we have observed that there may be a mismatch between favorable solutions of the optimization problem and solutions with the desired physiological characteristics. In this work, we use a method based on a convex optimization framework to explore the solution space and analyze whether the optimization criteria target their intended objective. PMID:22255195
Optimism predicts sustained vigorous physical activity in postmenopausal women
Directory of Open Access Journals (Sweden)
Ana M. Progovac
2017-12-01
Full Text Available Optimism and cynical hostility are associated with health behaviors and health outcomes, including morbidity and mortality. This analysis assesses their association with longitudinal vigorous physical activity (PA in postmenopausal women of the Women's Health Initiative (WHI. Subjects include 73,485 women nationwide without history of cancer or cardiovascular disease (CVD, and no missing baseline optimism, cynical hostility, or PA data. The Life Orientation Test-Revised Scale measured optimism. A Cook Medley questionnaire subscale measured cynical hostility. Scale scores were divided into quartiles. Vigorous PA three times or more per week was assessed via self-report at study baseline (1994–1998 and through follow-up year 6. Descriptive analysis mapped lifetime trajectories of vigorous PA (recalled at ages 18, 25, 50; prospectively assessed at baseline, and 3 and 6 years later. Hierarchical generalized linear mixed models examined the prospective association between optimism, cynical hostility, and vigorous PA over 6 years. Models adjusted for baseline sociodemographic variables, psychosocial characteristics, and health conditions and behaviors. Vigorous PA rates were highest for most optimistic women, but fell for all women by approximately 60% between age 50 and study baseline. In adjusted models from baseline through year 6, most vs. least optimistic women were 15% more likely to exercise vigorously (p < 0.001. Cynical hostility was not associated with lower odds of longitudinal vigorous PA after adjustment. Results did not differ by race/ethnicity or socioeconomic status. Higher optimism is associated with maintaining vigorous PA over time in post-menopausal women, and may protect women's health over the lifespan.
Reinforcement active learning in the vibrissae system: optimal object localization.
Gordon, Goren; Dorfman, Nimrod; Ahissar, Ehud
2013-01-01
Rats move their whiskers to acquire information about their environment. It has been observed that they palpate novel objects and objects they are required to localize in space. We analyze whisker-based object localization using two complementary paradigms, namely, active learning and intrinsic-reward reinforcement learning. Active learning algorithms select the next training samples according to the hypothesized solution in order to better discriminate between correct and incorrect labels. Intrinsic-reward reinforcement learning uses prediction errors as the reward to an actor-critic design, such that behavior converges to the one that optimizes the learning process. We show that in the context of object localization, the two paradigms result in palpation whisking as their respective optimal solution. These results suggest that rats may employ principles of active learning and/or intrinsic reward in tactile exploration and can guide future research to seek the underlying neuronal mechanisms that implement them. Furthermore, these paradigms are easily transferable to biomimetic whisker-based artificial sensors and can improve the active exploration of their environment. Copyright © 2012 Elsevier Ltd. All rights reserved.
Physical activity and optimal self-rated health of adults with and without diabetes
Directory of Open Access Journals (Sweden)
Balluz Lina S
2010-06-01
Full Text Available Abstract Background Regular physical activity can improve people's overall health and contribute to both primary and secondary prevention of many chronic diseases and conditions including diabetes. The aim of this study was to examine the association between levels of physical activity and optimal self-rated health (SRH of U.S. adults with and without diabetes in all 50 states and territories of the Unites States. Methods We estimated the prevalence of optimal SRH by diabetes status of 430,912 adults aged 18 years and older who participated in the 2007 state-based survey of the Behavioral Risk Factor Surveillance System (BRFSS. Prevalence ratios were produced with multivariate Cox regression models using levels of physical activity as a predictor and status of optimal SRH as an outcome variable while controlling for sociodemographic and behavioral health risk factors. Results The prevalence of reporting optimal SRH was 53.3%, 52.2%, and 86.2% for adults with type 1 diabetes, type 2 diabetes, and without diabetes, respectively. Also in the aforementioned order, adults who reported being active had an increased likelihood of 81%, 32%, and 18% for reporting optimal SRH, when compared with adults who reported being inactive. Conclusions Regular physical activity of adults, particularly adults with diabetes, is associated with optimal SRH. The findings of this study underscore the importance of advising and motivating adults with diabetes so that physical activity can be integrated into their lifestyle for diabetes care. Additionally, a population-based effort to promote physical activity in communities may benefit adults in general by improving their overall health and well-being.
Application of Taguchi method for cutting force optimization in rock
Indian Academy of Sciences (India)
In this paper, an optimization study was carried out for the cutting force (Fc) acting on circular diamond sawblades in rock sawing. The peripheral speed, traverse speed, cut depth and flow rate of cooling fluid were considered as operating variables and optimized by using Taguchi approach for the Fc. L16(44) orthogonal ...
Application of Taguchi method for cutting force optimization in rock ...
Indian Academy of Sciences (India)
In this paper, an optimization study was carried out for the cutting force (Fc) acting on circular diamond sawblades in rock sawing. The peripheral speed, traverse speed, cut depth and flow rate of cooling fluid were considered as operating variables and optimized by using Taguchi approach for the Fc. L16(44) orthogonal ...
Control Methods Utilizing Energy Optimizing Schemes in Refrigeration Systems
DEFF Research Database (Denmark)
Larsen, L.S; Thybo, C.; Stoustrup, Jakob
2003-01-01
The potential energy savings in refrigeration systems using energy optimal control has been proved to be substantial. This however requires an intelligent control that drives the refrigeration systems towards the energy optimal state. This paper proposes an approach for a control, which drives...
Laser: a Tool for Optimization and Enhancement of Analytical Methods
Energy Technology Data Exchange (ETDEWEB)
Preisler, Jan [Iowa State Univ., Ames, IA (United States)
1997-01-01
In this work, we use lasers to enhance possibilities of laser desorption methods and to optimize coating procedure for capillary electrophoresis (CE). We use several different instrumental arrangements to characterize matrix-assisted laser desorption (MALD) at atmospheric pressure and in vacuum. In imaging mode, 488-nm argon-ion laser beam is deflected by two acousto-optic deflectors to scan plumes desorbed at atmospheric pressure via absorption. All absorbing species, including neutral molecules, are monitored. Interesting features, e.g. differences between the initial plume and subsequent plumes desorbed from the same spot, or the formation of two plumes from one laser shot are observed. Total plume absorbance can be correlated with the acoustic signal generated by the desorption event. A model equation for the plume velocity as a function of time is proposed. Alternatively, the use of a static laser beam for observation enables reliable determination of plume velocities even when they are very high. Static scattering detection reveals negative influence of particle spallation on MS signal. Ion formation during MALD was monitored using 193-nm light to photodissociate a portion of insulin ion plume. These results define the optimal conditions for desorbing analytes from matrices, as opposed to achieving a compromise between efficient desorption and efficient ionization as is practiced in mass spectrometry. In CE experiment, we examined changes in a poly(ethylene oxide) (PEO) coating by continuously monitoring the electroosmotic flow (EOF) in a fused-silica capillary during electrophoresis. An imaging CCD camera was used to follow the motion of a fluorescent neutral marker zone along the length of the capillary excited by 488-nm Ar-ion laser. The PEO coating was shown to reduce the velocity of EOF by more than an order of magnitude compared to a bare capillary at pH 7.0. The coating protocol was important, especially at an intermediate pH of 7.7. The increase of p
Is Peer Interaction Necessary for Optimal Active Learning?
Linton, Debra L; Farmer, Jan Keith; Peterson, Ernie
2014-01-01
Meta-analyses of active-learning research consistently show that active-learning techniques result in greater student performance than traditional lecture-based courses. However, some individual studies show no effect of active-learning interventions. This may be due to inexperienced implementation of active learning. To minimize the effect of inexperience, we should try to provide more explicit implementation recommendations based on research into the key components of effective active learning. We investigated the optimal implementation of active-learning exercises within a "lecture" course. Two sections of nonmajors biology were taught by the same instructor, in the same semester, using the same instructional materials and assessments. Students in one section completed in-class active-learning exercises in cooperative groups, while students in the other section completed the same activities individually. Performance on low-level, multiple-choice assessments was not significantly different between sections. However, students who worked in cooperative groups on the in-class activities significantly outperformed students who completed the activities individually on the higher-level, extended-response questions. Our results provide additional evidence that group processing of activities should be the recommended mode of implementation for in-class active-learning exercises. © 2014 D. L. Linton et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Muscat Galea, Charlene; Didion, David; Clicq, David; Mangelings, Debby; Vander Heyden, Yvan
2017-12-01
A supercritical chromatographic method for the separation of a drug and its impurities has been developed and optimized applying an experimental design approach and chromatogram simulations. Stationary phase screening was followed by optimization of the modifier and injection solvent composition. A design-of-experiment (DoE) approach was then used to optimize column temperature, back-pressure and the gradient slope simultaneously. Regression models for the retention times and peak widths of all mixture components were built. The factor levels for different grid points were then used to predict the retention times and peak widths of the mixture components using the regression models and the best separation for the worst separated peak pair in the experimental domain was identified. A plot of the minimal resolutions was used to help identifying the factor levels leading to the highest resolution between consecutive peaks. The effects of the DoE factors were visualized in a way that is familiar to the analytical chemist, i.e. by simulating the resulting chromatogram. The mixture of an active ingredient and seven impurities was separated in less than eight minutes. The approach discussed in this paper demonstrates how SFC methods can be developed and optimized efficiently using simple concepts and tools. Copyright © 2017 Elsevier B.V. All rights reserved.
A calorimetric method to determine water activity.
Björklund, Sebastian; Wadsö, Lars
2011-11-01
A calorimetric method to determine water activity covering the full range of the water activity scale is presented. A dry stream of nitrogen gas is passed either over the solution whose activity should be determined or left dry before it is saturated by bubbling through water in an isothermal calorimeter. The unknown activity is in principle determined by comparing the thermal power of vaporization related to the gas stream with unknown activity to that with zero activity. Except for three minor corrections (for pressure drop, non-perfect humidification, and evaporative cooling) the unknown water activity is calculated solely based on the water activity end-points zero and unity. Thus, there is no need for calibration with references with known water activities. The method has been evaluated at 30 °C by measuring the water activity of seven aqueous sodium chloride solutions ranging from 0.1 mol kg(-1) to 3 mol kg(-1) and seven saturated aqueous salt solutions (LiCl, MgCl(2), NaBr, NaCl, KCl, KNO(3), and K(2)SO(4)) with known water activities. The performance of the method was adequate over the complete water activity scale. At high water activities the performance was excellent, which is encouraging as many other methods used for water activity determination have limited performance at high water activities. © 2011 American Institute of Physics
Activation of Students with Various Teaching Methods
DEFF Research Database (Denmark)
Andersen, Shuang Ma
2011-01-01
A group of teaching methodes to active engineer students have been tried out. The methodes are developed based on the Pedagogical Cyclic Workflow (PCW). Comparing with earlier evaluation, positive feedback is achieved among the students.......A group of teaching methodes to active engineer students have been tried out. The methodes are developed based on the Pedagogical Cyclic Workflow (PCW). Comparing with earlier evaluation, positive feedback is achieved among the students....
Directory of Open Access Journals (Sweden)
Zhengnan Li
2016-01-01
Full Text Available To solve the multiobjective optimization problem on hypersonic glider vehicle trajectory design subjected to complex constraints, this paper proposes a multiobjective trajectory optimization method that combines the boundary intersection method and pseudospectral method. The multiobjective trajectory optimization problem (MTOP is established based on the analysis of the feature of hypersonic glider vehicle trajectory. The MTOP is translated into a set of general optimization subproblems by using the boundary intersection method and pseudospectral method. The subproblems are solved by nonlinear programming algorithm. In this method, the solution that has been solved is employed as the initial guess for the next subproblem so that the time consumption of the entire multiobjective trajectory optimization problem shortens. The maximal range and minimal peak heat problem is solved by the proposed method. The numerical results demonstrate that the proposed method can obtain the Pareto front of the optimal trajectory, which can provide the reference for the trajectory design of hypersonic glider vehicle.
Directory of Open Access Journals (Sweden)
ZHANG Hao
2017-06-01
Full Text Available With waste walnut shell as raw material, biomass based porous active carbon was made by microwave oven method. The effects of microwave power, activation time and mass fraction of phosphoric acid on adsorptive property of biomass based porous active carbon in the process of physical activation of active carbon precursor were studied by response surface method and numerical simulation method, the preparation plan of biomass based porous active carbon was optimized, and the optimal biomass based porous active carbon property was characterized. The results show that three factors affect the adsorptive property of biomass based porous active carbon, but the effect of microwave power is obviously more significant than that of mass fraction of phosphoric acid, and the effect of mass fraction of phosphoric acid is more significant than that of activation time. The optimized preparation conditions are:microwave power is 746W, activation time is 11.2min and mass fraction of phosphoric acid is 85.9% in the process of physical activation of activated carbon precursor by microwave heating method. For the optimal biomass based porous active carbon, the adsorption value of iodine is 1074.57mg/g, adsorption value of methylene blue is 294.4mL/g and gain rate is 52.1%.
DEFF Research Database (Denmark)
Le, T.H.A.; Pham, D. T.; Canh, Nam Nguyen
2010-01-01
Both the efficient and weakly efficient sets of an affine fractional vector optimization problem, in general, are neither convex nor given explicitly. Optimization problems over one of these sets are thus nonconvex. We propose two methods for optimizing a real-valued function over the efficient...... and weakly efficient sets of an affine fractional vector optimization problem. The first method is a local one. By using a regularization function, we reformulate the problem into a standard smooth mathematical programming problem that allows applying available methods for smooth programming. In case...... the objective function is linear, we have investigated a global algorithm based upon a branch-and-bound procedure. The algorithm uses Lagrangian bound coupling with a simplicial bisection in the criteria space. Preliminary computational results show that the global algorithm is promising....
Analyses of Methods and Algorithms for Modelling and Optimization of Biotechnological Processes
Directory of Open Access Journals (Sweden)
Stoyan Stoyanov
2009-08-01
Full Text Available A review of the problems in modeling, optimization and control of biotechnological processes and systems is given in this paper. An analysis of existing and some new practical optimization methods for searching global optimum based on various advanced strategies - heuristic, stochastic, genetic and combined are presented in the paper. Methods based on the sensitivity theory, stochastic and mix strategies for optimization with partial knowledge about kinetic, technical and economic parameters in optimization problems are discussed. Several approaches for the multi-criteria optimization tasks are analyzed. The problems concerning optimal controls of biotechnological systems are also discussed.
Models and Methods for Structural Topology Optimization with Discrete Design Variables
DEFF Research Database (Denmark)
Stolpe, Mathias
Structural topology optimization is a multi-disciplinary research field covering optimal design of load carrying mechanical structures such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used...... such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used in the conceptual design phase to find innovative designs. The strength of topology optimization is the capability of determining both the optimal...
Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method
Chen, Xiaomin; Wang, Gang
2017-05-01
The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.
Iron Pole Shape Optimization of IPM Motors Using an Integrated Method
Directory of Open Access Journals (Sweden)
JABBARI, A.
2010-02-01
Full Text Available An iron pole shape optimization method to reduce cogging torque in Interior Permanent Magnet (IPM motors is developed by using the reduced basis technique coupled by finite element and design of experiments methods. Objective function is defined as the minimum cogging torque. The experimental design of Taguchi method is used to build the approximation model and to perform optimization. This method is demonstrated on the rotor pole shape optimization of a 4-poles/24-slots IPM motor.
Aeromechanics of an Optimized, Actively-Morphing Rotor System
2013-09-17
wind tunnel tests as well as a good description of the rotor geometry. UMARC has been validated...Morphing rotor final report: N000140911921 (Chopra, UMD) Graham Bowen-‐Davies 9/4/2013 Final Progress Report...on “Aeromechanics of an Optimized, Actively-Morphing Rotor System” to Office Naval Research Air Vehicle Technology
Optimizing process and equipment efficiency using integrated methods
D'Elia, Michael J.; Alfonso, Ted F.
1996-09-01
The semiconductor manufacturing industry is continually riding the edge of technology as it tries to push toward higher design limits. Mature fabs must cut operating costs while increasing productivity to remain profitable and cannot justify large capital expenditures to improve productivity. Thus, they must push current tool production capabilities to cut manufacturing costs and remain viable. Working to continuously improve mature production methods requires innovation. Furthermore, testing and successful implementation of these ideas into modern production environments require both supporting technical data and commitment from those working with the process daily. At AMD, natural work groups (NWGs) composed of operators, technicians, engineers, and supervisors collaborate to foster innovative thinking and secure commitment. Recently, an AMD NWG improved equipment cycle time on the Genus tungsten silicide (WSi) deposition system. The team used total productive manufacturing (TPM) to identify areas for process improvement. Improved in-line equipment monitoring was achieved by constructing a real time overall equipment effectiveness (OEE) calculator which tracked equipment down, idle, qualification, and production times. In-line monitoring results indicated that qualification time associated with slow Inspex turn-around time and machine downtime associated with manual cleans contributed greatly to reduced availability. Qualification time was reduced by 75% by implementing a new Inspex monitor pre-staging technique. Downtime associated with manual cleans was reduced by implementing an in-situ plasma etch back to extend the time between manual cleans. A designed experiment was used to optimize the process. Time between 18 hour manual cleans has been improved from every 250 to every 1500 cycles. Moreover defect density realized a 3X improvement. Overall, the team achieved a 35% increase in tool availability. This paper details the above strategies and accomplishments.
An optimized method for mouse liver sinusoidal endothelial cell isolation
Energy Technology Data Exchange (ETDEWEB)
Meyer, Jeremy, E-mail: jeremy.meyer@hcuge.ch [Division of Digestive and Transplantation Surgery, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil 4, 1211 Genève 14 (Switzerland); Unit of Surgical Research, University of Geneva, Rue Michel-Servet 1, 1206 Genève (Switzerland); Lacotte, Stéphanie, E-mail: stephanie.lacotte@unige.ch [Unit of Surgical Research, University of Geneva, Rue Michel-Servet 1, 1206 Genève (Switzerland); Morel, Philippe, E-mail: philippe.morel@hcuge.ch [Division of Digestive and Transplantation Surgery, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil 4, 1211 Genève 14 (Switzerland); Unit of Surgical Research, University of Geneva, Rue Michel-Servet 1, 1206 Genève (Switzerland); Gonelle-Gispert, Carmen, E-mail: carmen.gonelle@unige.ch [Unit of Surgical Research, University of Geneva, Rue Michel-Servet 1, 1206 Genève (Switzerland); Bühler, Léo, E-mail: leo.buhler@hcuge.ch [Division of Digestive and Transplantation Surgery, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil 4, 1211 Genève 14 (Switzerland); Unit of Surgical Research, University of Geneva, Rue Michel-Servet 1, 1206 Genève (Switzerland)
2016-12-10
The objective of the present study was to develop an accurate and reproducible method for liver sinusoidal endothelial cell (LSEC) isolation in mice. Non-parenchymal cells were isolated using a modified two-step collagenase digestion combined with Optiprep density gradient centrifugation. LSEC were further purified using two prevalent methods, short-term selective adherence and CD146+ magnetic-activated cell sorting (MACS), and compared in terms of cell yield, viability and purity to our purification technique using CD11b cell depletion combined with long-term selective adherence. LSEC purification using our technique allowed to obtain 7.07±3.80 million LSEC per liver, while CD146+ MACS and short-term selective adherence yielded 2.94±1.28 and 0.99±0.66 million LSEC, respectively. Purity of the final cell preparation reached 95.10±2.58% when using our method. In contrast, CD146+ MACS and short-term selective adherence gave purities of 86.75±3.26% and 47.95±9.82%, respectively. Similarly, contamination by non-LSEC was the lowest when purification was performed using our technique, with a proportion of contaminating macrophages of only 1.87±0.77%. Further, isolated cells analysed by scanning electron microscopy presented typical LSEC fenestrations organized in sieve plates, demonstrating that the technique allowed to isolate bona fide LSEC. In conclusion, we described a reliable and reproducible technique for the isolation of high yields of pure LSEC in mice. This protocol provides an efficient method to prepare LSEC for studying their biological functions. - Highlights: • This protocol provides an efficient method to prepare primary mouse LSEC for studying their biological functions. • The liver cell dispersion step was improved by performing a retrograde cannulation of the liver. • The cell yield and the purity obtained were higher than comparative techniques in mice. • Contaminating macrophages were removed by introducing a CD11b- magnetic –activated
A new method to optimize natural convection heat sinks
Lampio, K.; Karvinen, R.
2017-08-01
The performance of a heat sink cooled by natural convection is strongly affected by its geometry, because buoyancy creates flow. Our model utilizes analytical results of forced flow and convection, and only conduction in a solid, i.e., the base plate and fins, is solved numerically. Sufficient accuracy for calculating maximum temperatures in practical applications is proved by comparing the results of our model with some simple analytical and computational fluid dynamics (CFD) solutions. An essential advantage of our model is that it cuts down on calculation CPU time by many orders of magnitude compared with CFD. The shorter calculation time makes our model well suited for multi-objective optimization, which is the best choice for improving heat sink geometry, because many geometrical parameters with opposite effects influence the thermal behavior. In multi-objective optimization, optimal locations of components and optimal dimensions of the fin array can be found by simultaneously minimizing the heat sink maximum temperature, size, and mass. This paper presents the principles of the particle swarm optimization (PSO) algorithm and applies it as a basis for optimizing existing heat sinks.
Active teaching methods, studying responses and learning
DEFF Research Database (Denmark)
Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain
2010-01-01
Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed....
Active teaching methods, studying responses and learning
DEFF Research Database (Denmark)
Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain
Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching....
Development of Combinatorial Methods for Alloy Design and Optimization
International Nuclear Information System (INIS)
Pharr, George M.; George, Easo P.; Santella, Michael L
2005-01-01
The primary goal of this research was to develop a comprehensive methodology for designing and optimizing metallic alloys by combinatorial principles. Because conventional techniques for alloy preparation are unavoidably restrictive in the range of alloy composition that can be examined, combinatorial methods promise to significantly reduce the time, energy, and expense needed for alloy design. Combinatorial methods can be developed not only to optimize existing alloys, but to explore and develop new ones as well. The scientific approach involved fabricating an alloy specimen with a continuous distribution of binary and ternary alloy compositions across its surface--an ''alloy library''--and then using spatially resolved probing techniques to characterize its structure, composition, and relevant properties. The three specific objectives of the project were: (1) to devise means by which simple test specimens with a library of alloy compositions spanning the range interest can be produced; (2) to assess how well the properties of the combinatorial specimen reproduce those of the conventionally processed alloys; and (3) to devise screening tools which can be used to rapidly assess the important properties of the alloys. As proof of principle, the methodology was applied to the Fe-Ni-Cr ternary alloy system that constitutes many commercially important materials such as stainless steels and the H-series and C-series heat and corrosion resistant casting alloys. Three different techniques were developed for making alloy libraries: (1) vapor deposition of discrete thin films on an appropriate substrate and then alloying them together by solid-state diffusion; (2) co-deposition of the alloying elements from three separate magnetron sputtering sources onto an inert substrate; and (3) localized melting of thin films with a focused electron-beam welding system. Each of the techniques was found to have its own advantages and disadvantages. A new and very powerful technique for
Development of Combinatorial Methods for Alloy Design and Optimization
Energy Technology Data Exchange (ETDEWEB)
Pharr, George M.; George, Easo P.; Santella, Michael L
2005-07-01
The primary goal of this research was to develop a comprehensive methodology for designing and optimizing metallic alloys by combinatorial principles. Because conventional techniques for alloy preparation are unavoidably restrictive in the range of alloy composition that can be examined, combinatorial methods promise to significantly reduce the time, energy, and expense needed for alloy design. Combinatorial methods can be developed not only to optimize existing alloys, but to explore and develop new ones as well. The scientific approach involved fabricating an alloy specimen with a continuous distribution of binary and ternary alloy compositions across its surface--an ''alloy library''--and then using spatially resolved probing techniques to characterize its structure, composition, and relevant properties. The three specific objectives of the project were: (1) to devise means by which simple test specimens with a library of alloy compositions spanning the range interest can be produced; (2) to assess how well the properties of the combinatorial specimen reproduce those of the conventionally processed alloys; and (3) to devise screening tools which can be used to rapidly assess the important properties of the alloys. As proof of principle, the methodology was applied to the Fe-Ni-Cr ternary alloy system that constitutes many commercially important materials such as stainless steels and the H-series and C-series heat and corrosion resistant casting alloys. Three different techniques were developed for making alloy libraries: (1) vapor deposition of discrete thin films on an appropriate substrate and then alloying them together by solid-state diffusion; (2) co-deposition of the alloying elements from three separate magnetron sputtering sources onto an inert substrate; and (3) localized melting of thin films with a focused electron-beam welding system. Each of the techniques was found to have its own advantages and disadvantages. A new and very
Musci, Marilena; Yao, Shicong
2017-12-01
Pu-erh tea is a post-fermented tea that has recently gained popularity worldwide, due to potential health benefits related to the antioxidant activity resulting from its high polyphenolic content. The Folin-Ciocalteu method is a simple, rapid, and inexpensive assay widely applied for the determination of total polyphenol content. Over the past years, it has been subjected to many modifications, often without any systematic optimization or validation. In our study, we sought to optimize the Folin-Ciocalteu method, evaluate quality parameters including linearity, precision and stability, and then apply the optimized model to determine the total polyphenol content of 57 Chinese teas, including green tea, aged and ripened Pu-erh tea. Our optimized Folin-Ciocalteu method reduced analysis time, allowed for the analysis of a large number of samples, to discriminate among the different teas, and to assess the effect of the post-fermentation process on polyphenol content.
Optimal active recovery intensity in standardbreds after submaximal work.
Dahl, S; Cotrel, C; Leleu, C
2006-08-01
A retrospective study concerning spontaneous active recovery intensity, i.e. at a freely chosen speed, after a submaximal exercise in trotters showed that the mean intensity demanded by trainers corresponds to 40-50% of maximal heart rate (max HR; unpublished data). However, in human athletes, optimal active recovery intensity was found to be about 60-70% of max HR. Is the spontaneous recovery optimal after a submaximal exercise in trotters? To compare different recovery intensities and define the most efficient one. Thirty-seven trotters performed a standardised exercise test on the track. Horses were randomly divided into 4 groups of recovery: passive recovery (n = 10), 10 min walk recovery (n = 10, 100 m/min), 10 min slow trot recovery (n = 9, 250 m/min) and 10 min fast trot recovery (n = 8, 420 m/min). Before, during and 1 h after exercise, speed, heart rate, blood lactate concentration were measured as well as respiratory frequency and rectal temperature. Creatine kinase (CK) was measured 1, 3 and 5 h after exercise. Walk, slow trot and fast trot recovery corresponded respectively to 45-50%, 55-60% and 65-70% of max HR. Heart rate and blood lactate concentration were significantly lower after the 10 sec recovery with increasing intensity of recovery. The most efficient intensity of recovery was the 10 min fast trot recovery (65-70% max HR) as this type of recovery allows the optimal blood lactate disappearance. Considering the usual habits of trainers or drivers, recovery intensity after trot races should be increased in intensity to optimise its efficiency.
Directory of Open Access Journals (Sweden)
A. P. Karpenko
2014-01-01
Full Text Available We consider a class of stochastic search algorithms of global optimization which in various publications are called behavioural, intellectual, metaheuristic, inspired by the nature, swarm, multi-agent, population, etc. We use the last term.Experience in using the population algorithms to solve challenges of global optimization shows that application of one such algorithm may not always effective. Therefore now great attention is paid to hybridization of population algorithms of global optimization. Hybrid algorithms unite various algorithms or identical algorithms, but with various values of free parameters. Thus efficiency of one algorithm can compensate weakness of another.The purposes of the work are development of hybrid algorithm of global optimization based on known algorithms of harmony search (HS and swarm of particles (PSO, software implementation of algorithm, study of its efficiency using a number of known benchmark problems, and a problem of dimensional optimization of truss structure.We set a problem of global optimization, consider basic algorithms of HS and PSO, give a flow chart of the offered hybrid algorithm called PSO HS , present results of computing experiments with developed algorithm and software, formulate main results of work and prospects of its development.
Chenthamarakshan, Aiswarya; Parambayil, Nayana; Miziriya, Nafeesathul; Soumya, P S; Lakshmi, M S Kiran; Ramgopal, Anala; Dileep, Anuja; Nambisan, Padma
2017-02-13
Fungal laccase has profound applications in different fields of biotechnology due to its broad specificity and high redox potential. Any successful application of the enzyme requires large scale production. As laccase production is highly dependent on medium components and cultural conditions, optimization of the same is essential for efficient product production. Production of laccase by fungal strain Marasmiellus palmivorus LA1 under solid state fermentation was optimized by the Taguchi design of experiments (DOE) methodology. An orthogonal array (L8) was designed using Qualitek-4 software to study the interactions and relative influence of the seven selected factors by one factor at a time approach. The optimum condition formulated was temperature (28 °C), pH (5), galactose (0.8%w/v), cupric sulphate (3 mM), inoculum concentration (number of mycelial agar pieces) (6Nos.) and substrate length (0.05 m). Overall yield increase of 17.6 fold was obtained after optimization. Statistical optimization leads to the elimination of an insignificant medium component ammonium dihydrogen phosphate from the process and contributes to a 1.06 fold increase in enzyme production. A final production of 667.4 ± 13 IU/mL laccase activity paves way for the application of this strain for industrial applications. Study optimized lignin degrading laccases from Marasmiellus palmivorus LA1. This laccases can thus be used for further applications in different scales of production after analyzing the properties of the enzyme. Study also confirmed the use of taguchi method for optimizations of product production.
Optimal Bidding Strategy for Renewable Microgrid with Active Network Management
Directory of Open Access Journals (Sweden)
Seung Wan Kim
2016-01-01
Full Text Available Active Network Management (ANM enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG and Battery Energy Storage System (BESS units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.
Directory of Open Access Journals (Sweden)
Nan Nan
2017-10-01
Full Text Available Objective: To optimize the extraction and purification technologies of Gekko sulfated glycopeptide based on the content of glycopeptide, removal ratio of proteins, and anticancer activities. Methods: Different extraction methods, namely, water extraction, ultrasonic extraction, enzymatic hydrolysis-water extraction, and enzymatic hydrolysis-ultrasonic extraction were considered to determine the best extraction method. Single factor and orthogonal experiments were performed to determine the optimum extracting conditions. Sevage, enzymatic hydrolysis-Sevage, trichloroacetic acid (TCA, TCA-Sevage and enzymatic hydrolysis-TCA methods were tested to determine the best deproteinization method. The glycopeptide content and protein removal ratio were analyzed by the phenol-sulfuric acid and Coomassie Brilliant Blue methods. Results: Gekko sulfated glycopeptide obtained by water extraction could inhibit the proliferation of HepG2 and SKBR3, as well as promote that of lymphocytes. The glycopeptide content was 4.049% in the optimal extracting condition of a triple decoction extraction for 1 hour each time with a material to solvent ratio of 1:15. The enzymatic hydrolysis-TCA method was found to be the optimal deproteinization method, with a protein removal ratio of 50.46%, glycopeptide content of 14.27%, and inhibitory ratio on human HepG2 cells of 49.06%. Conclusion: This extraction and purification technique for Gekko sulfated glycopeptide is reasonable, feasible, and provides a scientific basis for industrial production.
International Nuclear Information System (INIS)
Wang, Shuang; Brigham, John C
2012-01-01
A proof-of-concept study is presented for a strategy to obtain maximally efficient and accurate morphing structures composed of active materials such as shape memory polymers (SMP) through synchronization of adaptable and localized activation and actuation. The work focuses on structures or structural components entirely composed of thermo-responsive SMP, and particularly utilizes the ability of such materials to display controllable variable stiffness. The study presents and employs a computational inverse mechanics approach that combines a computational representation of the SMP thermo-mechanical behavior with a nonlinear optimization algorithm to determine location, magnitude and sequencing of the activation and actuation to obtain a desired shape change subject to design objectives such as prevention of damage. Two numerical examples are presented in which the synchronization of the activation and actuation and the location of activation excitation were optimized with respect to the combined thermal and mechanical energy for design concepts in morphing skeletal structural components. In all cases the concept of localized activation along with the optimal design strategy were able to produce far more energy efficient morphing structures and more accurately reach the desired shape change in comparison to traditional methods that require complete structural activation prior to actuation. (paper)
DEFF Research Database (Denmark)
Justesen, Kristian Kjær; Andreasen, Søren Juhl
2015-01-01
In this work a method for choosing the optimal reformer temperature for a reformed methanol fuel cell system is presented based on a case study of a H3 350 module produced by Serenergy A/S. The method is based on ANFIS models of the dependence of the reformer output gas composition on the reforme...
Directory of Open Access Journals (Sweden)
Deep Pooja
2016-03-01
Full Text Available This data article contains the data related to the research article “Characterization, biorecognitive activity and stability of WGA grafted lipid nanostructures for the controlled delivery of rifampicin” (Pooja et al. 2015 [1]. In the present study, SLN were prepared by a single emulsification-solvent evaporation method and the various steps of SLN preparation are shown in a flow chart. The preparation of SLN was optimized for various formulation variables including type and quantity of lipid, surfactant, amount of co-surfactant and volume of organic phase. Similarly, effect of variables related to homogezation, sonication and stirring processes, on the size and surface potential of SLN was determined and optimized.
Intermediate levels of hippocampal activity appear optimal for associative memory formation.
Liu, X.; Qin, S.; Rijpkema, M.J.P.; Luo, J.; Fernandez, G.S.E.
2010-01-01
BACKGROUND: It is well established that hippocampal activity is positively related to effective associative memory formation. However, in biological systems often optimal levels of activity are contrasted by both sub- and supra-optimal levels. Sub-optimal levels of hippocampal activity are commonly
Optimization of Classical Hydraulic Engine Mounts Based on RMS Method
Directory of Open Access Journals (Sweden)
J. Christopherson
2005-01-01
Full Text Available Based on RMS averaging of the frequency response functions of the absolute acceleration and relative displacement transmissibility, optimal parameters describing the hydraulic engine mount are determined to explain the internal mount geometry. More specifically, it is shown that a line of minima exists to define a relationship between the absolute acceleration and relative displacement transmissibility of a sprung mass using a hydraulic mount as a means of suspension. This line of minima is used to determine several optimal systems developed on the basis of different clearance requirements, hence different relative displacement requirements, and compare them by means of their respective acceleration and displacement transmissibility functions. In addition, the transient response of the mount to a step input is also investigated to show the effects of the optimization upon the time domain response of the hydraulic mount.
International Nuclear Information System (INIS)
Jiang, Jianjun; Wang, Yiqun; Zhang, Li; Xie, Tian; Li, Min; Peng, Yuyuan; Wu, Daqing; Li, Peiyao; Ma, Congmin; Shen, Mengxu; Wu, Xing; Weng, Mengyun; Wang, Shiwei; Xie, Cen
2016-01-01
Highlights: • The authors present an optimization algorithm for interface task layout. • The performing process of the proposed algorithm was depicted. • The performance evaluation method adopted neural network method. • The optimization layouts of an event interface tasks were obtained by experiments. - Abstract: This is the last in a series of papers describing the optimal design for a digital human–computer interface of a nuclear power plant (NPP) from three different points based on human reliability. The purpose of this series is to propose different optimization methods from varying perspectives to decrease human factor events that arise from the defects of a human–computer interface. The present paper mainly solves the optimization method as to how to effectively layout interface tasks into different screens. The purpose of this paper is to decrease human errors by reducing the distance that an operator moves among different screens in each operation. In order to resolve the problem, the authors propose an optimization process of interface task layout for digital human–computer interface of a NPP. As to how to automatically layout each interface task into one of screens in each operation, the paper presents a shortest moving path optimization algorithm with dynamic flag based on human reliability. To test the algorithm performance, the evaluation method uses neural network based on human reliability. The less the human error probabilities are, the better the interface task layouts among different screens are. Thus, by analyzing the performance of each interface task layout, the optimization result is obtained. Finally, the optimization layouts of spurious safety injection event interface tasks of the NPP are obtained by an experiment, the proposed methods has a good accuracy and stabilization.
Optimal reliability design method for remote solar systems
Suwapaet, Nuchida
A unique optimal reliability design algorithm is developed for remote communication systems. The algorithm deals with either minimizing an unavailability of the system within a fixed cost or minimizing the cost of the system with an unavailability constraint. The unavailability of the system is a function of three possible failure occurrences: individual component breakdown, solar energy deficiency (loss of load probability), and satellite/radio transmission loss. The three mathematical models of component failure, solar power failure, transmission failure are combined and formulated as a nonlinear programming optimization problem with binary decision variables, such as number and type (or size) of photovoltaic modules, batteries, radios, antennas, and controllers. Three possible failures are identified and integrated in computer algorithm to generate the parameters for the optimization algorithm. The optimization algorithm is implemented with a branch-and-bound technique solution in MS Excel Solver. The algorithm is applied to a case study design for an actual system that will be set up in remote mountainous areas of Peru. The automated algorithm is verified with independent calculations. The optimal results from minimizing the unavailability of the system with the cost constraint case and minimizing the total cost of the system with the unavailability constraint case are consistent with each other. The tradeoff feature in the algorithm allows designers to observe results of 'what-if' scenarios of relaxing constraint bounds, thus obtaining the most benefit from the optimization process. An example of this approach applied to an existing communication system in the Andes shows dramatic improvement in reliability for little increase in cost. The algorithm is a real design tool, unlike other existing simulation design tools. The algorithm should be useful for other stochastic systems where component reliability, random supply and demand, and communication are
Directory of Open Access Journals (Sweden)
M. A. Farkov
2014-01-01
Full Text Available An analysis of numerical optimization methods for solving a problem of molecular docking has been performed. Some additional requirements for optimization methods according to GPU architecture features were specified. A promising method for implementation on GPU was selected. Its implementation was described and performance and accuracy tests were performed.
Computational Methods for Aerodynamic Design (Inverse) and Optimization
1990-01-01
design and optimization, one cannot oversee-recent developments in the field of Artificial Intelligence (Al), i.e. In the study of-how to make...coupling Artifical Intelligence wih Aerodynamic Design may use much of the recent progress In systematic-design and optimization developments. References...NtIS ton Ilans-les regions- subsoniques. i)autre p~art,, il ii d’assurl’r l’unicit -Il’u111 sol utioni pliybique. -mn v iseositd artificielle est
A topology optimization method for design of negative permeability metamaterials
DEFF Research Database (Denmark)
Diaz, A. R.; Sigmund, Ole
2010-01-01
the effective permeability, obtained after solving Maxwell's equations on a representative cell of a periodic arrangement using a full 3D finite element model. The effective permeability depends on the layout of copper, and the subject of the topology optimization problem is to find layouts that result......A methodology based on topology optimization for the design of metamaterials with negative permeability is presented. The formulation is based on the design of a thin layer of copper printed on a dielectric, rectangular plate of fixed dimensions. An effective media theory is used to estimate...
A mixed optimization method for automated design of fuselage structures.
Sobieszczanski, J.; Loendorf, D.
1972-01-01
A procedure for automating the design of transport aircraft fuselage structures has been developed and implemented in the form of an operational program. The structure is designed in two stages. First, an overall distribution of structural material is obtained by means of optimality criteria to meet strength and displacement constraints. Subsequently, the detailed design of selected rings and panels consisting of skin and stringers is performed by mathematical optimization accounting for a set of realistic design constraints. The practicality and computer efficiency of the procedure is demonstrated on cylindrical and area-ruled large transport fuselages.
Crown, William; Buyukkaramikli, Nasuh; Thokala, Praveen; Morton, Alec; Sir, Mustafa Y; Marshall, Deborah A; Tosh, Jon; Padula, William V; Ijzerman, Maarten J; Wong, Peter K; Pasupathy, Kalyan S
2017-03-01
Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Models and Methods for Structural Topology Optimization with Discrete Design Variables
DEFF Research Database (Denmark)
Stolpe, Mathias
Structural topology optimization is a multi-disciplinary research field covering optimal design of load carrying mechanical structures such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used...... or stresses, or fundamental frequencies. The design variables are either continuous or discrete and model dimensions, thicknesses, densities, or material properties. Structural topology optimization is a multi-disciplinary research field covering optimal design of load carrying mechanical structures......, densities, or material properties. This thesis is devoted to the development of mathematical models, theory, and advanced numerical optimization methods for solving structural topology optimization problems with discrete design variables to proven global optimality. The thesis begins with an introduction...
International Nuclear Information System (INIS)
Nishida, E.; Suzuki, K.; Yasuda, T.; Ohwa, Y.
1993-01-01
This paper deals with an optimum design method for joint elements in boiler plant structures which are excited by earthquakes. Characteristics of joint elements which connect the boiler and its supporting structure, are supposed to be viscoelastic, elasto-plastic, or a combination of both. Considering the expansion of this study to an active or semi-active aseismic structural control of joint elements, the structures are modeled with the aid of block diagram. In order to improve the efficiency of calculation, substructure synthesis method is introduced. Time-domain optimization is carried out using a nonlinear programming technique. To prevent seismic damage of pipes and ducts, limitations for relative displacements between the boiler and its supporting structure is introduced is inequality constraints. Elasto-plasticity and viscoelasticity of joint elements are simulated by a combination of a spring, a Coulomb friction, and a dashpot. These joint element characteristics are optimized to minimize seismic time-response of the structures. This method is applied to actual boiler plant structures and has proven to be effective and practical for aseismic designs of boiler plant structures
Experimental Methods for the Analysis of Optimization Algorithms
DEFF Research Database (Denmark)
In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, c...
Response surface method applied to optimization of estradiol ...
Indian Academy of Sciences (India)
torial design was built for the determination of the main factors affecting estradiol permeation. The independent factors analysed were: ... lation, waste water treatment, packaging in food industry and textile dyeing (Ravi Kumar 2000; ... Experimental design and optimization are tools that are used to systematically examine ...
Experimental Methods for the Analysis of Optimization Algorithms
DEFF Research Database (Denmark)
in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment...
Workload Indicators Of Staffing Need Method in determining optimal ...
African Journals Online (AJOL)
... available working hours, category and individual allowances, annual workloads from the previous year\\'s statistics and optimal departmental establishment of workers. Results: There was initial resentment to the exercise because of the notion that it was aimed at retrenching workers. The team was given autonomy by the ...
Optimization of porthole die geometrical variables by Taguchi method
Gagliardi, F.; Ciancio, C.; Ambrogio, G.; Filice, L.
2017-10-01
Porthole die extrusion is commonly used to manufacture hollow profiles made of lightweight alloys for numerous industrial applications. The reliability of extruded parts is affected strongly by the quality of the longitudinal and transversal seam welds. According to that, the die geometry must be designed correctly and the process parameters must be selected properly to achieve the desired product quality. In this study, numerical 3D simulations have been created and run to investigate the role of various geometrical variables on punch load and maximum pressure inside the welding chamber. These are important outputs to take into account affecting, respectively, the necessary capacity of the extrusion press and the quality of the welding lines. The Taguchi technique has been used to reduce the number of the required numerical simulations necessary for considering the influence of twelve different geometric variables. Moreover, the Analysis of variance (ANOVA) has been implemented to individually analyze the effect of each input parameter on the two responses. Then, the methodology has been utilized to determine the optimal process configuration individually optimizing the two investigated process outputs. Finally, the responses of the optimized parameters have been verified through finite element simulations approximating the predicted value closely. This study shows the feasibility of the Taguchi technique for predicting performance, optimization and therefore for improving the design of a porthole extrusion process.
Use of Simplex Method in Determination of Optimal Rational ...
African Journals Online (AJOL)
The optimal rational composition was found to be: Nsu Clay = 47.8%, quartz = 33.7% and CaCO3 = 18.5%. The other clay from Ukpor was found unsuitable at the firing temperature (l000°C) used. It showed bending strength lower than the standard requirement for all compositions studied. To improve the strength an ...
Optimization and Comparison of Different Digital Mammographic Tomosynthesis Reconstruction Methods
2008-04-01
changes.28 With point-by-point BP, the artifacts coming from the iso - centric x-ray tube’s movement are corrected. The in-plane structures are...for Digita... 9/27/2007http://proxy.lib.duke.edu:2948/getabs/servlet/GetabsServlet?prog= norma ... 32 Methodology of NEQ (f) analysis for optimization
A new method optimizing the subgraph centrality of large networks
Yan, Xin; Li, Chunlin; Zhang, Ling; Hu, Yaogai
2016-02-01
Since many realistic networks such as wireless sensor/ad hoc networks usually do not agree very well with the basic network models such as small-word and scale-free models, we often need to obtain some expected structural features such as a small average path length and a regular degree distribution while optimizing the connectivity of these networks. Although a minor addition of links for optimizing network connectivity is not likely to change the structural properties of a network, it is necessary to investigate the impact of link addition on network properties as the number of the added links increases. However, to the best of our knowledge, the study of that problem has not been found so far. Furthermore, two closely related questions to that problem, i.e., how to measure and how to improve network connectivity, have not been studied carefully enough yet. To address the three problems above, the authors derive a better measure of network connectivity for large networks and a new strategy that can increase/decrease network connectivity the most, and propose a spectral density algorithm optimizing the connectivity of large networks, which is able to indicate the impact on the structural properties of a network while increasing/decreasing its connectivity, providing us a guided optimization of network connectivity. In other words, our algorithm can optimize not only the connectivity of a large network but also its structural features. Meanwhile, our new findings about spectral density are also concluded in this paper. In addition, we may also apply this algorithm to solve all eigenvalues of an N × N matrix, with a low complexity of O(N2) at most.
DEFF Research Database (Denmark)
Ding, Tao; Li, Cheng; Yang, Yongheng
2017-01-01
nature of solar PV energy may affect the selection of the critical PV inverters and also the final optimal objective value. In order to address this issue, a two-stage robust optimization model is proposed in this paper to achieve a robust optimal solution to the PV inverter dispatch, which can hedge...... significant impact on the network voltage level. Following, it ensures the optimal set-points of both active power and reactive power for the selected inverters, guaranteeing the entire system operating constraints (e.g., the network voltage magnitude) within reasonable ranges. However, the intermittent...
Directory of Open Access Journals (Sweden)
Zhang De-Sheng
2016-01-01
Full Text Available Both efficiency and cavitation performance of the hydrofoil are the key technologies to design the tidal current turbine. In this paper, the hydrofoil efficiency and lift coefficient were improved based on particle swarm optimization method and XFoil codes. The cavitation performance of the optimized hydrofoil was also discussed by the computational fluid dynamic. Numerical results show the efficiency of the optimized hydrofoil was improved 11% ranging from the attack angle of 0-7° compared to the original NACA63-818 hydrofoil. The minimum pressure on leading edge of the optimized hydrofoil dropped above 15% at the high attack angle conditions of 10°, 15°, and 20°, respectively, which is benefit for the hydrofoil to avoiding the cavitation.
Activating teaching methods, studying responses and learning
Christensen, Hans Peter; Vigild, Martin E.; Thomsen, Erik; Szabo, Peter; Horsewell, Andy
2009-01-01
Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed. Peer Reviewed
International Nuclear Information System (INIS)
Ray, Santanu Saha
2015-01-01
In this article, two reliable techniques, Haar wavelet method and optimal homotopy asymptotic method (OHAM) are presented. Haar wavelet method is an efficient numerical method for the numerical solution of fractional order partial differential equation like Fisher type. The approximate solutions of the fractional Fisher type equation are compared with the optimal homotopy asymptotic method as well as with the exact solutions. Comparisons between the obtained solutions with the exact solutions exhibit that both the featured methods are effective and efficient in solving nonlinear problems. However, the results indicate that OHAM provides more accurate value than Haar wavelet method
Autonomous guided vehicles methods and models for optimal path planning
Fazlollahtabar, Hamed
2015-01-01
This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...
An Exact Method for a Discrete Multiobjective Linear Fractional Optimization
Directory of Open Access Journals (Sweden)
Mohamed El-Amine Chergui
2008-01-01
Full Text Available Integer linear fractional programming problem with multiple objective (MOILFP is an important field of research and has not received as much attention as did multiple objective linear fractional programming. In this work, we develop a branch and cut algorithm based on continuous fractional optimization, for generating the whole integer efficient solutions of the MOILFP problem. The basic idea of the computation phase of the algorithm is to optimize one of the fractional objective functions, then generate an integer feasible solution. Using the reduced gradients of the objective functions, an efficient cut is built and a part of the feasible domain not containing efficient solutions is truncated by adding this cut. A sample problem is solved using this algorithm, and the main practical advantages of the algorithm are indicated.
Novel Spreadsheet Direct Method for Optimal Control Problems
Directory of Open Access Journals (Sweden)
Chahid Kamel Ghaddar
2018-01-01
Full Text Available We devise a simple yet highly effective technique for solving general optimal control problems in Excel spreadsheets. The technique exploits Excel’s native nonlinear programming (NLP Solver Command, in conjunction with two calculus worksheet functions, namely, an initial value problem solver and a discrete data integrator, in a direct solution paradigm adapted to the spreadsheet. The technique is tested on several highly nonlinear constrained multivariable control problems with remarkable results in terms of reliability, consistency with pseudo-spectral reported answers, and computing times in the order of seconds. The technique requires no more than defining a few analogous formulas to the problem mathematical equations using basic spreadsheet operations, and no programming skills are needed. It introduces an alternative, simpler tool for solving optimal control problems in social and natural science disciplines.
Chen, Jie; Li, Wan-Chen; Gu, Xin-Li
2017-04-13
BACKGROUND This study performed optimized extraction, preliminary characterization, and in vitro antioxidant activities of polysaccharides from Glycyrrhiza uralensis Fisch. MATERIAL AND METHODS Three parameters (extraction temperature, ratio of water to raw material, and extraction time) were optimized for yields of G. uralensis polysaccharides (GUP) using response surface methodology with Box-Behnken design (BBD). The GUP was purified using DEAE cellulose 32-column chromatography. The main fraction obtained from G. uralensis Fisch was GUP-II, which was composed of rhamnose, arabinose, galactose, and glucose monosaccharide, was screened for antioxidant properties using DP Hand hydroxyl radical scavenging assays. In addition, immunological activity of GUP-II was determined by nitric oxide and lymphocyte proliferation assays. RESULTS Optimization revealed maximum GUP yields with an extraction temperature of 99°C, water: raw material ratio of 15: 1, and extraction duration of 2 h. GUP-II purified from G. uralensis Fisch had good in vitro DPPH and hydroxyl radical scavenging abilities. Immunologically, GUP-II significantly stimulated NO production in RAW 264.7 macrophages, and significantly enhanced LPS-induced lymphocyte proliferation. CONCLUSIONS Extraction of GUP from G. uralensis Fisch can be optimized with respect to temperature, extraction period, and ratio of water to material, using response surface methodology. The purified product (GUP-II) possesses excellent antioxidant and immunological activities.
Adjoint-based Mesh Optimization Method: The Development and Application for Nuclear Fuel Analysis
International Nuclear Information System (INIS)
Son, Seongmin; Lee, Jeong Ik
2016-01-01
In this research, methods for optimizing mesh distribution is proposed. The proposed method uses adjoint base optimization method (adjoint method). The optimized result will be obtained by applying this meshing technique to the existing code input deck and will be compared to the results produced from the uniform meshing method. Numerical solutions are calculated form an in-house 1D Finite Difference Method code while neglecting the axial conduction. The fuel radial node optimization was first performed to match the Fuel Centerline Temperature (FCT) the best. This was followed by optimizing the axial node which the Peak Cladding Temperature (PCT) is matched the best. After obtaining the optimized radial and axial nodes, the nodalization is implemented into the system analysis code and transient analyses were performed to observe the optimum nodalization performance. The developed adjoint-based mesh optimization method in the study is applied to MARS-KS, which is a nuclear system analysis code. Results show that the newly established method yields better results than that of the uniform meshing method from the numerical point of view. It is again stressed that the optimized mesh for the steady state can also give better numerical results even during a transient analysis
A multilevel, level-set method for optimizing eigenvalues in shape design problems
International Nuclear Information System (INIS)
Haber, E.
2004-01-01
In this paper, we consider optimal design problems that involve shape optimization. The goal is to determine the shape of a certain structure such that it is either as rigid or as soft as possible. To achieve this goal we combine two new ideas for an efficient solution of the problem. First, we replace the eigenvalue problem with an approximation by using inverse iteration. Second, we use a level set method but rather than propagating the front we use constrained optimization methods combined with multilevel continuation techniques. Combining these two ideas we obtain a robust and rapid method for the solution of the optimal design problem
Gekeler, Simon
2016-01-01
The book provides suggestions on how to start using bionic optimization methods, including pseudo-code examples of each of the important approaches and outlines of how to improve them. The most efficient methods for accelerating the studies are discussed. These include the selection of size and generations of a study’s parameters, modification of these driving parameters, switching to gradient methods when approaching local maxima, and the use of parallel working hardware. Bionic Optimization means finding the best solution to a problem using methods found in nature. As Evolutionary Strategies and Particle Swarm Optimization seem to be the most important methods for structural optimization, we primarily focus on them. Other methods such as neural nets or ant colonies are more suited to control or process studies, so their basic ideas are outlined in order to motivate readers to start using them. A set of sample applications shows how Bionic Optimization works in practice. From academic studies on simple fra...
International Nuclear Information System (INIS)
Daraji, A H; Hale, J M
2014-01-01
This study concerns new investigation of active vibration reduction of a stiffened plate bonded with discrete sensor/actuator pairs located optimally using genetic algorithms based on a developed finite element modeling. An isotropic plate element stiffened by a number of beam elements on its edges and having a piezoelectric sensor and actuator pair bonded to its surfaces is modeled using the finite element method and Hamilton’s principle, taking into account the effects of piezoelectric mass, stiffness and electromechanical coupling. The modeling is based on the first order shear deformation theory taking into account the effects of bending, membrane and shear deformation for the plate, the stiffening beam and the piezoelectric patches. A Matlab finite element program has been built for the stiffened plate model and verified with ANSYS and also experimentally. Optimal placement of ten piezoelectric sensor/actuator pairs and optimal feedback gain for active vibration reduction are investigated for a plate stiffened by two beams arranged in the form of a cross. The genetic algorithm was set up for optimization of sensor/actuator placement and feedback gain based on the minimization of the optimal linear quadratic index as an objective function to suppress the first six modes of vibration. Comparison study is presented for active vibration reduction of a square cantilever plate stiffened by crossed beams with two sensor/actuator configurations: firstly, ten piezoelectric sensor/actuator pairs are located in optimal positions; secondly, a piezoelectric layer of single sensor/actuator pair covering the whole of the stiffened plate as a SISO system. (paper)
Facility optimization to improve activation rate distributions during IVNAA
International Nuclear Information System (INIS)
Ebrahimi Khankook, Atiyeh; Rafat Motavalli, Laleh; Miri Hakimabad, Hashem
2013-01-01
Currently, determination of body composition is the most useful method for distinguishing between certain diseases. The prompt-gamma in vivo neutron activation analysis (IVNAA) facility for non-destructive elemental analysis of the human body is the gold standard method for this type of analysis. In order to obtain accurate measurements using the IVNAA system, the activation probability in the body must be uniform. This can be difficult to achieve, as body shape and body composition affect the rate of activation. The aim of this study was to determine the optimum pre-moderator, in terms of material for attaining uniform activation probability with a CV value of about 10% and changing the collimator role to increase activation rate within the body. Such uniformity was obtained with a high thickness of paraffin pre-moderator, however, because of increasing secondary photon flux received by the detectors it was not an appropriate choice. Our final calculations indicated that using two paraffin slabs with a thickness of 3 cm as a pre-moderator, in the presence of 2 cm Bi on the collimator, achieves a satisfactory distribution of activation rate in the body. (author)
DEFF Research Database (Denmark)
Chen, Peiyuan; Siano, Pierluigi; Chen, Zhe
2010-01-01
The increasing amount of wind power integrated to power systems presents a number of challenges to the system operation. One issue related to wind power integration concerns the location and capacities of the wind turbines (WTs) in the network. Although the location of wind turbines is mainly det...... setting of WTs. The sequential MCS takes into account the stochastic behaviour of wind power generation and load. The proposed hybrid optimization method is demonstrated on an 11 kV 69-bus distribution system......., which can enhance the power system security and improve the system steady-state performance by reducing network losses. This chapter presents a hybrid optimization method that minimizes the annual system power losses. The optimization considers a 95%-probability of fulfilling the voltage and current...
Interior Point Method Evaluation for Reactive Power Flow Optimization in the Power System
Directory of Open Access Journals (Sweden)
Zbigniew Lubośny
2013-03-01
Full Text Available The paper verifies the performance of an interior point method in reactive power flow optimization in the power system. The study was conducted on a 28 node CIGRE system, using the interior point method optimization procedures implemented in Power Factory software.
An Optimal Power Flow (OPF) Method with Improved Power System Stability
DEFF Research Database (Denmark)
Su, Chi; Chen, Zhe
2010-01-01
This paper proposes an optimal power flow (OPF) method taking into account small signal stability as additional constraints. Particle swarm optimization (PSO) algorithm is adopted to realize the OPF process. The method is programmed in MATLAB and implemented to a nine-bus test power system which ...
DEFF Research Database (Denmark)
Pingen, Georg; Evgrafov, Anton; Maute, Kurt
2009-01-01
We present an adjoint parameter sensitivity analysis formulation and solution strategy for the lattice Boltzmann method (LBM). The focus is on design optimization applications, in particular topology optimization. The lattice Boltzmann method is briefly described with an in-depth discussion of so...
Damage approach: A new method for topology optimization with local stress constraints
DEFF Research Database (Denmark)
Verbart, Alexander; Langelaar, Matthijs; van Keulen, Fred
2016-01-01
In this paper, we propose a new method for topology optimization with local stress constraints. In this method, material in which a stress constraint is violated is considered as damaged. Since damaged material will contribute less to the overall performance of the structure, the optimizer will p...
Luo, Yaqi; Zeng, Bi
2017-08-01
This paper researches the drainage routing problem in drainage pipe network, and propose an intelligent scheduling method. The method relates to the design of improved particle swarm optimization algorithm, the establishment of the corresponding model from the pipe network, and the process by using the algorithm based on improved particle swarm optimization to find the optimum drainage route in the current environment.
Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei
2018-03-01
A time varying filtering based empirical mode decomposition (EMD) (TVF-EMD) method was proposed recently to solve the mode mixing problem of EMD method. Compared with the classical EMD, TVF-EMD was proven to improve the frequency separation performance and be robust to noise interference. However, the decomposition parameters (i.e., bandwidth threshold and B-spline order) significantly affect the decomposition results of this method. In original TVF-EMD method, the parameter values are assigned in advance, which makes it difficult to achieve satisfactory analysis results. To solve this problem, this paper develops an optimized TVF-EMD method based on grey wolf optimizer (GWO) algorithm for fault diagnosis of rotating machinery. Firstly, a measurement index termed weighted kurtosis index is constructed by using kurtosis index and correlation coefficient. Subsequently, the optimal TVF-EMD parameters that match with the input signal can be obtained by GWO algorithm using the maximum weighted kurtosis index as objective function. Finally, fault features can be extracted by analyzing the sensitive intrinsic mode function (IMF) owning the maximum weighted kurtosis index. Simulations and comparisons highlight the performance of TVF-EMD method for signal decomposition, and meanwhile verify the fact that bandwidth threshold and B-spline order are critical to the decomposition results. Two case studies on rotating machinery fault diagnosis demonstrate the effectiveness and advantages of the proposed method.
Optimization of a radiochemistry method for plutonium determination in biological samples
International Nuclear Information System (INIS)
Cerchetti, Maria L.; Arguelles, Maria G.
2005-01-01
Plutonium has been widely used for civilian an military activities. Nevertheless, the methods to control work exposition have not evolved in the same way, remaining as one of the major challengers for the radiological protection practice. Due to the low acceptable incorporation limit, the usual determination is based on indirect methods in urine samples. Our main objective was to optimize a technique used to monitor internal contamination of workers exposed to Plutonium isotopes. Different parameters were modified and their influence on the three steps of the method was evaluated. Those which gave the highest yield and feasibility were selected. The method involves: 1-) Sample concentration (coprecipitation); 2-) Plutonium purification; and 3-) Source preparation by electrodeposition. On the coprecipitation phase, changes on temperature and concentration of the carrier were evaluated. On the ion-exchange separation, changes on the type of the resin, elution solution for hydroxylamine (concentration and volume), length and column recycle were evaluated. Finally, on the electrodeposition phase, we modified the following: electrolytic solution, pH and time. Measures were made by liquid scintillation counting and alpha spectrometry (PIPS). We obtained the following yields: 88% for coprecipitation (at 60 C degree with 2 ml of CaHPO 4 ), 71% for ion-exchange (resins AG 1x8 Cl - 100-200 mesh, hydroxylamine 0.1N in HCl 0.2N as eluent, column between 4.5 and 8 cm), and 93% for electrodeposition (H 2 SO 4 -NH 4 OH, 100 minutes and pH from 2 to 2.8). The expand uncertainty was 30% (NC 95%), the decision threshold (Lc) was 0.102 Bq/L and the minimum detectable activity was 0.218 Bq/L of urine. We obtained an optimized method to screen workers exposed to Plutonium. (author)
International Nuclear Information System (INIS)
Yang, Hong-Tzer; Peng, Pai-Chun
2012-01-01
Highlights: ► We propose an improved Taguchi method to determine the optimal contract capacities with SOGUs. ► We solve the highly discrete and nonlinear optimization problem for the contract capacities with SOGUs. ► The proposed improved Taguchi method integrates PSO in Taguchi method. ► The customer using the proposed optimization approach may save up to 12.18% of power expenses. ► The improved Taguchi method can also be well applied to the other similar problems. - Abstract: Contract capacity setting for industrial consumer with self-owned generating units (SOGUs) is a highly discrete and nonlinear optimization problem considering expenditure on the electricity from the utility and operation costs of the SOGUs. This paper proposes an improved Taguchi method that combines existing Taguchi method and particle swarm optimization (PSO) algorithm to solve this problem. Taguchi method provides fast converging characteristics in searching the optimal solution through quality analysis in orthogonal matrices. The integrated PSO algorithm generates new solutions in the orthogonal matrices based on the searching experiences during the evolution process to further improve the quality of solution. To verify feasibility of the proposed method, the paper uses the real data obtained from a large optoelectronics factory in Taiwan. In comparison with the existing optimization methods, the proposed improved Taguchi method has superior performance as revealed in the numerical results in terms of the convergence process and the quality of solution obtained.
Budiarso; Adanta, Dendy; Warjito; Siswantara, A. I.; Saputra, Pradhana; Dianofitra, Reza
2018-03-01
Rapid economic and population growth in Indonesia lead to increased energy consumption, including electricity needs. Pico hydro is considered as the right solution because the cost of investment and operational cost are fairly low. Additionally, Indonesia has many remote areas with high hydro-energy potential. The overshot waterwheel is one of technology that is suitable to be applied in remote areas due to ease of operation and maintenance. This study attempts to optimize bucket dimensions with the available conditions. In addition, the optimization also has a good impact on the amount of generated power because all available energy is utilized maximally. Analytical method is used to evaluate the volume of water contained in bucket overshot waterwheel. In general, there are two stages performed. First, calculation of the volume of water contained in each active bucket is done. If the amount total of water contained is less than the available discharge in active bucket, recalculation at the width of the wheel is done. Second, calculation of the torque of each active bucket is done to determine the power output. As the result, the mechanical power generated from the waterwheel is 305 Watts with the efficiency value of 28%.
Intelligent and nature inspired optimization methods in medicine
DEFF Research Database (Denmark)
Marinakis, Yannis; Marinaki, Magdalene; Dounias, Georgios
2009-01-01
, decrease noise and improve speed by the elimination of irrelevant or redundant features. The present paper deals with the optimization of nearest neighbour classifiers via intelligent and nature inspired algorithms for a very significant medical problem, the Pap smear cell classification problem...... by expert cyto-technicians and doctors. Each cell is described by 20 numerical features, and the cells fall into seven classes representing a variety of normal and abnormal cases. Nevertheless, from the medical diagnosis viewpoint, a minimum requirement corresponds to the general two-class problem...
Reliability-Based Shape Optimization using Stochastic Finite Element Methods
DEFF Research Database (Denmark)
Enevoldsen, Ib; Sørensen, John Dalsgaard; Sigurdsson, G.
1991-01-01
stochastic fields (e.g. loads and material parameters such as Young's modulus and the Poisson ratio). In this case stochastic finite element techniques combined with FORM analysis can be used to obtain measures of the reliability of the structural systems, see Der Kiureghian & Ke (6) and Liu & Der Kiureghian...... (7). In this paper a reliability-based shape optimization problem is formulated with the total expected cost as objective function and some requirements for the reliability measures (element or systems reliability measures) as constraints, see section 2. As design variables sizing variables...
Trip optimization system and method for a train
Kumar, Ajith Kuttannair; Shaffer, Glenn Robert; Houpt, Paul Kenneth; Movsichoff, Bernardo Adrian; Chan, David So Keung
2017-08-15
A system for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives, the system including a locator element to determine a location of the train, a track characterization element to provide information about a track, a sensor for measuring an operating condition of the locomotive consist, a processor operable to receive information from the locator element, the track characterizing element, and the sensor, and an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of the locomotive consist in accordance with one or more operational criteria for the train.
A primal-dual interior point method for large-scale free material optimization
DEFF Research Database (Denmark)
Weldeyesus, Alemseged Gebrehiwot; Stolpe, Mathias
2015-01-01
Free Material Optimization (FMO) is a branch of structural optimization in which the design variable is the elastic material tensor that is allowed to vary over the design domain. The requirements are that the material tensor is symmetric positive semidefinite with bounded trace. The resulting...... optimization problem is a nonlinear semidefinite program with many small matrix inequalities for which a special-purpose optimization method should be developed. The objective of this article is to propose an efficient primal-dual interior point method for FMO that can robustly and accurately solve large...... of iterations the interior point method requires is modest and increases only marginally with problem size. The computed optimal solutions obtain a higher precision than other available special-purpose methods for FMO. The efficiency and robustness of the method is demonstrated by numerical experiments on a set...
International Nuclear Information System (INIS)
Yamamoto, Akio; Jagawa, Suetsugu; Sato, Daisuke; Sato, Hitoshi; Yamasaki, Masatoshi
2006-01-01
The theories of loading pattern optimization, the methods and the tools using by PWR and BWR are stated. Needs for core design and loading pattern optimization, operating of PWR/BWR, designs of loading pattern, optimization of the loading pattern and design variables, the basic theories of loading pattern optimization, the optimization tools of loading pattern in Japan are explained. The basic theories consist of the determinism methods, the probability methods and heuristic method. Four tools such as INSIGHT (PWR), Pearls th (PWR), FINELOAD (BWR) and ePrometheus (BWR) are described by outline, principles, characteristics, functions, and application examples. These tools are a great success of limiting the seek area and short-time calculation using the high speed simulation method of core functions. (S.Y.)
Simulation Research on Vehicle Active Suspension Controller Based on G1 Method
Li, Gen; Li, Hang; Zhang, Shuaiyang; Luo, Qiuhui
2017-09-01
Based on the order relation analysis method (G1 method), the optimal linear controller of vehicle active suspension is designed. The system of the main and passive suspension of the single wheel vehicle is modeled and the system input signal model is determined. Secondly, the system motion state space equation is established by the kinetic knowledge and the optimal linear controller design is completed with the optimal control theory. The weighting coefficient of the performance index coefficients of the main passive suspension is determined by the relational analysis method. Finally, the model is simulated in Simulink. The simulation results show that: the optimal weight value is determined by using the sequence relation analysis method under the condition of given road conditions, and the vehicle acceleration, suspension stroke and tire motion displacement are optimized to improve the comprehensive performance of the vehicle, and the active control is controlled within the requirements.
Efficiency of operation of wind turbine rotors optimized by the Glauert and Betz methods
DEFF Research Database (Denmark)
Okulov, Valery; Mikkelsen, Robert Flemming; Litvinov, I. V.
2015-01-01
The models of two types of rotors with blades constructed using different optimization methods are compared experimentally. In the first case, the Glauert optimization by the pulsed method is used, which is applied independently for each individual blade cross section. This method remains the mai...... time as a result of direct experimental comparison that the rotor constructed using the Betz method makes it possible to extract more kinetic energy from the homogeneous incoming flow....
Potency of Amylase-producing Bacteria and Optimization Amylase Activities
Indriati, G.; Megahati, R. R. P.; Rosba, E.
2018-04-01
Enzymes are capable to act as biocatalyst for a wide variety of chemical reactions. Amylase have potential biotechnological applications in a wide range of industrial processes and account for nearly 30% of the world’s enzyme market. Amylase are extracellular enzymes that catalyze the hydrolysis of internal α-1,4-glycosidic linkages in starch to dextrin, and other small carbohydrate molecules constituted of glucose units. Although enzymes are produced from animal and plant sources, the microbial sources are generally the most suitable for commercial applications. Bacteria from hot springs is widely used as a source of various enzymes, such as amylase. But the amount of amylase-producing bacteria is still very limited. Therefore it is necessary to search sources of amylase-producing bacteria new, such as from hot springs Pariangan. The purpose of this study was to isolation of amylase-producing bacteria from Pariangan hot spring, West Sumatera and amylase activity optimization. The results were obtained 12 isolates of thermophilic bacteria and 5 isolates of amyalse-producing bacteria with the largest amylolytic index of 3.38 mm. The highest amylase activity was obtained at 50°C and pH 7.5.
Detecting anthropogenic climate change with an optimal fingerprint method
International Nuclear Information System (INIS)
Hegerl, G.C.; Storch, H. von; Hasselmann, K.; Santer, B.D.; Jones, P.D.
1994-01-01
We propose a general fingerprint strategy to detect anthropogenic climate change and present application to near surface temperature trends. An expected time-space-variable pattern of anthropogenic climate change (the 'signal') is identified through application of an appropriate optimally matched space-time filter (the 'fingerprint') to the observations. The signal and the fingerprint are represented in a space with sufficient observed and simulated data. The signal pattern is derived from a model-generated prediction of anthropogenic climate change. Application of the fingerprint filter to the data yields a scalar detection variable. The statistically optimal fingerprint is obtained by weighting the model-predicted pattern towards low-noise directions. A combination of model output and observations is used to estimate the noise characteristics of the detection variable, arising from the natural variability of climate in the absence of external forcing. We test then the null hypothesis that the observed climate change is part of natural climate variability. We conclude that a statistically significant externally induced warming has been observed, with the caveat of a possibly inadequate estimate of the internal climate variability. In order to attribute this warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g. changes in solar radiation, volcanic or anthropogenic aerosols) and their interaction is needed. (orig./KW)
Optimization of renal transfection using a renal suction-mediated transfection method in mice.
Taniguchi, Yota; Kawakami, Shigeru; Fuchigami, Yuki; Oyama, Natsuko; Yamashita, Fumiyoshi; Konishi, Satoshi; Shimizu, Kazunori; Hashida, Mitsuru
2016-01-01
We previously developed a suction-mediated transfection method in mice. The purpose of this study was to optimize the suction-mediated transfection conditions using a pressure-controlled computer system for efficient and safe kidney-targeted gene delivery in mice. Naked pCMV-Luc was injected into the tail vein in mice, and then the right kidney was suctioned by a device of the suction pressure-controlled system. The effects of renal transfection conditions, such as the suction pressure degree, suction pressure waveform and device area were evaluated by measuring luciferase expression. In addition, renal injury was examined. The renal suction-mediated transfection method at -30 kPa showed high transgene expression. The renal suction waveform did not affect the transfection activity. Under the optimized conditions, the high transgene expression was mostly observed at the renal suctioned site. The transfection conditions used did not induce histological defects or increases in two renal injury biomarkers (Kidney injury molecule-1 mRNA and Clusterin mRNA). We have clarified the transfection conditions for efficient and safe transfection in the kidney using the suction-mediated transfection method in mice.
Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells
Directory of Open Access Journals (Sweden)
Amanda L. Peterson
2016-09-01
Full Text Available Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions.
Complex Method Mixed with PSO Applying to Optimization Design of Bridge Crane Girder
Directory of Open Access Journals (Sweden)
He Yan
2017-01-01
Full Text Available In engineer design, basic complex method has not enough global search ability for the nonlinear optimization problem, so it mixed with particle swarm optimization (PSO has been presented in the paper,that is the optimal particle evaluated from fitness function of particle swarm displacement complex vertex in order to realize optimal principle of the largest complex central distance.This method is applied to optimization design problems of box girder of bridge crane with constraint conditions.At first a mathematical model of the girder optimization has been set up,in which box girder cross section area of bridge crane is taken as the objective function, and its four sizes parameters as design variables, girder mechanics performance, manufacturing process, border sizes and so on requirements as constraint conditions. Then complex method mixed with PSO is used to solve optimization design problem of cane box girder from constrained optimization studying approach, and its optimal results have achieved the goal of lightweight design and reducing the crane manufacturing cost . The method is reliable, practical and efficient by the practical engineer calculation and comparative analysis with basic complex method.
An Efficient Kernel Optimization Method for Radar High-Resolution Range Profile Recognition
Directory of Open Access Journals (Sweden)
Chen Bo
2007-01-01
Full Text Available A kernel optimization method based on fusion kernel for high-resolution range profile (HRRP is proposed in this paper. Based on the fusion of -norm and -norm Gaussian kernels, our method combines the different characteristics of them so that not only is the kernel function optimized but also the speckle fluctuations of HRRP are restrained. Then the proposed method is employed to optimize the kernel of kernel principle component analysis (KPCA and the classification performance of extracted features is evaluated via support vector machines (SVMs classifier. Finally, experimental results on the benchmark and radar-measured data sets are compared and analyzed to demonstrate the efficiency of our method.
First-order Convex Optimization Methods for Signal and Image Processing
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm
2012-01-01
In this thesis we investigate the use of first-order convex optimization methods applied to problems in signal and image processing. First we make a general introduction to convex optimization, first-order methods and their iteration complexity. Then we look at different techniques, which can...... be used with first-order methods such as smoothing, Lagrange multipliers and proximal gradient methods. We continue by presenting different applications of convex optimization and notable convex formulations with an emphasis on inverse problems and sparse signal processing. We also describe the multiple...
Optimization method for an evolutional type inverse heat conduction problem
International Nuclear Information System (INIS)
Deng Zuicha; Yu Jianning; Yang Liu
2008-01-01
This paper deals with the determination of a pair (q, u) in the heat conduction equation u t -u xx +q(x,t)u=0, with initial and boundary conditions u(x,0)=u 0 (x), u x vertical bar x=0 =u x vertical bar x=1 =0, from the overspecified data u(x, t) = g(x, t). By the time semi-discrete scheme, the problem is transformed into a sequence of inverse problems in which the unknown coefficients are purely space dependent. Based on the optimal control framework, the existence, uniqueness and stability of the solution (q, u) are proved. A necessary condition which is a couple system of a parabolic equation and parabolic variational inequality is deduced
Control and optimization system and method for chemical looping processes
Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao
2015-02-17
A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.
Research on optimization method of deep neural network
Liu, Pengfei; Zhao, Huaici; Cao, Feidao
2017-11-01
Image recognition technology has been widely applied and played an important role in various fields nowadays. Because of multi-layer structure of deep network can use a more concise way to express complex functions, deep neural network (DNN) will be applied to the image recognition to improve the accuracy of image classification. Analysis the existing problems of deep neural network. Then put forward new approaches to solve the gradient vanishing and over-fitting problems. The experimental results which verified on the MNIST, show that our proposed approaches can improve the classification accuracy greatly and accelerate the convergence speed. Compared to support vector machine (SVM), the optimized model of the neural network is not only effective, but also converged quickly.
An optimal adaptive wavelet method without coarsening of the iterands
Gantumur, T.; Harbrecht, H.; Stevenson, R.
2007-01-01
In this paper, an adaptive wavelet method for solving linear operator equations is constructed that is a modification of the method from [Math. Comp, 70 (2001), pp. 27-75] by Cohen, Dahmen and DeVore, in the sense that there is no recurrent coarsening of the iterands. Despite this, it will be shown
Mathematical foundation of the optimization-based fluid animation method
DEFF Research Database (Denmark)
Erleben, Kenny; Misztal, Marek Krzysztof; Bærentzen, Jakob Andreas
2011-01-01
We present the mathematical foundation of a fluid animation method for unstructured meshes. Key contributions not previously treated are the extension to include diffusion forces and higher order terms of non-linear force approximations. In our discretization we apply a fractional step method...
Directory of Open Access Journals (Sweden)
Laura A. Smith Callahan
2016-06-01
Full Text Available Combinatorial method/high throughput strategies, which have long been used in the pharmaceutical industry, have recently been applied to hydrogel optimization for tissue engineering applications. Although many combinatorial methods have been developed, few are suitable for use in tissue engineering hydrogel optimization. Currently, only three approaches (design of experiment, arrays and continuous gradients have been utilized. This review highlights recent work with each approach. The benefits and disadvantages of design of experiment, array and continuous gradient approaches depending on study objectives and the general advantages of using combinatorial methods for hydrogel optimization over traditional optimization strategies will be discussed. Fabrication considerations for combinatorial method/high throughput samples will additionally be addressed to provide an assessment of the current state of the field, and potential future contributions to expedited material optimization and design.
Villanueva Perez, Carlos Hernan
Computational design optimization provides designers with automated techniques to develop novel and non-intuitive optimal designs. Topology optimization is a design optimization technique that allows for the evolution of a broad variety of geometries in the optimization process. Traditional density-based topology optimization methods often lack a sufficient resolution of the geometry and physical response, which prevents direct use of the optimized design in manufacturing and the accurate modeling of the physical response of boundary conditions. The goal of this thesis is to introduce a unified topology optimization framework that uses the Level Set Method (LSM) to describe the design geometry and the eXtended Finite Element Method (XFEM) to solve the governing equations and measure the performance of the design. The methodology is presented as an alternative to density-based optimization approaches, and is able to accommodate a broad range of engineering design problems. The framework presents state-of-the-art methods for immersed boundary techniques to stabilize the systems of equations and enforce the boundary conditions, and is studied with applications in 2D and 3D linear elastic structures, incompressible flow, and energy and species transport problems to test the robustness and the characteristics of the method. A comparison of the framework against density-based topology optimization approaches is studied with regards to convergence, performance, and the capability to manufacture the designs. Furthermore, the ability to control the shape of the design to operate within manufacturing constraints is developed and studied. The analysis capability of the framework is validated quantitatively through comparison against previous benchmark studies, and qualitatively through its application to topology optimization problems. The design optimization problems converge to intuitive designs and resembled well the results from previous 2D or density-based studies.
Directory of Open Access Journals (Sweden)
Seyed Heja Seyed Taheri
Full Text Available Abstract The current study presents an enhanced biogeography-based optimization (EBBO algorithm for size and shape optimization of truss structures with natural frequency constraints. The BBO algorithm is one of the recently developed meta-heuristic algorithms inspired by the mathematical models in biogeography science and is based on the migration behavior of species among the habitats in the nature. In this study, the overall performance of the standard BBO algorithm is enhanced by new migration and mutation operators. The efficiency of the proposed algorithm is demonstrated by utilizing four benchmark truss design examples with frequency constraints. Numerical results show that the proposed EBBO algorithm not only significantly improves the performance of the standard BBO algorithm, but also finds competitive results compared with recently developed optimization methods.
DEFF Research Database (Denmark)
Sidelmann, Johannes Jakobsen; Jespersen, J; Gram, J
1995-01-01
We introduce a new fibrin plate assay performed in microtiter plates. By means of spectroscopic studies we optimized the structure of the fibrin gel and then used the optimized fibrin gel to determine plasminogen activator activity. Plasminogen activator solutions were applied on top of the fibri...
A Review of Human Activity Recognition Methods
Directory of Open Access Journals (Sweden)
Michalis eVrigkas
2015-11-01
Full Text Available Recognizing human activities from video sequences or still images is a challenging task due to problems such as background clutter, partial occlusion, changes in scale, viewpoint, lighting, and appearance. Many applications, including video surveillance systems, human-computer interaction, and robotics for human behavior characterization, require a multiple activity recognition system. In this work, we provide a detailed review of recent and state-of-the-art research advances in the field of human activity classification. We propose a categorization of human activity methodologies and discuss their advantages and limitations. In particular, we divide human activity classification methods into two large categories according to whether they use data from different modalities or not. Then, each of these categories is further analyzed into sub-categories, which reflect how they model human activities and what type of activities they are interested in. Moreover, we provide a comprehensive analysis of the existing, publicly available human activity classification datasets and examine the requirements for an ideal human activity recognition dataset. Finally, we report the characteristics of future research directions and present some open issues on human activity recognition.
Towards an optimized method of olive tree crown volume measurement.
Miranda-Fuentes, Antonio; Llorens, Jordi; Gamarra-Diezma, Juan L; Gil-Ribes, Jesús A; Gil, Emilio
2015-02-04
Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA), Ellipsoid Volume method (VE) and Tree Silhouette Volume method (VTS). Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R2 = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended.
Towards an Optimized Method of Olive Tree Crown Volume Measurement
Miranda-Fuentes, Antonio; Llorens, Jordi; Gamarra-Diezma, Juan L.; Gil-Ribes, Jesús A.; Gil, Emilio
2015-01-01
Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA), Ellipsoid Volume method (VE) and Tree Silhouette Volume method (VTS). Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R2 = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended. PMID:25658396
Towards an Optimized Method of Olive Tree Crown Volume Measurement
Directory of Open Access Journals (Sweden)
Antonio Miranda-Fuentes
2015-02-01
Full Text Available Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA, Ellipsoid Volume method (VE and Tree Silhouette Volume method (VTS. Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R2 = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended.
Resolution and optimization methods for tour planning problems
International Nuclear Information System (INIS)
Vasserot, Jean-Pierre
1976-12-01
The aim of this study is to describe computerized methods for the resolution of the computer supported tour planning problem. After a presentation of this problem in operational research, the different existing methods of resolution are reviewed with the different approaches which have led to their elaboration. Different critics and comparisons are made on these methods and some improvements and new procedures are proposed, some of them allowing to solve more general problems. Finally, the structure of such a program, made at the CII to solve this kind of problem under multiple constraints is analysed [fr
Energy Technology Data Exchange (ETDEWEB)
Tung, Wu-Hsiung, E-mail: wstong@iner.gov.tw; Lee, Tien-Tso; Kuo, Weng-Sheng; Yaur, Shung-Jung
2017-03-15
Highlights: • An optimization method for axial enrichment distribution in a BWR fuel was developed. • Block coordinate descent method is employed to search for optimal solution. • Scoping libraries are used to reduce computational effort. • Optimization search space consists of enrichment difference parameters. • Capability of the method to find optimal solution is demonstrated. - Abstract: An optimization method has been developed to search for the optimal axial enrichment distribution in a fuel assembly for a boiling water reactor core. The optimization method features: (1) employing the block coordinate descent method to find the optimal solution in the space of enrichment difference parameters, (2) using scoping libraries to reduce the amount of CASMO-4 calculation, and (3) integrating a core critical constraint into the objective function that is used to quantify the quality of an axial enrichment design. The objective function consists of the weighted sum of core parameters such as shutdown margin and critical power ratio. The core parameters are evaluated by using SIMULATE-3, and the cross section data required for the SIMULATE-3 calculation are generated by using CASMO-4 and scoping libraries. The application of the method to a 4-segment fuel design (with the highest allowable segment enrichment relaxed to 5%) demonstrated that the method can obtain an axial enrichment design with improved thermal limit ratios and objective function value while satisfying the core design constraints and core critical requirement through the use of an objective function. The use of scoping libraries effectively reduced the number of CASMO-4 calculation, from 85 to 24, in the 4-segment optimization case. An exhausted search was performed to examine the capability of the method in finding the optimal solution for a 4-segment fuel design. The results show that the method found a solution very close to the optimum obtained by the exhausted search. The number of
Topology optimization of bounded acoustic problems using the hybrid finite element-wave based method
DEFF Research Database (Denmark)
Goo, Seongyeol; Wang, Semyung; Kook, Junghwan
2017-01-01
This paper presents an alternative topology optimization method for bounded acoustic problems that uses the hybrid finite element-wave based method (FE-WBM). The conventional method for the topology optimization of bounded acoustic problems is based on the finite element method (FEM), which...... is limited to low frequency applications due to considerable computational efforts. To this end, we propose a gradient-based topology optimization method that uses the hybrid FE-WBM whereby the entire domain of a problem is partitioned into design and non-design domains. In this respect, the FEM is used...... as a design domain of topology optimization, and the WBM is used as a non-design domain to increase computational efficiency. The adjoint variable method based on the hybrid FE-WBM is also proposed as a means of computing design sensitivities. Numerical examples are presented to demonstrate the effectiveness...
Natural frequency optimization of structures using a soft-kill BESO method
International Nuclear Information System (INIS)
Huang Xiaodong; Xie Yimin
2010-01-01
Frequency optimization is of great importance in the design of machines and structures subjected to dynamic loading. When the natural frequencies of considered structures are maximized using the Solid Isotropic Material with Penalization (SIMP) model, artificial localized modes may occur in areas where elements are assigned with low density values. In this paper, a modified SIMP model is developed to effectively avoid the artificial modes. Based on this model, a new bi-directional evolutionary structural optimization (BESO) method combined with rigorous optimality criteria is developed for topology frequency optimization problems. Numerical results show that the proposed BESO method is efficient and convergent and solid-void or bi-material optimal solutions can be achieved for a variety of frequency optimization problems of continuum structures.
Natural frequency optimization of structures using a soft-kill BESO method
Huang, Xiaodong; Xie, Yi Min
2010-06-01
Frequency optimization is of great importance in the design of machines and structures subjected to dynamic loading. When the natural frequencies of considered structures are maximized using the Solid Isotropic Material with Penalization (SIMP) model, artificial localized modes may occur in areas where elements are assigned with low density values. In this paper, a modified SIMP model is developed to effectively avoid the artificial modes. Based on this model, a new bi-directional evolutionary structural optimization (BESO) method combined with rigorous optimality criteria is developed for topology frequency optimization problems. Numerical results show that the proposed BESO method is efficient and convergent and solid-void or bi-material optimal solutions can be achieved for a variety of frequency optimization problems of continuum structures.
A novel technique for active vibration control, based on optimal ...
Indian Academy of Sciences (India)
BEHROUZ KHEIRI SARABI
2017-07-11
Jul 11, 2017 ... an actuator weighing matrix and k f represents the final location of the vector. Optimal control that optimizes the performance index is given by [23–25] u. ∗(k) = −L(k)x. ∗(k) + Lg(k)g(k + 1). (8). Quantities with an asterisk represent optimal quantities. L(k) and Lg(k) are control gains and vector g (k) is given as.
Directory of Open Access Journals (Sweden)
Abdul Wadood
2018-04-01
Full Text Available In an electrical power system, the coordination of the overcurrent relays plays an important role in protecting the electrical system by providing primary as well as backup protection. To reduce power outages, the coordination between these relays should be kept at the optimum value to minimize the total operating time and ensure that the least damage occurs under fault conditions. It is also imperative to ensure that the relay setting does not create an unintentional operation and consecutive sympathy trips. In a power system protection coordination problem, the objective function to be optimized is the sum of the total operating time of all main relays. In this paper, the coordination of overcurrent relays in a ring fed distribution system is formulated as an optimization problem. Coordination is performed using proposed continuous particle swarm optimization. In order to enhance and improve the quality of this solution a local search algorithm (LSA is implanted into the original particle swarm algorithm (PSO and, in addition to the constraints, these are amalgamated into the fitness function via the penalty method. The results achieved from the continuous particle swarm optimization algorithm (CPSO are compared with other evolutionary optimization algorithms (EA and this comparison showed that the proposed scheme is competent in dealing with the relevant problems. From further analyzing the obtained results, it was found that the continuous particle swarm approach provides the most globally optimum solution.
Method for determining optimal supercell representation of interfaces.
Stradi, Daniele; Jelver, Line; Smidstrup, Søren; Stokbro, Kurt
2017-05-10
The geometry and structure of an interface ultimately determines the behavior of devices at the nanoscale. We present a generic method to determine the possible lattice matches between two arbitrary surfaces and to calculate the strain of the corresponding matched interface. We apply this method to explore two relevant classes of interfaces for which accurate structural measurements of the interface are available: (i) the interface between pentacene crystals and the (1 1 1) surface of gold, and (ii) the interface between the semiconductor indium-arsenide and aluminum. For both systems, we demonstrate that the presented method predicts interface geometries in good agreement with those measured experimentally, which present nontrivial matching characteristics and would be difficult to guess without relying on automated structure-searching methods.
USING OF THE COVER AMOUNTS METHOD FOR OPTIMIZATION OF INCOME
Directory of Open Access Journals (Sweden)
A. V. Volkov
2007-01-01
Full Text Available The method of cover amounts (marginal income gives possibility to determine profitableness of each kind of the production and their real contribution into the result of work of enterprise.
Optimizing distance-based methods for large data sets
Scholl, Tobias; Brenner, Thomas
2015-10-01
Distance-based methods for measuring spatial concentration of industries have received an increasing popularity in the spatial econometrics community. However, a limiting factor for using these methods is their computational complexity since both their memory requirements and running times are in {{O}}(n^2). In this paper, we present an algorithm with constant memory requirements and shorter running time, enabling distance-based methods to deal with large data sets. We discuss three recent distance-based methods in spatial econometrics: the D&O-Index by Duranton and Overman (Rev Econ Stud 72(4):1077-1106, 2005), the M-function by Marcon and Puech (J Econ Geogr 10(5):745-762, 2010) and the Cluster-Index by Scholl and Brenner (Reg Stud (ahead-of-print):1-15, 2014). Finally, we present an alternative calculation for the latter index that allows the use of data sets with millions of firms.
Applying the Taguchi Method to River Water Pollution Remediation Strategy Optimization
Directory of Open Access Journals (Sweden)
Tsung-Ming Yang
2014-04-01
Full Text Available Optimization methods usually obtain the travel direction of the solution by substituting the solutions into the objective function. However, if the solution space is too large, this search method may be time consuming. In order to address this problem, this study incorporated the Taguchi method into the solution space search process of the optimization method, and used the characteristics of the Taguchi method to sequence the effects of the variation of decision variables on the system. Based on the level of effect, this study determined the impact factor of decision variables and the optimal solution for the model. The integration of the Taguchi method and the solution optimization method successfully obtained the optimal solution of the optimization problem, while significantly reducing the solution computing time and enhancing the river water quality. The results suggested that the basin with the greatest water quality improvement effectiveness is the Dahan River. Under the optimal strategy of this study, the severe pollution length was reduced from 18 km to 5 km.
Applying the Taguchi method to river water pollution remediation strategy optimization.
Yang, Tsung-Ming; Hsu, Nien-Sheng; Chiu, Chih-Chiang; Wang, Hsin-Ju
2014-04-15
Optimization methods usually obtain the travel direction of the solution by substituting the solutions into the objective function. However, if the solution space is too large, this search method may be time consuming. In order to address this problem, this study incorporated the Taguchi method into the solution space search process of the optimization method, and used the characteristics of the Taguchi method to sequence the effects of the variation of decision variables on the system. Based on the level of effect, this study determined the impact factor of decision variables and the optimal solution for the model. The integration of the Taguchi method and the solution optimization method successfully obtained the optimal solution of the optimization problem, while significantly reducing the solution computing time and enhancing the river water quality. The results suggested that the basin with the greatest water quality improvement effectiveness is the Dahan River. Under the optimal strategy of this study, the severe pollution length was reduced from 18 km to 5 km.
Optimization of polyhydroxylalkanoates production from excess activated sludge
International Nuclear Information System (INIS)
Chua, H.; Yu, P.H.F.; Ma, C.K.
2000-01-01
Polyhydroxy alkanoates (PHAS) produced by microbial fermentation are biodegradable and can be used as environmentally-friendly substitutes for conventional plastics to resolve the environmental problems associated with plastics wastes. However, widespread applications of PHA are hampered by high production cost. In this study, activated sludge bacteria from a conventional wastewater treatment process were induced, by controlling the carbon-nitrogen (C:N) ratio in the reactor liquor, to accumulate PHA as a low-cost source of biodegradable plastic. Specific polymer yield increased to a maximum of O.27 g polymer/g dry cell mass when the C:N ratio was increased from 24 to 144, whereas specific growth yield decreased with increasing C:N ratio. An optimum C:N ratio of 96 provided the highest overall polymer production yield of 0.09 g polymer/g carbonaceous substrate consumed. Moreover, an intermittent nitrogen feeding program was established to further optimize the polymer volumetric productivity. The overall polymer production yield of O.11 g polymer/g carbonaceous substrate consumed was achieved under C:N ratio of 96 by feeding nitrogen in the reactor liquor once every 4 cycles. While reducing the production costs of biodegradable plastics, this technique also reduced the amount of excess sludge generated from the wastewater treatment process as the polymer portion of biomass was extracted for use. (Author)
Optimization to improve precision in neutron activation analysis
International Nuclear Information System (INIS)
Yustina Tri Handayani
2010-01-01
The level of precision or accuracy required in analysis should be satisfied the general requirements and customer needs. In presenting the results of the analysis, the level of precision is expressed as uncertainty. Requirement general is Horwitz prediction. Factors affecting the uncertainty in the Neutron Activation Analysis (NAA) include the mass of sample, mass standards, concentration in standard, count of sample, count of standard and counting geometry. Therefore, to achieve the expected level of precision, these parameters need to be optimized. A standard concentration of similar materials is applied as a basis of calculation. In the calculation NIST SRM 2704 is applied for sediment samples. Mass of sample, irradiation time and cooling time can be modified to obtain the expected uncertainty. The prediction results show the level of precision for Al, V, Mg, Mn, K, Na, As, Cr, Co, Fe, and Zn eligible the Horwitz. The predictive the count and standard deviation for Mg-27 and Zn-65 were higher than the actual value occurred due to overlapping of Mg-27 and Mn-54 peaks and Zn-65 and Fe-59 peaks. Precision level of Ca is greater than the Horwitz, since the value of microscopic cross section, the probability of radiation emission of Ca-49 and gamma spectrometer efficiency at 3084 keV is relatively small. Increased precision can only be done by extending the counting time and multiply the number of samples, because of the fixed value. The prediction results are in accordance with experimental results. (author)
Directory of Open Access Journals (Sweden)
Radu Virgil GRIGORIU
2011-11-01
Full Text Available The objectives of the industrial products manufacturers are generally oriented to manufacture high quality level products, in less time and with maximum economic efficiency. The achievement of these objectives can be realized, generally, by optimizing the processes and the technological manufacturing equipment parameters. In order to optimize these parameters it is necessary to apply series of optimization methods and principles that allow the identification and establishment of the best solution from a variety of alternatives.
Optimal design of a DC MHD pump by simulated annealing method
Directory of Open Access Journals (Sweden)
Bouali Khadidja
2014-01-01
Full Text Available In this paper a design methodology of a magnetohydrodynamic pump is proposed. The methodology is based on direct interpretation of the design problem as an optimization problem. The simulated annealing method is used for an optimal design of a DC MHD pump. The optimization procedure uses an objective function which can be the minimum of the mass. The constraints are both of geometrics and electromagnetic in type. The obtained results are reported.
Drenth-van Maanen, A. Clara; van Marum, Rob J.; Knol, Wilma; van der Linden, Carolien M. J.; Jansen, Paul A. F.
2009-01-01
Background: Optimizing polypharmacy is often difficult, and critical appraisal of medication use often leads to one or more changes. We developed the Prescribing Optimization Method (POM) to assist physicians, especially general practitioners (GPs), in their attempts to optimize polypharmacy in
Intermediate levels of hippocampal activity appear optimal for associative memory formation.
Directory of Open Access Journals (Sweden)
Xiao Liu
Full Text Available BACKGROUND: It is well established that hippocampal activity is positively related to effective associative memory formation. However, in biological systems often optimal levels of activity are contrasted by both sub- and supra-optimal levels. Sub-optimal levels of hippocampal activity are commonly attributed to unsuccessful memory formation, whereas the supra-optimal levels of hippocampal activity related to unsuccessful memory formation have been rarely studied. It is still unclear under what circumstances such supra-optimal levels of hippocampal activity occur. To clarify this issue, we aimed at creating a condition, in which supra-optimal hippocampal activity is associated with encoding failure. We assumed that such supra-optimal activity occurs when task-relevant information is embedded in task-irrelevant, distracting information, which can be considered as noise. METHODOLOGY/PRINCIPAL FINDINGS: In the present fMRI study, we probed neural correlates of associative memory formation in a full-factorial design with associative memory (subsequently remembered versus forgotten and noise (induced by high versus low distraction as factors. Results showed that encoding failure was associated with supra-optimal activity in the high-distraction condition and with sub-optimal activity in the low distraction condition. Thus, we revealed evidence for a bell-shape function relating hippocampal activity with associative encoding success. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that intermediate levels of hippocampal activity are optimal while both too low and too high levels appear detrimental for associative memory formation. Supra-optimal levels of hippocampal activity seem to occur when task-irrelevant information is added to task-relevant signal. If such task-irrelevant noise is reduced adequately, hippocampal activity is lower and thus optimal for associative memory formation.
Development of methods for evaluating active faults
International Nuclear Information System (INIS)
2013-01-01
The report for long-term evaluation of active faults was published by the Headquarters for Earthquake Research Promotion on Nov. 2010. After occurrence of the 2011 Tohoku-oki earthquake, the safety review guide with regard to geology and ground of site was revised by the Nuclear Safety Commission on Mar. 2012 with scientific knowledges of the earthquake. The Nuclear Regulation Authority established on Sep. 2012 is newly planning the New Safety Design Standard related to Earthquakes and Tsunamis of Light Water Nuclear Power Reactor Facilities. With respect to those guides and standards, our investigations for developing the methods of evaluating active faults are as follows; (1) For better evaluation on activities of offshore fault, we proposed a work flow to date marine terrace (indicator for offshore fault activity) during the last 400,000 years. We also developed the analysis of fault-related fold for evaluating of blind fault. (2) To clarify the activities of active faults without superstratum, we carried out the color analysis of fault gouge and divided the activities into thousand of years and tens of thousands. (3) To reduce uncertainties of fault activities and frequency of earthquakes, we compiled the survey data and possible errors. (4) For improving seismic hazard analysis, we compiled the fault activities of the Yunotake and Itozawa faults, induced by the 2011 Tohoku-oki earthquake. (author)
Optimizing methods and dodging pitfalls in microbiome research.
Kim, Dorothy; Hofstaedter, Casey E; Zhao, Chunyu; Mattei, Lisa; Tanes, Ceylan; Clarke, Erik; Lauder, Abigail; Sherrill-Mix, Scott; Chehoud, Christel; Kelsen, Judith; Conrad, Máire; Collman, Ronald G; Baldassano, Robert; Bushman, Frederic D; Bittinger, Kyle
2017-05-05
Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.
Optimization of Robotic Spray Painting process Parameters using Taguchi Method
Chidhambara, K. V.; Latha Shankar, B.; Vijaykumar
2018-02-01
Automated spray painting process is gaining interest in industry and research recently due to extensive application of spray painting in automobile industries. Automating spray painting process has advantages of improved quality, productivity, reduced labor, clean environment and particularly cost effectiveness. This study investigates the performance characteristics of an industrial robot Fanuc 250ib for an automated painting process using statistical tool Taguchi’s Design of Experiment technique. The experiment is designed using Taguchi’s L25 orthogonal array by considering three factors and five levels for each factor. The objective of this work is to explore the major control parameters and to optimize the same for the improved quality of the paint coating measured in terms of Dry Film thickness(DFT), which also results in reduced rejection. Further Analysis of Variance (ANOVA) is performed to know the influence of individual factors on DFT. It is observed that shaping air and paint flow are the most influencing parameters. Multiple regression model is formulated for estimating predicted values of DFT. Confirmation test is then conducted and comparison results show that error is within acceptable level.
Optimal Active Vibration Suppression of Smart Composite Wind Turbine Blades
Abd El-Maksoud Mohamed, Sherif Ibrahim
The purpose of this study is to apply active vibration control technique numerically for suppressing the vibrational level of a horizontal axis wind turbine blade. Two systems are studied to apply active vibration control on the wind turbine blade model, the first is a uniform cantilever beam and the other system is a non-uniform (tapered) cantilever beam. A single piezoelectric actuator and sensor are bonded on the upper and lower surface of the systems, respectively. The vibration analysis and dynamic characteristics of smart systems are obtained using approximate analytical methods. The entire structure is modeled in the state space form using the state space method, generalized coordinates and piezoelectric theory. Two types of controllers are designed to study the performance of the piezoelectric active controller. The first is a Proportional-Derivative (PD) controller and the other type is a Linear Quadratic Regulator (LQR). The Linear Quadratic Regulator (LQR) demonstrates better results for vibration suppression. The MATLAB code Simulink is used to simulate the different cases.
Vitório, Paulo Cezar; Leonel, Edson Denner
2017-12-01
The structural design must ensure suitable working conditions by attending for safe and economic criteria. However, the optimal solution is not easily available, because these conditions depend on the bodies' dimensions, materials strength and structural system configuration. In this regard, topology optimization aims for achieving the optimal structural geometry, i.e. the shape that leads to the minimum requirement of material, respecting constraints related to the stress state at each material point. The present study applies an evolutionary approach for determining the optimal geometry of 2D structures using the coupling of the boundary element method (BEM) and the level set method (LSM). The proposed algorithm consists of mechanical modelling, topology optimization approach and structural reconstruction. The mechanical model is composed of singular and hyper-singular BEM algebraic equations. The topology optimization is performed through the LSM. Internal and external geometries are evolved by the LS function evaluated at its zero level. The reconstruction process concerns the remeshing. Because the structural boundary moves at each iteration, the body's geometry change and, consequently, a new mesh has to be defined. The proposed algorithm, which is based on the direct coupling of such approaches, introduces internal cavities automatically during the optimization process, according to the intensity of Von Mises stress. The developed optimization model was applied in two benchmarks available in the literature. Good agreement was observed among the results, which demonstrates its efficiency and accuracy.
International Nuclear Information System (INIS)
Xu, Yun-Chao; Chen, Qun
2013-01-01
The vapor-compression refrigeration systems have been one of the essential energy conversion systems for humankind and exhausting huge amounts of energy nowadays. Surrounding the energy efficiency promotion of the systems, there are lots of effectual optimization methods but mainly relied on engineering experience and computer simulations rather than theoretical analysis due to the complex and vague physical essence. We attempt to propose a theoretical global optimization method based on in-depth physical analysis for the involved physical processes, i.e. heat transfer analysis for condenser and evaporator, through introducing the entransy theory and thermodynamic analysis for compressor and expansion valve. The integration of heat transfer and thermodynamic analyses forms the overall physical optimization model for the systems to describe the relation between all the unknown parameters and known conditions, which makes theoretical global optimization possible. With the aid of the mathematical conditional extremum solutions, an optimization equation group and the optimal configuration of all the unknown parameters are analytically obtained. Eventually, via the optimization of a typical vapor-compression refrigeration system with various working conditions to minimize the total heat transfer area of heat exchangers, the validity and superior of the newly proposed optimization method is proved. - Highlights: • A global optimization method for vapor-compression systems is proposed. • Integrating heat transfer and thermodynamic analyses forms the optimization model. • A mathematical relation between design parameters and requirements is derived. • Entransy dissipation is introduced into heat transfer analysis. • The validity of the method is proved via optimization of practical cases
Towards Optimal IT Availability Planning: Methods and Tools
Zambon, Emmanuele
2011-01-01
The availability of an organisation’s IT infrastructure is of vital importance for supporting business activities. IT outages are a cause of competitive liability, chipping away at a company financial performance and reputation. To achieve the maximum possible IT availability within the available
Design and Optimization Method of a Two-Disk Rotor System
Huang, Jingjing; Zheng, Longxi; Mei, Qing
2016-04-01
An integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.
A Primal-Dual Augmented Lagrangian Method for Optimal Control of ...
African Journals Online (AJOL)
Numerical experiments verify the efficiency of the proposed method. Keywords: Optimal control,primal-dual methods, augmented Lagrangian methods, conjugate gradient method, sequential quadratic programming. Journal of the Nigerian Association of Mathematical Physics, Volume 20 (March, 2012), pp 165 – 174 ...
OPTIMIZATION OF I-SECTION PROFILE DESIGN BY THE FINITE ELEMENT METHOD
Directory of Open Access Journals (Sweden)
Patryk Różyło
2016-03-01
Full Text Available This paper discusses the problem of design optimization for an I-section profile. The optimization process was performed using the Abaqus program. The numerical analysis of a strictly static problem was based on the finite element method. The scope of the analysis involved both determination of stresses and displacements in the profile and structure topology optimization. The main focus of the numerical analysis was put on reducing profile volume while maintaining the same load and similar stresses prior to and after optimization. The solution of the optimization problem is just an example of the potential of using this method in combination with the finite element method in the Abaqus environment. Nowadays numerical analysis is the most effective cost-reducing alternative to experimental tests and it enables structure examination by means of a computer.
Construction of molecular potential energy curves by an optimization method
Wang, J.; Blake, A. J.; McCoy, D. G.; Torop, L.
1991-01-01
A technique for determining the potential energy curves for diatomic molecules from measurements of diffused or continuum spectra is presented. It is based on a numerical procedure which minimizes the difference between the calculated spectra and the experimental measurements and can be used in cases where other techniques, such as the conventional RKR method, are not applicable. With the aid of suitable spectral data, the associated dipole electronic transition moments can be simultaneously obtained. The method is illustrated by modeling the "longest band" of molecular oxygen to extract the E 3Σ u- and B 3Σ u- potential curves in analytical form.
Analysis of Precision of Activation Analysis Method
DEFF Research Database (Denmark)
Heydorn, Kaj; Nørgaard, K.
1973-01-01
The precision of an activation-analysis method prescribes the estimation of the precision of a single analytical result. The adequacy of these estimates to account for the observed variation between duplicate results from the analysis of different samples and materials, is tested by the statistic T...
Monte Carlo method in neutron activation analysis
International Nuclear Information System (INIS)
Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.
2009-01-01
Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA
Methods for using polypeptides having cellobiohydrolase activity
Morant, Marc D; Harris, Paul
2016-08-23
The present invention relates to isolated polypeptides having cellobiohydrolase activity and isolated polynucleotides encoding the polypeptides. The invention also relates to nucleic acid constructs, vectors, and host cells comprising the polynucleotides as well as methods of producing and using the polypeptides.
A LEVEL SET BASED SHAPE OPTIMIZATION METHOD FOR AN ELLIPTIC OBSTACLE PROBLEM
Burger, Martin
2011-04-01
In this paper, we construct a level set method for an elliptic obstacle problem, which can be reformulated as a shape optimization problem. We provide a detailed shape sensitivity analysis for this reformulation and a stability result for the shape Hessian at the optimal shape. Using the shape sensitivities, we construct a geometric gradient flow, which can be realized in the context of level set methods. We prove the convergence of the gradient flow to an optimal shape and provide a complete analysis of the level set method in terms of viscosity solutions. To our knowledge this is the first complete analysis of a level set method for a nonlocal shape optimization problem. Finally, we discuss the implementation of the methods and illustrate its behavior through several computational experiments. © 2011 World Scientific Publishing Company.
A novel optimized LCL-filter designing method for grid connected converter
DEFF Research Database (Denmark)
Guohong, Zeng; Rasmussen, Tonny Wederberg; Teodorescu, Remus
2010-01-01
This paper presents a new LCL-filters optimized designing method for grid connected voltage source converter. This method is based on the analysis of converter output voltage components and inherent relations among LCL-filter parameters. By introducing an optimizing index of equivalent total...... frequency distortion is fulfilled. Compared to the existing methods, the proposed method contains only four steps without try-and-error process, so it is efficient and easy to implement. Simulation results of a 50kVA grid-connected inverter with two sets of LCL-filter parameters under different optimizing...... capacity of all filter components, with clear physical meaning of minimum cost and volume, a set of optimal values of attenuation ratio and inductancesplit- ratio is obtained for deciding all LCL-filter parameters. With this method, filter overall capacity can be minimized while the grid limit of switching...
Application of Taguchi method for cutting force optimization in rock ...
Indian Academy of Sciences (India)
As a result of this increase, there has been recently more attention for sustainability during their productions .... tical measure of performance in Taguchi method was subsequently used to analyse the results. Table 3. .... The performance of circular diamond sawblades was evaluated for Fc with respect to the Eq. (14) and the ...
Experimental Methods for the Analysis of Optimization Algorithms
DEFF Research Database (Denmark)
of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists...
Method of optimizing performance of Rankine cycle power plants
Pope, William L.; Pines, Howard S.; Doyle, Padraic A.; Silvester, Lenard F.
1982-01-01
A method for efficiently operating a Rankine cycle power plant (10) to maximize fuel utilization efficiency or energy conversion efficiency or minimize costs by selecting a turbine (22) fluid inlet state which is substantially in the area adjacent and including the transposed critical temperature line (46).
Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications
2015-06-24
include the exact solution of larger Q3AP problems and of still larger QAP problems. - 2 – An emphasis was here to avoid academic problems and...problems of these larger sizes through a sequence of two-dimensional QAPs , see [6]. As the graphs in [6] show, our method is giving by far the best
Integrating methods to optimize circumplex description and comparison of groups.
Wright, Aidan G C; Pincus, Aaron L; Conroy, David E; Hilsenroth, Mark J
2009-07-01
Using the interpersonal circumplex as an exemplar, this article serves as a methodological primer for integrating techniques of group description and comparison when employing circumplex-based assessment instruments. Circular statistics (Mardia & Jupp, 1999) and the structural summary method (Gurtman & Balakrishnan, 1998) each offer unique and incrementally useful information when applied to group-level data on circumplex measures. Circular statistics offer a set of parameters that are conceptually similar to their linear equivalents (i.e., mean, variance, and confidence intervals). In interpersonal circumplex models, these parameters each provide specific information regarding substantive theme and group homogeneity and allow for the statistical comparison of groups based on the geometry of the circular model. In a similar fashion, the structural summary method for circumplex data provides a set of parameters that complement circular statistics by offering measures of the interpersonal prototypicality of the group profile, levels of profile differentiation and elevation, and a weighted measure of substantive theme. Used in conjunction, these methods offer more information than is available using either in isolation. We provide 4 examples to demonstrate the complementary information the 2 methods provide for assessments employing interpersonal circumplex measures. These examples will allow investigators to generalize the methods to other personality assessment domains in which circumplex models are utilized, such as emotion and vocational preference. [Supplementary materials are available for this article. Go to the publisher's online edition of the Journal of Personality Assessment for the following free supplemental resources: an Excel file that calculates the circular statistics and structural summary information described in this article using manually entered octant scores from up to 500 participants.
Improving the ensemble optimization method through covariance matrix adaptation (CMA-EnOpt)
Fonseca, R.M.; Leeuwenburgh, O.; Hof, P.M.J. van den; Jansen, J.D.
2013-01-01
Ensemble Optimization (EnOpt) is a rapidly emerging method for reservoir model based production optimization. EnOpt uses an ensemble of controls to approximate the gradient of the objective function with respect to the controls. Current implementations of EnOpt use a Gaussian ensemble with a
Improving the ensemble-optimization method through covariance-matrix adaptation
Fonseca, R.M.; Leeuwenburgh, O.; Hof, P.M.J. van den; Jansen, J.D.
2015-01-01
Ensemble optimization (referred to throughout the remainder of the paper as EnOpt) is a rapidly emerging method for reservoirmodel-based production optimization. EnOpt uses an ensemble of controls to approximate the gradient of the objective function with respect to the controls. Current
DEFF Research Database (Denmark)
Yoon, Gil Ho; Park, Y.K.; Kim, Y.Y.
2007-01-01
A new topology optimization scheme, called the element stacking method, is developed to better handle design optimization involving material-dependent boundary conditions and selection of elements of different types. If these problems are solved by existing standard approaches, complicated finite...
Beam shaping and its solution with the use of an optimization method.
Cong, W X; Chen, N X; Gu, B Y
1998-07-10
We present an exact mathematical description of beam shaping and indicate that a rigorous solution does not exist: only an optimal solution can be found. An optimization method is proposed to search for the solution. The simulation results for an example are given in detail.
Van Dijk, N.P.
2012-01-01
This thesis aims at understanding and improving topology optimization techniques focusing on density-based level-set methods and geometrical nonlinearities. Central in this work are the numerical modeling of the mechanical response of a design and the consistency of the optimization process itself.
A generic method to optimize instructions for the control of evacuations
Huibregtse, O.L.; Hoogendoorn, S.P.; Pel, A.J.; Bliemer, M.C.J.
2010-01-01
A method is described to develop a set of optimal instructions to evacuate by car the population of a region threatened by a hazard. By giving these instructions to the evacuees, traffic conditions and therefore the evacuation efficiency can be optimized. The instructions, containing a departure
The equivalence of multi-criteria methods for radiotherapy plan optimization
International Nuclear Information System (INIS)
Breedveld, Sebastiaan; Storchi, Pascal R M; Heijmen, Ben J M
2009-01-01
Several methods can be used to achieve multi-criteria optimization of radiation therapy treatment planning, which strive for Pareto-optimality. The property of the solution being Pareto optimal is desired, because it guarantees that no criteria can be improved without deteriorating another criteria. The most widely used methods are the weighted-sum method, in which the different treatment objectives are weighted, and constrained optimization methods, in which treatment goals are set and the algorithm has to find the best plan fulfilling these goals. The constrained method used in this paper, the 2pεc (2-phase ε-constraint) method is based on the ε-constraint method, which generates Pareto-optimal solutions. Both approaches are uniquely related to each other. In this paper, we will show that it is possible to switch from the constrained method to the weighted-sum method by using the Lagrange multipliers from the constrained optimization problem, and vice versa by setting the appropriate constraints. In general, the theory presented in this paper can be useful in cases where a new situation is slightly different from the original situation, e.g. in online treatment planning, with deformations of the volumes of interest, or in automated treatment planning, where changes to the automated plan have to be made. An example of the latter is given where the planner is not satisfied with the result from the constrained method and wishes to decrease the dose in a structure. By using the Lagrange multipliers, a weighted-sum optimization problem is constructed, which generates a Pareto-optimal solution in the neighbourhood of the original plan, but fulfills the new treatment objectives.
A global optimization method for evaporative cooling systems based on the entransy theory
International Nuclear Information System (INIS)
Yuan, Fang; Chen, Qun
2012-01-01
Evaporative cooling technique, one of the most widely used methods, is essential to both energy conservation and environment protection. This contribution introduces a global optimization method for indirect evaporative cooling systems with coupled heat and mass transfer processes based on the entransy theory to improve their energy efficiency. First, we classify the irreversible processes in the system into the heat transfer process, the coupled heat and mass transfer process and the mixing process of waters in different branches, where the irreversibility is evaluated by the entransy dissipation. Then through the total system entransy dissipation, we establish the theoretical relationship of the user demands with both the geometrical structures of each heat exchanger and the operating parameters of each fluid, and derive two optimization equation groups focusing on two typical optimization problems. Finally, an indirect evaporative cooling system is taken as an example to illustrate the applications of the newly proposed optimization method. It is concluded that there exists an optimal circulating water flow rate with the minimum total thermal conductance of the system. Furthermore, with different user demands and moist air inlet conditions, it is the global optimization, other than parametric analysis, will obtain the optimal performance of the system. -- Highlights: ► Introduce a global optimization method for evaporative cooling systems. ► Establish the direct relation between user demands and the design parameters. ► Obtain two groups of optimization equations for two typical optimization objectives. ► Solving the equations offers the optimal design parameters for the system. ► Provide the instruction for the design of coupled heat and mass transfer systems.
Hadi, Muhammad N. S.; Uz, Mehmet E.
2015-02-01
This study proposes the optimal passive and active damper parameters for achieving the best results in seismic response mitigation of coupled buildings connected to each other by dampers. The optimization to minimize the H2 and H∞ norms in the performance indices is carried out by genetic algorithms (GAs). The final passive and active damper parameters are checked for adjacent buildings connected to each other under El Centro NS 1940 and Kobe NS 1995 excitations. Using real coded GA in H∞ norm, the optimal controller gain is obtained by different combinations of the measurement as the feedback for designing the control force between the buildings. The proposed method is more effective than other metaheuristic methods and more feasible, although the control force increased. The results in the active control system show that the response of adjacent buildings is reduced in an efficient manner.
Engine optimization grate multipurpose analysis method with quality function deployment
Directory of Open Access Journals (Sweden)
Nukman
2017-01-01
Full Text Available The object that will be developed in this study is a simple technology shredding machine design, artificial and has been patented by Andi Patolla (1988. which is often used by people specifically to grate the coconut. The methods used for product development using QFD. This method is needed to analyze and evaluate the level of consumer desires in order to develop products grate machine. The subject matter of the research outlined in the distribution table discussion. The research instrument used when data collection is questionnaire technique, which is supported by the observation technique, documentation, and interviews. From the discussion that has been done, it can be concluded that the priority consumers are very stressed to do a modification component or an additional tool in the machine grater multipurpose namely Cover Safeguard Fan Belt, Exhaust, Priority Motor Driving Fuel Gasoline, layout position Mover, Motor Starter, Plastic cleaning brush Roll Grate, and Plate Cap. 2.
Optimization Method of Fusing Model Tree into Partial Least Squares
Directory of Open Access Journals (Sweden)
Yu Fang
2017-01-01
Full Text Available Partial Least Square (PLS can’t adapt to the characteristics of the data of many fields due to its own features multiple independent variables, multi-dependent variables and non-linear. However, Model Tree (MT has a good adaptability to nonlinear function, which is made up of many multiple linear segments. Based on this, a new method combining PLS and MT to analysis and predict the data is proposed, which build MT through the main ingredient and the explanatory variables(the dependent variable extracted from PLS, and extract residual information constantly to build Model Tree until well-pleased accuracy condition is satisfied. Using the data of the maxingshigan decoction of the monarch drug to treat the asthma or cough and two sample sets in the UCI Machine Learning Repository, the experimental results show that, the ability of explanation and predicting get improved in the new method.
A RECREATION OPTIMIZATION MODEL BASED ON THE TRAVEL COST METHOD
Hof, John G.; Loomis, John B.
1983-01-01
A recreation allocation model is developed which efficiently selects recreation areas and degree of development from an array of proposed and existing sites. The model does this by maximizing the difference between gross recreation benefits and travel, investment, management, and site-opportunity costs. The model presented uses the Travel Cost Method for estimating recreation benefits within an operations research framework. The model is applied to selection of potential wilderness areas in C...
Automated sizing of large structures by mixed optimization methods
Sobieszczanski, J.; Loendorf, D.
1973-01-01
A procedure for automating the sizing of wing-fuselage airframes was developed and implemented in the form of an operational program. The program combines fully stressed design to determine an overall material distribution with mass-strength and mathematical programming methods to design structural details accounting for realistic design constraints. The practicality and efficiency of the procedure is demonstrated for transport aircraft configurations. The methodology is sufficiently general to be applicable to other large and complex structures.
A method for minimum risk portfolio optimization under hybrid uncertainty
Egorova, Yu E.; Yazenin, A. V.
2018-03-01
In this paper, we investigate a minimum risk portfolio model under hybrid uncertainty when the profitability of financial assets is described by fuzzy random variables. According to Feng, the variance of a portfolio is defined as a crisp value. To aggregate fuzzy information the weakest (drastic) t-norm is used. We construct an equivalent stochastic problem of the minimum risk portfolio model and specify the stochastic penalty method for solving it.
Evaluation of methods to assess physical activity
Leenders, Nicole Y. J. M.
Epidemiological evidence has accumulated that demonstrates that the amount of physical activity-related energy expenditure during a week reduces the incidence of cardiovascular disease, diabetes, obesity, and all-cause mortality. To further understand the amount of daily physical activity and related energy expenditure that are necessary to maintain or improve the functional health status and quality of life, instruments that estimate total (TDEE) and physical activity-related energy expenditure (PAEE) under free-living conditions should be determined to be valid and reliable. Without evaluation of the various methods that estimate TDEE and PAEE with the doubly labeled water (DLW) method in females there will be eventual significant limitations on assessing the efficacy of physical activity interventions on health status in this population. A triaxial accelerometer (Tritrac-R3D, (TT)), an uniaxial (Computer Science and Applications Inc., (CSA)) activity monitor, a Yamax-Digiwalker-500sp°ler , (YX-stepcounter), by measuring heart rate responses (HR method) and a 7-d Physical Activity Recall questionnaire (7-d PAR) were compared with the "criterion method" of DLW during a 7-d period in female adults. The DLW-TDEE was underestimated on average 9, 11 and 15% using 7-d PAR, HR method and TT. The underestimation of DLW-PAEE by 7-d PAR was 21% compared to 47% and 67% for TT and YX-stepcounter. Approximately 56% of the variance in DLW-PAEE*kgsp{-1} is explained by the registration of body movement with accelerometry. A larger proportion of the variance in DLW-PAEE*kgsp{-1} was explained by jointly incorporating information from the vertical and horizontal movement measured with the CSA and Tritrac-R3D (rsp2 = 0.87). Although only a small amount of variance in DLW-PAEE*kgsp{-1} is explained by the number of steps taken per day, because of its low cost and ease of use, the Yamax-stepcounter is useful in studies promoting daily walking. Thus, studies involving the
Directory of Open Access Journals (Sweden)
Panfeng Huang
2014-09-01
Full Text Available The tethered space robot (TSR is a new concept of space robot which consists of a robot platform, space tether and operation robot. This paper presents a multi-objective optimal trajectory planning and a coordinated tracking control scheme for TSR based on velocity impulse in the approaching phase. Both total velocity impulse and flight time are included in this optimization. The non-dominated sorting genetic algorithm is employed to obtain the optimal trajectory Pareto solution using the TSR dynamic model and optimal trajectory planning model. The coordinated tracking control scheme utilizes optimal velocity impulse. Furthermore, the PID controller is designed in order to compensate for the distance measurement errors. The PID control force is optimized and distributed to thrusters and the space tether using a simulated annealing algorithm. The attitude interferential torque of the space tether is compensated a using time-delay algorithm through reaction wheels. The simulation results show that the multi-objective optimal trajectory planning method can reveal the relationships among flight time, fuel consumption, planar view angle and velocity impulse number. This method can provide a series of optimal trajectory according to a number of special tasks. The coordinated control scheme can significantly save thruster fuel for tracking the optimal trajectory, restrain the attitude interferential torque produced by space tether and maintain the relative attitude stability of the operation robot.
Wang, Xiaoqin; Jiang, Ying; Hu, Daode
2016-01-01
Curcuma wenyujin, a member of the genus Curcuma, has been widely prescribed for anti-cancer therapy. Multiple response surface optimization has attracted a great attention, while, the research about optimizing three or more responses employing response surface methodology (RSM) was very few. RSM and desirability function (DF) were employed to get the optimum ultrasonic extraction parameters, in which the extraction yields of curdione, furanodienone, curcumol and germacrone from C. wenyujin were maximum. The yields in the extract were accurately quantified using the validated high performance liquid chromatography method with a good precision and accuracy. The optimization results indicated that the maximum combined desirability 97.1 % was achieved at conditions as follows: liquid-solid ratio, 8 mL g(-1); ethanol concentration, 70 % and ultrasonic time, 20 min. The extraction yields gained from three verification experiments were in fine agreement with those of the model's predictions. The surface morphologies of the sonication-treated C. wenyujin were loose and rough. The extract of C. wenyujin presented obvious antiproliferative activities against RKO and HT-29 cells in vitro. Response surface methodology was successfully applied to model and optimize the ultrasonic extraction of four bioactive components from C. wenyujin for antiproliferative activitiy.Graphical abstract.
Solar activity explored with new wavelet methods
Directory of Open Access Journals (Sweden)
H. Lundstedt
2005-06-01
Full Text Available In order to improve the forecasts of the impact of solar activity on the terrestrial environment on time scales longer than days, improved understanding and forecasts of the solar activity are needed. The first results of a new approach of modelling and forecasting solar activity are presented. Time series of solar activity indicators, such as sunspot number, group sunspot number, F10.7, E10.7, solar magnetic mean field, Mount Wilson plage and sunspot index, have been studied with new wavelet methods; ampligrams and time-scale spectra. Wavelet power spectra of the sunspot number for the period 1610 up to the present show not only that a dramatic increase in the solar activity took place after 1940 but also that an interesting change occurred in 1990. The main 11-year solar cycle was further studied with ampligrams for the period after 1850. time-scale spectra were used to examine the processes behind the variability of the solar activity. Several interesting deterministic and more stochastic features were detected in the time series of the solar activity indicators. The solar nature of these features will be further studied. Keywords. Solar physics, astrophysics and astronomy (Magnetic fields; Stellar interiors and dynamo theory – Space plasma physics (nonlinear phenomena
Optimal Monotonicity-Preserving Perturbations of a Given Runge–Kutta Method
Higueras, Inmaculada
2018-02-14
Perturbed Runge–Kutta methods (also referred to as downwind Runge–Kutta methods) can guarantee monotonicity preservation under larger step sizes relative to their traditional Runge–Kutta counterparts. In this paper we study the question of how to optimally perturb a given method in order to increase the radius of absolute monotonicity (a.m.). We prove that for methods with zero radius of a.m., it is always possible to give a perturbation with positive radius. We first study methods for linear problems and then methods for nonlinear problems. In each case, we prove upper bounds on the radius of a.m., and provide algorithms to compute optimal perturbations. We also provide optimal perturbations for many known methods.
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.
Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine
Directory of Open Access Journals (Sweden)
Bambang Wahono
2014-01-01
Full Text Available This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, NOx, and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.